[NBK] Cover Buy Sell for XAU Cover Buy Sell for XAU — Engulfing Reversals with EMA/ATR Trend & Quality Filters
{Update for XAU}
What it does
This indicator flags high-quality bullish/bearish reversal candles only when they align with a short-term trend and pass several objective quality filters. It is not a simple mashup: each component serves a distinct role and they work together to keep early/low-quality signals out.
How it works (components & interaction)
Pattern engine (entry candidates)
Bullish side (Cover Buy):
Body Engulf: current green body fully covers the prior red body, or
Piercing (relaxed): prior red → current green closes above the prior body’s midpoint (not beyond prior open).
Bearish side (Cover Sell):
Full-candle Engulf: current red candle (body + wicks) covers the entire prior candle, or
Body Engulf: current red body fully covers the prior body, or
Dark-Cloud (relaxed): prior green → current red closes below the prior body’s midpoint.
Short-term trend gate (non-repainting)
Trend is defined by the EMA slope between bar-1 and bar-2, scaled by ATR to require minimum strength.
Slope < 0 → only bullish candidates pass. Slope > 0 → only bearish candidates pass.
Body-size filter (noise control)
Rejects tiny candles: each body is compared with the lookback average body size.
For bearish candidates an additional ratio check requires current body ≥ a fraction of the prior body (to avoid weak top-ticks).
Peak filters for bearish signals (late, cleaner tops)
Distance above EMA: the high must be at least X × ATR above EMA (avoids mid-range noise).
Near local high: the high of the current bar (or bar-1) must be close to the highest high in a recent window.
Break confirmation: close must break low by at least Y × ATR (filters shallow dark-clouds).
Only when a candidate satisfies the pattern ➝ trend ➝ size ➝ peak sequence is a signal printed/alerted.
Inputs (key parameters)
EMA length, Min EMA slope vs ATR, ATR length: trend strength.
Lookback for average body, Min body vs average, Bear body ratio: body-quality filters.
High distance above EMA (×ATR), Local high lookback, Tolerance to local high (×ATR), Min break of low (×ATR): bearish peak confirmation.
Alerts
Built-in alerts fire on bar close for both Cover Buy and Cover Sell.
How to use
Increase High distance above EMA / Local high lookback / Min break of low to reduce early Cover Sell in ranges.
If you miss good tops, ease those thresholds slightly.
Works across symbols/timeframes; evaluated on bar close; no repaint from the trend gate.
Notes
This tool is a signal screener, not financial advice. For best results, combine with your structure/SR zones, risk management, and execution rules.
13 thg 10
Phát hành các Ghi chú
Cover Buy Sell — Engulfing Reversals with EMA/ATR Trend & Quality/Peak Filters
What this script does
Flags high-quality bullish/bearish engulfing reversals only when short-term trend and price-action quality conditions are met. Signals evaluate on bar close. No promotions, no links, no external calls.
Why this is an original combination (mashup justification)
Raw engulfing patterns are noisy in ranges. This script is a pipeline where each module solves a specific failure mode, not a simple merge of indicators:
Pattern engine (candidates):
Bullish (Cover Buy): body-engulf of prior red body, or relaxed Piercing (close above prior body midpoint, not beyond prior open).
Bearish (Cover Sell): full-candle engulf (body+wicks), body-engulf, or relaxed Dark-Cloud (close below prior body midpoint).
Short-term trend gate (non-repainting):
EMA slope is measured between bar-1 and bar-2 and must exceed an ATR-scaled threshold (slopeAtrPct).
Slope < 0 → only bullish candidates pass.
Slope > 0 → only bearish candidates pass.
Body-size filter (noise control):
Bodies must not be tiny vs the average over lenBodyRef. For bearish candidates, an alternate check allows current body ≥ bearRatioMin × prior body to keep decisive tops.
Bearish peak filters (late, cleaner tops):
High must be far above EMA (≥ emaDistAtrMin × ATR), near the local high (current or prior bar within nearHighLen & nearHighTol × ATR), and the close must break prior low by ≥ breakAtrMin × ATR.
These remove premature Cover Sell flags in chop and keep the later, higher-quality reversal.
Only candidates that pass Pattern → Trend → Size → Peak become signals. This staged design is the core originality.
How to use (practical guidance)
To reduce early Cover Sell in ranges: raise emaDistAtrMin, raise nearHighLen, and/or raise breakAtrMin.
If you miss clean tops: slightly lower those thresholds.
Typical starting points: lenTrend=4–6, slopeAtrPct=0.03–0.06, atrLen=14; adjust to instrument/TF volatility.
Combine with structure/SR zones and your risk rules. This tool is for analysis only and is not investment advice.
Alerts
Two alert conditions are included: Cover Buy and Cover Sell, both evaluated on bar close.
Non-repainting note
The trend gate uses confirmed data (EMA slope from bar-1 vs bar-2). Pattern and filters also use confirmed values; no forward-looking references.
English translations of UI strings (if your on-chart UI uses another language)
“Strict engulf (không cho bằng nhau)” → Strict engulf (no equality)
“EMA length (trend ngắn hạn)” → EMA length (short-term trend)
“Lookback tính thân trung bình” → Lookback for average body size
“Ngưỡng thân tối thiểu vs trung bình” → Min body vs average (ratio)
“Bear: thân hiện tại ≥ rRatio * thân trước” → Bear: current body ≥ rRatio × prior body
“Bear: HIGH cách EMA tối thiểu (x ATR)” → Bear: HIGH distance above EMA (× ATR) min
“Bear: cửa sổ đỉnh cục bộ (bars)” → Bear: local high lookback (bars)
“Bear: dung sai tới đỉnh (x ATR)” → Bear: tolerance to local high (× ATR)
“Bear: mức phá LOW tối thiểu (x ATR)” → Bear: min break of LOW (× ATR)
Compliance notes
English-only title, English appears first in this description; no ads, logos, links, or solicitations.
This is an original, closed-source script with a meaningful explanation of what, how, why, and how to use.
(Vietnamese short summary)
Chỉ báo bắt tín hiệu engulfing chất lượng cao khi có xu hướng EMA ngắn hạn (đo bằng độ dốc/ATR) và vượt qua lọc kích thước thân + điều kiện đỉnh cho tín hiệu bán. Chuỗi xử lý Mẫu → Xu hướng → Kích thước → Đỉnh giúp loại tín hiệu sớm trong vùng đi ngang. Có alert Cover Buy/Sell, đánh giá theo bar close, không quảng cáo/đường link, và không phải khuyến nghị đầu tư.
Cerca negli script per "bear"
Trend Pulse Algo (LTM)Trend Pulse Algo LTM Indicator Description
Overview
Trend Pulse Algo LTM is an advanced multi layer technical indicator designed for TradingView that combines moving average MA crossovers confirmation signals pivot based structure analysis imbalance zone detection and overextension warnings to identify potential trend shifts continuations and reversal points. It aims to provide traders with reliable entry and exit signals in trending markets while highlighting areas of market inefficiency imbalances and overextended price moves that could signal exhaustion.
This indicator operates on a pulse concept where it detects rhythmic shifts in market momentum through layered MAs a quick MA for short term sensitivity a mid MA for intermediate confirmation and a long MA as a baseline trend filter. Signals are generated based on alignments and crosses between these MAs but with added layers of confirmation to reduce false positives such as requiring consecutive bars above below the long MA and breaks of prior pivot highs lows. It incorporates higher timeframe HTF analysis for imbalance zones to capture broader market context making it suitable for swing trading trend following or scalping on lower timeframes when combined with the overextension detector.
Unlike simple MA crossover systems for example standard dual EMA strategies this algo uses adaptive MA types based on timeframe pivot deviation for structural breaks and a tally based confirmation to filter noise. Imbalance zones identify fair value gaps or inefficiencies between candle bodies and wicks where price may retrace to fill. Overextension is calculated relative to the mid MA using a rolling mean absolute deviation MAD ratio highlighting potential tops bottoms in strong trends. The result is a visually clean or detailed based on mode overlay that colors bars backgrounds plots labels for signals and pivots and draws zones to guide decision making.
How It Works
MA Layers and Signal Generation
Three MAs quick mid long are computed using either SMA or EMA selected dynamically based on the charts timeframe for optimal responsiveness for example EMA on lower TFs for faster signals.
Early Signals A crossover of the quick MA above the mid MA while above the long MA triggers a Possible Bull label indicating early momentum shifts. A crossunder below triggers Possible Bear.
Confirmed Signals Bullish confirmation requires a set number of bars closing above the long MA plus alignment quick greater than mid and a break above the prior pivot high. Bearish requires bars below the long MA and a break below the prior pivot low. This uses a counter mechanism to ensure persistence reducing whipsaws. Breaks are detected via crossovers under of close versus prior highs lows.
State persistence tracks the current regime bull bear warn early coloring the chart accordingly until a new signal overrides it.
Pivot Detection and Structure
Pivots are identified by scanning for highs lows separated by a minimum bar depth with a percentage deviation threshold to confirm validity. This follows a zigzag like approach but with deviation filtering for robustness.
Labels like HH Higher High HL Higher Low LH Lower High LL Lower Low highlight market structure helping identify trends for example HH HL for uptrends or breakdowns. These are used internally to validate signal breaks.
Imbalance Zones
Zones detect imbalances or gaps between candle bodies and prior highs lows where unfilled inefficiencies attract price.
For bullish zones If open greater than close and high minus low two less than zero a zone is drawn from calculated top bottom limits. Bearish similarly for close greater than open.
Supports current TF HTF or both. Zones extend rightward until filled price touches the opposite side or mid line if enabled then either delete or shorten based on settings. Mid lines can act as fill triggers for partial closures.
HTF data is fetched via security for broader context resetting on new HTF bars.
Overextension Indicator
Measures price deviation from the mid MA relative to a rolling average RMA of relative deviations over a length.
Multipliers define tiers mild for example two times avg deviation moderate three times extreme four times. Circles plot above below bars in bull bear states when thresholds are exceeded signaling potential reversals for example red for extreme tops in uptrends. This is akin to a Bollinger Band squeeze expansion but normalized to MA distance for trend specific warnings.
Chart Coloring and Visuals
Background or candle coloring reflects the state green for bull red for bear orange for warn blue for early.
Modes control clutter Clean hides MAs zones pivots Balanced shows essentials Detailed includes all.
How to Use It
Setup Add to your chart via TradingViews indicator search. Adjust inputs based on asset timeframe for example shorter MA periods for volatile cryptos longer for stocks.
Trading Strategy Ideas
Trend Following Enter long on Confirmed Bull labels exit on Confirmed Bear or extreme overextension circles. Use imbalance zones as support resistance for stops targets for example buy dips to unfilled bullish zones.
Reversal Scalping Watch for Possible Bull Bear near pivot labels for example HL LL and overextension in the opposite direction. Confirm with zone fills.
Multi TF Analysis Set HTF to D for daily context on hourly charts zones from HTF often act as magnets.
Risk Management Place stops below prior lows in bulls or above highs in bears. Target zone edges or MA crosses. Avoid trading against strong states without confirmation.
Alerts Set up via TradingView for Early Up Down or Up Down Confirm to notify on signal edges.
Limitations Best in trending markets may lag in ranges. Test on historical data no indicator is foolproof combine with volume price action.
Detailed Input Settings
Below is a comprehensive breakdown of all user adjustable inputs from the settings panel grouped as in the script. Each explains what it controls its effect on the indicators logic and usage tips. Defaults are provided for reference.
Chart Mode
Chart Mode default Detailed Mode options Clean Mode Balanced Mode Detailed Mode
Controls visual detail level. Clean Mode hides MAs imbalance zones and pivots for a minimal overlay focused on signals and coloring. Balanced Mode shows MAs and signals but omits zones pivots. Detailed Mode displays everything for in depth analysis. Use Clean for live trading to reduce clutter Detailed for backtesting structure review.
Display Settings
Color Style default Candles options Background Candles
Determines how states bull bear warn early are visualized. Background colors the chart area for example green shading for bull. Candles colors bar bodies wicks directly. Background is subtler for multi indicator setups Candles emphasizes signals on naked charts.
Imbalance Zone HTF Config
Higher TF Period default D
Sets the higher timeframe for imbalance detection for example D for daily four H for four hour. This fetches broader data to identify significant zones. Use a TF four to five times your current for context for example daily on one H charts avoid very high TFs like W on intraday for relevance.
TF Mode default Current TF options Current TF Current plus HTF HTF Only
Defines timeframe handling for zones. Current TF uses only your charts TF. Current plus HTF combines both for layered zones. HTF Only ignores current TF. Current plus HTF is ideal for multi TF confluence HTF Only simplifies for swing traders.
Shift default ten min zero max five hundred
Horizontal offset in bars for current TF zone labels. Higher values shift labels rightward to avoid overlap. Adjust if labels crowd the chart.
HTF Shift default twenty min zero max five hundred
Similar to Shift but for HTF zone labels. Use larger offsets for HTF to distinguish them visually.
Imbalance Zone Core Options
Mid Line Fill default false
Enables a midpoint line in each zone zones fill close short when price touches this mid line instead of the far edge. Activates partial fill logic for more conservative zone closure. Enable for tighter risk in volatile markets.
Remove Filled Zones default true
If true completely deletes filled zones if false shortens them to the fill point keeping history. True clears clutter false retains context for review.
Display TF on Zone default false
Shows the timeframe for example D IZ on zone labels. Useful for distinguishing current versus HTF zones in combined mode.
Max Upward Zones default twenty min one max fifty
Limits displayed bullish upward zones removes oldest when exceeded. Lower for cleaner charts higher for historical depth.
Max Downward Zones default twenty min one max fifty
Same as above but for bearish downward zones.
Imbalance Zone Visuals
Upward Zone color green at ninety percent transparency
Color for current TF upward imbalance zones. Adjust opacity for visibility.
HTF Upward Zone color lime at eighty percent transparency
Color for higher timeframe upward imbalance zones. Differentiate from current for example lighter shade.
Downward Zone color red at ninety percent transparency
Color for current TF downward imbalance zones.
HTF Downward Zone color maroon at eighty percent transparency
Color for higher timeframe downward imbalance zones.
Mid Line Color color white at eighty five percent transparency
Color for the optional midpoint line in zones.
Text Color color white
Color for text labels on zones.
MA Layers
Quick MA Period default ten min one
Length for the fastest moving average sensitive to short term price. Shorter for example five for scalping longer for example fifteen for less noise.
Mid MA Period default twenty min one
Intermediate MA length used for crossovers and overextension base. Typically two times quick for balance.
Long MA Period default fifty min one
Baseline trend filter length. Longer for example one hundred for major trends shorter for active trading.
MA Variants by Period
Under one H default EMA options SMA EMA
MA type for timeframes under one hour for example EMA for faster response.
One H to less than five H default EMA options SMA EMA
MA type for one to five hour timeframes.
Five H to less than one D default EMA options SMA EMA
MA type for five hour to one day timeframes.
One D plus default EMA options SMA EMA
MA type for daily and higher timeframes. Adapt to market EMA for trends SMA for mean reversion.
Signal Confirmation
Bull Confirm Bars default one min zero
Consecutive bars needed above long MA for bull confirmation. Zero for instant higher for example three filters noise but delays entries.
Bear Confirm Bars default two min zero
Same for bear below long MA. Asymmetrical default higher for bears assumes uptrend bias.
Pivot Detection
Pivot Depth default six min one
Min bars between pivots. Higher reduces minor swings lower captures more structure.
Pivot Deviation percent default one point zero min zero point one
Percent change required for new pivot. Higher ignores small moves for example two percent for stocks zero point five percent for forex.
Display HH and HL default true
Shows labels for Higher Highs Lows bullish structure.
Display LH and LL default true
Shows labels for Lower Highs Lows bearish structure.
Overextension Indicator
Show Overextension Circles Potential Tops default true
Enables circles above bars in bull states for potential tops.
Show Overextension Circles Potential Bottoms default true
Enables below bars in bear states for bottoms.
Overextension Length default fourteen min one
Period for rolling relative deviation average. Matches RSI STOCH defaults for alignment.
Mild Multiplier default two point zero min zero point zero
Threshold for mild overextension yellow circle. Zero disables tier.
Moderate Multiplier default three point zero min zero point zero
For moderate orange.
Extreme Multiplier default four point zero min zero point zero
For extreme red. Tune lower for sensitive warnings in ranging markets.
MTF Multi EMA - IntradayMTF Multi EMA – Intraday
Purpose:
To quickly analyze trend direction and alignment across multiple timeframes (1m, 3m, 5m, 15m, 30m, and 60m) using fast and slow EMAs for each timeframe — and combine them into a simple “stack score” for easy visual decision-making. The script is tuned for Intraday Trading indicator by default.
Concept
Each timeframe (TF) — like 1m, 3m, 5m, etc. — has two EMAs:
A fast EMA (shorter length)
A slow EMA (longer length)
When the fast EMA > slow EMA, that timeframe is bullish.
When the fast EMA < slow EMA, that timeframe is bearish.
By combining multiple timeframes together, the indicator helps you:
Identify when all trends align bullishly (strong buy bias)
Identify when all trends align bearishly (strong sell bias)
Stay out during mixed or sideways phases
Inputs Explained
Setting Description
1m / 3m / 5m / 15m / 30m / 60m EMA Lengths Controls the EMA period for each timeframe’s fast and slow EMAs.
Fast EMA Color Color for all fast EMAs plotted on chart.
Slow EMA Color Color for all slow EMAs plotted on chart.
Use Smooth Interpolation Ensures smoother plots when merging higher TF data into a smaller chart (recommended ON).
Show Toggle visibility of each timeframe’s EMAs.
Table Position Lets you move the mini dashboard to any chart corner.
Stack Score
The Stack Score measures how many timeframes are bullish vs bearish:
Stack Score Meaning
+6 All timeframes bullish → Strong Uptrend
+3 to +5 Majority bullish → Bullish Bias
0 Neutral / Mixed → Sideways Market
−3 to −5 Majority bearish → Bearish Bias
−6 All timeframes bearish → Strong Downtrend
Table Display
At the chosen chart corner, you’ll see:
TF Direction
1m 🟢 B (Bullish) / 🔴 S (Bearish)
3m 🟢 B (Bullish) / 🔴 S (Bearish)
5m 🟢 B (Bullish) / 🔴 S (Bearish)
15m 🟢 B (Bullish) / 🔴 S (Bearish)
30m 🟢 B (Bullish) / 🔴 S (Bearish)
60m 🟢 B (Bullish) / 🔴 S (Bearish)
Score Final alignment score (color-coded)
Color meanings:
🟢 Green cell = bullish for that TF
🔴 Red cell = bearish for that TF
The Score cell background color changes with strength:
Bright green → strong bull
Yellow → neutral
Red / Maroon → strong bear
How to Use for Trading (Intraday NIFTY 5m)
Recommended Chart: 5-minute timeframe on NIFTY Futures or major index stocks.
🔹 1. Identify Trend Alignment
When Score ≥ +3 → Market bias is bullish.
→ Look for long entries (buy breakouts or EMA retests).
When Score ≤ −3 → Market bias is bearish.
→ Look for short entries (sell breakdowns or retests).
When Score is between −2 and +2 → Trend is mixed.
→ Best to wait — avoid trading in choppy conditions.
🔹 2. Combine with Price Action
Use it with:
Trendline breaks or retests
Candle confirmation (e.g. bullish engulfing or rejection)
Volume surge
Example:
On NIFTY 5m — if score = +5, price breaks above a descending trendline, and 1m–15m EMAs are all rising → strong long signal.
🔹 3. Avoid Conflicts
If lower timeframes (1m/3m/5m) are bullish but higher ones (30m/60m) are bearish,
→ Trend is short-term bullish but larger bias is down — scalps only, not swings.
Optional Alerts
If you add alert conditions (as suggested earlier):
“Strong Bullish Alignment” triggers when score ≥ +5
“Strong Bearish Alignment” triggers when score ≤ −5
This gives you early alerts when full trend alignment occurs — ideal for breakout setups.
Some more Tips
Use 5m or 15m chart as your main view.
Use Stack Score as a trend filter — trade with it, not against it.
Combine with Breakout + Retest strategy or Trendline color-coded system you’re building.
In sideways days (score near 0), reduce risk or skip trades.
Gabriel's Squeeze Momentum📊 Gabriel’s Squeeze Momentum — Deluxe Volatility + Momentum Suite
An advanced, all-in-one squeeze & momentum framework that times volatility compression/expansion and trend shifts, with optional CVD (cumulative volume delta) momentum, ATR zone context, Discontinued Signal Lines (DSL) scalps, Colored DMI trend label, Williams VIX Fix (WVF) low-volatility exhaustion pings, Buff’s VTTI/VPCI volume confirmation, and real-time divergence detection.
What it does:
Discover Squeezes. They occur when volatility contracts, often preceding significant price moves.
Measures momentum with a fast, ATR-normalized linear regression—optionally on Price or CVD—so you see direction and “how hard it’s pushing.”
🧭 Signal Legend ~ Colors the squeeze so you instantly know regime:
🟡 / 🟣 (Tight/Very Tight): Coiled spring; prepare a plan.
🔴 / ⚫ = (Regular/Wide): Watch for Divergences between Price and Momentum.
🟢 (Fired): Expansion started; trade with momentum cross and bias.
Adds context bands at ±1/±2/±3 ATR (“trend / expansion / OB-OS”) to filter late or weak signals.
DSL (Discontinued Signal Lines) give early scalp flips on momentum vs. adaptive bands.
DMI label & triangles communicate trend strength and whether +DI / −DI is in control.
Williams VIX Fix flags capitulation/exhaustion style spikes (with optional VIX proxy).
VTTI/VPCI modules confirm when volume aligns with price trend or contradicts it.
Divergences (regular & hidden) auto-draw with optional live (may repaint) or on-close.
🎢 Squeeze Momentum — How the Logic Works 🎢
The Squeeze Momentum model is built on the principle of volatility compression and expansion. In markets, periods of low volatility are often followed by explosive moves, while high volatility eventually contracts. The “squeeze” seeks to identify these compression phases and prepare traders for the likely expansion that follows.
This indicator achieves that by comparing Bollinger Bands (BB) to Keltner Channels (KC).
Bands: Bollinger vs. Keltner
Bollinger Bands (BB): Calculated using a Simple Moving Average (SMA) of price and standard deviations (σ) of the closing price. The bands expand and contract depending on volatility.
Keltner Channels (KC): Built from an SMA plus/minus multiples of the Average True Range (ATR). Unlike some simplified squeeze indicators that approximate ATR, this implementation uses a true ATR-based KC, ensuring accuracy across different assets and timeframes.
By comparing whether the Bollinger Bands are inside or outside the Keltner Channels, the indicator identifies different squeeze regimes, each representing a distinct volatility environment.
📦 Regime Colors
The squeeze states are color-coded for quick interpretation:
🔹Wide Squeeze (⚫): BB inside KC with a high ATR multiplier. Extremely low volatility, often before major expansion.
🔹Normal Squeeze (🔴): BB inside KC with a moderate ATR multiplier (about 25% more sensitive than Wide). Typical compression setting.
🔹Narrow Squeeze (🟡): BB inside KC with a lower ATR multiplier (about 50% more sensitive than Wide). Signals tighter compression.
🔹Very Narrow Squeeze (🟣): BB inside KC with the lowest ATR multiplier (100% more sensitive than Wide). Indicates extreme coiling.
🔹Fired Squeeze (🟢): BB break outside KC. Marks the release of volatility and potential trend acceleration.
This multi-layered system improves upon classical SQZPRO by using precisely calculated Keltner Channels and multiple sensitivity levels, giving traders more granular information about volatility states.
🔒 Multi-Timeframe Support
The indicator automatically adjusts squeeze thresholds for different timeframes — hourly, 4-hour, daily, weekly, and monthly charts. Each regime has been manually tuned for its timeframe, allowing traders to use the same tool whether scalping, swing trading, or holding longer-term positions.
🎯 Momentum Core
Detecting a squeeze is only half the equation — the indicator also includes a momentum engine to determine direction and strength.
Price momentum is measured as the distance of Close from its Highest High and Lowest Low range, smoothed with a Simple Moving Average, and refined with Linear Regression.
This value is then divided by ATR, normalizing momentum relative to volatility.
Optionally, CVD Mode (Cumulative Volume Delta ÷ Volume) can replace price momentum for assets where order-flow and volume dynamics dominate (e.g., crypto).
🦆 Signal Line
Momentum is paired with a Simple Moving Average signal line:
🔹Bullish: Momentum > Signal.
🔹Bearish: Momentum < Signal.
This crossover logic provides directional bias and filters for false squeezes.
🚀 When to Use Price vs. CVD
CVD Mode (Crypto, FX with tick volume): Best for assets with strong volume/order-flow signals.
Price Mode (Equities, Commodities, Higher TFs): Best for assets with irregular or thin volume data.
🛢️ATR Zones (context filter) 🛢️
Its design is straightforward yet effective: it measures the difference between the current price from its highest highs, lowest lows, and a moving average over a chosen period, then expresses that difference in terms of the Average True Range (ATR) over the same period. By normalizing price deviations against volatility, ATR provides a clear sense of how far and how fast price is moving relative to its “normal” range.
Interpreting the Zone
Positive Values: When it is above zero, price is trading above its HH, LL, and moving average, suggesting bullish momentum. The higher the value, the stronger the momentum relative to volatility.
Negative Values: When the Momentum is below zero, price is trading below its HH, LL, and moving average, signaling bearish momentum. The deeper the reading, the stronger the downside pressure.
Magnitude Matters: Because the Momentum is expressed in ATR units, traders can immediately gauge whether the move is small (less than 1 ATR), moderate (1–2 ATRs), or extreme (3+ ATRs). This makes it especially useful for assessing overbought or oversold conditions in a normalized way.
Strengths:
🔹Volatility-Normalized: Unlike simple squeeze momentum oscillators that have different OB/OS levels, this Momentum adjusts for volatility. This makes signals more consistent across assets with different volatility profiles.
🔹Simplicity:
±1 ATR: trending zone (bulls above +1, bears below −1)
±2 ATR: expansion (keep, add, or trail). Stretch/risk of mean reversion.
±3 ATR: potential exhaustion/mean-revert zone.
🔹Momentum Clarity: By framing momentum in ATR terms, it is easier to distinguish between a small deviation from trend and a genuinely significant move. Sometimes it is a good sign that it trend to ±3/2 ATR, looks for similar directional moves.
Color: The script shades +2/+3 (OB) and −2/−3 (OS) areas and provides swing alerts at ±1 ATR.
💚 What Are Discontinued Signal Lines (DSL)? 💚
In technical analysis, one of the most common tools for smoothing out noisy data is the signal line. This concept appears in many indicators, such as the MACD or stochastic oscillator, where the raw value of an indicator is compared to a smoothed version of itself. The signal line acts as a lagging filter, making it easier to identify shifts in momentum, crossovers, and directional changes.
While useful, the classic signal line approach has limitations. By design, a single smoothed line introduces lag, which means traders may receive signals later than ideal. Additionally, a one-size-fits-all smoothing process often struggles to adapt to different levels of volatility or rapidly changing market conditions.
This is where Discontinued Signal Lines (DSL) come in. DSL is an advanced extension of the traditional signal line concept. Instead of relying on just one smoothed comparison, DSL employs multiple adaptive lines that adjust dynamically to the current state of the indicator. These adaptive lines effectively “discontinue” the dependence on a single, fixed smoothing method, producing a more flexible and nuanced representation of market conditions.
How DSL Works?
Traditional Signal Line: Compares an the Momentum against its own moving average. Provides crossover signals when the raw indicator value moves above or below the smoothed line.
Strength: reduces noise. Weakness: delayed signals and limited adaptability.
DSL Extension: Uses multiple adaptive lines that respond differently to the indicator’s current behavior. Instead of one static moving average, the DSL approach creates faster and slower “reaction lines.” These lines adapt dynamically, capturing acceleration or deceleration in the indicator’s state.
Result: Traders see how momentum is evolving across multiple adaptive thresholds. This reduces false signals and improves responsiveness in volatile conditions.
Benefits of Discontinued Signal Lines
🔹Nuanced Trend Detection
DSL doesn’t just flag when momentum changes direction—it shows the quality of that shift, highlighting whether it is gaining strength, losing steam, or consolidating.
🔹Adaptability Across Markets
Because DSL adjusts to the Momentum’s own dynamics, it works well across different asset classes and timeframes, from equities and futures to forex and crypto.
🔹Earlier Signal Recognition
Multiple adaptive lines allow traders to spot developing trends earlier than with a single smoothed signal line, without being overwhelmed by raw indicator noise.
🔹Better Confirmation
DSL is particularly useful for confirmation. If both adaptive lines agree then a fill is applied in the direction, confidence in the trend is higher as the color turns bull/bear.
🔹Practical Uses
Momentum Trading: Spot acceleration or deceleration in trend strength.
Trend Confirmation: Verify whether a breakout has momentum behind it.
Noise Filtering: Smooth out erratic moves while retaining adaptability.
⚖️ Colored Directional Movement Index (CDMI) ⚖️
The Directional Movement Index (DMI), created by J. Welles Wilder, is one of the most respected trend-following indicators in technical analysis. It is actually a family of three separate indicators combined into one: the +DI (Positive Directional Indicator), the –DI (Negative Directional Indicator), and the ADX (Average Directional Index). Together, they measure not only whether the market is trending but also the strength of that trend. Traders have used the DMI for decades to identify trend direction, gauge momentum, and filter out periods of market noise.
However, despite its reliability, the traditional DMI can be challenging to interpret. Reading three separate lines at once and extracting meaningful signals requires both experience and careful observation. This complexity often discourages newer traders from fully utilizing its power.
The Colored Directional Movement Index (CDMI) is a modern reinterpretation of Wilder’s classic tool. It condenses the same information into a single visual line while using color, shape, and density to communicate what’s happening beneath the surface. The goal is simple: make the DMI’s insights faster to read, easier to act upon, and more intuitive to integrate into trading decisions.
Key Features of CDMI
🔹Color Scale for Trend Strength
The main triangle changes its base color depending on the strength of the DI reading. Dark Red or Green, colors correspond to stronger trends, while faded Gray or lighter yellow tones signal weaker or fading trends. This makes it visually clear when the market is consolidating versus trending strongly.
🔹Color Density for Momentum
Beyond strength, the CDMI uses color density to represent momentum in the trend’s strength. If the ADX is rising (trend gaining momentum), the triangles grows more darker. If the ADX is falling (trend losing momentum), the triangle becomes paler. This provides an instant sense of whether a trend is accelerating or decelerating.
🔹Directional Triangles for Trend Direction
To replace the separate +DI and –DI lines, the CDMI plots small triangle shapes along the bottom axis. An upward-facing triangle indicates that +DI is dominant, confirming bullish direction. A downward-facing triangle signals –DI dominance, confirming bearish direction. This way, both strength and direction are shown without the clutter of multiple overlapping lines.
🔹Label Display for Detailed Values
For traders who want precise data alongside the visuals, CDMI includes a label that shows:
Current trend strength (ADX value).
Current +DI and –DI values.
Momentum status of the ADX (rising or falling).
Historical values of DMI readings, so traders can track how the indicator has evolved over time.
Tooltips are also available to explain “How to read the colored DMI line”, making this version more beginner-friendly.
Why CDMI Matters
The CDMI retains the proven reliability of Wilder’s DMI while solving its biggest drawback—interpretation difficulty. Instead of juggling three separate plots, traders get a single, information-rich line supplemented with intuitive shapes and labels. This streamlined format makes trend verification, momentum analysis, and signal confirmation much faster.
For trading applications, the CDMI can help:
Confirm Entries by showing whether the market is trending strongly enough to justify a position.
Avoid False Signals by filtering out periods of low ADX (weak trend).
Enhance Timing by tracking momentum shifts in trend strength.
By simplifying the complexity of the original DMI into an elegant, color-coded tool, the CDMI makes one of technical analysis’ most advanced indicators practical for everyday use.
😅 The VIX, the Williams Vix Fix, and Market Bottoms 😎
The VIX, formally known as the CBOE Volatility Index, has long been considered one of the most reliable indicators for spotting major market bottoms. Often referred to as the “fear gauge,” it measures the market’s expectation of volatility in the S&P 500 over the next 30 days. When fear grips investors and volatility spikes, the VIX rises sharply. Historically, these moments of extreme fear often coincide with powerful buying opportunities, as markets have a tendency to rebound once panic selling exhausts itself.
Larry Williams, a well-known trader and author, developed the Williams Vix Fix as a way to replicate the insights of the VIX across any tradable asset. While the VIX itself is tied specifically to S&P 500 options, Williams wanted a tool that could capture similar panic-driven dynamics in stocks, futures, forex, and other markets where the VIX is not directly applicable. His “fix” uses price action and volatility formulas to approximate the same emotional extremes reflected in the official VIX, creating almost identical results in practice. This makes the Williams Vix Fix a powerful addition to the trader’s toolbox, allowing the same principle that works on U.S. equities to be applied universally.
One of the most important characteristics of both the VIX and the Williams Vix Fix is that they are far more reliable at signaling market bottoms than market tops. The reason is psychological as much as it is mathematical. At market bottoms, fear and panic are widespread. Retail investors often capitulate, selling in a frenzy as prices drop. This panic drives volatility higher, producing the spikes we see in the VIX. At the same time, professional traders and institutions—those with larger capital and more disciplined strategies—tend to step in when volatility is stretched. They buy when others are fearful, using the panic of retail investors as an opportunity to acquire assets at discounted prices. This confluence of retail panic and institutional buying power is what makes the VIX such a strong bottom-finding tool.
In contrast, at market tops, the dynamic is very different. Tops tend not to be marked by panic or fear. Instead, they form quietly as enthusiasm fades, liquidity dries up, and buying interest wanes. Investors are often complacent, assuming prices will continue to rise, while professional money begins distributing their positions. Because there is no surge in fear, volatility remains muted, and the VIX does not offer a clear warning. This is why traders who rely on the VIX or the Williams Vix Fix must understand its limitations: it is exceptional for detecting bottoms but less useful for anticipating tops.
For traders, the lesson is straightforward. When you see the VIX or Williams Vix Fix spiking to extreme levels, it often indicates a high-probability environment for a rebound. These tools should not be used in isolation, but when combined with support levels, sentiment indicators, and market breadth, they can provide some of the most reliable bottom-fishing signals available. While no indicator is perfect, few have stood the test of time as consistently as the VIX—and thanks to Williams’ adaptation, its power can now be applied to nearly every market.
Indicator Signals (Great in risk-off charts):
🔹Flags spike events (tops/bottoms) with both original and filtered (AE/FE) criteria.
🔹Great as a risk overlay: tighten stops into AE/FE, or require “no spike” to enter.
🤯 Volume Comfirmation: VTTI & VPCI (Buff Dormeier) 🤯
Volume Trend Technical Indicator (VTTI)
The Volume Trend Technical Indicator (VTTI) is a momentum-style tool that analyzes how volume trends interact with price movement. Unlike basic volume measures that simply report how many shares or contracts were traded, the VTTI evaluates whether volume is expanding or contracting in the same direction as the prevailing price trend. The underlying logic is that healthy trends are supported by rising volume, while weakening trends often occur on shrinking volume.
At its core, VTTI looks at the rate of change in volume compared to price movements. By smoothing and normalizing these relationships, the indicator helps traders determine whether momentum is accelerating, decelerating, or diverging.
Rising VTTI: Suggests that volume is confirming the current price trend, strengthening the case for continuation. Flips BG Green after crossing it's signal.
Falling VTTI: Indicates that the trend may be losing participation, often a sign of possible consolidation or reversal. Flips BG Red after crossing it's signal.
Traders often use VTTI to filter entries and exits. For example, if price breaks out but VTTI does not rise above zero, the breakout may lack conviction. On the other hand, when both price and VTTI are aligned, probability of continuation improves.
Volume Price Confirmation Indicator (VPCI)
The Volume Price Confirmation Indicator (VPCI), developed by Buff Dormeier, takes the relationship between price and volume a step further. While traditional indicators like On-Balance Volume (OBV) or Chaikin Money Flow look at cumulative patterns, VPCI breaks price and volume into trend and volatility components and then recombines them to measure how well they confirm each other.
In essence, VPCI asks: “Does volume confirm what price is signaling?”
The formula integrates:
Price Trend Component – whether the market is trending upward or downward.
Volume Trend Component – whether trading activity supports that price trend.
Volatility Adjustments – to account for irregular swings.
The resulting oscillator fluctuates around a zero line:
Positive VPCI: Indicates that price and volume trends are in agreement (bullish confirmation).
Negative VPCI: Suggests that price and volume are diverging (bearish warning or false move).
Crossovers of Zero: Can serve as potential buy or sell signals, depending on context.
A key strength of VPCI is its sensitivity to divergence. When prices continue rising but VPCI begins falling, it often foreshadows a weakening rally. Conversely, a rising VPCI during a flat or down market can highlight early accumulation.
VTTI (Entry Signal) vs. VPCI (Exit Signal)
While both indicators study price-volume dynamics, their focus differs:
VTTI is simpler, emphasizing the trend of volume relative to price for momentum confirmation.
VPCI is more advanced, decomposing both price and volume into multiple components to produce a nuanced oscillator.
Used together, they provide complementary insights. VTTI helps quickly spot whether volume is supporting a move, while VPCI offers deeper confirmation and highlights subtle divergences.
Note: The Up/Down Volume Alert works better on the 4 HR, for Daily scalps or 30 minute for HR scalps. Intraday it's 2/10 minute.
🦅 Divergence toolkit 🦅
Divergences in Technical Analysis
Divergence occurs when the price action of an asset moves in one direction while a technical indicator, such as RSI, MACD, or Momentum, moves in the opposite direction. This disagreement between price and indicator often signals a shift in underlying market dynamics. Traders use divergences to anticipate either potential reversals or continuations in trends.
There are two main types of divergences: regular divergences, which typically precede reversals, and hidden divergences, which suggest continuation of the current trend.
Regular Divergence (Reversal Signals)
A regular divergence occurs when price and indicator disagree during a trend extension. These divergences signal that momentum is no longer fully supporting the current trend and that a reversal may be imminent.
🔹Regular Bullish Divergence
Price Action: Forms a lower low.
Indicator: Forms a higher low.
Interpretation: Price is making new lows, but the indicator is gaining strength. This suggests that selling pressure is weakening, and a reversal to the upside may occur.
Example: RSI rising while price dips to fresh lows.
🔹Regular Bearish Divergence
Price Action: Forms a higher high.
Indicator: Forms a lower high.
Interpretation: Price is reaching new highs, but the indicator shows weakening momentum. This implies that buying pressure is fading, warning of a potential downside reversal.
Example: MACD histogram falling while price makes higher highs.
Regular divergences are often spotted near the end of trends and are most powerful when aligned with key support/resistance levels or overbought/oversold conditions.
Hidden Divergence (Continuation Signals)
A hidden divergence occurs during retracements within a trend. Unlike regular divergences, hidden divergences suggest that the prevailing trend still has strength and is likely to continue.
🔹Hidden Bullish Divergence
Price Action: Forms a higher low.
Indicator: Forms a lower low.
Interpretation: Price is retracing within an uptrend, but the indicator is overshooting downward. This shows that momentum remains intact, supporting continuation upward.
🔹Hidden Bearish Divergence
Price Action: Forms a lower high.
Indicator: Forms a higher high.
Interpretation: Price is retracing within a downtrend, while the indicator overshoots upward. This indicates that bearish momentum remains strong, supporting continuation downward.
Hidden divergences often appear during pullbacks, helping traders time entries in the direction of the prevailing trend.
Practical Use of Divergences
🔹Trend Reversal Alerts – Regular divergences are early warnings that a trend may be ending.
🔹Trend Continuation Signals – Hidden divergences help confirm that retracements are simply pauses, not full reversals.
🔹Confluence with Other Tools – Divergences are more reliable when combined with support/resistance, candlestick patterns, or volume analysis.
🔹Multi-Timeframe Analysis – Spotting divergences on higher timeframes often produces stronger signals.
🕭🔔🛎️ Alert 🛎️🔔🕭
🔹Squeeze
🟢 Fired Squeeze
⚫ Low (Wide) Squeeze / 🔴 Normal / 🟡 Tight / 🟣 Very Tight
🔹Momentum
🐂 Bullish Trend Reversal (Crossover of Momentum and Signal from sub −2)
🐻 Bearish Trend Reversal (Crossover of Momentum and Signal from above +2)
📈 Bullish Swing (cross above +1 ATR) / 📉 Bearish Swing (cross below −1 ATR)
🔹DSL
💚 Bullish DSL Scalp / 💔 Bearish DSL Scalp
🔹Volume
🎯 Strong Up Volume (VPCI > 0 and VTTI up)
⏳ Strong Down Volume (VPCI < 0 and VTTI down)
🔹Divergences
🦅 Bullish, 🦆 Bearish, 🦅 Bullish Hidden, 🦆 Bearish Hidden
Management: Search Vanguard ETFs in your browser, look up full list of VOO holdings. Download it, or copy paste all the ticker symbols. Place that with a AI, just ask it to place , in between each ticker. NVDA, TSLA, AVGO, etc. Create a new watchlist, in the + add all tickers separated by commas. Place a watchlist alert ⚠️ only available for premium + subscribers.
Practical playbook
1) Classic Squeeze Break
Setup: 🔴(D)/🟡(2D)/🟣(3D) squeeze → wait for 🟢(1HR) Fired.
Confirm: Momentum > Signal and above +1 ATR (or DMI strong & rising).
Manage: add on pullbacks that hold +1 ATR; scale near +2 ATR or WVF AE/FE.
2) DSL Scalp in Trend
Setup: Clear trend (DMI strong) + DSL bull/bear trigger in the direction of trend.
Filter: avoid tight/very tight yellow/purple unless you want micro-scalps.
Exit: opposite DSL or ATR midline loss.
3) Mean-Reversion Fade
Setup: Momentum extended to ±3 ATR, WVF spike, and a regular divergence.
Entry: Counter signal only when mom crosses back through ±3 ATR toward mid. Exit early if squeeze ⚫/🔴, Momentum may extend to ±3/2 ATR in the same direction.
Risk: reduce size; this is a fade, not trend following.
4) Volume-Confirmed Breakout
Setup: Squeeze → 🟢 Fired + VPCI > 0 and VTTI up → trend continuation.
Manage: trail behind +1 ATR (long) or −1 ATR (short). 9 SMA works good.
Inputs at a glance (key ones)
Mode: Price or CVD momentum; Squeeze Sensitivity (σ); Momentum Length; Signal Length; ATR Smoothing.
🧮 Colors:
SQZMOM: per squeeze regime, momentum, ATR fills.
DSL: On/Off, Fast/Slow, Length.
ATR Zones: Bullish/Bearish levels (±1), ±2/±3 zone lines & fills.
DMI: Lengths, key & weak thresholds, label on/off.
WVF/VIX: Lookbacks, bands, AE/FE toggles, VIX proxy symbol.
VTTI/VPCI: Fast/slow/signal (VTTI), Short/Long (VPCI), and volume source (Tick/CVD/NVI/PVI/OBV/PVT/AccDist/VWAP).
Divergences: Regular/Hidden toggles, Sensitivity %, Lifetime, Live vs On-Close, Lines/Labels.
🔎 Suggested defaults (feel free to tweak)
Calibration: Size Momentum, so that when it's above zero the asset is trending up. For the signal, it can be kept the same or lower.
Intraday (60–240m): σ = 2.0, 18~20, 3~5, DSL Fast, DMI key 23, weak 17.
Daily/Weekly: keep σ = 2.0, consider DSL Slow, DMI key 25, weak 20, widen ATR filters; lean on VPCI/VTTI (4-HR).
CVD mode: use where tick/volume quality is high (index futures, liquid equities, crypto majors).
🪟 Tips & caveats
Swing Screener: Favor liquid underlyings (index futures/ETFs, large caps). Large-Cap, 2 M Vol, Mid-Cap, 500K Vol. Squeeze: BB( 20) upper < KC (20) upper, and BB (20) lower > KC (20) lower. Optional: Price above 9 SMA, 21 SMA, and 50 SMA, they are my SMA of choice. 200 SMA too, unless you are willing to fish in a bear market. Vice-versa for shorts. Optional: ADX 4 HR > 17, or 23 depending on what you are looking for.
Scalp Screener: Same as above, change the D 9 SMA to 5, and the BB/KC from D to 1 HR. Scalps may last 2~3 days.
Position Screener: Change all daily setting to W, aside from Volume. Optional: PEG < 1.5, FCF > 0, ROA > 8% or ROE > 6%.
Good with Moving averages (9/21/50) and low-volume zones.
Position size by IV, ATR, and account risk. Consider stop/hedge rules around ±2/±3 ATR.
Let alerts stage your watchlist; act only on combined squeeze + momentum signals.
Divergences in live mode can repaint (Real-Time); for algo or alerts, use on-close.
Tight/Very tight squeezes are great for scalps but choppy; combine with DMI rising + VPCI>0.
±3 ATR is exhaustion context, not an auto-fade—look for WVF/Div/DSL confirmation.
For alerts, pair “Fired Squeeze + Bullish Swing” (or bearish) to avoid false starts.
🎯 How to Trade Entry ~ Recap:
Tight/very tight squeeze → fires → momentum crosses up (or DSL bull).
Exit/Flip: Momentum crosses down into/after expansion or hits +2/+3 ATR with fade signs. Filter: Avoid fresh longs at +3 ATR; avoid fresh shorts at −3 ATR unless fading with confirmation.
📐 Options Integrations
✅ Risk Reversal/Modified Risk Reversal (Bullish: Short Put + Long Call)
Use when: Squeeze fires up from 🟡/🟣 and momentum crosses above signal (or zero/DSL).
Playbook Entry: On or just after the bullish fire and momentum upcross. DMI or Volume supports trend as well.
Structure: Sell a put at/just below the −2 ATR reference (or recent swing support). Buy a call at/above the breakout zone (prior high/mid-range +1 to +2 ATR).
A classic risk reversal is a long call plus a short put. That’s a very bullish structure—you gain if the price rallies (via the call), and you collect a premium by selling a put. But it has a naked downside risk. The modified risk reversal fixes that by adding a long lower put (making the short put into a defined put credit spread).
Management: If momentum stays above signal, ride toward +2 → +3 ATR. Sell the put near the current price → receive big premium. Buy the lower put → spend part of that premium (risk cap). Buy the call above the current price → spend more, but the short put premium mostly pays for it.
Exits/Adjust: Momentum downcross or squeeze flips back on (new compression) → reduce. If price retests −1/−2 ATR and holds, you can roll the short put down/out.
Breakout = Big Success; No Breakout = you keep the initial credit. Reversal = Max loss is capped by the long lower put.
✅ Iron Condor (Neutral: Short OTM Put Spread + Short OTM Call Spread)
Use when: Squeeze is active (🟡/🟣), momentum is flat near zero, and there is no directional edge. 🟢 lasts for around 5~8 bars typically. I measure the historical duration of it, and wait for a range period to occur.
Playbook Entry: During compression, set wings outside ±2 ATR (or recent range extremes). I prefer identifying boxes where the rectangle pattern occurs on the chart.
Management: Time decay works while price remains trapped in the coil. High-winrate ~80%, but 1 loser can wipe most of the gains.
Exits/Adjust: If a squeeze fires and momentum breaks hard one way, close the losing side, consider converting to a vertical or rotating to a directional spread aligned with momentum.
4HR-Bullish, closing one wing:
Tip: Align daily/weekly context with your intraday entries. 9 > 50 on Weekly, similar on Daily. Sell premium into compression; switch to directional spreads on expansion and momentum confirmation.
✅ Naked Call/Puts (Directional: 10~30 Delta Calls)
Stick to naked calls and puts when the squeezes are fired from either 🔴 or ⚫.
Look for Strikes slightly out of the money with an OI and Volume spread less than <10%.
If Strike Date is >45, manage 21 Days before expiration. Scalp: Expiration Strikes of 1/4 of the Squeeze period. Leap: Expiration Strikes of 1.75x of the Squeeze period.
📐 Futures Integrations
Playbook Entry:
Verify if the squeeze on the hourly is red or green, and enter on the 2- or 5-minute during a similar squeeze state.
Trend-Following: Traditional 2 Renko Block above 21 SMA and Momentum is bullish, or vice versa. (2~ES, 5~NQ)
Structure: Go long at/just below the ATR reference (or recent swing support). Exit below the breakout zone (prior high/mid-range +1 to +2 ATR).
Management: If momentum stays above +1 ATR ride toward +2 → +3 ATR, etc. House-money, should be kept.
Exits/Adjust: Momentum downcross or squeeze flips back on (new compression) → exit. On Renko Charts, lower the sensitivity to 0.7~1. If price retests 0/−1/−2 ATR and holds, you can enter when the 9 SMA flips. The 50 SMA is better for Daily and up; I wouldn't trade against it then.
📌 FOMO Trading Playbook
Credits & License
Credits: @JF10R (Multi-Timeframe Squeeze), @BigBeluga (DSL), @OskarGallard (Colored DMI base), @ChrisMoody (WVF ideas), @PineCodersTASC (VTTI/VPCI), @EliCobra (Divergence toolkit).
License: Mozilla Public License 2.0 (MPL-2.0).
Author: © GabrielAmadeusLau
Emperor RSI CandleDescription:
The Emperor RSI Candle is a real-time, non-lagging trading indicator that colors candles based on RSI (Relative Strength Index) levels. It offers instant visual feedback on market momentum, making it easy to identify trend strength, overbought/oversold zones, and potential reversals with precision.
Unlike traditional RSI indicators, which display RSI values in a separate panel, Emperor RSI Candle integrates RSI signals directly into the candles, providing a cleaner, more intuitive charting experience. Its multi-timeframe RSI box shows RSI values across different timeframes, offering confluence confirmation for better trade decisions.
🔥 Emperor RSI Candle is original because it includes a multi-timeframe RSI box that displays RSI values from:
1 min → Monthly timeframes simultaneously.
📊 How this is unique:
Traders can instantly compare RSI values across different timeframes.
This helps them spot confluence and divergences, which is not possible with standard RSI indicators.
The multi-timeframe confluence feature makes the indicator highly effective for both short-term and long-term traders.
🚀 What the script does:
Real-time candle coloring based on RSI levels.
Multi-timeframe RSI box for confluence insights.
Customizable RSI settings for adaptability.
How it benefits traders:
Instant visual feedback for momentum and reversals.
No lag signals for precise trading decisions.
Flexible customization for different trading styles.
Unique visual signals:
Green, red, parrot green, and blue candles → Clearly indicating bullish/bearish momentum and overbought/oversold zones.
Multi-timeframe RSI box → For cross-timeframe confluence.
⚡️ 🔥 UNIQUE FEATURES 🔥:
✅ Multi-Timeframe RSI Box:
Displays RSI values from 1 min to monthly timeframes, helping traders confirm confluence across different timeframes.
✅ Fully Customizable RSI Levels & Display:
Modify RSI thresholds, source, and appearance to fit your trading style.
✅ Dynamic Candle Borders for Weak Signals:
Green border → Weak bullishness (RSI between 50-60).
Red border → Weak bearishness (RSI between 40-50).
✅ Lag-Free, Real-Time Accuracy:
No repainting or delay—instant visual signals for accurate decisions.
✅ Scalable for Any Trading Style:
Perfect for both intraday scalping and positional trading.
📊 🔥 HOW IT WORKS 🔥:
The indicator dynamically colors candles based on RSI values, providing real-time visual signals:
🟢 Above 60 RSI → Green candle:
Indicates bullish momentum, signaling potential upward continuation.
🟩 Above 80 RSI → Parrot green candle:
Overbought zone → Possible reversal or profit booking.
🟥 Below 40 RSI → Red candle:
Signals bearish momentum, indicating potential downward continuation.
🔵 Below 20 RSI → Blue candle:
Oversold zone → Possible reversal opportunity.
🔲 Neutral candles:
50-60 RSI → Green border: Weak bullishness.
40-50 RSI → Red border: Weak bearishness.
📊 🔥 MULTI-TIMEFRAME RSI BOX 🔥:
The Emperor RSI Candle includes an RSI box displaying multi-timeframe RSI values from 1 min to monthly. This provides:
✅ Confluence confirmation:
Compare RSI across multiple timeframes to strengthen trade conviction.
✅ Spot divergences:
Identify hidden trends by comparing smaller and larger timeframes.
✅ Validate trade entries/exits:
Use higher timeframe RSI to confirm smaller timeframe signals
⚙️ 🔥 HOW TO USE IT 🔥:
To maximize the accuracy and clarity of Emperor RSI Candle, follow these steps:
🔧 STEP 1: Chart Settings Configuration
Go to Chart Settings → Symbols
Uncheck the following options:
Body
Borders
Wick
✅ This ensures that only the Emperor Candle colors are visible, making the signals clear and distinct.
🔧 STEP 2: Style Settings for Emperor Candle
After applying the Emperor RSI Candle:
Go to Settings → Style tab
Wick section:
Select Color 2 and Color 3 → Set Opacity to 100%.
Border section:
Select Color 2 and Color 3 → Set Opacity to 100%.
✅ This ensures the candles display with full visibility and accurate colors.
⚙️ 🔥 CUSTOMIZATION OPTIONS 🔥:
Emperor RSI Candle offers full flexibility to match your trading style:
✅ RSI Length:
Modify the period used for RSI calculation (default: 10).
✅ Top & Bottom Levels:
Adjust the overbought (default: 80) and oversold (default: 20) thresholds.
✅ Intermediate Levels:
Up Level: Default: 60 → Bullish RSI threshold.
Down Level: Default: 40 → Bearish RSI threshold.
Mid Level: Default: 50 → Neutral zone.
✅ RSI Source:
Select the price source for RSI calculation (Close, Open, High, Low).
✅ RSI Period:
Customize the RSI calculation period (default: 10).
✅ Font Size:
Adjust the RSI box font size for better visibility.
✅ Box Position:
Choose where to display the RSI box:
Top Left / Top Center / Top Right
Bottom Left / Bottom Center / Bottom Right
💡 🔥 HOW IT IMPROVES TRADING 🔥:
✅ Clear trend identification:
Instantly recognize bullish, bearish, or neutral conditions through candle colors.
✅ Precise entries and exits:
Spot overbought and oversold zones with visual clarity.
✅ Multi-timeframe confirmation:
Validate trades with RSI confluence across multiple timeframes.
✅ No lag, real-time accuracy:
Immediate visual signals for faster and more reliable trade decisions.
✅ Customizable settings:
Tailor the indicator to fit your trading strategy and preferences.
✅ Works for all trading styles:
Suitable for scalping, day trading, and swing trading.
🔥How Traders Can Use Emperor RSI Candle for Trading:
🟢 Green Candles (Above 60 RSI) → Bullish Momentum:
Indicates strong upward movement → Ideal for long entries.
Traders can hold until RSI approaches 80 for profit booking.
🟥 Red Candles (Below 40 RSI) → Bearish Momentum:
Signals strong downward movement → Ideal for short trades.
Traders can exit or book profits near RSI 20.
2. Spotting Overbought and Oversold Zones for Reversals:
🟩 Parrot Green Candles (Above 80 RSI) → Overbought Zone:
Indicates potential for reversals or profit booking.
Traders can tighten stop-losses or exit positions.
🔵 Blue Candles (Below 20 RSI) → Oversold Zone:
Signals a potential reversal opportunity.
Traders can look for buy signals with confluence confirmation.
3. Catching Weak Bullish and Bearish Trends with Border Colors:
🟢 Green Border (RSI 50-60) → Weak Bullishness:
Indicates mild upward momentum.
Traders can consider cautious long entries.
🔴 Red Border (RSI 40-50) → Weak Bearishness:
Indicates mild downward pressure.
Traders can consider cautious short entries.
4. Using the RSI Multi-Timeframe Box for Confluence:
✅ Displays RSI values from 1 min to monthly timeframes.
Usage:
Confluence confirmation:
Multiple timeframes showing bullish RSI → Strong uptrend → Reliable buy signals.
Multiple timeframes showing bearish RSI → Strong downtrend → Reliable sell signals.
Spotting divergences:
If lower timeframes are bullish but higher timeframes are bearish, it indicates a potential reversal.
5. Customization Tips for Different Trading Styles:
✅ For Scalping:
Use a smaller RSI period (9-10) for faster signals.
Check the multi-timeframe RSI box to confirm signals quickly.
✅ For Swing Trading:
Use the default RSI period (14-15) for more accurate signals.
Focus on higher timeframes (1 hr, 4 hr, daily) for stronger trend confirmation.
YinYang TrendTrend Analysis has always been an important aspect of Trading. There are so many important types of Trend Analysis and many times it may be difficult to identify what to use; let alone if an Indicator can/should be used in conjunction with another. For these exact reasons, we decided to make YinYang Trend. It is a Trend Analysis Toolkit which features many New and many Well Known Trend Analysis Indicators. However, everything in there is added specifically for the reason that it may work well in conjunction with the other Indicators prevalent within. You may be wondering, why bother including common Trend Analysis, why not make everything unique? Ideally, we would, however, you need to remember Trend Analysis may be one of the most common forms of charting. Therefore, many other traders may be using similar Trend Analysis either through plotting manually or within other Indicators. This all boils down to Psychology; you are trading against other traders, who may be seeing some of the similar information you are, and therefore, you may likewise want to see this information. What affects their trading decisions may affect yours as well.
Now enough about Trend Analysis, what is within this Indicator, and what does it do? Well, first let’s quickly mention all of its components, then we will, through a Tutorial, discuss each individually and finally how each comes together as a cohesive whole. This Indicator features many aspects:
Bull and Bear Signals
Take Profit Signals
Bull and Bear Zones
Information Tables displaying: (Boom Meter, Bull/Bear Strength, Yin/Yang State)
16 Cipher Signals
Extremes
Pivots
Trend Lines
Custom Bollinger Bands
Boom Meter Bar Colors
True Value Zones
Bar Strength Indexes
Volume Profile
There are many things to cover within our Tutorial so let's get started, chronologically from the list above.
Tutorial:
Bull and Bear Signals:
We’ve zoomed out quite a bit for this example to help give you a broader aspect of how these Bull and Bear signals work. When a signal appears, it is displaying that there may be a large amount of Bullish or Bearish Trend Analysis occurring. These signals will remain in their state of Bull or Bear until there is enough momentum change that they change over. There are a couple Options within the Settings that dictate when/where/why these signals appear, and this example is using their default Settings of ‘Medium’. They are, Purchase Speed and Purchase Strength. Purchase Speed refers to how much Price Movement is needed for a signal to occur and Purchase Strength refers to how many verifications are required for a signal to occur. For instance:
'High' uses 15 verifications to ensure signal strength.
'Medium' uses 10 verifications to ensure signal strength.
'Low' uses 5 verifications to ensure signal strength.
'Very Low' uses 3 verifications to ensure signal strength.
By default it is set to Medium (10 verifications). This means each verification is worth 10%. The verifications used are also relevant to the Purchase Speed; meaning they will be verified faster or slower depending on its speed setting. You may find that Faster Speeds and Lower Verifications may work better on Higher Time Frames; and Slower Speeds and Higher Verifications may work better on Lower Time Frames.
We will demonstrate a few examples as to how the Speed and Strength Settings work, and why it may be beneficial to adjust based on the Time Frame you’re on:
In this example above, we’ve kept the same Time Frame (1 Day), and scope; but we’ve changed Purchase Speed from Medium->Fast and Purchase Strength from Medium-Very Low. As you can see, it now generates quite a few more signals. The Speed and Strength settings that you use will likely be based on your trading style / strategy. Are you someone who likes to stay in trades longer or do you like to swing trade daily? Likewise, how do you go about identifying your Entry / Exit locations; do you start on the 1 Day for confirmation, then move to the 15/5 minute for your entry / exit? How you trade may determine which Speed and Strength settings work right for you. Let's jump to a lower Time Frame now so you can see how it works on the 15/5 minute.
Above is what BTC/USDT looks like on the 15 Minute Time Frame with Purchase Speed and Strength set to Medium. You may note that the signals require a certain amount of movement before they get started. This is normal with Medium and the amount of movement is generally dictated by the Time Frame. You may choose to use Medium on a Lower Time Frame as it may work well, but it may also be best to change it to a little slower.
We are still on the 15 Minute Time Frame here, however we simply changed Purchase Speed from Medium->Slow. As you can see, lots of the signals have been removed. Now signals may ‘hold their ground’ for much longer. It is important to adjust your Purchase Speed and Strength Settings to your Time Frame and personalized trading style accordingly.
Above we have now jumped down to the 5 Minute Time Frame. Our Purchase Speed is Slow and our Purchase Strength is Medium. We can see it looks pretty good, although there is some signal clustering going on in the middle there. If we change our Settings, we may be able to get rid of that.
We have changed our Purchase Speed from Slow->Snail (Slowest it can go) and Purchase Strength from Medium->Very Low (Lowest it can go). Changing it from Slow-Snail helped get rid of the signal clustering. You may be wondering why we lowered the Strength from Medium->Very Low, rather than going from Medium->High. This is a use case scenario and one you’ll need to decide for yourself, but we noticed when we changed the Speed from Slow->Snail that the signal clustering was gone, so then we checked both High and Very Low for Strengths to see which produced the best looking signal locations.
Please remember, you don’t have to use it the exact way we’ve displayed in this Tutorial. It is meant to be used to suit your Trading Style and Strategy. This is why we allow you to modify these settings, rather than just automating the change based on Time Frames. You’ll likely need to play around with it, as you’ll notice different settings may work better on certain pairs and Time Frames than others.
Take Profit Signals:
We’ve reset our Purchase Settings, everything is on defaults right now at Medium. We’ve enabled Take Profit signals. As you can see there are both Take Profit signals for the Bulls and the Bears. These signals are not meant to be used within automation. In fact, none of this indicator is. These signals are meant to show there has been a strong change in momentum, to such an extent that the signal may switch from its current (Bull or Bear) and now may be a good time to Take Profit. Your Take Profit Settings likewise has a Speed and Strength, and you can set them differently than your Purchase Settings. This is in case you want to Take Profit in a different manner than your Purchase Signals. For instance:
In the example above we’ve kept Purchase Strength and Speed at Medium but we changed our Take Profit Speed from Medium->Snail and our Take Profit Strength from medium->Very Low. This greatly reduces the amount of Take Profit signals, and in some cases, none are even produced. This form of Take Profit may act more as a Trailing Take Profit that if it’s not hit, nothing appears.
In this example we have changed our Purchase Speed from Medium->Fast, our Purchase Strength from Medium->Very Low. We’ve also changed our Take Profit Speed from Snail->Medium and kept our Take Profit Strength on Very Low. Now we may get our signals quicker and likewise our Take Profit may be more rare. There are many different ways you can set up your Purchase and Take Profit Settings to fit your Trading Style / Strategy.
Bull and Bear Zones:
We have disabled our Take Profit locations so that you can see the Bull and Bear Zones. These zones change color when the Signals switch. They may represent some strong Support and Resistance locations, but more importantly may be useful for visualizing changes in momentum and consolidation. These zones allow you to see various Moving Averages; and when they start to ‘fold’ (cross) each other you may see changes in momentum. Whereas, when they’re fully stretched out and moving all in the same direction, it can provide insight that the current rally may be strong. There is also the case where they look like they’re ‘twisted’ together. This happens when all of the Moving Averages are very close together and may be a sign of Consolidation. We will go over a few examples of each of these scenarios so you can understand what we’re referring to.
In this example above, there are a few different things happening. First we have the yellow circle, where the final and slowest Moving Average (MA) crossed over and now all of the MA’s that form the zone are Bullish. You can see this in the white circle where there are no MA’s that are crossing each other. Lastly, within the blue circle, we can see how some of the faster MA’s are crossing under each other. This is a bullish momentum change. The Faster moving MA’s will always be the first ones to cross before the Slower ones do. There is a color scheme in place here to represent the Speed of the MA within the Zone. Light blue is the fastest moving Bull color -> Light Green and finally -> Dark Green. Yellow is the fastest moving Bear color -> Orange and finally -> Red / Dark Red within the Zone.
Next we will review a couple different examples of what Consolidation looks like and why it is very important to look out for. Consolidation is when Most, if not All of the MA’s are very tightly ‘twisted’ together. There is very little spacing between almost all of the MA’s in the example above; highlighted by the white circle. Consolidation is important as it may indicate a strong price movement in either direction will occur soon. When the price is consolidating it means it has had very little upwards or downwards movement recently. When this happens for long enough, MA’s may all get very similar in value. This may cause high volatility as the price tries to break out of Consolidation. Let's look at another example.
Above we have two more examples of what Consolidation looks like and how high Volatility may occur after the Consolidation is broken. Please note, not all Consolidation will create high Volatility but it is something you may want to look out for.
Information Tables displaying: (Boom Meter, Bull/Bear Strength, Yin/Yang State):
Information tables are a very important way of displaying information. It contains 3 crucial pieces of information:
Boom Meter
Bull/Bear Strength
Yin/Yang State
Boom Meter is a meter that goes from 0-100% and displays whether the current price is Dumping (0 - 29%), Consolidating (30 - 70%) or Pumping (71 - 100%). The Boom Meter is meant to be a Gauge to how the price is currently fairing. It is composed of ~50 different calculations that all vary different weights to calculate its %. Many of the calculations it uses are likewise used in other things, such as the Bull/Bear Strength, Bull/Bear Zone MA cross’, Yin/Yang State, Market Cipher Signals, RSI, Volume and a few others. The Boom Meter, although not meant to be used solely to make purchase decisions, may give you a good idea of current market conditions considering how many different things it evaluates.
Bull/Bear Strength is relevant to your Purchase Speed and Strength. It displays which state it is currently in, and the % it is within that state. When a % hits 0, is when the state changes. When states change, they always start at 100% initially and will go down at the rate of Purchase Strength (how many verifications are needed). For instance, if your Purchase Strength is set to ‘Medium’ it will move 10% per verification +/-, if it is set to High, it will move 6.67% per verification +/-. Bull/Bear Strength is a good indicator of how well that current state is fairing. For instance if you started a Long when the state changed to Bull and now it is currently at Bull with 20% left, that may be a good indication it is time to get out (obviously refer to other data as well, but it may be a good way to know that the state is 20% away from transitioning to Bear).
Yin/Yang State is the strongest MA cross within our Indicator. It is unique in the sense that it is slow to change, but not so much that it moves slowly. It isn’t as simple as say a Golden/Death Cross (50/200), but it crosses more often and may hold similar weight as it. Yin stands for Negative (Bearish) and Yang stands for Positive (Bullish). The price will always be in either a state of Yin or Yang, and just because it is in one, doesn’t mean the price can’t/won’t move in the opposite direction; it simply means the price may be favoring the state it is in.
16 Cipher Signals:
Cipher Signals are key visuals of MA cross’ that may represent price movement and momentum. It would be too confusing and hard to decipher these MA’s as lines on a chart, and therefore we decided to use signals in the form of symbols instead. There are 12 Standard and 4 Predictive/Confirming Cipher signals. The Standard Cipher signals are composed of 6 Bullish and 6 Bearish (they all have opposites that balance each other out). There can never be 2 of the same signal in a row, as the Bull and Bear cancel each other out and it's always in a state of one or the other. When all 6 Bullish or Bearish signals appear in a row, very closely together, without any of the opposing signals it may represent a strong momentum movement is about to occur.
If you refer to the example above, you’ll see that the 6 Bullish Cipher signals appeared exactly as mentioned above. Shortly after the Green Circle appeared, there was a large spike in price movement in favor of the Bulls. Cipher signals don’t need to appear in a cluster exactly like the white circle in this photo for momentum to occur, but when it does, it may represent volatility more than if it is broken up with opposing signals or spaced out over a longer time span.
Above is an example of the opposite, where all 6 Bearish Cipher signals appeared together without being broken by a Bullish Cipher signal or being too far spaced out. As you can see, even though past it there was a few Bullish signals, they were quickly reversed back to Bearish before a large price movement occurred in favor of the Bears.
In the example above we’ve changed Cipher signals to Predictive and Confirming. Support Crosses (Green +) and Blood Diamonds (Red ♦) are the normal Cipher Signals that appear within the Standard Set. They are the first Cipher Signal that appears and are the most common ones as well. However, just because they are the first, that doesn’t mean they aren’t a powerful Cipher signal. For this reason, there are Predictive and Confirming Cipher signals for these. The Predictive do just that, they appear slightly sooner (if not the same bar) as the regular and the Confirming appear later (1+ bars usually). There will be times that the Predictive appears, but it doesn’t resort to the Regular appearing, or the Regular appears and the Confirming doesn’t. This is normal behavior and also the purpose of them. They are meant to be an indication of IF they may appear soon and IF the regular was indeed a valid signal.
Extremes:
Extremes are MA’s that have a very large length. They are useful for seeing Cross’ and Support and Resistance over a long period of time. However, because they are so long and slow moving, they might not always be relevant. It’s usually advised to turn them on, see if any are close to the current price point, and if they aren’t to turn them off. The main reason being is they stretch out the chart too much if they’re too far away and they also may not be relevant at that point.
When they are close to the price however, they may act as strong Support and Resistance locations as circled in the example above.
Pivots:
Pivots are used to help identify key Support and Resistance locations. They adjust on their own in an attempt to keep their locations as relevant as possible and likewise will adjust when the price pushes their current bounds. They may be useful for seeing when the Price is currently testing their level as this may represent Overbought or Oversold. Keep in mind, just because the price is testing their levels doesn’t mean it will correct; sometimes with high volatility or geopolitical news, movement may continue even if it is exhibiting Overbought or Oversold traits. Pivots may also be useful for seeing how far the price may correct to, giving you a benchmark for potential Take Profit and Stop Loss locations.
Trend Lines:
Trend Lines may be useful for identifying Support and Resistance locations on the Vertical. Trend Lines may form many different patterns, such as Pennants, Channels, Flags and Wedges. These formations may help predict and drive the price in specific directions. Many traders draw or use Indicators to help create Trend Lines to visualize where these formations will be and they may be very useful alone even for identifying possible Support and Resistance locations.
If you refer to the previous example, and now to this example, you’ll notice that the Trend Line that supported it in 2023 was actually created in June 2020 (yellow circle). Trend Lines may be crucial for identifying Support and Resistance locations on the Vertical that may withhold over time.
Custom Bollinger Bands:
Bollinger Bands are used to help see Movement vs Consolidation Zones (When it's wide vs narrow). It's also very useful for seeing where the correction areas may be. Price may bounce between top and bottom of the Bollinger Bands, unless in a pump or dump. The Boom Meter will show you whether it is currently: Dumping, Consolidation or Pumping. If combined with Boom Meter Bar Colors it may be a good indication if it will break the Bollinger Band (go outside of it). The Middle Line of the Bollinger Band (White Line) may be a very strong support / resistance location. If the price closes above or below it, it may be a good indication of the trend changing (it may indicate one of the first stages to a pump or dump). The color of the Bollinger Bands change based on if it is within a Bull or Bear Zone.
What makes this Bollinger Band special is not only that it uses a custom multiplier, but it also incorporates volume to help add weight to the calculation.
Boom Meter Bar Colors:
Boom Meter Bar Colors are a way to see potential Overbought and Oversold locations on a per bar basis. There are 6 different colors within the Boom Meter bar colors. You have:
Overbought and Very Bullish = Dark Green
Overbought and Slightly Bullish = Light Green
Overbought and Slight Bearish = Light Red
Oversold and Very Bearish = Dark Red
Oversold and Slightly Bearish = Orange
Oversold and Slightly Bullish = Light Purple
When there is no Boom Meter Bar Color prevalent there won’t be a color change within the bar at all.
Just because there is a Boom Meter Bar Color change doesn’t mean you should act on it purchase or sell wise, but it may be an indication as to how that bar is fairing in an Overbought / Oversold perspective. Boom Meter Bar Colors are mainly based on RSI but do take in other factors like price movement to determine if it is Overbought or Oversold. When it comes to Boom Meter Bar Color, you should take it as it is, in the sense that it may be useful for seeing how Individual bars are fairing, but also note that there may be things such as:
When there is Very Overbought (Dark Green) or Very Oversold (Dark Red), during massive pump or dumps, it will maintain this color. However, once it has lost ‘some’ momentum it will likely lose this color.
When there has been a massive Pump or Dump, and there is likewise a light purple or light red, this may mean there is a correction or consolidation incoming.
True Value Zones:
True Value zones are our custom way of displaying something that is similar to a Bollinger Band that can likewise twist like an MA cross. The main purpose of it is to display where the price may reside within. Much like a Bollinger Band it has its High and Low within its zone to specify this location. Since it has the ability to cross over and under, it has the ability to specify what it thinks may be a Bullish or Bearish zone. This zone uses its upper level to display what may be a Resistance location and its lower level to display what may be a Support location. These Support and Resistance locations are based on Momentum and will move with the price in an attempt to stay relevant.
You may use these True Values zones as a gauge of if the price is Overbought or Oversold. When the price faces high volatility and moves outside of the True Value Zones, it may face consolidation or likewise a correction to bring it back within these zones. These zones may act as a guideline towards where the price is currently valued at and may belong within.
Bar Strength Indexes:
Bar Strength Indexes are our way of ranking each bar in correlation to the last few. It is based on a few things but is highly influenced on Open/Close/High/Low, Volume and how the price has moved recently. They may attempt to ‘rate’ each bar and how Bullish/Bearish each of these bars are. The Green number under the bar is its Bullish % and the Red number above the bar is its Bearish %. These %’s will always equal 100% when combined together. Bar Strength Indexes may be useful for seeing when either Bullish or Bearish momentum is picking up or when there may be a reversal / consolidation.
These Bar Strength Indexes may allow you to decipher different states. If you refer to the example above, you may notice how based on how the numbers are changing, you may see when it has entered / exited Bullish, Bearish and Consolidation. Likewise, if you refer to the current bar (yellow circle), you can see that the Bullish % has dropped from 93 to 49; this may be signifying that the Bullish movement is losing momentum. You may use these changes in Bar Indexes as a guide to when to enter / end trades.
Volume Profile:
Volume Profile has been something that has been within TradingView for quite some time. It is a very useful way of seeing at what Horizontal Price there has been the most volume. This may be very useful for seeing not only Support and Resistance locations based on Volume, but also seeing where the majority of Limit Orders are placed. Limit Orders are where traders decide they want to either Buy / Sell but have the order placed so the trade won’t happen until the price reaches a certain amount. Either through many orders from many traders, or a single order from a ‘Whale’ (trader with a lot of capital); you may see Support and Resistance at specific Price Points that have large Volume.
Many Volume Profile Indicators feature a breakdown of all the different locations of volume, along with a Point Of Control (POC) line to designate where the most Volume has been. To try and reduce clutter within our already very saturated Toolkit Indicator, we’ve decided to strip our Volume Profile to only display this POC line. This may allow you to see where the crucial Volume Support and Resistance is without all of the clutter.
You may be wondering, well how important is this Volume Profile POC line and how do I go about using it? Aside from it being a gauge towards where Support and Resistance may be within Volume, it may also be useful for identifying good Long/Short locations. If you think of the line as a ‘Battle’ between the Bulls and Bears, they’re both fighting over that line. The Bears are wanting to break through it downwards, and the Bulls are wanting to break through it upwards. When one side has temporarily won this battle, this means they may have more Capital to push the price in their direction. For instance, if both the Bulls and the Bears are fighting over this POC price, that means the Bears think that price is a good spot to sell; however, the Bulls also deem that price to be a good point to buy. If the Bulls were to win this battle, that means the Bears either canceled their orders to reevaluate, or all of their orders have been completed from the Bulls buying them all. What may happen after that is, if the Bulls were able to purchase all of these Limit Sell Orders, then they may still have more Capital left to continue to pressure the price upwards. The same may be true for if the Bears were to win this ‘Battle’.
How to use YinYang Trend as a cohesive whole:
Hopefully you’ve read and understand how each aspect of this Indicator works on its own, as knowing how/what they each do is important to understanding how it is used as a cohesive whole. Due to the fact that this Toolkit of an Indicator displays so much data, you may find it easier to use and understand when you’re zoomed in a little, somewhat like we are in this example above.
If we refer to the example above, you may like us, deduce a few things:
1. The current price may be VERY Overbought. This may be seen by a few different things:
The Boom Meter Bar Colors have been exhibiting a Dark Green color for 6 bars in a row.
The price has continuously been moving the High (red) Pivot Upwards.
Our Boom Meter displays ‘Pumping’ at 100%.
The price broke through a Downward Trend Line that was created in February of 2022 at 45,000 like it was nothing.
The Bar Strength Index hit a Bullish value of 93%.
The Price broke out of the Bollinger Bands and continues to test its upper levels.
The Low is much greater than our fastest moving MA that creates the Purchase Zones.
The Price is vastly outside of the True Value Zone.
The Bar Strength Index of our current bar is 50% bullish, which is a massive decrease from the previous bar of 93%. This may indicate that a correction is coming soon.
2. Since we’ve identified the current price may be VERY Overbought, next we need to identify if/when/to where it may correct to:
We’ve created a new example here to display potential correction areas. There are a few places it has the ability to correct to / within:
The downward Trend Line (red) below the current bar sitting currently at 32,750. This downward Trend Line is at the same price point as the Fastest MA of our Purchase Zone which may provide some decent Support there.
Between two crucial Pivot heights, within a zone of 30,000 to 31,815. This zone has the second fastest MA from the Purchase Zone right near the middle of it at 31,200 which may act as a Support within the Zone. Likewise there is the Bollinger Band Basis which is also resting at 30,000 which may provide a strong Support location here.
If 30,000 fails there may be a correction all the way to the bottom of our True Value Zone and the top of one of our Extremes at 27,850.
If 27,850 fails it may correct all the way to the bottom of our Purchase Zone / lowest of our Extremes at 27,350.
If all of the above fails, it may test our Volume Profile POC of 26,430. If this POC fails, the trend may switch to Bearish and continue further down to lower levels of Support.
The price can always correct more than the prices mentioned above, but considering overall this Indicator is favoring the Bulls, we will tailor this analysis in Favor of the Bullish Momentum maintaining even during this correction. For these reasons, we think the price may correct between the 30,000 and 31,815 zone before continuing upwards and maintaining this Bullish Momentum.
Please note, these correction estimates are just that, they’re estimates. Aside from the fact that the price is very overbought right now and our Bar Strength Index may be declining (bar hasn’t closed yet); the Boom Meter Strength remains at 100%, meaning there may not be much Bearish momentum changes happening yet. We just want to show you how an Preemptive analysis may be done before there are even Bearish Cipher Signals appearing.
Using this Indicator, you may be able to decipher Entry and Exits. In the previous example, we went over how you may use it to see where a correction (Exit / Take Profit) may be and how far this correction may go. In this example above we will be discussing how to identify Entry locations. We will be discussing a Bullish Buy entry but the same rules apply for a Bearish Sell Entry just the opposite with the Cipher Signals.
If you refer to where we circled in white, this is where the Purchase Zones faced Consolidation. When the Purchase Zones all get tight and close together like that, this may represent Volatility and Momentum in either direction may occur soon.
This was then followed by all 6 of the Standard Cipher Signals closely in succession to each other. This means the Momentum may be favoring the Bulls. If this was likewise all 6 of the Bearish Cipher Signals closely in succession, than the momentum change would favor the Bears.
If you were looking for an entry, and you saw Consolidation with the Purchase Zones and then shortly after you saw the Green Circle and Blue Flag (they can swap order); this may now be a good Entry location.
We will conclude this Tutorial here. Hopefully this has taught you how this Trend Analysis Toolkit may help you locate multiple different types of important Support and Resistance locations; as well as possible Entry and Exit locations.
Settings:
1. Bull/Bear Zones:
1.1. Purchase Speed (Bull/Bear Signals and Take Profit Signals):
Speed determines how much price movement is needed for a signal to occur.
'Sonic' uses the extremities to try and get you the best entry and exit points, but is so quick, its speed may reduce accuracy.
'Fast' may attempt to capitalize on price movements to help you get SOME or attempt to lose LITTLE quickly.
'Medium' may attempt to get you the most optimal entry and exit locations, but may miss extremities.
'Slow' may stay in trades until it is clear that momentum has changed.
'Snail' may stay in trades even if momentum has changed. Snail may only change when the price has moved significantly (This may result in BIG gains, but potentially also BIG losses).
1.2. Purchase Strength (Bull/Bear Signals and Take Profit Signals):
Strength ensures a certain amount of verifications required for signals to happen. The more verifications the more accurate that signal is, but it may also change entry and exit points, and you may miss out on some of the extremities. It is highly advised to find the best combination between Speed and Strength for the TimeFrame and Pair you are trading in, as all pairs and TimeFrames move differently.
'High' uses 15 verifications to ensure signal strength.
'Medium' uses 10 verifications to ensure signal strength.
'Low' uses 5 verifications to ensure signal strength.
'Very Low' uses 3 verifications to ensure signal strength.
2. Cipher Signals:
Cipher Signals are very strong EMA and SMA crosses, which may drastically help visualize movement and help you to predict where the price will go. All Symbols have counter opposites that cancel each other out (YinYang). Here is a list, in order of general appearance and strength:
White Cross / Diamond (Predictive): The initial indicator showing trend movement.
Green Cross / Diamond (Regular): Confirms the Predictive and may add a fair bit of strength to trend movement.
Blue Cross / Diamond (Confirming): Confirms the Regular, showing the trend might have some decent momentum now.
Green / Red X: Gives momentum to the current trend direction, possibly confirming the Confirming Cross/Diamond.
Blue / Orange Triangle: may confirm the X, Possible pump / dump of decent size may be coming soon.
Green / Red Circle: EITHER confirms the Triangle and may mean big pump / dump is potentially coming, OR it just hit its peak and signifies a potential reversal correction. PAY ATTENTION!
Green / Red Flag: Oddball that helps confirm trend movements on the short term.
Blue / Yellow Flag: Oddball that helps confirm trend movements on the medium term (Yin / Yang is the long term Oddball).
3. Bull/Bear Signals:
Bear and Bull signals are where the momentum has changed enough based on your Purchase Speed and Strength. They generally represent strong price movement in the direction of the signal, and may be more reliable on higher TimeFrames. Please don’t use JUST these signals for analysis, they are only meant to be a fraction of the important data you are using to make your technical analysis.
4. Take Profit Signals:
Take Profit signals are guidelines that momentum has started to change back and now may be a good time to take profit. Your Take Profit signals are based on your Take Profit Speed and Strength and may be adjusted to fit your trading style.
5. Information Tables:
Information tables display very important data and help to declutter the screen as they are much less intrusive compared to labels. Our Information tables display: Boom Meter, Purchase Strength of Bull/Bear Zones and Yin/Yang State.
Boom Meter: Uses over 50 different calculations to determine if the pair is currently 'Dumping' (0-29%), 'Consolidating' (30-70%), or 'Pumping' (71-100%).
Bull / Bear Strength: Shows the strength of the current Bull / Bear signal from 0-100% (Signals start at 100% and change when they hit 0%). The % it moves up or down is based on your 'Purchase Strength'.
Yin / Yang state: Is one of the strongest EMA/SMA crosses (long term Oddball) within this Indicator and may be a great indication of which way the price is moving. Do keep in mind if the price is consolidating when changing state, it may have the highest chance of switching back also. Once momentum kicks in and there is price movement the state may be confirmed. Refer to other Cipher Symbols, Extremes, Trend, BOLL, Boom %, Bull / Bear % and Bar colors when Bull / Bear Zones are consolidating and Yin / Yang State changes as this is a very strong indecision zone.
6. Bull / Bear Zones:
Our Bull / Bear zones are composed of 8 very important EMA lengths that may act as not only Support and Resistance, but they help to potentially display consolidation and momentum change. You can tell when they are getting tight and close together it may represent consolidation and when they start to flip over on each other it may represent a change in momentum.
7. MA Extremes:
Our MA Extremes may be 3 of the most important long term moving averages. They don’t always play a role in trades as sometimes they’re way off from the price (cause they’re extreme lengths), but when they are around price or they cross under or over each other, it may represent large changes in price are about to occur. They may be very useful for seeing strong resistance / support locations based on price averages. Extremes may transition from a Support to a Resistance based on its position above or below them and how many times the price has either bounced up off them (Supporting) or Bounced back down after hitting them (Resistance).
8. Pivots:
Pivots may be a very important indicator of support and resistance for horizontal price movement. Pivots may represent the current strongest Support and Resistance. When the Pivot changes, it means a new strong Support or Resistance has been created. Sometimes you'll notice the price constantly pushes the pivot during a massive Pump or Dump. This is normal, and may indicate high levels of volatility. This generally also happens when the price is outside of the Bollinger Bands and is also Over or Undervalued. The price usually consolidates for a while after something like this happens before more drastic movement may occur.
9. Trend Lines:
Trend lines may be one of the best indicators of support and resistance for diagonal price movement. When a Trend Line fails to hold it may be a strong indication of a dump. Keep a close eye to where Upward and Downward Trend Lines meet. Trend lines can create different trading formations known as Pennants, Flags and Wedges. Please familiarize yourself with these formations So you know what to look for.
10. Bollinger Bands (BOLL):
Bollinger Bands may be very useful, and ours have been customized so they may be even more accurate by using a modified calculation that also incorporates volume.
Bollinger Bands may be used to see Movement vs Consolidation Zones (When it’s wide vs narrow). It also may be very useful for seeing where the correction areas are likely to be. Price may bounce between top and bottom of the BOLL, unless perhaps in a pump or dump. The Boom Meter may show you whether it is currently: Dumping, Consolidation or Pumping, along with Boom Meter Bar Colors, may be a good indication if it will break the BOLL. The Middle Line of the BOLL (White Line) may be a very strong support / resistance line. If the price closes above or below it, it may be a good indication of the trend changing (it may be one of the first stages to a pump or dump).
11. Boom Meter Bar Colors:
Boom Meter bar colors may be very useful for seeing when the bar is Overbought or Underbought. There are 6 different types of boom meter bar colors, they are:
Dark Green: RSI may be very Overbought and price going UP (May be in a big pump. NOTICE, chance of small dump correction if Cherry Red bar appears).
Light Green: RSI may be slightly Overbought and price going UP (chance of small pump).
Light Purple: RSI may be very Underbought and price going UP (May have chance of small correction).
Dark Red: RSI may be very Underbought and price going DOWN (May be in a big dump. NOTICE, chance of small pump correction if Light Purple bar appears).
Light Orange: RSI may be slightly Underbought and price going DOWN (chance of small dump).
Cherry Red: RSI may be very Overbought and price going DOWN (Chance of small correction).
12. True Value Zone:
True Value Zones display zones that represent ranges to show what the price may truly belong within. They may be very useful for knowing if the Price is currently not valued correctly, which generally means a correction may happen soon. True Value Zones can swap from Bullish to Bearish and are represented by Red for Bearish and Green for Bullish. For example, if the price is ABOVE and OUTSIDE of the True Value Zone, this means it may be very overvalued and might correct to go back inside the True Value Zone. This correction may be done by either dumping in price back into the zone, or consolidating horizontally back into it over a longer period of time. Vice Versa is also true if it is BELOW and OUTSIDE of the True Value Zone.
13. Bar Strength Index:
Bar Strength Index may display how Bullish/Bearish the current bar is. The strength is important to help see if a pump may be losing momentum or vice versa if a dump may correct. Keep in mind, the Bar Strength Index does a small 'refresh' to account for new bars. It may help to keep the Index more accurate.
14. Volume Profile:
Volume Profiles may be important to know where the Horizontal Support/Resistance is in Price base on Volume. Our Volume Profile may identify the point where the most volume has occurred within the most relevant timeframe. Volume Profiles are helpful at identifying where Whales have their orders placed. The reason why they are so helpful at identifying whales is when the volume is profiled to a specific area, there may likely be lots of Limit Buy and/or Sells around there. Limit Buys may act as Support and Limit Sells may act as Resistance. It may be very useful to know where these lie within the price, similar to looking at Order Book Data for Whale locations.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
wtt volume
This indicator is based on the chapter Progress in Volume Capacity of WTT. The Fundamentals and Advance of Natural Trading Theory.
Progress in volume capacity focuses on the absolute strength or relative strength of the volume capacity of bulls and bears in a single k-bar.
The book grades volume capacity as follows:
Absolute Strength:
Absolute strength of bulls: the bulls win and close, with long lower shadow or long solid body.
Absolute strength of bears: the bears win and close, with long upper shadow or long solid body.
Relative Strength
Relative strength of bulls: long lower shadow much longer than the solid K-bar, even when the bears win; or well-matched solid K-bar and upper shadow when the bulls close.
Relative strength of bears: long upper shadow much longer than the solid K-bar, even when the bulls win; or well-matched solid K-bar and lower shadow when the bears close.
Crosshairs
Frequently found in market shocks or before turning points, to be analyzed on top of the above relative and absolute strength.
This indicator colors the volume by the size of volume capacity, dark colors for the strong, light colors for the weak, and grey crosshairs. This is to make it easier for you to draw the curve of volume capacity and feel the contrast of strength between the bulls and the bears. You may therefore have better timing and position for opening and closing a position. The bull-bear strength comparison reflected by a single k-bar helps you better decide the next move within a very short period, which could be opening a position, coming into the position at low, underweighting, or closing a position.
本指标根据《WTT.自然交易理论基础与进阶》量能精进一章编写。
量能精进关注的，是单个K柱中多空双方量能的绝对强势或相对强势。
该书把量能分为以下几个等级：
绝对强势
多头绝对强势：多头获胜收线，带有长下影线或长实心柱体。
空头绝对强势：空头获胜收线，带有长上影线或长实心柱体。
相对强势
多头相对强势：长下影线相对实心K柱长很多，即使是空头获胜收线；或多头收线时实心K柱与上影线旗鼓相当。
空头相对强势：长上影线相对实心K柱长很多，即使是多头获胜收线；或空头收线时实心K柱与下影线旗鼓相当。
十字线
在震荡行情或出现拐点前出现频率较高，可结合上述相对强势和绝对强势进行综合判断。
本指标根据量能强弱对交易量进行染色，强势为深色，弱势为浅色，灰色为十字线，方便你手绘量能曲线，感受多空量能强弱。能给你提供更优的开平仓时机和点位。通过单个k柱形态反映出来的多空强弱关系，你可以更好地执行下一个极短周期内的操作，可能是开仓，也可能是补仓、减仓或平仓。
Market Energy & Direction DashboardMarket Energy & Direction Dashboard - Daytrading
Overview
A comprehensive real-time market internals dashboard that combines NYSE TICK, NYSE Advance-Decline (ADD) momentum, VIX direction, and relative volume into a single visual traffic light system with intelligent signal synthesis. Designed for active daytraders who need instant confirmation of market direction and energy based on momentum alignment across all major internals.
What It Does
This indicator synthesizes multiple market internals using directional momentum analysis rather than static thresholds to provide clear, actionable signals:
• Traffic Light System: Single glance confirmation of market state
o Bright Green: Maximum bullish - all internals aligned (TICK + ADD rising + VIX falling + volume)
o Bright Red: Maximum bearish - all internals aligned (TICK + ADD falling + VIX rising + volume)
o Yellow: Exhaustion warning - TICK at extremes, potential reversal imminent
o Moderate Colors: Partial alignment - some confirmation but not complete
o Gray: Choppy, neutral, or conflicting signals
• Real-Time Dashboard displays:
o Current TICK value with exhaustion warnings
o Current ADD with directional momentum indicator (↑ rising = breadth improving, ↓ falling = breadth deteriorating, ± compression)
o VIX level with directional indicator (↓ declining = bullish, ↑ rising = bearish, ± compression = neutral)
o Relative volume (current vs 20-period average)
o Composite status message synthesizing all data into clear directional summary
Key Features
✓ Momentum-based analysis - all indicators show direction/change, not just levels ✓ Intelligent signal hierarchy from "Maximum" to "Moderate" based on internal alignment ✓ ADD directional momentum - catches breadth shifts early, works in all market conditions ✓ VIX directional analysis - shows if fear is increasing, decreasing, or stagnant ✓ Color-coded traffic light for instant decision making ✓ Detects TICK/ADD divergences (conflicting signals = caution) ✓ Exhaustion warnings at extreme TICK levels (±1000+) ✓ Composite status messages - "Maximum Bull", "Strong Bull", "Moderate Bull", etc. ✓ Customizable thresholds for all parameters ✓ Moveable dashboard (9 position options) ✓ Built-in alerts for all signal strengths, exhaustion, and divergences
How To Use
Setup:
1. Add indicator to your main trading chart (SPY, ES, NQ, etc.)
2. Default settings work well for most traders, but you can customize:
o TICK Extreme Level (default 1000)
o ADD Compression Threshold (default 100 - detects when breadth is stagnant)
o VIX Elevated Level (default 20)
o VIX Compression Threshold (default 2% - detects low volatility)
o Volume Threshold (default 1.5x average)
3. Position dashboard wherever convenient on your chart
Reading The Signals:
Signal Hierarchy (Strongest to Weakest):
MAXIMUM SIGNALS ⭐ (Brightest colors - All 4 internals aligned)
• "✓ MAXIMUM BULL": TICK bullish + ADD rising (↑) + VIX falling (↓) + Volume elevated
o This is the holy grail setup - all momentum aligned, highest conviction longs
• "✓ MAXIMUM BEAR": TICK bearish + ADD falling (↓) + VIX rising (↑) + Volume elevated
o Perfect storm bearish - all momentum aligned, highest conviction shorts
STRONG SIGNALS (Bright colors - Core internals aligned)
• "✓ STRONG BULL": TICK bullish + ADD rising (↑)
o Strong confirmation even without VIX/volume - breadth supporting the move
• "✓ STRONG BEAR": TICK bearish + ADD falling (↓)
o Strong confirmation - both momentum and breadth deteriorating
MODERATE SIGNALS (Faded colors - Partial confirmation)
• "MODERATE BULL": TICK bullish but ADD not confirming direction
o Proceed with caution - momentum present but breadth questionable
• "MODERATE BEAR": TICK bearish but ADD not confirming direction
o Proceed with caution - selling but breadth not fully participating
WARNING SIGNALS
• "⚠ EXHAUSTION" (Yellow): TICK at ±1000+ extremes
o Potential reversal zone - prepare to fade or take profits
o Often marks blow-off tops or capitulation bottoms
NEUTRAL/AVOID
• "CHOPPY/NEUTRAL" (Gray): Conflicting signals or low conviction
o Stay out or reduce size significantly
Individual Indicator Interpretation:
TICK:
• Green: Bullish momentum (>+300)
• Red: Bearish momentum (<-300)
• Yellow: Exhaustion (±1000+)
• Gray: Neutral
ADD (Advance-Decline):
• Green (↑): Breadth improving - more stocks participating in the move
• Red (↓): Breadth deteriorating - fewer stocks participating
• Gray (±): Breadth stagnant - no clear participation trend
VIX:
• Green (↓): Fear declining - healthy environment for rallies
• Red (↑): Fear rising - risk-off mode, supports downward moves
• Gray (±): Volatility compression - often precedes explosive moves
Volume:
• Green: High conviction (>1.5x average)
• Gray: Low conviction
Trading Strategy:
1. Wait for "MAXIMUM" or "STRONG" signals for highest probability entries
o Maximum signals = go full size with confidence
o Strong signals = good conviction, normal position sizing
2. Confirm directional alignment:
o For longs: Want ADD ↑ (rising) and VIX ↓ (falling)
o For shorts: Want ADD ↓ (falling) and VIX ↑ (rising)
3. Use exhaustion warnings (yellow) to:
o Take profits on existing positions
o Prepare counter-trend entries
o Tighten stops
4. Avoid "MODERATE" signals unless you have strong conviction from other analysis
o These work best as confirmation for existing setups
o Not strong enough to initiate new positions alone
5. Never trade "CHOPPY/NEUTRAL" signals
o Gray means stay out - preserve capital
o Wait for clear alignment
6. Watch for divergences:
o Price making new highs but ADD ↓ (falling) = distribution warning
o Price making new lows but ADD ↑ (rising) = potential bottom
o Divergence alert will notify you
Best Practices:
• Use on 1-5 minute charts for daytrading
• Combine with your price action or technical setup (support/resistance, trendlines, patterns)
• The dashboard confirms when to take your setup, not what setup to take
• Most effective during regular market hours (9:30 AM - 4:00 PM ET) when volume is present
• The strongest edge comes from "MAXIMUM" signals - wait for these for best risk/reward
• Pay special attention to ADD direction - it's the most predictive breadth indicator
• VIX compression (gray ±) often signals upcoming volatility expansion - prepare for bigger moves
Customization Option
All thresholds are adjustable in settings:
• TICK Extreme: Higher = fewer exhaustion warnings (try 1200-1500 for less sensitivity)
• ADD Compression Threshold: Change detection sensitivity
o Default 100 = balanced
o Lower (50) = more sensitive to small breadth changes
o Higher (200-300) = only shows major breadth shifts
• VIX Elevated: Adjust for current volatility regime (15-25 typical range)
• VIX Compression Threshold:
o Default 2% = balanced
o Lower (0.5-1%) = catches subtle VIX changes
o Higher (3-5%) = only shows significant VIX moves
• Volume Threshold: Lower for quieter stocks/times, higher for more confirmation
Alerts Available
• Maximum Bullish: All 4 internals aligned bullish (TICK + ADD↑ + VIX↓ + Volume)
• Maximum Bearish: All 4 internals aligned bearish (TICK + ADD↓ + VIX↑ + Volume)
• Strong Bullish: TICK bullish + ADD rising
• Strong Bearish: TICK bearish + ADD falling
• Exhaustion Warning: TICK at extreme levels
• Divergence Warning: TICK and ADD directions conflicting
Understanding the Signal Synthesis
The indicator uses intelligent logic to combine all internals:
"MAXIMUM" Signals require:
• TICK direction (bullish/bearish)
• ADD momentum (rising/falling) in same direction
• VIX direction (falling for bulls, rising for bears)
• Volume elevated (>1.5x average)
"STRONG" Signals require:
• TICK direction (bullish/bearish)
• ADD momentum (rising/falling) in same direction
• (VIX and volume are bonuses but not required)
"MODERATE" Signals:
• TICK showing direction
• But ADD not confirming or contradicting
• Weakest actionable signal
This hierarchy ensures you know exactly how much conviction the market has behind any move.
Technical Details
• Pulls real-time data from NYSE TICK (USI:TICK), NYSE ADD (USI:ADD), and CBOE VIX
• ADD direction calculated using bar-to-bar change with compression detection
• VIX direction calculated using bar-to-bar percentage change
• Volume calculation uses 20-period simple moving average
• Dashboard updates every bar
• No repainting - all calculations based on closed bar data
Who This Is For
• Active daytraders of stocks, futures (ES/NQ), and options
• Scalpers needing quick directional confirmation with multiple internal alignment
• Swing traders looking to time intraday entries with maximum confluence
• Volatility traders who monitor VIX behavior
• Market makers and professionals who trade based on breadth and internals
• Anyone who monitors market internals but wants intelligent synthesis vs raw data
Tips For Success
Trading Philosophy:
• Quality over quantity - wait for "MAXIMUM" signals for best results
• One "MAXIMUM" signal trade is worth five "MODERATE" signal trades
• Gray/neutral is not a sign of missing opportunity - it's protecting your capital
Signal Confidence Levels:
1. MAXIMUM (95%+ confidence) - Trade these aggressively with full size
2. STRONG (80-85% confidence) - Trade these with normal position sizing
3. MODERATE (60-70% confidence) - Only if confirmed by strong technical setup
4. CHOPPY/NEUTRAL - Do not trade, wait for clarity
Advanced Techniques:
• Breadth divergences: Watch for price making new highs while ADD shows ↓ (falling) = major warning
• VIX/Price divergences: Rallies with rising VIX (↑) are usually false moves
• Volume confirmation: "MAXIMUM" signals with 2x+ volume are the absolute best
• Compression zones: When both ADD and VIX show compression (±), expect explosive breakout soon
• Sequential signals: Back-to-back "MAXIMUM" signals in same direction = strong trending day
Common Patterns:
• Opening surge with "MAXIMUM BULL" that shifts to "EXHAUSTION" (yellow) = fade the high
• Selloff with "MAXIMUM BEAR" followed by ADD ↑ (rising) divergence = potential reversal
• Choppy morning followed by "MAXIMUM" signal afternoon = best trending opportunity
Example Scenarios
Perfect Bull Entry:
• Bright green signal box
• TICK: +650
• ADD: +1200 (↑)
• VIX: 18.30 (↓)
• Volume: 2.3x
• Status: "✓ MAXIMUM BULL" → ALL SYSTEMS GO - Take aggressive long positions
Strong Bull (Good Confidence):
• Green signal box (slightly less bright)
• TICK: +500
• ADD: +800 (↑)
• VIX: 19.50 (±)
• Volume: 1.2x
• Status: "✓ STRONG BULL" → Good long setup - breadth confirming even without VIX/volume
Caution Bull (Moderate):
• Faded green signal box
• TICK: +400
• ADD: +900 (↓)
• VIX: 20.10 (↑)
• Volume: 0.9x
• Status: "MODERATE BULL" → CAUTION - TICK bullish but breadth deteriorating and VIX rising = weak rally
Exhaustion Warning:
• Yellow signal box
• TICK: +1350 ⚠
• ADD: +2100 (↑)
• VIX: 17.20 (↓)
• Volume: 1.8x
• Status: "⚠ EXHAUSTION" → Take profits or prepare to fade - TICK overextended despite good internals
Divergence Setup (Potential Reversal):
• Faded green signal
• TICK: +300
• ADD: +1800 (↓)
• VIX: 21.50 (↑)
• Volume: 1.6x
• Status: "MODERATE BULL" → WARNING - Price rallying but breadth collapsing and fear rising = distribution
Perfect Bear Entry:
• Bright red signal box
• TICK: -780
• ADD: -1600 (↓)
• VIX: 24.80 (↑)
• Volume: 2.5x
• Status: "✓ MAXIMUM BEAR" → Perfect short setup - all momentum bearish with conviction
Compression (Wait Mode):
• Gray signal box
• TICK: +50
• ADD: -200 (±)
• VIX: 16.40 (±)
• Volume: 0.7x
• Status: "CHOPPY/NEUTRAL" → STAY OUT - Volatility compression, no conviction, await breakout
Performance Optimization
Best Market Conditions:
• Works excellent in trending markets (up or down)
• Particularly powerful during high-volume sessions (first/last hours)
• "MAXIMUM" signals most reliable during 9:45-11:00 AM and 2:00-3:30 PM ET
Less Effective During:
• Lunch period (11:30 AM - 1:30 PM) - lower volume reduces signal quality
• Low-volatility environments - compression signals dominate
• Major news events in first 5 minutes - wait for internals to stabilize
Recommended Use Cases:
• Scalping: Trade only "MAXIMUM" signals for quick 5-15 minute moves
• Daytrading: Use "MAXIMUM" and "STRONG" signals for position entries
• Swing entries: Use "MAXIMUM" signals for optimal intraday entry timing
• Exit timing: Use "EXHAUSTION" (yellow) warnings to take profits
________________________________________
Pro Tip: Create a dedicated workspace with this indicator on SPY/ES/NQ charts. Set alerts for "MAXIMUM BULL", "MAXIMUM BEAR", and "EXHAUSTION" signals. Most professional traders only trade the "MAXIMUM" setups and ignore everything else - this alone can dramatically improve win rates.
MACD HTF Hardcoded (A/B Presets) + Regimes [CHE] MACD HTF Hardcoded (A/B Presets) + Regimes — Higher-timeframe MACD emulation with acceptance-based regime filter and on-chart diagnostics
Summary
This indicator emulates a higher-timeframe MACD directly on the current chart using two hardcoded preset families and a time-bucket mapping, avoiding cross-timeframe requests. It classifies four MACD regimes and applies an acceptance filter that requires several consecutive bars before a state is considered valid. A small dead-band around zero reduces noise near the axis. An on-chart table reports the active preset, the inferred time bucket, the resolved lengths, and the current regime.
Pine version: v6
Overlay: false
Primary outputs: MACD line, Signal line, Histogram columns, zero line, regime-change alert, info table
Motivation: Why this design?
Cross-timeframe indicators often rely on external timeframe requests, which can introduce repaint paths and added latency. This design provides a deterministic alternative: it maps the current chart’s timeframe to coarse higher-timeframe buckets and uses fixed EMA lengths that approximate those views. The dead-band suppresses flip-flops around zero, and the acceptance counter reduces whipsaw by requiring sustained agreement across bars before acknowledging a regime.
What’s different vs. standard approaches?
Baseline: Classical MACD with user-selected lengths on the same timeframe, or higher-timeframe MACD via cross-timeframe requests.
Architecture differences:
Hardcoded A and B length families with a bucket map derived from the chart timeframe.
No `request.security`; all calculations occur on the current series.
Regime classification from MACD and Histogram sign, gated by an acceptance count and a small zero dead-band.
Diagnostics table for transparency.
Practical effect: The MACD behaves like a slower, higher-timeframe variant without external requests. Regimes switch less often due to the dead-band and acceptance logic, which can improve stability in choppy sessions.
How it works (technical)
The script derives a coarse bucket from the chart timeframe using `timeframe.in_seconds` and maps it to preset-specific EMA lengths. EMAs of the source build MACD and Signal; their difference is the Histogram. Signs of MACD and Histogram define four regimes: strong bull, weak bull, strong bear, and weak bear. A small, user-defined band around zero treats values near the axis as neutral. An acceptance counter checks whether the same regime persisted for a given number of consecutive bars before it is emitted as the filtered regime. A single alert condition fires when the filtered regime changes. The histogram columns change shade based on position relative to zero and whether they are rising or falling. A persistent table object shows preset, bucket tag, resolved lengths, and the filtered regime. No cross-timeframe requests are used, so repaint risk is limited to normal live-bar movement; values stabilize on close.
Parameter Guide
Source — Input series for MACD — Default: Close — Using a smoother source increases stability but adds lag.
Preset — A or B length family — Default: “3,10,16” — Switch to “12,26,9” for the classic family mapped to buckets.
Table Position — Anchor for the info table — Default: Top right — Choose a corner that avoids covering price action.
Table Size — Table text size — Default: Normal — Use small on dense charts, large for presentations.
Dark Mode — Table theme — Default: Enabled — Match your chart background for readability.
Show Table — Toggle diagnostics table — Default: Enabled — Disable for a cleaner pane.
Zero dead-band (epsilon) — Noise gate around zero — Default: Zero — Increase slightly when you see frequent flips near zero.
Acceptance bars (n) — Bars required to confirm a regime — Default: Three — Raise to reduce whipsaw; lower to react faster.
Reading & Interpretation
Histogram columns: Above zero indicates bullish pressure; below zero indicates bearish pressure. Darker shade implies the histogram increased compared with the prior bar; lighter shade implies it decreased.
MACD vs. Signal lines: The spread corresponds to histogram height.
Regimes:
Strong bull: MACD above zero and Histogram above zero.
Weak bull: MACD above zero and Histogram below zero.
Strong bear: MACD below zero and Histogram below zero.
Weak bear: MACD below zero and Histogram above zero.
Table: Inspect active preset, bucket tag, resolved lengths, and the filtered regime number with its description.
Practical Workflows & Combinations
Trend following: Use strong bull to favor long exposure and strong bear to favor short exposure. Use weak states as pullback or transition context. Combine with structure tools such as swing highs and lows or a baseline moving average for confirmation.
Exits and risk: In strong trends, consider exiting partial size on a regime downgrade to a weak state. In choppy sessions, increase the acceptance bars to reduce churn.
Multi-asset / Multi-timeframe: Works on time-based charts across liquid futures, indices, currencies, and large-cap equities. Bucket mapping helps retain a consistent feel when moving from lower to higher timeframes.
Behavior, Constraints & Performance
Repaint/confirmation: No cross-timeframe requests; values can evolve intrabar and settle on close. Alerts follow your TradingView alert timing settings.
Resources: `max_bars_back` is set to five thousand. Very large resolved lengths require sufficient history to seed EMAs; expect a warm-up period on first load or after switching symbols.
Known limits: Dead-band and acceptance can delay recognition at sharp turns. Extremely thin markets or large gaps may still cause brief regime reversals.
Sensible Defaults & Quick Tuning
Start with preset “3,10,16”, dead-band near zero, and acceptance of three bars.
Too many flips near zero: increase the dead-band slightly or raise the acceptance bars.
Too sluggish in clean trends: reduce the acceptance bars by one.
Too sensitive on fast lower timeframes: switch to the “12,26,9” preset family or raise the acceptance bars.
Want less clutter: hide the table and keep the alert.
What this indicator is—and isn’t
This is a visualization and regime layer for MACD using higher-timeframe emulation and stability gates. It is not a complete trading system and does not generate position sizing or risk management. Use it with market structure, execution rules, and protective stops.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Cnagda Pure Price ActionCnagda Pure Price Action (CPPA) indicator is a pure price action-based system designed to provide traders with real-time, dynamic analysis of the market. It automatically identifies key candles, support and resistance zones, and potential buy/sell signals by combining price, volume, and multiple popular trend indicators.
How Price Action & Volume Analysis Works
Silver Zone – Logic, Reason, and Trade Planning
Logic & Visualization:
The Silver Zone is created when the closing price is the lowest in the chosen window and volume is the highest in that window.
Visually, a large silver-colored box/rectangle appears on the chart.
Thick horizontal lines (top and bottom) are drawn at the high and low of that candle/bar, extending to the right.
Reasoning:
This combination typically occurs at strong “accumulation” or support areas:
Sellers push the price down to the lowest point, but aggressive buyers step in with high volume, absorbing supply.
Indicates potential exhaustion of selling and likely shift in market control to buyers.
How to Plan Trades Using Silver Zone:
Watch if price returns to the Silver Zone in the future: It often acts as powerful support.
Bullish entries (buys) can be planned when price tests or slightly pierces this zone, especially if new buy signals occur (like yellow/green candle labels).
Place your stop-loss below the bottom line of the Silver Zone.
Target: Look for the nearest resistance or opposing zone, or use indicator’s bullish label as confirmation.
Extra Tip:
Multiple touches of the Silver Zone reinforce its importance, but if price closes deeply below it with high volume, that’s a caution signal—support may be breaking.
Black Zone – Logic, Reason, and Trade Planning (as CPPA):
Logic & Visualization:
The Black Zone is created when the closing price is the highest in the chosen window and volume is the lowest in that window.
Visually, a large black-colored box/rectangle appears on the chart, along with thick horizontal lines at the top (high) and bottom (low) of the candle, extending to the right.
Reasoning:
This combination signals a strong “distribution” or resistance area:
Buyers push the price up to a local high, but low volume means there is not much follow-through or conviction in the move.
Often marks exhaustion where uptrend may pause or reverse, as sellers can soon step in.
How to Plan Trades Using Black Zone:
If price revisits the Black Zone in the future, it often acts as major resistance.
Bearish entries (sells) are considered when price is near, testing, or slightly above the Black Zone—especially if new sell signals appear (like blue/red candle labels).
Place your stop-loss just above the top line of the Black Zone.
Target: Nearest support zone (such as a Silver Zone) or next indicator’s bearish label.
Extra Tip:
Multiple touches of the Black Zone make it stronger, but if price closes far above with rising volume, be cautious—resistance might be breaking.
Support Line – Logic, Reason, and Trade Planning (as Cppa):
Logic & Visualization:
The Support Line is a dynamically drawn dashed line (usually blue) that marks key price levels where the market has previously shown significant buying interest.
The line is generated whenever a candle forms a high price with high volume (orange logic).
The script checks for historical pivot lows, past support zones, and even higher timeframe (HTF) supports, and then extends a blue dashed line from that price level to the right, labeling it (sometimes as “Prev Support Orange, HTF”).
Reasoning:
This line helps you visually identify where demand has been strong enough to hold price from falling further—essentially a floor in the market used by professional traders.
If price approaches or re-tests this line, there’s a good chance buyers will defend it again.
How to Plan Trades Using Support Line:
Watch for price to approach the Support Line during down moves. If you see a bullish candlestick pattern, buy labels (yellow/green), or other indicators aligning, this can be a high-probability entry zone.
Great for planning stop-loss for long trades: place stops just below this line.
Target: Next resistance zone, Black Zone, or the top of the last swing.
Extra Tip:
Multiple confirmations (support line + Silver Zone + bullish label) provide powerful entry signals.
If price closes strongly below the Support Line with volume, be cautious—support may be breaking, and a trend reversal or deeper correction could follow.
Resistance Line – Logic, Reason, and Trade Planning (from CPPA):
Logic & Visualization:
The Resistance Line is a dynamically drawn dashed line (usually purple or red) that identifies price levels where the market has previously faced significant selling pressure.
This line is created when a candle reaches a high price combined with high volume (orange logic), or from a historical pivot high/resistance,
The script also tracks higher timeframe (HTF) resistance lines, labeled as “Prev Resistance Orange, HTF,” and extends these dashed lines to the right across the chart.
Reasoning:
Resistance Lines are visual markers of “supply zones,” where buyers previously failed, and sellers took control.
If the price returns to this line later, sellers may get active again to defend this level, halting the uptrend.
How to Plan Trades Using Resistance Line:
Watch for price to approach the Resistance Line during up moves. If you see bearish candlestick patterns, sell labels (blue/red), or bearish indicator confirmation, this becomes a strong shorting opportunity.
Perfect for placing stop-loss in short trades—put your stop just above the Resistance Line.
Target: Next support zone (Silver Zone) or bottom of the last swing.
If the price breaks above with high volume, avoid shorting—resistance may be failing.
Extra Tip:
Multiple resistances (Resistance Line + Black Zone + bearish label) make short signals stronger.
Choppy movement around this line often signals indecision; wait for a clear rejection before entering trades.
Bullish / Bearish Label – Logic, Reason, and Trade Planning:
Logic & Visualization:
The indicator constantly calculates a "Bull Score" and a "Bear Score" based on several factors:
Trend direction from price slope
Confirmation by popular indicators (RSI, ADX, SAR, CMF, OBV, CCI, Bollinger Bands, TWAP)
Adaptive scoring (higher score for each bullish/bearish condition met)
If Bull Score > Bear Score, the chart displays a green "BULLISH" label (usually below the bar).
If Bear Score > Bull Score, the chart displays a red "BEARISH" label (usually above the bar).
If neither dominates, a "NEUTRAL" label appears.
Reasoning:
The labels summarize complex price action and indicator analysis into a simple, actionable sentiment cue:
Bullish: Majority of conditions indicate buying strength; trend is up.
Bearish: Majority signals show selling pressure; trend is down.
How to Use in Trade Planning:
Use the Bullish label as confirmation to enter or hold long (buy) positions, especially if near support/Silver Zone.
Use the Bearish label to enter/hold short (sell) positions, especially if near resistance/Black Zone.
For best results, combine with candle color, volume analysis, or other labels (yellow/green for buys, blue/red for sells).
Avoid trading against these labels unless you have strong confluence from zones/support levels.
Yellow Label (Buy Signal) – Logic, Reason & Trade Planning:
Logic & Visualization:
The yellow label appears below a candle (label.style_label_up, yloc.belowbar) and marks a potential buy signal.
Script conditions:
The candle must be a “yellow candle” (which means it’s at the local lowest close, not a high, with normal volume).
Volume is decreasing for 2 consecutive candles (current volume < previous volume, previous volume < second previous).
When these conditions are met, a yellow label is plotted below the candle.
Reasoning:
This scenario often marks the end of selling pressure and start of possible accumulation—buyers may be stepping in as sellers exhaust.
Decreasing volume during a local price low means selling is slowing, possibly hinting at a reversal.
How to Trade Using Yellow Label:
Entry: Consider buying at/just above the yellow-labeled candle’s close.
Stop-loss: A bit below the candle’s low (or Silver Zone line, if present).
Target: Next resistance level, Black Zone, or chart’s bullish label.
Extra Tip:
If the yellow label is found at/near a Silver Zone or Support Line, and trend is “Bullish,” the setup gets even stronger.
Avoid trading if overall indicator shows “Bearish.”
Green Label (Buy with Increasing Volume) – Logic, Reason & Trade Planning:
Logic & Visualization:
The green label is plotted below a candle (label.style_label_up, yloc.belowbar) and marks a strong buy signal.
Script conditions:
The candle must be a “yellow candle” (at the local lowest close, normal volume).
Volume is increasing for 2 consecutive candles (current volume > previous volume, previous volume > second previous).
When these conditions are met, a green label is plotted below the candle.
Reasoning:
This scenario signals that buyers are stepping in aggressively at a local price low—the end of a downtrend with strong, rising activity.
Increasing volume at a price low is a classic sign of accumulation, where institutions or large players may be buying.
How to Trade Using Green Label:
Entry: Consider buying at/just above the green-labeled candle’s close for a momentum-based reversal.
Stop-loss: Slightly below the candle’s low, or the Silver Zone/support line if present.
Target: Nearest resistance zone/Black Zone, indicator’s bullish label, or next swing high.
Extra Tip:
If the green label is near other supports (Silver Zone, Support Line), the setup is extra strong.
Use confirmation from Bullish labels or trend signals for best results.
Green label setups are suitable for quick, high momentum trades due to increasing volume
Blue Label (Sell Signal on Decreasing Volume) – Logic, Reason & Trade Planning:
Logic & Visualization:
The blue label is plotted above a candle (label.style_label_down, yloc.abovebar) as a potential sell signal.
Script conditions:
The candle is a “blue candle” (local highest close, but not also lowest, and volume is neither highest nor lowest).
Volume is decreasing over 2 consecutive candles (current volume < previous, previous < two ago).
When these match, a blue label appears above the candle.
Reasoning:
This typically signals buyer exhaustion at a local high: price has gone up, but volume is dropping, suggesting big players may not be buying any more at these levels.
The trend is losing strength, and a reversal or pullback is likely.
How to Trade Using Blue Label:
Entry: Look to sell at/just below the candle with the blue label.
Stop-loss: Just above the candle’s high (or above the Black Zone/resistance if present).
Target: Nearest support, Silver Zone, or a swing low.
Extra Tip:
Blue label signals are stronger if they appear near Black Zones or Resistance Lines, or when the general market label is "Bearish."
As with buy setups, always check for confirmation from trend or volume before trading aggressively.
Blue Label (Sell Signal on Decreasing Volume) – Logic, Reason & Trade Planning:
Logic & Visualization:
The blue label is plotted above a candle (label.style_label_down, yloc.abovebar) as a potential sell signal.
Script conditions:
The candle is a “blue candle” (local highest close, but not also lowest, and volume is neither highest nor lowest).
Volume is decreasing over 2 consecutive candles (current volume < previous, previous < two ago).
When these match, a blue label appears above the candle.
Reasoning:
This typically signals buyer exhaustion at a local high: price has gone up, but volume is dropping, suggesting big players may not be buying any more at these levels.
The trend is losing strength, and a reversal or pullback is likely.
How to Trade Using Blue Label:
Entry: Look to sell at/just below the candle with the blue label.
Stop-loss: Just above the candle’s high (or above the Black Zone/resistance if present).
Target: Nearest support, Silver Zone, or a swing low.
Extra Tip:
Blue label signals are stronger if they appear near Black Zones or Resistance Lines, or when the general market label is "Bearish."
As with buy setups, always check for confirmation from trend or volume before trading aggressively.
Here’s a summary of all key chart labels, zones, and trading logic of your Price Action script:
Silver Zone: Powerful support zone. Created at lowest close + highest volume. Best for buy entries near its lines.
Black Zone: Strong resistance zone. Created at highest close + lowest volume. Ideal for short trades near its levels.
Support Line: Blue dashed line at historical demand; buyers defend here. Look for bullish setups when price approaches.
Resistance Line: Purple/red dashed line at supply; sellers defend here. Great for bearish setups when price nears.
Bullish/Bearish Labels: Summarize trend direction using price action + multiple indicator confirmations. Plan buys, holds on bullish; sells, shorts on bearish.
Yellow Label: Buy signal on decreasing volume and local price low. Entry above candle, stop below, target next resistance.
Green Label: Strong buy on increasing volume at a price low. Entry for momentum trade, stop below, target next zone.
Blue Label: Sell signal on dropping volume and local price high. Entry below candle, stop above, target next support.
Best Practices:
Always combine zone/label signals for higher probability trades.
Use stop-loss near zones/lines for risk management.
Prefer trading in the trend direction (bullish/bearish label agrees with your entry).
if Any Question, Suggestion Feel free to ask
Disclaimer:
All information provided by this indicator is for educational and analysis purposes only, and should not be considered financial advice.
Liquidity StatusKey Points
The Liquidity Status (LS) indicator is designed to directly monitor liquidity conditions and determine if they are Bullish or Bearish.
If conditions are bullish, the candle is painted green (or whichever color is chosen by you to represent bullish liquidity) and the expected price action is up.
If conditions are bearish, the candle is painted red (or whichever color is chosen by you to represent bearish liquidity) and the expected price action is down.
LS allows you to monitor for when traders are absorbing or supplying liquidity and in which direction the liquidity is flowing.
LS works on equities, cryptocurrencies, forex, options data, and futures.
Summary
The Liquidity Status (LS) indicator measures liquidity directly without relying on bid/ask spreads, order-book information, or any other traditional means. The benefit of this non-traditional approach is a novel and unique way to interpret and analyze liquidity in the market.
LS is designed to be as straightforward as possible: when conditions are bullish then the outlook is bullish and the candles are painted the bullish color (default: green), and when conditions are bearish then the outlook is bearish and the candles are painted the bearish color (default: red).
This means the candles are not colored based on their price movements but rather based on their liquidity status.
Additionally, LS indicates Liquidity Flow (LF) as well. LF indicates where the source of liquidity is or is moving towards: either towards the Ask (if the Bid is requiring liquidity then the liquidity source becomes the Ask), or towards the Bid (if the Ask is requiring liquidity then the liquidity source becomes the Bid). This can be helpful in early identification of trend changes.
The default settings are designed to be streamlined but the Settings section below outlines how to add additional information and detail to your charts if desired.
Examples
An example of LS on default setting:
With Full and Declarative reporting:
ES Futures:
Details
In the default settings, LS indicates if conditions are:
Bullish : meaning that current liquidity is bullish and so too are outlooks, or
Bearish: meaning that current liquidity is bearish and so too are outlooks.
There are additional data that are provided via LS, if toggled on (as described below). They include:
Aggressive Bid / Ask : This indicates that there is an aggressive trader present. Aggressive traders are large liquidity absorbers and are defined as having a sense of urgency in their trading that will cause them to go where-ever (whichever price) they can in order to transact. A classic Aggressive Bid, for instance, is a short-seller currently being squeezed.
Eager Bid / Ask : This indicates that there is an eager trader present. Eager traders are defined by their willingness to “cross the isle” in order to transact. For example, an eager bid will move to the ask in order to transact whereas an organic bid would not.
Organic Bid / Ask : This indicates that transactions are occurring at the organic traders. Organic traders are defined as having a large time-horizon and are value-seekers. For instance, an organic ask will likely move price up in order to sell high (the second part of buy low, sell high).
Additionally, LS indicates LF by specifying which party has the demand for liquidity and which has the supply for liquidity.
Flow to Ask : This indicates that the demand to transact is flowing to the ask (i.e.: the bid needs to transact more than the ask) and thus the ask is becoming the liquidity supplier.
Flow to Bid : This indicates that the demand to transact is flowing to the bid (i.e.: the ask needs to transact more than the bid) and thus the bid is becoming the liquidity supplier.
Neutral : No discernable difference in liquidity demand.
In combination, these signals can produce powerful measurements of underlying liquidity activity. For instance:
If LS indicates “At Organic Ask” and LF indicates “Flow to Ask” then this means that (1) transactions are predominantly occurring at or near the organic ask and (2) the organic ask is the dominate liquidity supplier. The consequence is likely substantial price appreciation (remember: the organic ask wants to sell high and now they are setting the terms and conditions of transacting!).
Example - How it started: transactions started to occur at the Organic Ask with Flow to Ask:
Example - How it ended:
Conversely, “At Organic Bid” and “Flow to Bid” indicates that transactions are predominantly occurring at or near the organic bid (who wants to buy low) and they the ones fulfilling the demand to transact coming from the ask. The expected outlook? Price depreciation as the organic bid lowers their orders to average down!
Example - How it started: transactions started to occur at Organic Bid with Flow to Bid:
Example - How it ended:
Lastly, LS (in combination with Liquidity Triggers) can identify moments of high-risk for bull and bear traps (see FAQ for details on how traps are found).
Example: Bear-Trap (with LT displayed)
Example: Bull-Trap (with LT displayed)
Customization
LS has many customization options available.
Sensitivity Mode
LS comes in a variety of sensitivities (for the nerds: adjusting the Sensitivity vs. Specificity), outlined below:
Aggressive : The Aggressive sensitivity mode puts LS in a state of hyper-awareness for anything that might indicate a change in overall liquidity status (i.e.: Bullish to Bearish or Bearish to Bullish) is underway. The benefit of the Aggressive mode is that it does not take much for LS to change its mind about current conditions. The trade-off, however, is increase in false alarms.
Balance : The balanced setting works to balance specificity (how right LS is) with sensitivity (how much chang it takes to convince LS to change its mind).
Conservative : The conservative setting is prone to change slower than both Aggressive and Balance but is intended to be more “certain” of the changes when they are indicated. This can lower the sensitivity (early entrances to trend-changes might be delayed slightly) in exchange for greater confidence in the future.
Diamond : This is the most specific and least sensitive option. Designed for when you only want LS to indicate a change with the strictest of criteria met.
Examples:
Aggressive LS:
Balanced LS:
Conservative LS:
Diamond LS:
LS Detail Amount
Controls how much detail and information you want displayed.
Simplified : Keeps messaging straightforward: Bearish or Bullish.
Full : Parsing the data for greater detail about if conditions are Strong or Weak. Produces candles and text output.
LS Reporting Style
Interpretive : Text output from LS is kept as either Bullish or Bearish.
Declarative : Additional information regarding if the transactions are being performed by an Aggressive, Eager or Organic trader.
LS Candle Replacement
In order to have LS produce candles colored by liquidity, the `LS Candle Replacement` option must be selected, along with deselecting the charts candle-making by going to Settings -> Symbol and de-selecting `Body`, `Border`, and `Wick`.
Otherwise, LS’ colors will be over-ridden by the chart.
Alerts
LS comes with several alerts to help keep track of changing liquidity conditions in the market. They include:
Is Bullish / Bearish : fires at the start of the candle if conditions are bullish/bearish.
Has Become Bullish / Bearish : Fires at the end of the candle if conditions have swapped (as compared to the previous candle).
Flow is to Ask / Bid : Fires at the start of the candle to indicate which direction liquidity is flowing via LF.
Flow Switch to Bid / Ask : Fires if there is a change in the LF from one to the other.
Suspected Bear Trap : Fires if a bear trap is detected.
Suspected Bear Trap Ended : Fires if an on-going bear-trap has ended.
Suspected Bull Trap : Fires if a bull trap is detected.
Suspected Bull Trap Ended : Fires if an on-going bull-trap has ended.
Frequently Asked Questions
How can I get access to LS?
Please see the Author’s Instructions for more information.
Where can I get more information on LS?
Please see the Author’s Instructions for more information.
I tried to add LS to my chart but nothing is showing.
That’s no good! Be sure that the indicator hasn’t errored out (if there is a small red dot next to its name then it has errored out). If it has, then try re-applying the indicator to your chart.
If there is no error indicated, and you still do not see anything it may be likely that the requested symbol either:
Doesn’t have sufficient data to calculate LS on, or
Lacks the data for LS to be calculated completed.
To check, try using LS on a smaller interval. If LS starts to populate, it is likely that the needed data is present but just not enough for the timeframe you were interested in. If there is no LS even when moving to lower intervals, then it may be that the specified underlying lacks the required data.
How come LS is saying things are Bearish but price is going up?
Sometimes that can happen! But until LS indicates bullish liquidity, the expectation is that price will fall back down.
How come LS is saying things are Bullish but price is going down?
Sometimes that can happen! But until LS indicates bearish liquidity, the expectation is that price will recover and continue moving on upwards.
How do you locate Bear and Bull traps?
LS has LT (Liquidity Triggers) baked into it for alerts and uses LT to compare expected conditions with real conditions. If LS and LT are mismatched then a trap is detected. The LT conditions checked are:
If LT is in a bull-stack : that means LT(144) > LT(377) > LT(610), or
If LT is in a bear-stack : that means LT(610) < LT(377) < LT(144)
Then once the stack is determined, if LS disagrees:
LS is indicating Bullish while LT is in a bear-stack, or
LS is indicating Bearish while LT is in a bull-stack
Then the alert is triggered (based off of LT’s orientation). This means:
If conditions are Bullish but LT is showing a Bearish stack, then a Bull Trap is detected, and
If conditions are Bearish but LT is showing a Bullish Stack, then a Bear Trap is detected.
I have questions and maybe a bug!
Please reach out and report! Please refer to the Author’s Instructions for more information on how to reach out.
Does LS get updates?
Yup! Improvements come relatively frequently and if you have any suggestions for improvements, please don’t hesitate to reach out.
Trend Fib Zone Bounce (TFZB) [KedArc Quant]Description:
Trend Fib Zone Bounce (TFZB) trades with the latest confirmed Supply/Demand zone using a single, configurable Fib pullback (0.3/0.5/0.6). Trade only in the direction of the most recent zone and use a single, configurable fib level for pullback entries.
• Detects market structure via confirmed swing highs/lows using a rolling window.
• Draws Supply/Demand zones (bearish/bullish rectangles) from the latest MSS (CHOCH or BOS) event.
• Computes intra zone Fib guide rails and keeps them extended in real time.
• Triggers BUY only inside bullish zones and SELL only inside bearish zones when price touches the selected fib and closes back beyond it (bounce confirmation).
• Optional labels print BULL/BEAR + fib next to the triangle markers.
What it does
Finds structure using confirmed swing highs/lows (you choose the confirmation length).
Builds the latest zone (bullish = demand, bearish = supply) after a CHOCH/BOS event.
Draws intra-zone “guide rails” (Fib lines) and extends them live.
Signals only with the trend of that zone:
BUY inside a bullish zone when price tags the selected Fib and closes back above it.
SELL inside a bearish zone when price tags the selected Fib and closes back below it.
Optional labels print BULL/BEAR + Fib next to triangles for quick context
Why this is different
Most “zone + fib + signal” tools bolt together several indicators, or fire counter-trend signals because they don’t fully respect structure. TFZB is intentionally minimal:
Single bias source: the latest confirmed zone defines direction; nothing else overrides it.
Single entry rule: one Fib bounce (0.3/0.5/0.6 selectable) inside that zone—no counter-trend trades by design.
Clean visuals: you can show only the most recent zone, clamp overlap, and keep just the rails that matter.
Deterministic & transparent: every plot/label comes from the code you see—no external series or hidden smoothing
How it helps traders
Cuts decision noise: you always know the bias and the only entry that matters right now.
Forces discipline: if price isn’t inside the active zone, you don’t trade.
Adapts to volatility: pick 0.3 in strong trends, 0.5 as the default, 0.6 in chop.
Non-repainting zones: swings are confirmed after Structure Length bars, then used to build zones that extend forward (they don’t “teleport” later)
How it works (details)
*Structure confirmation
A swing high/low is only confirmed after Structure Length bars have elapsed; the dot is plotted back on the original bar using offset. Expect a confirmation delay of about Structure Length × timeframe.
*Zone creation
After a CHOCH/BOS (momentum shift / break of prior swing), TFZB draws the new Supply/Demand zone from the swing anchors and sets it active.
*Fib guide rails
Inside the active zone TFZB projects up to five Fib lines (defaults: 0.3 / 0.5 / 0.7) and extends them as time passes.
*Entry logic (with-trend only)
BUY: bar’s low ≤ fib and close > fib inside a bullish zone.
SELL: bar’s high ≥ fib and close < fib inside a bearish zone.
*Optionally restrict to one signal per zone to avoid over-trading.
(Optional) Aggressive confirm-bar entry
When do the swing dots print?
* The code confirms a swing only after `structureLen` bars have elapsed since that candidate high/low.
* On a 5-min chart with `structureLen = 10`, that’s about 50 minutes later.
* When the swing confirms, the script plots the dot back on the original bar (via `offset = -structureLen`). So you *see* the dot on the old bar, but it only appears on the chart once the confirming bar arrives.
> Practical takeaway: expect swing markers to appear roughly `structureLen × timeframe` later. Zones and signals are built from those confirmed swings.
Best timeframe for this Indicator
Use the timeframe that matches your holding period and the noise level of the instrument:
* Intraday :
* 5m or 15m are the sweet spots.
* Suggested `structureLen`:
* 5m: 10–14 (confirmation delay \~50–70 min)
* 15m: 8–10 (confirmation delay \~2–2.5 hours)
* Keep Entry Fib at 0.5 to start; try 0.3 in strong trends, 0.6 in chop.
* Tip: avoid the first 10–15 minutes after the open; let the initial volatility set the early structure.
* Swing/overnight:
* 1h or 4h.
* `structureLen`:
* 1h: 6–10 (6–10 hours confirmation)
* 4h: 5–8 (20–32 hours confirmation)
* 1m scalping: not recommended here—the confirmation lag relative to the noise makes zones less reliable.
Inputs (all groups)
Structure
• Show Swing Points (structureTog)
o Plots small dots on the bar where a swing point is confirmed (offset back by Structure Length).
• Structure Length (structureLen)
o Lookback used to confirm swing highs/lows and determine local structure. Higher = fewer, stronger swings; lower = more reactive.
Zones
• Show Last (zoneDispNum)
o Maximum number of zones kept on the chart when Display All Zones is off.
• Display All Zones (dispAll)
o If on, ignores Show Last and keeps all zones/levels.
• Zone Display (zoneFilter): Bullish Only / Bearish Only / Both
o Filters which zone types are drawn and eligible for signals.
• Clean Up Level Overlap (noOverlap)
o Prevents fib lines from overlapping when a new zone starts near the previous one (clamps line start/end times for readability).
Fib Levels
Each row controls whether a fib is drawn and how it looks:
• Toggle (f1Tog…f5Tog): Show/hide a given fib line.
• Level (f1Lvl…f5Lvl): Numeric ratio in . Defaults active: 0.3, 0.5, 0.7 (0 and 1 off by default).
• Line Style (f1Style…f5Style): Solid / Dashed / Dotted.
• Bull/Bear Colors (f#BullColor, f#BearColor): Per-fib color in bullish vs bearish zones.
Style
• Structure Color: Dot color for confirmed swing points.
• Bullish Zone Color / Bearish Zone Color: Rectangle fills (transparent by default).
Signals
• Entry Fib for Signals (entryFibSel): Choose 0.3, 0.5 (default), or 0.6 as the trigger line.
• Show Buy/Sell Signals (showSignals): Toggles triangle markers on/off.
• One Signal Per Zone (oneSignalPerZone): If on, suppresses additional entries within the same zone after the first trigger.
• Show Signal Text Labels (Bull/Bear + Fib) (showSignalLabels): Adds a small label next to each triangle showing zone bias and the fib used (e.g., BULL 0.5 or BEAR 0.3).
How TFZB decides signals
With trend only:
• BUY
1. Latest active zone is bullish.
2. Current bar’s close is inside the zone (between top and bottom).
3. The bar’s low ≤ selected fib and it closes > selected fib (bounce).
• SELL
1. Latest active zone is bearish.
2. Current bar’s close is inside the zone.
3. The bar’s high ≥ selected fib and it closes < selected fib.
Markers & labels
• BUY: triangle up below the bar; optional label “BULL 0.x” above it.
• SELL: triangle down above the bar; optional label “BEAR 0.x” below it.
Right-Panel Swing Log (Table)
What it is
A compact, auto-updating log of the most recent Swing High/Low events, printed in the top-right of the chart.
It helps you see when a pivot formed, when it was confirmed, and at what price—so you know the earliest bar a zone-based signal could have appeared.
Columns
Type – Swing High or Swing Low.
Date – Calendar date of the swing bar (follows the chart’s timezone).
Swing @ – Time of the original swing bar (where the dot is drawn).
Confirm @ – Time of the bar that confirmed that swing (≈ Structure Length × timeframe after the swing). This is also the earliest moment a new zone/entry can be considered.
Price – The swing price (high for SH, low for SL).
Why it’s useful
Clarity on repaint/confirmation: shows the natural delay between a swing forming and being usable—no guessing.
Planning & journaling: quick reference of today’s pivots and prices for notes/backtesting.
Scanning intraday: glance to see if you already have a confirmed zone (and therefore valid fib-bounce entries), or if you’re still waiting.
Context for signals: if a fib-bounce triangle appears before the time listed in Confirm @, it’s not a valid trade (you were too early).
Settings (Inputs → Logging)
Log swing times / Show table – turn the table on/off.
Rows to keep – how many recent entries to display.
Show labels on swing bar – optional tags on the chart (“Swing High 11:45”, “Confirm SH 14:15”) that match the table.
Recommended defaults
• Structure Length: 10–20 for intraday; 20–40 for swing.
• Entry Fib for Signals: 0.5 to start; try 0.3 in stronger trends and 0.6 in choppier markets.
• One Signal Per Zone: ON (prevents over trading).
• Zone Display: Both.
• Fib Lines: Keep 0.3/0.5/0.7 on; turn on 0 and 1 only if you need anchors.
Alerts
Two alert conditions are available:
• BUY signal – fires when a with trend bullish bounce at the selected fib occurs inside a bullish zone.
• SELL signal – fires when a with trend bearish bounce at the selected fib occurs inside a bearish zone.
Create alerts from the chart’s Alerts panel and select the desired condition. Use Once Per Bar Close to avoid intrabar flicker.
Notes & tips
• Swing dots are confirmed only after Structure Length bars, so they plot back in time; zones built from these confirmed swings do not repaint (though they extend as new bars form).
• If you don’t see a BUY where you expect one, check: (1) Is the active zone bullish? (2) Did the candle’s low actually pierce the selected fib and close above it? (3) Is One Signal Per Zone suppressing a second entry?
• You can hide visual clutter by reducing Show Last to 1–3 while keeping Display All Zones off.
Glossary
• CHOCH (Change of Character): A shift where price breaks beyond the last opposite swing while local momentum flips.
• BOS (Break of Structure): A cleaner break beyond the prior swing level in the current momentum direction.
• MSS: Either CHOCH or BOS – any event that spawns a new zone.
Extension ideas (optional)
• Add fib extensions (1.272 / 1.618) for target lines.
• Zone quality score using ATR normalization to filter weak impulses.
• HTF filter to only accept zones aligned with a higher timeframe trend.
⚠️ Disclaimer This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
RSI WMA VWMA Divergence Indicator// This Pine Script® code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © Kenndjk
//@version=6
indicator(title="RSI WMA VWMA Divergence Indicator", shorttitle="Kenndjk", format=format.price, precision=2)
oscType = input.string("RSI", "Oscillator Type", options = , group="General Settings")
// RSI Settings
rsiGroup = "RSI Settings"
rsiLengthInput = input.int(14, minval=1, title="RSI Length", group=rsiGroup)
rsiSourceInput = input.source(close, "Source", group=rsiGroup)
// WMA VWMA
wmaLength = input.int(9, "WMA Length", minval=1, group="WMA Settings")
vwmaLength = input.int(3, "VWMA Length", minval=1, group="WMA Settings")
wma = ta.wma(close, wmaLength)
vwma = ta.vwma(close, vwmaLength)
useVWMA = input.bool(true, "Use VWMA for Divergence (when WMA + VWMA mode)", group="WMA Settings")
// Oscillator selection
rsi = ta.rsi(rsiSourceInput, rsiLengthInput) // Calculate RSI always, but use conditionally
osc = oscType == "RSI" ? rsi : useVWMA ? vwma : wma
// RSI plots (conditional)
isRSI = oscType == "RSI"
rsiPlot = plot(isRSI ? rsi : na, "RSI", color=isRSI ? #7E57C2 : na)
rsiUpperBand = hline(isRSI ? 70 : na, "RSI Upper Band", color=isRSI ? #787B86 : na)
midline = hline(isRSI ? 50 : na, "RSI Middle Band", color=isRSI ? color.new(#787B86, 50) : na)
rsiLowerBand = hline(isRSI ? 30 : na, "RSI Lower Band", color=isRSI ? #787B86 : na)
fill(rsiUpperBand, rsiLowerBand, color=isRSI ? color.rgb(126, 87, 194, 90) : na, title="RSI Background Fill")
midLinePlot = plot(isRSI ? 50 : na, color = na, editable = false, display = display.none)
fill(rsiPlot, midLinePlot, 100, 70, top_color = isRSI ? color.new(color.green, 0) : na, bottom_color = isRSI ? color.new(color.green, 100) : na, title = "Overbought Gradient Fill")
fill(rsiPlot, midLinePlot, 30, 0, top_color = isRSI ? color.new(color.red, 100) : na, bottom_color = isRSI ? color.new(color.red, 0) : na, title = "Oversold Gradient Fill")
// WMA VWMA plots
wmaColor = oscType != "RSI" ? (useVWMA ? color.new(color.blue, 70) : color.blue) : na
wmaWidth = useVWMA ? 1 : 2
vwmaColor = oscType != "RSI" ? (useVWMA ? color.orange : color.new(color.orange, 70)) : na
vwmaWidth = useVWMA ? 2 : 1
plot(oscType != "RSI" ? wma : na, "WMA", color=wmaColor, linewidth=wmaWidth)
plot(oscType != "RSI" ? vwma : na, "VWMA", color=vwmaColor, linewidth=vwmaWidth)
// Smoothing MA inputs (only for RSI)
GRP = "Smoothing (RSI only)"
TT_BB = "Only applies when 'Show Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maLengthSMA = input.int(14, "SMA Length", minval=1, group=GRP, display=display.data_window)
maLengthEMA = input.int(14, "EMA Length", minval=1, group=GRP, display=display.data_window)
maLengthRMA = input.int(14, "SMMA (RMA) Length", minval=1, group=GRP, display=display.data_window)
maLengthWMA = input.int(14, "WMA Length", minval=1, group=GRP, display=display.data_window)
maLengthVWMA = input.int(14, "VWMA Length", minval=1, group=GRP, display=display.data_window)
bbMultInput = input.float(2.0, "BB StdDev", minval=0.001, maxval=50, step=0.5, tooltip=TT_BB, group=GRP, display=display.data_window)
showSMA = input.bool(false, "Show SMA", group=GRP)
showEMA = input.bool(false, "Show EMA", group=GRP)
showRMA = input.bool(false, "Show SMMA (RMA)", group=GRP)
showWMAsmooth = input.bool(false, "Show WMA", group=GRP)
showVWMAsmooth = input.bool(false, "Show VWMA", group=GRP)
showBB = input.bool(false, "Show SMA + Bollinger Bands", group=GRP, tooltip=TT_BB)
// Smoothing MA Calculations
sma_val = (showSMA or showBB) and isRSI ? ta.sma(rsi, maLengthSMA) : na
ema_val = showEMA and isRSI ? ta.ema(rsi, maLengthEMA) : na
rma_val = showRMA and isRSI ? ta.rma(rsi, maLengthRMA) : na
wma_val = showWMAsmooth and isRSI ? ta.wma(rsi, maLengthWMA) : na
vwma_val = showVWMAsmooth and isRSI ? ta.vwma(rsi, maLengthVWMA) : na
smoothingStDev = showBB and isRSI ? ta.stdev(rsi, maLengthSMA) * bbMultInput : na
// Smoothing MA plots
plot(sma_val, "RSI-based SMA", color=(showSMA or showBB) ? color.yellow : na, display=(showSMA or showBB) ? display.all : display.none, editable=(showSMA or showBB))
plot(ema_val, "RSI-based EMA", color=showEMA ? color.purple : na, display=showEMA ? display.all : display.none, editable=showEMA)
plot(rma_val, "RSI-based RMA", color=showRMA ? color.red : na, display=showRMA ? display.all : display.none, editable=showRMA)
plot(wma_val, "RSI-based WMA", color=showWMAsmooth ? color.blue : na, display=showWMAsmooth ? display.all : display.none, editable=showWMAsmooth)
plot(vwma_val, "RSI-based VWMA", color=showVWMAsmooth ? color.orange : na, display=showVWMAsmooth ? display.all : display.none, editable=showVWMAsmooth)
bbUpperBand = plot(showBB ? sma_val + smoothingStDev : na, title="Upper Bollinger Band", color=showBB ? color.green : na, display=showBB ? display.all : display.none, editable=showBB)
bbLowerBand = plot(showBB ? sma_val - smoothingStDev : na, title="Lower Bollinger Band", color=showBB ? color.green : na, display=showBB ? display.all : display.none, editable=showBB)
fill(bbUpperBand, bbLowerBand, color=showBB ? color.new(color.green, 90) : na, title="Bollinger Bands Background Fill", display=showBB ? display.all : display.none, editable=showBB)
// Divergence Settings
divGroup = "Divergence Settings"
calculateDivergence = input.bool(true, title="Calculate Divergence", group=divGroup, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
lookbackLeft = input.int(5, "Pivot Lookback Left", minval=1, group=divGroup)
lookbackRight = input.int(5, "Pivot Lookback Right", minval=1, group=divGroup)
rangeLower = input.int(5, "Min Range for Divergence", minval=0, group=divGroup)
rangeUpper = input.int(60, "Max Range for Divergence", minval=1, group=divGroup)
showHidden = input.bool(true, "Show Hidden Divergences", group=divGroup)
bearColor = color.red
bullColor = color.green
textColor = color.white
noneColor = color.new(color.white, 100)
_inRange(cond) =>
bars = ta.barssince(cond)
rangeLower <= bars and bars <= rangeUpper
bool plFound = false
bool phFound = false
bool bullCond = false
bool bearCond = false
bool hiddenBullCond = false
bool hiddenBearCond = false
float oscLBR = na
float lowLBR = na
float highLBR = na
float prevPlOsc = na
float prevPlLow = na
float prevPhOsc = na
float prevPhHigh = na
if calculateDivergence
plFound := not na(ta.pivotlow(osc, lookbackLeft, lookbackRight))
phFound := not na(ta.pivothigh(osc, lookbackLeft, lookbackRight))
oscLBR := osc
lowLBR := low
highLBR := high
prevPlOsc := ta.valuewhen(plFound, oscLBR, 1)
prevPlLow := ta.valuewhen(plFound, lowLBR, 1)
prevPhOsc := ta.valuewhen(phFound, oscLBR, 1)
prevPhHigh := ta.valuewhen(phFound, highLBR, 1)
// Regular Bullish
oscHL = oscLBR > prevPlOsc and _inRange(plFound )
priceLL = lowLBR < prevPlLow
bullCond := priceLL and oscHL and plFound
// Regular Bearish
oscLL = oscLBR < prevPhOsc and _inRange(phFound )
priceHH = highLBR > prevPhHigh
bearCond := priceHH and oscLL and phFound
// Hidden Bullish
oscLL_hidden = oscLBR < prevPlOsc and _inRange(plFound )
priceHL = lowLBR > prevPlLow
hiddenBullCond := priceHL and oscLL_hidden and plFound and showHidden
// Hidden Bearish
oscHH_hidden = oscLBR > prevPhOsc and _inRange(phFound )
priceLH = highLBR < prevPhHigh
hiddenBearCond := priceLH and oscHH_hidden and phFound and showHidden
// Plot divergences (lines and labels on pane)
if bullCond
leftBar = ta.valuewhen(plFound, bar_index , 1)
line.new(leftBar, prevPlOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bullColor, width=2)
label.new(bar_index , oscLBR, "R Bull", style=label.style_label_up, color=noneColor, textcolor=textColor)
if bearCond
leftBar = ta.valuewhen(phFound, bar_index , 1)
line.new(leftBar, prevPhOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bearColor, width=2)
label.new(bar_index , oscLBR, "R Bear", style=label.style_label_down, color=noneColor, textcolor=textColor)
if hiddenBullCond
leftBar = ta.valuewhen(plFound, bar_index , 1)
line.new(leftBar, prevPlOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bullColor, width=2, style=line.style_dashed)
label.new(bar_index , oscLBR, "H Bull", style=label.style_label_up, color=noneColor, textcolor=textColor)
if hiddenBearCond
leftBar = ta.valuewhen(phFound, bar_index , 1)
line.new(leftBar, prevPhOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bearColor, width=2, style=line.style_dashed)
label.new(bar_index , oscLBR, "H Bear", style=label.style_label_down, color=noneColor, textcolor=textColor)
// Alert conditions
alertcondition(bullCond, title="Regular Bullish Divergence", message="Found a new Regular Bullish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(bearCond, title="Regular Bearish Divergence", message="Found a new Regular Bearish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(hiddenBullCond, title="Hidden Bullish Divergence", message="Found a new Hidden Bullish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(hiddenBearCond, title="Hidden Bearish Divergence", message="Found a new Hidden Bearish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
RSI WMA VWMA Divergence Indicator//@version=6
indicator(title="RSI WMA VWMA Divergence Indicator", shorttitle="Osc Div", format=format.price, precision=2)
oscType = input.string("RSI", "Oscillator Type", options = , group="General Settings")
// RSI Settings
rsiGroup = "RSI Settings"
rsiLengthInput = input.int(14, minval=1, title="RSI Length", group=rsiGroup)
rsiSourceInput = input.source(close, "Source", group=rsiGroup)
// WMA VWMA
wma9 = ta.wma(close, 9)
vwma3 = ta.vwma(close, 3)
useVWMA = input.bool(true, "Use VWMA3 for Divergence (when WMA9 + VWMA3 mode)", group="WMA Settings")
// Oscillator selection
rsi = ta.rsi(rsiSourceInput, rsiLengthInput) // Calculate RSI always, but use conditionally
osc = oscType == "RSI" ? rsi : useVWMA ? vwma3 : wma9
// RSI plots (conditional)
isRSI = oscType == "RSI"
rsiPlot = plot(isRSI ? rsi : na, "RSI", color=isRSI ? #7E57C2 : na)
rsiUpperBand = hline(isRSI ? 70 : na, "RSI Upper Band", color=isRSI ? #787B86 : na)
midline = hline(isRSI ? 50 : na, "RSI Middle Band", color=isRSI ? color.new(#787B86, 50) : na)
rsiLowerBand = hline(isRSI ? 30 : na, "RSI Lower Band", color=isRSI ? #787B86 : na)
fill(rsiUpperBand, rsiLowerBand, color=isRSI ? color.rgb(126, 87, 194, 90) : na, title="RSI Background Fill")
midLinePlot = plot(isRSI ? 50 : na, color = na, editable = false, display = display.none)
fill(rsiPlot, midLinePlot, 100, 70, top_color = isRSI ? color.new(color.green, 0) : na, bottom_color = isRSI ? color.new(color.green, 100) : na, title = "Overbought Gradient Fill")
fill(rsiPlot, midLinePlot, 30, 0, top_color = isRSI ? color.new(color.red, 100) : na, bottom_color = isRSI ? color.new(color.red, 0) : na, title = "Oversold Gradient Fill")
// WMA VWMA plots
plot(oscType != "RSI" ? wma9 : na, "WMA9", color=oscType != "RSI" ? color.blue : na)
plot(oscType != "RSI" ? vwma3 : na, "VWMA3", color=oscType != "RSI" ? color.orange : na)
// Smoothing MA inputs (only for RSI)
GRP = "Smoothing (RSI only)"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maTypeInput = input.string("SMA", "Type", options = , group = GRP, display = display.data_window)
maLengthInput = input.int(14, "Length", group = GRP, display = display.data_window)
bbMultInput = input.float(2.0, "BB StdDev", minval = 0.001, maxval = 50, step = 0.5, tooltip = TT_BB, group = GRP, display = display.data_window)
enableMA = maTypeInput != "None" and oscType == "RSI"
isBB = maTypeInput == "SMA + Bollinger Bands" and oscType == "RSI"
// Smoothing MA Calculation
ma(source, length, MAtype) =>
switch MAtype
"SMA" => ta.sma(source, length)
"SMA + Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
// Smoothing MA plots
smoothingMA = enableMA ? ma(rsi, maLengthInput, maTypeInput) : na
smoothingStDev = isBB ? ta.stdev(rsi, maLengthInput) * bbMultInput : na
plot(smoothingMA, "RSI-based MA", color=enableMA ? color.yellow : na, display = enableMA ? display.all : display.none, editable = enableMA)
bbUpperBand = plot(isBB ? smoothingMA + smoothingStDev : na, title = "Upper Bollinger Band", color=isBB ? color.green : na, display = isBB ? display.all : display.none, editable = isBB)
bbLowerBand = plot(isBB ? smoothingMA - smoothingStDev : na, title = "Lower Bollinger Band", color=isBB ? color.green : na, display = isBB ? display.all : display.none, editable = isBB)
fill(bbUpperBand, bbLowerBand, color= isBB ? color.new(color.green, 90) : na, title="Bollinger Bands Background Fill", display = isBB ? display.all : display.none, editable = isBB)
// Divergence Settings
divGroup = "Divergence Settings"
calculateDivergence = input.bool(true, title="Calculate Divergence", group=divGroup, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
lookbackLeft = input.int(5, "Pivot Lookback Left", minval=1, group=divGroup)
lookbackRight = input.int(5, "Pivot Lookback Right", minval=1, group=divGroup)
rangeLower = input.int(5, "Min Range for Divergence", minval=0, group=divGroup)
rangeUpper = input.int(60, "Max Range for Divergence", minval=1, group=divGroup)
showHidden = input.bool(true, "Show Hidden Divergences", group=divGroup)
bearColor = color.red
bullColor = color.green
textColor = color.white
noneColor = color.new(color.white, 100)
_inRange(cond) =>
bars = ta.barssince(cond)
rangeLower <= bars and bars <= rangeUpper
bool plFound = false
bool phFound = false
bool bullCond = false
bool bearCond = false
bool hiddenBullCond = false
bool hiddenBearCond = false
float oscLBR = na
float lowLBR = na
float highLBR = na
float prevPlOsc = na
float prevPlLow = na
float prevPhOsc = na
float prevPhHigh = na
if calculateDivergence
plFound := not na(ta.pivotlow(osc, lookbackLeft, lookbackRight))
phFound := not na(ta.pivothigh(osc, lookbackLeft, lookbackRight))
oscLBR := osc
lowLBR := low
highLBR := high
prevPlOsc := ta.valuewhen(plFound, oscLBR, 1)
prevPlLow := ta.valuewhen(plFound, lowLBR, 1)
prevPhOsc := ta.valuewhen(phFound, oscLBR, 1)
prevPhHigh := ta.valuewhen(phFound, highLBR, 1)
// Regular Bullish
oscHL = oscLBR > prevPlOsc and _inRange(plFound )
priceLL = lowLBR < prevPlLow
bullCond := priceLL and oscHL and plFound
// Regular Bearish
oscLL = oscLBR < prevPhOsc and _inRange(phFound )
priceHH = highLBR > prevPhHigh
bearCond := priceHH and oscLL and phFound
// Hidden Bullish
oscLL_hidden = oscLBR < prevPlOsc and _inRange(plFound )
priceHL = lowLBR > prevPlLow
hiddenBullCond := priceHL and oscLL_hidden and plFound and showHidden
// Hidden Bearish
oscHH_hidden = oscLBR > prevPhOsc and _inRange(phFound )
priceLH = highLBR < prevPhHigh
hiddenBearCond := priceLH and oscHH_hidden and phFound and showHidden
// Plot divergences (lines and labels on pane)
if bullCond
leftBar = ta.valuewhen(plFound, bar_index , 1)
line.new(leftBar, prevPlOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bullColor, width=2)
label.new(bar_index , oscLBR, "R Bull", style=label.style_label_up, color=noneColor, textcolor=textColor)
if bearCond
leftBar = ta.valuewhen(phFound, bar_index , 1)
line.new(leftBar, prevPhOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bearColor, width=2)
label.new(bar_index , oscLBR, "R Bear", style=label.style_label_down, color=noneColor, textcolor=textColor)
if hiddenBullCond
leftBar = ta.valuewhen(plFound, bar_index , 1)
line.new(leftBar, prevPlOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bullColor, width=2, style=line.style_dashed)
label.new(bar_index , oscLBR, "H Bull", style=label.style_label_up, color=noneColor, textcolor=textColor)
if hiddenBearCond
leftBar = ta.valuewhen(phFound, bar_index , 1)
line.new(leftBar, prevPhOsc, bar_index , oscLBR, xloc=xloc.bar_index, color=bearColor, width=2, style=line.style_dashed)
label.new(bar_index , oscLBR, "H Bear", style=label.style_label_down, color=noneColor, textcolor=textColor)
// Alert conditions
alertcondition(bullCond, title="Regular Bullish Divergence", message="Found a new Regular Bullish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(bearCond, title="Regular Bearish Divergence", message="Found a new Regular Bearish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(hiddenBullCond, title="Hidden Bullish Divergence", message="Found a new Hidden Bullish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
alertcondition(hiddenBearCond, title="Hidden Bearish Divergence", message="Found a new Hidden Bearish Divergence, Pivot Lookback Right number of bars to the left of the current bar.")
Market Zone Analyzer[BullByte]Understanding the Market Zone Analyzer
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1. Purpose of the Indicator
The Market Zone Analyzer is a Pine Script™ (version 6) indicator designed to streamline market analysis on TradingView. Rather than scanning multiple separate tools, it unifies four core dimensions—trend strength, momentum, price action, and market activity—into a single, consolidated view. By doing so, it helps traders:
• Save time by avoiding manual cross-referencing of disparate signals.
• Reduce decision-making errors that can arise from juggling multiple indicators.
• Gain a clear, reliable read on whether the market is in a bullish, bearish, or sideways phase, so they can more confidently decide to enter, exit, or hold a position.
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2. Why a Trader Should Use It
• Unified View: Combines all essential market dimensions into one easy-to-read score and dashboard, eliminating the need to piece together signals manually.
• Adaptability: Automatically adjusts its internal weighting for trend, momentum, and price action based on current volatility. Whether markets are choppy or calm, the indicator remains relevant.
• Ease of Interpretation: Outputs a simple “BULLISH,” “BEARISH,” or “SIDEWAYS” label, supplemented by an intuitive on-chart dashboard and an oscillator plot that visually highlights market direction.
• Reliability Features: Built-in smoothing of the net score and hysteresis logic (requiring consecutive confirmations before flips) minimize false signals during noisy or range-bound phases.
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3. Why These Specific Indicators?
This script relies on a curated set of well-established technical tools, each chosen for its particular strength in measuring one of the four core dimensions:
1. Trend Strength:
• ADX/DMI (Average Directional Index / Directional Movement Index): Measures how strong a trend is, and whether the +DI line is above the –DI line (bullish) or vice versa (bearish).
• Moving Average Slope (Fast MA vs. Slow MA): Compares a shorter-period SMA to a longer-period SMA; if the fast MA sits above the slow MA, it confirms an uptrend, and vice versa for a downtrend.
• Ichimoku Cloud Differential (Senkou A vs. Senkou B): Provides a forward-looking view of trend direction; Senkou A above Senkou B signals bullishness, and the opposite signals bearishness.
2. Momentum:
• Relative Strength Index (RSI): Identifies overbought (above its dynamically calculated upper bound) or oversold (below its lower bound) conditions; changes in RSI often precede price reversals.
• Stochastic %K: Highlights shifts in short-term momentum by comparing closing price to the recent high/low range; values above its upper band signal bullish momentum, below its lower band signal bearish momentum.
• MACD Histogram: Measures the difference between the MACD line and its signal line; a positive histogram indicates upward momentum, a negative histogram indicates downward momentum.
3. Price Action:
• Highest High / Lowest Low (HH/LL) Range: Over a defined lookback period, this captures breakout or breakdown levels. A closing price near the recent highs (with a positive MA slope) yields a bullish score, and near the lows (with a negative MA slope) yields a bearish score.
• Heikin-Ashi Doji Detection: Uses Heikin-Ashi candles to identify indecision or continuation patterns. A small Heikin-Ashi body (doji) relative to recent volatility is scored as neutral; a larger body in the direction of the MA slope is scored bullish or bearish.
• Candle Range Measurement: Compares each candle’s high-low range against its own dynamic band (average range ± standard deviation). Large candles aligning with the prevailing trend score bullish or bearish accordingly; unusually small candles can indicate exhaustion or consolidation.
4. Market Activity:
• Bollinger Bands Width (BBW): Measures the distance between BB upper and lower bands; wide bands indicate high volatility, narrow bands indicate low volatility.
• Average True Range (ATR): Quantifies average price movement (volatility). A sudden spike in ATR suggests a volatile environment, while a contraction suggests calm.
• Keltner Channels Width (KCW): Similar to BBW but uses ATR around an EMA. Provides a second layer of volatility context, confirming or contrasting BBW readings.
• Volume (with Moving Average): Compares current volume to its moving average ± standard deviation. High volume validates strong moves; low volume signals potential lack of conviction.
By combining these tools, the indicator captures trend direction, momentum strength, price-action nuances, and overall market energy, yielding a more balanced and comprehensive assessment than any single tool alone.
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4. What Makes This Indicator Stand Out
• Multi-Dimensional Analysis: Rather than relying on a lone oscillator or moving average crossover, it simultaneously evaluates trend, momentum, price action, and activity.
• Dynamic Weighting: The relative importance of trend, momentum, and price action adjusts automatically based on real-time volatility (Market Activity State). For example, in highly volatile conditions, trend and momentum signals carry more weight; in calm markets, price action signals are prioritized.
• Stability Mechanisms:
• Smoothing: The net score is passed through a short moving average, filtering out noise, especially on lower timeframes.
• Hysteresis: Both Market Activity State and the final bullish/bearish/sideways zone require two consecutive confirmations before flipping, reducing whipsaw.
• Visual Interpretation: A fully customizable on-chart dashboard displays each sub-indicator’s value, regime, score, and comment, all color-coded. The oscillator plot changes color to reflect the current market zone (green for bullish, red for bearish, gray for sideways) and shows horizontal threshold lines at +2, 0, and –2.
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5. Recommended Timeframes
• Short-Term (5 min, 15 min): Day traders and scalpers can benefit from rapid signals, but should enable smoothing (and possibly disable hysteresis) to reduce false whipsaws.
• Medium-Term (1 h, 4 h): Swing traders find a balance between responsiveness and reliability. Less smoothing is required here, and the default parameters (e.g., ADX length = 14, RSI length = 14) perform well.
• Long-Term (Daily, Weekly): Position traders tracking major trends can disable smoothing for immediate raw readings, since higher-timeframe noise is minimal. Adjust lookback lengths (e.g., increase adxLength, rsiLength) if desired for slower signals.
Tip: If you keep smoothing off, stick to timeframes of 1 h or higher to avoid excessive signal “chatter.”
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6. How Scoring Works
A. Individual Indicator Scores
Each sub-indicator is assigned one of three discrete scores:
• +1 if it indicates a bullish condition (e.g., RSI above its dynamically calculated upper bound).
• 0 if it is neutral (e.g., RSI between upper and lower bounds).
• –1 if it indicates a bearish condition (e.g., RSI below its dynamically calculated lower bound).
Examples of individual score assignments:
• ADX/DMI:
• +1 if ADX ≥ adxThreshold and +DI > –DI (strong bullish trend)
• –1 if ADX ≥ adxThreshold and –DI > +DI (strong bearish trend)
• 0 if ADX < adxThreshold (trend strength below threshold)
• RSI:
• +1 if RSI > RSI_upperBound
• –1 if RSI < RSI_lowerBound
• 0 otherwise
• ATR (as part of Market Activity):
• +1 if ATR > (ATR_MA + stdev(ATR))
• –1 if ATR < (ATR_MA – stdev(ATR))
• 0 otherwise
Each of the four main categories shares this same +1/0/–1 logic across their sub-components.
B. Category Scores
Once each sub-indicator reports +1, 0, or –1, these are summed within their categories as follows:
• Trend Score = (ADX score) + (MA slope score) + (Ichimoku differential score)
• Momentum Score = (RSI score) + (Stochastic %K score) + (MACD histogram score)
• Price Action Score = (Highest-High/Lowest-Low score) + (Heikin-Ashi doji score) + (Candle range score)
• Market Activity Raw Score = (BBW score) + (ATR score) + (KC width score) + (Volume score)
Each category’s summed value can range between –3 and +3 (for Trend, Momentum, and Price Action), and between –4 and +4 for Market Activity raw.
C. Market Activity State and Dynamic Weight Adjustments
Rather than contributing directly to the netScore like the other three categories, Market Activity determines how much weight to assign to Trend, Momentum, and Price Action:
1. Compute Market Activity Raw Score by summing BBW, ATR, KCW, and Volume individual scores (each +1/0/–1).
2. Bucket into High, Medium, or Low Activity:
• High if raw Score ≥ 2 (volatile market).
• Low if raw Score ≤ –2 (calm market).
• Medium otherwise.
3. Apply Hysteresis (if enabled): The state only flips after two consecutive bars register the same high/low/medium label.
4. Set Category Weights:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use the trader’s base weight inputs (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 % by default).
D. Calculating the Net Score
5. Normalize Base Weights (so that the sum of Trend + Momentum + Price Action always equals 100 %).
6. Determine Current Weights based on the Market Activity State (High/Medium/Low).
7. Compute Each Category’s Contribution: Multiply (categoryScore) × (currentWeight).
8. Sum Contributions to get the raw netScore (a floating-point value that can exceed ±3 when scores are strong).
9. Smooth the netScore over two bars (if smoothing is enabled) to reduce noise.
10. Apply Hysteresis to the Final Zone:
• If the smoothed netScore ≥ +2, the bar is classified as “Bullish.”
• If the smoothed netScore ≤ –2, the bar is classified as “Bearish.”
• Otherwise, it is “Sideways.”
• To prevent rapid flips, the script requires two consecutive bars in the new zone before officially changing the displayed zone (if hysteresis is on).
E. Thresholds for Zone Classification
• BULLISH: netScore ≥ +2
• BEARISH: netScore ≤ –2
• SIDEWAYS: –2 < netScore < +2
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7. Role of Volatility (Market Activity State) in Scoring
Volatility acts as a dynamic switch that shifts which category carries the most influence:
1. High Activity (Volatile):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal +1.
• The script sets Trend weight = 50 % and Momentum weight = 35 %. Price Action weight is minimized at 15 %.
• Rationale: In volatile markets, strong trending moves and momentum surges dominate, so those signals are more reliable than nuanced candle patterns.
2. Low Activity (Calm):
• Detected when at least two sub-scores out of BBW, ATR, KCW, and Volume equal –1.
• The script sets Price Action weight = 55 %, Trend = 25 %, and Momentum = 20 %.
• Rationale: In quiet, sideways markets, subtle price-action signals (breakouts, doji patterns, small-range candles) are often the best early indicators of a new move.
3. Medium Activity (Balanced):
• Raw Score between –1 and +1 from the four volatility metrics.
• Uses whatever base weights the trader has specified (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
Because volatility can fluctuate rapidly, the script employs hysteresis on Market Activity State: a new High or Low state must occur on two consecutive bars before weights actually shift. This avoids constant back-and-forth weight changes and provides more stability.
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8. Scoring Example (Hypothetical Scenario)
• Symbol: Bitcoin on a 1-hour chart.
• Market Activity: Raw volatility sub-scores show BBW (+1), ATR (+1), KCW (0), Volume (+1) → Total raw Score = +3 → High Activity.
• Weights Selected: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Signals:
• ADX strong and +DI > –DI → +1
• Fast MA above Slow MA → +1
• Ichimoku Senkou A > Senkou B → +1
→ Trend Score = +3
• Momentum Signals:
• RSI above upper bound → +1
• MACD histogram positive → +1
• Stochastic %K within neutral zone → 0
→ Momentum Score = +2
• Price Action Signals:
• Highest High/Lowest Low check yields 0 (close not near extremes)
• Heikin-Ashi doji reading is neutral → 0
• Candle range slightly above upper bound but trend is strong, so → +1
→ Price Action Score = +1
• Compute Net Score (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 1 × 0.15 = 0.15
• Raw netScore = 1.50 + 0.70 + 0.15 = 2.35
• Since 2.35 ≥ +2 and hysteresis is met, the final zone is “Bullish.”
Although the netScore lands at 2.35 (Bullish), smoothing might bring it slightly below 2.00 on the first bar (e.g., 1.90), in which case the script would wait for a second consecutive reading above +2 before officially classifying the zone as Bullish (if hysteresis is enabled).
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9. Correlation Between Categories
The four categories—Trend Strength, Momentum, Price Action, and Market Activity—often reinforce or offset one another. The script takes advantage of these natural correlations:
• Bullish Alignment: If ADX is strong and pointed upward, fast MA is above slow MA, and Ichimoku is positive, that usually coincides with RSI climbing above its upper bound and the MACD histogram turning positive. In such cases, both Trend and Momentum categories generate +1 or +2. Because the Market Activity State is likely High (given the accompanying volatility), Trend and Momentum weights are at their peak, so the netScore quickly crosses into Bullish territory.
• Sideways/Consolidation: During a low-volatility, sideways phase, ADX may fall below its threshold, MAs may flatten, and RSI might hover in the neutral band. However, subtle price-action signals (like a small breakout candle or a Heikin-Ashi candle with a slight bias) can still produce a +1 in the Price Action category. If Market Activity is Low, Price Action’s weight (55 %) can carry enough influence—even if Trend and Momentum are neutral—to push the netScore out of “Sideways” into a mild bullish or bearish bias.
• Opposing Signals: When Trend is bullish but Momentum turns negative (for example, price continues up but RSI rolls over), the two scores can partially cancel. Market Activity may remain Medium, in which case the netScore lingers near zero (Sideways). The trader can then wait for either a clearer momentum shift or a fresh price-action breakout before committing.
By dynamically recognizing these correlations and adjusting weights, the indicator ensures that:
• When Trend and Momentum align (and volatility supports it), the netScore leaps strongly into Bullish or Bearish.
• When Trend is neutral but Price Action shows an early move in a low-volatility environment, Price Action’s extra weight in the Low Activity State can still produce actionable signals.
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10. Market Activity State & Its Role (Detailed)
The Market Activity State is not a direct category score—it is an overarching context setter for how heavily to trust Trend, Momentum, or Price Action. Here’s how it is derived and applied:
1. Calculate Four Volatility Sub-Scores:
• BBW: Compare the current band width to its own moving average ± standard deviation. If BBW > (BBW_MA + stdev), assign +1 (high volatility); if BBW < (BBW_MA × 0.5), assign –1 (low volatility); else 0.
• ATR: Compare ATR to its moving average ± standard deviation. A spike above the upper threshold is +1; a contraction below the lower threshold is –1; otherwise 0.
• KCW: Same logic as ATR but around the KCW mean.
• Volume: Compare current volume to its volume MA ± standard deviation. Above the upper threshold is +1; below the lower threshold is –1; else 0.
2. Sum Sub-Scores → Raw Market Activity Score: Range between –4 and +4.
3. Assign Market Activity State:
• High Activity: Raw Score ≥ +2 (at least two volatility metrics are strongly spiking).
• Low Activity: Raw Score ≤ –2 (at least two metrics signal unusually low volatility or thin volume).
• Medium Activity: Raw Score is between –1 and +1 inclusive.
4. Hysteresis for Stability:
• If hysteresis is enabled, a new state only takes hold after two consecutive bars confirm the same High, Medium, or Low label.
• This prevents the Market Activity State from bouncing around when volatility is on the fence.
5. Set Category Weights Based on Activity State:
• High Activity: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Low Activity: Trend = 25 %, Momentum = 20 %, Price Action = 55 %.
• Medium Activity: Use trader’s base weights (e.g., Trend = 40 %, Momentum = 30 %, Price Action = 30 %).
6. Impact on netScore: Because category scores (–3 to +3) multiply by these weights, High Activity amplifies the effect of strong Trend and Momentum scores; Low Activity amplifies the effect of Price Action.
7. Market Context Tooltip: The dashboard includes a tooltip summarizing the current state—e.g., “High activity, trend and momentum prioritized,” “Low activity, price action prioritized,” or “Balanced market, all categories considered.”
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11. Category Weights: Base vs. Dynamic
Traders begin by specifying base weights for Trend Strength, Momentum, and Price Action that sum to 100 %. These apply only when volatility is in the Medium band. Once volatility shifts:
• High Volatility Overrides:
• Trend jumps from its base (e.g., 40 %) to 50 %.
• Momentum jumps from its base (e.g., 30 %) to 35 %.
• Price Action is reduced to 15 %.
Example: If base weights were Trend = 40 %, Momentum = 30 %, Price Action = 30 %, then in High Activity they become 50/35/15. A Trend score of +3 now contributes 3 × 0.50 = +1.50 to netScore; a Momentum +2 contributes 2 × 0.35 = +0.70. In total, Trend + Momentum can easily push netScore above the +2 threshold on its own.
• Low Volatility Overrides:
• Price Action leaps from its base (30 %) to 55 %.
• Trend falls to 25 %, Momentum falls to 20 %.
Why? When markets are quiet, subtle candle breakouts, doji patterns, and small-range expansions tend to foreshadow the next swing more effectively than raw trend readings. A Price Action score of +3 in this state contributes 3 × 0.55 = +1.65, which can carry the netScore toward +2—even if Trend and Momentum are neutral or only mildly positive.
Because these weight shifts happen only after two consecutive bars confirm a High or Low state (if hysteresis is on), the indicator avoids constantly flipping its emphasis during borderline volatility phases.
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12. Dominant Category Explained
Within the dashboard, a label such as “Trend Dominant,” “Momentum Dominant,” or “Price Action Dominant” appears when one category’s absolute weighted contribution to netScore is the largest. Concretely:
• Compute each category’s weighted contribution = (raw category score) × (current weight).
• Compare the absolute values of those three contributions.
• The category with the highest absolute value is flagged as Dominant for that bar.
Why It Matters:
• Momentum Dominant: Indicates that the combined force of RSI, Stochastic, and MACD (after weighting) is pushing netScore farther than either Trend or Price Action. In practice, it means that short-term sentiment and speed of change are the primary drivers right now, so traders should watch for continued momentum signals before committing to a trade.
• Trend Dominant: Means ADX, MA slope, and Ichimoku (once weighted) outweigh the other categories. This suggests a strong directional move is in place; trend-following entries or confirming pullbacks are likely to succeed.
• Price Action Dominant: Occurs when breakout/breakdown patterns, Heikin-Ashi candle readings, and range expansions (after weighting) are the most influential. This often happens in calmer markets, where subtle shifts in candle structure can foreshadow bigger moves.
By explicitly calling out which category is carrying the most weight at any moment, the dashboard gives traders immediate insight into why the netScore is tilting toward bullish, bearish, or sideways.
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13. Oscillator Plot: How to Read It
The “Net Score” oscillator sits below the dashboard and visually displays the smoothed netScore as a line graph. Key features:
1. Value Range: In normal conditions it oscillates roughly between –3 and +3, but extreme confluences can push it outside that range.
2. Horizontal Threshold Lines:
• +2 Line (Bullish threshold)
• 0 Line (Neutral midline)
• –2 Line (Bearish threshold)
3. Zone Coloring:
• Green Background (Bullish Zone): When netScore ≥ +2.
• Red Background (Bearish Zone): When netScore ≤ –2.
• Gray Background (Sideways Zone): When –2 < netScore < +2.
4. Dynamic Line Color:
• The plotted netScore line itself is colored green in a Bullish Zone, red in a Bearish Zone, or gray in a Sideways Zone, creating an immediate visual cue.
Interpretation Tips:
• Crossing Above +2: Signals a strong enough combined trend/momentum/price-action reading to classify as Bullish. Many traders wait for a clear crossing plus a confirmation candle before entering a long position.
• Crossing Below –2: Indicates a strong Bearish signal. Traders may consider short or exit strategies.
• Rising Slope, Even Below +2: If netScore climbs steadily from neutral toward +2, it demonstrates building bullish momentum.
• Divergence: If price makes a higher high but the oscillator fails to reach a new high, it can warn of weakening momentum and a potential reversal.
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14. Comments and Their Necessity
Every sub-indicator (ADX, MA slope, Ichimoku, RSI, Stochastic, MACD, HH/LL, Heikin-Ashi, Candle Range, BBW, ATR, KCW, Volume) generates a short comment that appears in the detailed dashboard. Examples:
• “Strong bullish trend” or “Strong bearish trend” for ADX/DMI
• “Fast MA above slow MA” or “Fast MA below slow MA” for MA slope
• “RSI above dynamic threshold” or “RSI below dynamic threshold” for RSI
• “MACD histogram positive” or “MACD histogram negative” for MACD Hist
• “Price near highs” or “Price near lows” for HH/LL checks
• “Bullish Heikin Ashi” or “Bearish Heikin Ashi” for HA Doji scoring
• “Large range, trend confirmed” or “Small range, trend contradicted” for Candle Range
Additionally, the top-row comment for each category is:
• Trend: “Highly Bullish,” “Highly Bearish,” or “Neutral Trend.”
• Momentum: “Strong Momentum,” “Weak Momentum,” or “Neutral Momentum.”
• Price Action: “Bullish Action,” “Bearish Action,” or “Neutral Action.”
• Market Activity: “Volatile Market,” “Calm Market,” or “Stable Market.”
Reasons for These Comments:
• Transparency: Shows exactly how each sub-indicator contributed to its category score.
• Education: Helps traders learn why a category is labeled bullish, bearish, or neutral, building intuition over time.
• Customization: If, for example, the RSI comment says “RSI neutral” despite an impending trend shift, a trader might choose to adjust RSI length or thresholds.
In the detailed dashboard, hovering over each comment cell also reveals a tooltip with additional context (e.g., “Fast MA above slow MA” or “Senkou A above Senkou B”), helping traders understand the precise rule behind that +1, 0, or –1 assignment.
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15. Real-Life Example (Consolidated)
• Instrument & Timeframe: Bitcoin (BTCUSD), 1-hour chart.
• Current Market Activity: BBW and ATR both spike (+1 each), KCW is moderately high (+1), but volume is only neutral (0) → Raw Market Activity Score = +2 → State = High Activity (after two bars, if hysteresis is on).
• Category Weights Applied: Trend = 50 %, Momentum = 35 %, Price Action = 15 %.
• Trend Sub-Scores:
1. ADX = 25 (above threshold 20) with +DI > –DI → +1.
2. Fast MA (20-period) sits above Slow MA (50-period) → +1.
3. Ichimoku: Senkou A > Senkou B → +1.
→ Trend Score = +3.
• Momentum Sub-Scores:
4. RSI = 75 (above its moving average +1 stdev) → +1.
5. MACD histogram = +0.15 → +1.
6. Stochastic %K = 50 (mid-range) → 0.
→ Momentum Score = +2.
• Price Action Sub-Scores:
7. Price is not within 1 % of the 20-period high/low and slope = positive → 0.
8. Heikin-Ashi body is slightly larger than stdev over last 5 bars with haClose > haOpen → +1.
9. Candle range is just above its dynamic upper bound but trend is already captured, so → +1.
→ Price Action Score = +2.
• Calculate netScore (before smoothing):
• Trend contribution = 3 × 0.50 = 1.50
• Momentum contribution = 2 × 0.35 = 0.70
• Price Action contribution = 2 × 0.15 = 0.30
• Raw netScore = 1.50 + 0.70 + 0.30 = 2.50 → Immediately classified as Bullish.
• Oscillator & Dashboard Output:
• The oscillator line crosses above +2 and turns green.
• Dashboard displays:
• Trend Regime “BULLISH,” Trend Score = 3, Comment = “Highly Bullish.”
• Momentum Regime “BULLISH,” Momentum Score = 2, Comment = “Strong Momentum.”
• Price Action Regime “BULLISH,” Price Action Score = 2, Comment = “Bullish Action.”
• Market Activity State “High,” Comment = “Volatile Market.”
• Weights: Trend 50 %, Momentum 35 %, Price Action 15 %.
• Dominant Category: Trend (because 1.50 > 0.70 > 0.30).
• Overall Score: 2.50, posCount = (three +1s in Trend) + (two +1s in Momentum) + (two +1s in Price Action) = 7 bullish signals, negCount = 0.
• Final Zone = “BULLISH.”
• The trader sees that both Trend and Momentum are reinforcing each other under high volatility. They might wait one more candle for confirmation but already have strong evidence to consider a long.
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Disclaimer
This indicator is strictly a technical analysis tool and does not constitute financial advice. All trading involves risk, including potential loss of capital. Past performance is not indicative of future results. Traders should:
• Always backtest the “Market Zone Analyzer ” on their chosen symbols and timeframes before committing real capital.
• Combine this tool with sound risk management, position sizing, and, if possible, fundamental analysis.
• Understand that no indicator is foolproof; always be prepared for unexpected market moves.
Goodluck
-BullByte!
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BTC Markup/Markdown Zones by Koenigsegg📈 BTC Markup/Markdown Zones
A handcrafted indicator designed to mark Bitcoin's most critical High Time Frame (HTF) structure shifts. This tool overlays true institutional-level Markup and Markdown Zones, selected manually after deep market review. Whether you're testing strategies or actively trading, this tool gives you the bigger picture at all times.
🔍 Key Features:
✅ HTF Markup & Markdown Zones
Every zone is manually selected — no indicators, no repainting. Just raw market history and real structure.
✅ Two Display Modes
• Background Zones — soft overlays with low opacity for visual context — with the option to increase opacity manually if desired.
• Start Candle Highlight — sharply highlighted candle marking the final pivot before a macro reversal.
✅ Custom Color Controls (Style Tab)
All visual styling lives in the Style tab, with clearly labeled fields:
• Markup Zone
• Markdown Zone
• Start Candle Highlight Markup
• Start Candle Highlight Markdown
✅ Minimal Input Section
Just one toggle: display mode. Everything else is kept clean and intuitive.
🧠 Purpose:
This script is made for any timeframe:
• Zoom into lower timeframes to know whether you're trading inside a Markup or Markdown
• Use it during strategy testing for true structural awareness
📅 Handpicked Macro Turning Points:
Each zone originates from a manually confirmed candle — the last meaningful candle before a shift in control between bulls and bears:
• FRI 19 AUG 2011 12PM – MARK DOWN
• THU 20 OCT 2011 12AM – MARK UP
• WED 10 APR 2013 12PM – MARK DOWN
• FRI 12 APR 2013 12PM – MARK UP
• SAT 30 NOV 2013 12AM – MARK DOWN
• WED 14 JAN 2015 12PM – MARK UP
• SUN 17 DEC 2017 12PM – MARK DOWN
• SAT 15 DEC 2018 12PM – MARK UP
• WED 14 APR 2021 4AM – MARK DOWN
• TUE 22 JUN 2021 12PM – MARK UP
• WED 10 NOV 2021 12PM – MARK DOWN
• MON 21 NOV 2022 8PM – MARK UP
• THU 14 MAR 2024 4AM – MARK DOWN
• MON 5 AUG 2024 12PM – MARK UP
• MON 20 JAN 2025 4AM – MARK DOWN
💡 Zones are manually updated by me after each new confirmed Markup or Markdown.
🧬 Fractal Structure for MTF Systems
Price is fractal — meaning the same principles of structure repeat across all timeframes. In Version 2, this tool evolves by introducing manually selected sub-zones inside each High Time Frame (HTF) Markup or Markdown. These sub-zones reflect Medium Timeframe (MTF) structure shifts, offering precision for traders who operate on both intraday and swing levels.
This makes the indicator ideal for low timeframe (LTF) Markup/Markdown awareness — whether you're managing 15m entries or building multi-timeframe confluence systems.
No auto-zones. No guesswork. Just clean, intentional structure division within the broader trend, handpicked for maximum clarity and edge.
💡 Pro Tip:
When price is inside a Markup Zone, shorting becomes riskier — you're trading against a macro bullish structure.
When inside a Markdown Zone, longing becomes riskier — you're fighting against confirmed bearish momentum.
Use this tool to stay aligned with the broader move, especially when zoomed into smaller timeframes or managing entries/exits during intraday setups.
📈 Markup Phase – Bullish Sentiment
Definition: A period where price makes higher highs and higher lows — the uptrend is in full force.
Why sentiment is bullish:
- Institutions and smart money are already positioned long.
- Public/institutional demand drives prices up.
- Momentum is supported by positive news, breakouts, and FOMO.
- Higher highs confirm buyers are in control.
📉 Markdown Phase – Bearish Sentiment
Definition: A period where price makes lower lows and lower highs — clear downtrend.
Why sentiment is bearish:
- Distribution has already occurred, and supply outweighs demand.
- Smart money is short or sidelined, waiting for deeper prices.
- Panic selling or trend-following traders add downside momentum.
- Lower lows confirm sellers are in control.
❌ Trading Against the Trend — Consequences:
-Reduced Probability of Success
-You’re fighting the dominant flow. Most participants are pushing in the opposite direction.
-Drawdowns & Stop-Outs
-Countertrend trades often get wicked or flushed before any meaningful move, especially without structure-based entries.
-Low Risk-Reward Ratio
-Trends offer sustained moves. Countertrend trades may have small take-profit zones or chop.
-Mental Drain & Doubt
-Fighting momentum causes anxiety, second-guessing, and emotional reactions.
-Missed Opportunities
-Focusing on fighting the trend makes you blind to the high-probability setups with the trend.
-Increased Transaction Costs
-More stop-outs and re-entries mean more fees, more friction.
-FOMO from Watching the Trend Run
-Entering countertrend means you might watch the trend explode without you.
-Confirmation Bias & Stubbornness
-Countertrend traders often look for reasons to justify staying in the wrong direction — leading to bigger losses.
🧠 Summary
In markup = bulls dominate → you swim with the current.
In markdown = bears dominate → going long is like pushing a rock uphill.
Trading with the trend is not just safer, it's smarter. The edge lives in momentum — not ego.
⚠️ Disclaimer
This indicator is for educational and analytical use only. It is not financial advice and should not be relied on for decision-making without personal analysis.
This is not a predictive tool. No indicator can forecast upcoming price movements.
What you see here is based purely on past market behavior — specifically, historical tops and bottoms that marked the start of confirmed reversals.
This script does not know where the next reversal begins, nor can it determine where a new Markup or Markdown starts or ends. It is designed to provide context, not prediction.
Always trade with responsibility and perform your own due diligence.
Turbo Oscillator [RunRox]Introducing Turbo Oscillator by RunRox, our new indicator that combines a multitude of useful and unique features, which we will detail in this post.
List of Advanced Technologies:
Real-Time Divergences: Detects discrepancies between price movements and oscillator indicators to forecast potential price reversals.
Real-Time Hidden Divergences: We identify hidden divergences in real-time. These are not the standard type of divergences; they are opposite to regular divergences, providing unique insights into potential market movements.
Overbought and Oversold Zones: Identifies areas where the market is potentially overextended, suggesting possible entry and exit points.
Signal Line: Indicates the market direction, helping traders to quickly understand current trends.
Money Flow Histogram: Shows the flow of money into and out of the market, providing insights into buying and selling pressure.
Predicted Reversal Zones: Pinpoints areas where the market might experience reversals, aiding in strategic planning and risk management. These zones also serve as potential areas for taking profits, enhancing their utility for exit strategy planning.
Customizable Alerts: You can flexibly set up alerts for any events detected by our indicator, ensuring you stay informed about critical market movements.
To begin with, I would like to describe the difference between classic divergences and hidden divergences.
As you can see, these are opposite situations. Our oscillator identifies both types of divergences and displays them in real-time.
Divergences can serve as points where the price might reverse in the opposite direction, making both classic and hidden divergences powerful tools for spotting reversal points. I'll show a few examples of how divergences are used in our oscillator.
Classic Divergences - which we identify in real-time. As you can see, the price often reacts strongly to the formation of these divergences, frequently changing its direction.
Hidden Divergences - we also observe frequent movement in the opposite direction on the chart. The advantage of our indicator is that we show divergences in real-time without delays, allowing you to react immediately to trend changes.
Overbought and Oversold Zones - These zones allow you to see trend changes when the price is clearly overbought or oversold. When the color changes from a contrasting shade to a neutral one, you can observe the trend shift. The lines work by combining the positivity/negativity of the histogram, the positivity/negativity of the signal line, and the direction of the signal line (red/green). This sophisticated interaction provides precise insights into market conditions, making it an invaluable tool for traders.
Signal Line - This provides insights into trend changes and price reversals. The points on the line better indicate the beginning of a trend shift. These points can vary in size, offering a clearer understanding of the strength of the emerging trend. This feature works in combination with RSI, Stochastic, and MFI. RSI and MFI are top-tier indicators, while Stochastic adds responsiveness and sensitivity to trend changes, ensuring you capture every market movement accurately and promptly.
Money Flow Histogram - As shown in the example, our histogram displays the divergence between money flow and the actual price. You can see that while the price is rising, the money flow is decreasing, indicating insufficient demand for the asset and an imminent trend change. This feature uses MFI with an extended period, providing a more comprehensive and accurate analysis of market conditions. The extended period enhances the reliability of the Money Flow Index, making it an essential tool for identifying subtle shifts in market dynamics.
Predicted Reversal Zones - We automatically identify potential price reversal zones and display them above our overbought and oversold zones. In cases of strong overbought or oversold conditions, we detect potential price pullbacks and mark the beginning of a trend change. This helps you better identify trend shifts. We recommend considering these zones as potential take profit points for your trades.
Customizable Alerts - Our flexible alert system allows you to receive notifications only for the events you are interested in. These can include:
1. Classic Divergences
2. Hidden Divergences
3. Overbought or Oversold conditions on the status line
4. Strong Overbought or Oversold conditions on the status line
5. Signals from the signal line
6. Reversal zones in any direction
Our oscillator is a unique indicator that provides a comprehensive understanding of price movements. It can be used as a standalone tool for analyzing price action.
Here are a few examples of using our Oscillator in practice:
In the example above, you can see three conditions that have formed for a potential trade:
1. Clear overbought condition with a formed reversal point.
2. Decreasing Money Flow Index diverging from the rising price.
3. Formed classic divergence.
The entry point could be the formed divergence, while the exit point could be the overbought condition at the bottom of the oscillator along with the reversal points.
Here's another example of using hidden divergence, where you can see three conditions for a potential trade:
1. Overbought zone
2. Formed hidden divergence
3. Start of bearish movement indicated by the signal line
You can enter the trade either when the hidden divergence forms or wait for confirmation of the trend change by the signal line and enter the trade when the corresponding signal forms on the signal line. The exit point could be the opposite reversal point or the formation of a new hidden divergence.
We have demonstrated a few examples of how you can use our indicator, but we are confident that you will find many more applications in your own strategies.
Oscillator offers a variety of customizable parameters to tailor the indicator to your trading preferences. Here’s what our settings include:
Signal Line
Turn On/Off: Enable or disable the signal line.
Length: Set the length period for the signal line calculation.
Smooth: Adjust the smoothing level of the signal line for more accurate display.
Histogram
Turn On/Off: Enable or disable the histogram.
Length: Set the length period for the histogram calculation.
Smooth: Adjust the smoothing level of the histogram.
Other
Show Divergence Line: Display divergence lines on the chart.
Show Hidden Divergence: Display hidden divergences.
Show Status Line: Show the status line indicating overbought or oversold conditions.
Show TP Signal: Display signals for take profit.
Show Reversal Points: Display potential trend reversal points.
Delete Broken Divergence Lines: Remove broken divergence lines from the chart.
Alerts Customization
Signal Line Bull/Bear: Set alerts for bullish or bearish signals from the signal line.
TP Bull/Bear: Set alerts for take profit signals.
Status Bull/Bear: Set alerts for bullish or bearish status conditions.
Status Bull+/Bear+: Set enhanced alerts for stronger bullish or bearish status conditions.
Divergence Bull/Bear: Set alerts for bullish or bearish divergences.
Hidden Divergence Bull/Bear: Set alerts for hidden bullish or bearish divergences.
With these comprehensive settings, you can fine-tune the Oscillator to perfectly fit your trading strategy and preferences.
Our indicator utilizes technologies such as RSI, Stochastic, and Money Flow Index, with numerous enhancements from our team. It includes exclusive features such as real-time detection of hidden and classic divergences, identification of reversal points using our unique methodology, and much more.
Disclaimer:
While we consider our Turbo Oscillator to be an excellent tool, it is important to understand that past performance is not indicative of future results. We recommend approaching market analysis comprehensively, using a combination of tools and techniques to make well-informed trading decisions. Always consider the full range of market data and risks when using any trading indicator.
Defensive Nexus ShieldIndicator: Defensive Nexus Shield , capturing profits in the breakout trend.
Defensive Nexus Shield is a trend signal and support resistance display. Identify the short-term bullish and bearish defensive area through the effective extreme value of bulls and bears, and trigger trading opportunities when there are characteristics of breaking through the defensive area.
Usage：
Signal direction: "B" means that the bulls attacked and the bears failed, and entered a bullish trend. "S" means that the bears attacked and the bulls failed, entering a bearish trend.
Defense point of bulls and bears: "Blue line" represents the bearish defense line. The "green line" represents the bullish defensive line. The "purple line" represents the junction of bulls and bears.
Tip I：
Trend signal. When the signal "B" appears, it means that the bulls are attacking, and the market is bullish. Please refer to the signal for corresponding operations.
Tip II：
Breakout signal. After the trend signal appears, if the trend is confirmed, it will continue to enter the breakthrough signal.
Take the bull signal as an example. When B appears, the price continues to rise and breaks through the blue line, the bearish defense line, which triggers the bullish breakthrough signal. At this time, the bulls will strengthen. Provide signal reference for traders who do short-term breakthrough transactions.
*The signals in the indicators are for reference only and not intended as investment advice. Past performance of a strategy is not indicative of future earnings results.
Update - 2023.09.05
Optimize the alarm function. If you need to monitor the "B" or "S" signal, when creating an alarm, set the condition bar to:
Defensive Nexus Shield --> "B" or "S" --> Crossing Up --> value -> 0.5
Kịch bản của tôi//@version=6
indicator(title="Relative Strength Index", shorttitle="Gấu Trọc RSI", format=format.price, precision=2, timeframe="", timeframe_gaps=true)
rsiLengthInput = input.int(14, minval=1, title="RSI Length", group="RSI Settings")
rsiSourceInput = input.source(close, "Source", group="RSI Settings")
calculateDivergence = input.bool(false, title="Calculate Divergence", group="RSI Settings", display = display.data_window, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
change = ta.change(rsiSourceInput)
up = ta.rma(math.max(change, 0), rsiLengthInput)
down = ta.rma(-math.min(change, 0), rsiLengthInput)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
rsiPlot = plot(rsi, "RSI", color=#7E57C2)
rsiUpperBand1 = hline(98, "RSI Upper Band1", color=#787B86)
rsiUpperBand = hline(70, "RSI Upper Band", color=#787B86)
midline = hline(50, "RSI Middle Band", color=color.new(#787B86, 50))
rsiLowerBand = hline(30, "RSI Lower Band", color=#787B86)
rsiLowerBand2 = hline(14, "RSI Lower Band2", color=#787B86)
fill(rsiUpperBand, rsiLowerBand, color=color.rgb(126, 87, 194, 90), title="RSI Background Fill")
midLinePlot = plot(50, color = na, editable = false, display = display.none)
fill(rsiPlot, midLinePlot, 100, 70, top_color = color.new(color.green, 0), bottom_color = color.new(color.green, 100), title = "Overbought Gradient Fill")
fill(rsiPlot, midLinePlot, 30, 0, top_color = color.new(color.red, 100), bottom_color = color.new(color.red, 0), title = "Oversold Gradient Fill")
// Smoothing MA inputs
GRP = "Smoothing"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maTypeInput = input.string("SMA", "Type", options = , group = GRP, display = display.data_window)
var isBB = maTypeInput == "SMA + Bollinger Bands"
maLengthInput = input.int(14, "Length", group = GRP, display = display.data_window, active = maTypeInput != "None")
bbMultInput = input.float(2.0, "BB StdDev", minval = 0.001, maxval = 50, step = 0.5, tooltip = TT_BB, group = GRP, display = display.data_window, active = isBB)
var enableMA = maTypeInput != "None"
// Smoothing MA Calculation
ma(source, length, MAtype) =>
switch MAtype
"SMA" => ta.sma(source, length)
"SMA + Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
// Smoothing MA plots
smoothingMA = enableMA ? ma(rsi, maLengthInput, maTypeInput) : na
smoothingStDev = isBB ? ta.stdev(rsi, maLengthInput) * bbMultInput : na
plot(smoothingMA, "RSI-based MA", color=color.yellow, display = enableMA ? display.all : display.none, editable = enableMA)
bbUpperBand = plot(smoothingMA + smoothingStDev, title = "Upper Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
bbLowerBand = plot(smoothingMA - smoothingStDev, title = "Lower Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
fill(bbUpperBand, bbLowerBand, color= isBB ? color.new(color.green, 90) : na, title="Bollinger Bands Background Fill", display = isBB ? display.all : display.none, editable = isBB)
// Divergence
lookbackRight = 5
lookbackLeft = 5
rangeUpper = 60
rangeLower = 5
bearColor = color.red
bullColor = color.green
textColor = color.white
noneColor = color.new(color.white, 100)
_inRange(bool cond) =>
bars = ta.barssince(cond)
rangeLower <= bars and bars <= rangeUpper
plFound = false
phFound = false
bullCond = false
bearCond = false
rsiLBR = rsi
if calculateDivergence
//------------------------------------------------------------------------------
// Regular Bullish
// rsi: Higher Low
plFound := not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight))
rsiHL = rsiLBR > ta.valuewhen(plFound, rsiLBR, 1) and _inRange(plFound )
// Price: Lower Low
lowLBR = low
priceLL = lowLBR < ta.valuewhen(plFound, lowLBR, 1)
bullCond := priceLL and rsiHL and plFound
//------------------------------------------------------------------------------
// Regular Bearish
// rsi: Lower High
phFound := not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight))
rsiLH = rsiLBR < ta.valuewhen(phFound, rsiLBR, 1) and _inRange(phFound )
// Price: Higher High
highLBR = high
priceHH = highLBR > ta.valuewhen(phFound, highLBR, 1)
bearCond := priceHH and rsiLH and phFound
plot(
plFound ? rsiLBR : na,
offset = -lookbackRight,
title = "Regular Bullish",
linewidth = 2,
color = (bullCond ? bullColor : noneColor),
display = display.pane,
editable = calculateDivergence)
plotshape(
bullCond ? rsiLBR : na,
offset = -lookbackRight,
title = "Regular Bullish Label",
text = " Bull ",
style = shape.labelup,
location = location.absolute,
color = bullColor,
textcolor = textColor,
display = display.pane,
editable = calculateDivergence)
plot(
phFound ? rsiLBR : na,
offset = -lookbackRight,
title = "Regular Bearish",
linewidth = 2,
color = (bearCond ? bearColor : noneColor),
display = display.pane,
editable = calculateDivergence)
plotshape(
bearCond ? rsiLBR : na,
offset = -lookbackRight,
title = "Regular Bearish Label",
text = " Bear ",
style = shape.labeldown,
location = location.absolute,
color = bearColor,
textcolor = textColor,
display = display.pane,
editable = calculateDivergence)
alertcondition(bullCond, title='Regular Bullish Divergence', message="Found a new Regular Bullish Divergence, `Pivot Lookback Right` number of bars to the left of the current bar.")
alertcondition(bearCond, title='Regular Bearish Divergence', message='Found a new Regular Bearish Divergence, `Pivot Lookback Right` number of bars to the left of the current bar.')
RSI + BB + RSI Advanced MTF Panel//@version=6
indicator(title="RSI + BB + RSI Advanced MTF Panel", shorttitle="RSI + BB + RSI Advance MTF Panel", format=format.price, precision=2, overlay=false)
bb_group = "BB (Price Overlay)"
bb_length = input.int(50, minval=1, group = bb_group)
bb_maType = input.string("SMA", "Basis MA Type", options = , group = bb_group)
bb_src = input.source(close, title="Source", group = bb_group)
bb_mult = input.float(0.2, minval=0.001, maxval=50, title="StdDev", group = bb_group)
BasisColor = input.color(color.rgb(163, 41, 245), "Basis Color", group = bb_group, display = display.none)
UpperColor = input.color(color.rgb(120, 156, 202,100), "Upper Color", group = bb_group, display = display.none)
LowerColor = input.color(color.rgb(120, 156, 202,100), "Lower Color", group = bb_group, display = display.none)
offset = input.int(0, "Offset", minval = -500, maxval = 500, display = display.data_window, group = bb_group)
ma(source, bb_length, _type) =>
switch _type
"SMA" => ta.sma(source, bb_length)
"EMA" => ta.ema(source, bb_length)
"SMMA (RMA)" => ta.rma(source, bb_length)
"WMA" => ta.wma(source, bb_length)
"VWMA" => ta.vwma(source, bb_length)
basis = ma(bb_src, bb_length, bb_maType)
dev = bb_mult * ta.stdev(bb_src, bb_length)
upper = basis + dev
lower = basis - dev
plot(basis, "Basis", color=BasisColor, offset = offset, force_overlay = true)
p1 = plot(upper, "Upper", color=UpperColor, offset = offset, force_overlay = true)
p2 = plot(lower, "Lower", color=LowerColor, offset = offset, force_overlay = true)
fill(p1, p2, title = "Background", color=color.rgb(163, 41, 245, 90))
rsiLengthInput = input.int(30, minval=1, title="RSI Length", group="RSI Settings")
rsiSourceInput = input.source(close, "Source", group="RSI Settings")
calculateDivergence = input.bool(false, title="Calculate Divergence", group="RSI Settings", display = display.data_window, tooltip = "Calculating divergences is needed in order for divergence alerts to fire.")
SignalDot = input.bool(false, title="Signal Dot", group="Smoothing", display = display.data_window, tooltip = "Signal for possible entry")
change = ta.change(rsiSourceInput)
up = ta.rma(math.max(change, 0), rsiLengthInput)
down = ta.rma(-math.min(change, 0), rsiLengthInput)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
rsiPlot = plot(rsi, "RSI", color= rsi >= 51 ? color.rgb(13, 197, 230) : color.red)
rsiUpperBand = hline(70, "RSI Upper Band", color=#787B86)
midline = hline(50, "RSI Middle Band", color=color.new(#787B86, 50))
rsiLowerBand = hline(30, "RSI Lower Band", color=#787B86)
fill(rsiUpperBand, rsiLowerBand, color=color.rgb(126, 87, 194, 90), title="RSI Background Fill")
midLinePlot = plot(50, color = na, editable = false, display = display.none)
fill(rsiPlot, midLinePlot, 100, 70, top_color = color.new(color.green, 0), bottom_color = color.new(color.green, 100), title = "Overbought Gradient Fill")
fill(rsiPlot, midLinePlot, 30, 0, top_color = color.new(color.red, 100), bottom_color = color.new(color.red, 0), title = "Oversold Gradient Fill")
GRP = "Smoothing"
TT_BB = "Only applies when 'SMA + Bollinger Bands' is selected. Determines the distance between the SMA and the bands."
maTypeInput = input.string("SMA", "Type", options = , group = GRP, display = display.data_window)
maLengthInput = input.int(14, "Length", group = GRP, display = display.data_window)
bbMultInput = input.float(2.0, "BB StdDev", minval = 0.001, maxval = 50, step = 0.5, tooltip = TT_BB, group = GRP, display = display.data_window)
var enableMA = maTypeInput != "None"
var isBB = maTypeInput == "SMA + Bollinger Bands"
smoothma(source, length, MAtype) =>
switch MAtype
"SMA" => ta.sma(source, length)
"SMA + Bollinger Bands" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
"SMMA (RMA)" => ta.rma(source, length)
"WMA" => ta.wma(source, length)
"VWMA" => ta.vwma(source, length)
smoothingMA = enableMA ? smoothma(rsi, maLengthInput, maTypeInput) : na
smoothingStDev = isBB ? ta.stdev(rsi, maLengthInput) * bbMultInput : na
plot(smoothingMA, "RSI-based MA", color=color.yellow, display = enableMA ? display.all : display.none, editable = enableMA)
bbUpperBand = plot(smoothingMA + smoothingStDev, title = "Upper Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
bbLowerBand = plot(smoothingMA - smoothingStDev, title = "Lower Bollinger Band", color=color.green, display = isBB ? display.all : display.none, editable = isBB)
fill(bbUpperBand, bbLowerBand, color= isBB ? color.new(color.green, 90) : na, title="Bollinger Bands Background Fill", display = isBB ? display.all : display.none, editable = isBB)
lookbackRight = 5
lookbackLeft = 5
rangeUpper = 60
rangeLower = 5
bearColor = color.red
bullColor = color.green
textColor = color.white
noneColor = color.new(color.white, 100)
_calcBarsSince(cond) =>
ta.barssince(cond)
rsiLBR = rsi
// 1. Calculate Pivots Unconditionally
plFound = not na(ta.pivotlow(rsi, lookbackLeft, lookbackRight))
phFound = not na(ta.pivothigh(rsi, lookbackLeft, lookbackRight))
// 2. Calculate History Unconditionally
barsSincePL = _calcBarsSince(plFound )
barsSincePH = _calcBarsSince(phFound )
// 3. Check Ranges Unconditionally
inRangePL = rangeLower <= barsSincePL and barsSincePL <= rangeUpper
inRangePH = rangeLower <= barsSincePH and barsSincePH <= rangeUpper
// 4. Calculate Conditions
var bool bullCond = false
var bool bearCond = false
if calculateDivergence
rsiHL = rsiLBR > ta.valuewhen(plFound, rsiLBR, 1) and inRangePL
lowLBR = low
priceLL = lowLBR < ta.valuewhen(plFound, lowLBR, 1)
bullCond := priceLL and rsiHL and plFound
rsiLH = rsiLBR < ta.valuewhen(phFound, rsiLBR, 1) and inRangePH
highLBR = high
priceHH = highLBR > ta.valuewhen(phFound, highLBR, 1)
bearCond := priceHH and rsiLH and phFound
else
bullCond := false
bearCond := false
plot(plFound ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bullish", linewidth = 2, color = (bullCond ? bullColor : noneColor), display = display.pane, editable = calculateDivergence)
plotshape(bullCond ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bullish Label", text = " Bull ", style = shape.labelup, location = location.absolute, color = bullColor, textcolor = textColor, display = display.pane, editable = calculateDivergence)
plot(phFound ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bearish", linewidth = 2, color = (bearCond ? bearColor : noneColor), display = display.pane, editable = calculateDivergence)
plotshape(bearCond ? rsiLBR : na, offset = -lookbackRight, title = "Regular Bearish Label", text = " Bear ", style = shape.labeldown, location = location.absolute, color = bearColor, textcolor = textColor, display = display.pane, editable = calculateDivergence)
alertcondition(bullCond, title='Regular Bullish Divergence', message="Found a new Regular Bullish Divergence.")
alertcondition(bearCond, title='Regular Bearish Divergence', message='Found a new Regular Bearish Divergence.')
// --- Panel Options (General) ---
g_panel = 'MTF Panel Options'
i_orientation = input.string('Vertical', 'Orientation', options = , group = g_panel)
i_position = input.string('Bottom Right', 'Position', options = , group = g_panel)
i_border_width = input.int(1, 'Border Width', minval = 0, maxval = 10, group = g_panel, inline = 'border')
i_color_border = input.color(#000000, '', group = g_panel, inline = 'border')
i_showHeaders = input.bool(true, 'Show Headers', group = g_panel)
i_color_header_bg = input.color(#5d606b, 'Headers Background', group = g_panel, inline = 'header')
i_color_header_text = input.color(color.white, 'Text', group = g_panel, inline = 'header')
i_color_tf_bg = input.color(#2a2e39, 'Timeframe Background', group = g_panel, inline = 'tf')
i_color_tf_text = input.color(color.white, 'Text', group = g_panel, inline = 'tf')
i_debug = input.bool(false, 'Display colors palette (debug)', group = g_panel)
// --- RSI Colors (Conditional Formatting) ---
g_rsi = 'MTF RSI Colors'
i_threshold_ob = input.int(70, 'Overbought Threshold', minval=51, maxval=100, group = g_rsi)
i_color_ob = input.color(#128416, 'Overbought Background', inline = 'ob', group = g_rsi)
i_tcolor_ob = input.color(color.white, 'Text', inline = 'ob', group = g_rsi)
i_threshold_uptrend = input.int(60, 'Uptrend Threshold', minval=51, maxval=100, group = g_rsi)
i_color_uptrend = input.color(#2d472e, 'Uptrend Background', inline = 'up', group = g_rsi)
i_tcolor_uptrend = input.color(color.white, 'Text', inline = 'up', group = g_rsi)
i_color_mid = input.color(#131722, 'No Trend Background', group = g_rsi, inline = 'mid')
i_tcolor_mid = input.color(#b2b5be, 'Text', group = g_rsi, inline = 'mid')
i_threshold_downtrend = input.int(40, 'Downtrend Threshold', group = g_rsi, minval=0, maxval=49)
i_color_downtrend = input.color(#5b2e2e, 'Downtrend Background', group = g_rsi, inline = 'down')
i_tcolor_downtrend = input.color(color.white, 'Text', group = g_rsi, inline = 'down')
i_threshold_os = input.int(30, 'Oversold Threshold', minval=0, maxval=49, group = g_rsi)
i_color_os = input.color(#db3240, 'Oversold Background', group = g_rsi, inline = 'os')
i_tcolor_os = input.color(color.white, 'Text', group = g_rsi, inline = 'os')
// --- Individual RSI Settings (MTF Sources) ---
g_rsi1 = 'RSI #1'
i_rsi1_enabled = input.bool(true, title = 'Enabled', group = g_rsi1)
i_rsi1_tf = input.timeframe('5', 'Timeframe', group = g_rsi1)
i_rsi1_len = input.int(30, 'Length', minval = 1, group = g_rsi1)
i_rsi1_src = input.source(close, 'Source', group = g_rsi1) * 10000
v_rsi1 = i_rsi1_enabled ? request.security(syminfo.tickerid, i_rsi1_tf, ta.rsi(i_rsi1_src, i_rsi1_len)) : na
g_rsi2 = 'RSI #2'
i_rsi2_enabled = input.bool(true, title = 'Enabled', group = g_rsi2)
i_rsi2_tf = input.timeframe('15', 'Timeframe', group = g_rsi2)
i_rsi2_len = input.int(30, 'Length', minval = 1, group = g_rsi2)
i_rsi2_src = input.source(close, 'Source', group = g_rsi2) * 10000
v_rsi2 = i_rsi2_enabled ? request.security(syminfo.tickerid, i_rsi2_tf, ta.rsi(i_rsi2_src, i_rsi2_len)) : na
g_rsi3 = 'RSI #3'
i_rsi3_enabled = input.bool(true, title = 'Enabled', group = g_rsi3)
i_rsi3_tf = input.timeframe('60', 'Timeframe', group = g_rsi3)
i_rsi3_len = input.int(30, 'Length', minval = 1, group = g_rsi3)
i_rsi3_src = input.source(close, 'Source', group = g_rsi3) * 10000
v_rsi3 = i_rsi3_enabled ? request.security(syminfo.tickerid, i_rsi3_tf, ta.rsi(i_rsi3_src, i_rsi3_len)) : na
g_rsi4 = 'RSI #4'
i_rsi4_enabled = input.bool(true, title = 'Enabled', group = g_rsi4)
i_rsi4_tf = input.timeframe('240', 'Timeframe', group = g_rsi4)
i_rsi4_len = input.int(30, 'Length', minval = 1, group = g_rsi4)
i_rsi4_src = input.source(close, 'Source', group = g_rsi4) * 10000
v_rsi4 = i_rsi4_enabled ? request.security(syminfo.tickerid, i_rsi4_tf, ta.rsi(i_rsi4_src, i_rsi4_len)) : na
g_rsi5 = 'RSI #5'
i_rsi5_enabled = input.bool(true, title = 'Enabled', group = g_rsi5)
i_rsi5_tf = input.timeframe('D', 'Timeframe', group = g_rsi5)
i_rsi5_len = input.int(30, 'Length', minval = 1, group = g_rsi5)
i_rsi5_src = input.source(close, 'Source', group = g_rsi5) * 10000
v_rsi5 = i_rsi5_enabled ? request.security(syminfo.tickerid, i_rsi5_tf, ta.rsi(i_rsi5_src, i_rsi5_len)) : na
g_rsi6 = 'RSI #6'
i_rsi6_enabled = input.bool(true, title = 'Enabled', group = g_rsi6)
i_rsi6_tf = input.timeframe('W', 'Timeframe', group = g_rsi6)
i_rsi6_len = input.int(30, 'Length', minval = 1, group = g_rsi6)
i_rsi6_src = input.source(close, 'Source', group = g_rsi6) * 10000
v_rsi6 = i_rsi6_enabled ? request.security(syminfo.tickerid, i_rsi6_tf, ta.rsi(i_rsi6_src, i_rsi6_len)) : na
g_rsi7 = 'RSI #7'
i_rsi7_enabled = input.bool(false, title = 'Enabled', group = g_rsi7)
i_rsi7_tf = input.timeframe('W', 'Timeframe', group = g_rsi7)
i_rsi7_len = input.int(30, 'Length', minval = 1, group = g_rsi7)
i_rsi7_src = input.source(close, 'Source', group = g_rsi7) * 10000
v_rsi7 = i_rsi7_enabled ? request.security(syminfo.tickerid, i_rsi7_tf, ta.rsi(i_rsi7_src, i_rsi7_len)) : na
g_rsi8 = 'RSI #8'
i_rsi8_enabled = input.bool(false, title = 'Enabled', group = g_rsi8)
i_rsi8_tf = input.timeframe('W', 'Timeframe', group = g_rsi8)
i_rsi8_len = input.int(30, 'Length', minval = 1, group = g_rsi8)
i_rsi8_src = input.source(close, 'Source', group = g_rsi8) * 10000
v_rsi8 = i_rsi8_enabled ? request.security(syminfo.tickerid, i_rsi8_tf, ta.rsi(i_rsi8_src, i_rsi8_len)) : na
g_rsi9 = 'RSI #9'
i_rsi9_enabled = input.bool(false, title = 'Enabled', group = g_rsi9)
i_rsi9_tf = input.timeframe('W', 'Timeframe', group = g_rsi9)
i_rsi9_len = input.int(30, 'Length', minval = 1, group = g_rsi9)
i_rsi9_src = input.source(close, 'Source', group = g_rsi9) * 10000
v_rsi9 = i_rsi9_enabled ? request.security(syminfo.tickerid, i_rsi9_tf, ta.rsi(i_rsi9_src, i_rsi9_len)) : na
g_rsi10 = 'RSI #10'
i_rsi10_enabled = input.bool(false, title = 'Enabled', group = g_rsi10)
i_rsi10_tf = input.timeframe('W', 'Timeframe', group = g_rsi10)
i_rsi10_len = input.int(30, 'Length', minval = 1, group = g_rsi10)
i_rsi10_src = input.source(close, 'Source', group = g_rsi10) * 10000
v_rsi10 = i_rsi10_enabled ? request.security(syminfo.tickerid, i_rsi10_tf, ta.rsi(i_rsi10_src, i_rsi10_len)) : na
// --- Panel Helper Functions ---
// Function 4: String Position to Constant (Indentation cleaned)
f_StrPositionToConst(_p) =>
switch _p
'Top Left' => position.top_left
'Top Right' => position.top_right
'Top Center' => position.top_center
'Middle Left' => position.middle_left
'Middle Right' => position.middle_right
'Middle Center' => position.middle_center
'Bottom Left' => position.bottom_left
'Bottom Right' => position.bottom_right
'Bottom Center' => position.bottom_center
=> position.bottom_right
// Function 5: Timeframe to Human Readable (Indentation cleaned)
f_timeframeToHuman(_tf) =>
seconds = timeframe.in_seconds(_tf)
if seconds < 60
_tf
else if seconds < 3600
str.tostring(seconds / 60) + 'm'
else if seconds < 86400
str.tostring(seconds / 60 / 60) + 'h'
else
switch _tf
"1D" => "D"
"1W" => "W"
"1M" => "M"
=> str.tostring(_tf)
type TPanel
table src = na
bool vertical_orientation = true
int row = 0
int col = 0
// Method 1: Increment Column (Indentation cleaned)
method incCol(TPanel _panel) =>
if _panel.vertical_orientation
_panel.col += 1
else
_panel.row += 1
// Method 2: Increment Row (Indentation cleaned)
method incRow(TPanel _panel) =>
if not _panel.vertical_orientation
_panel.col += 1
_panel.row := 0
else
_panel.row += 1
_panel.col := 0
// Method 3: Add Cell (Indentation cleaned)
method add(TPanel _panel, string _v1, color _bg1, color _ctext1, string _v2, color _bg2, color _ctext2) =>
table.cell(_panel.src, _panel.col, _panel.row, _v1, text_color = _ctext1, bgcolor = _bg1)
_panel.incCol()
table.cell(_panel.src, _panel.col, _panel.row, _v2, text_color = _ctext2, bgcolor = _bg2)
_panel.incRow()
// Function 6: Background Color
f_bg(_rsi) =>
c_line = na(_rsi) ? i_color_mid :
_rsi >= i_threshold_ob ? i_color_ob :
_rsi >= i_threshold_uptrend ? i_color_uptrend :
_rsi <= i_threshold_os ? i_color_os :
_rsi <= i_threshold_downtrend ? i_color_downtrend :
i_color_mid
// Function 7: Text Color
f_rsi_text_color(_rsi) =>
c_line = na(_rsi) ? i_tcolor_mid :
_rsi >= i_threshold_ob ? i_tcolor_ob :
_rsi >= i_threshold_uptrend ? i_tcolor_uptrend :
_rsi <= i_threshold_os ? i_tcolor_os :
_rsi <= i_threshold_downtrend ? i_tcolor_downtrend :
i_tcolor_mid
f_formatRsi(_rsi) => na(_rsi) ? 'N/A' : str.tostring(_rsi, '0.00')
// --- Panel Execution Logic ---
if barstate.islast
v_panel = TPanel.new(vertical_orientation = i_orientation == 'Vertical')
v_max_rows = 20
v_panel.src := table.new(f_StrPositionToConst(i_position), v_max_rows, v_max_rows, border_width = i_border_width, border_color = i_color_border)
if i_showHeaders
v_panel.add('TF', i_color_header_bg, i_color_header_text, 'RSI', i_color_header_bg, i_color_header_text)
if i_rsi1_enabled
v_panel.add(f_timeframeToHuman(i_rsi1_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi1), f_bg(v_rsi1), f_rsi_text_color(v_rsi1))
if i_rsi2_enabled
v_panel.add(f_timeframeToHuman(i_rsi2_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi2), f_bg(v_rsi2), f_rsi_text_color(v_rsi2))
if i_rsi3_enabled
v_panel.add(f_timeframeToHuman(i_rsi3_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi3), f_bg(v_rsi3), f_rsi_text_color(v_rsi3))
if i_rsi4_enabled
v_panel.add(f_timeframeToHuman(i_rsi4_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi4), f_bg(v_rsi4), f_rsi_text_color(v_rsi4))
if i_rsi5_enabled
v_panel.add(f_timeframeToHuman(i_rsi5_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi5), f_bg(v_rsi5), f_rsi_text_color(v_rsi5))
if i_rsi6_enabled
v_panel.add(f_timeframeToHuman(i_rsi6_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi6), f_bg(v_rsi6), f_rsi_text_color(v_rsi6))
if i_rsi7_enabled
v_panel.add(f_timeframeToHuman(i_rsi7_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi7), f_bg(v_rsi7), f_rsi_text_color(v_rsi7))
if i_rsi8_enabled
v_panel.add(f_timeframeToHuman(i_rsi8_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi8), f_bg(v_rsi8), f_rsi_text_color(v_rsi8))
if i_rsi9_enabled
v_panel.add(f_timeframeToHuman(i_rsi9_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi9), f_bg(v_rsi9), f_rsi_text_color(v_rsi9))
if i_rsi10_enabled
v_panel.add(f_timeframeToHuman(i_rsi10_tf), i_color_tf_bg, i_color_tf_text, f_formatRsi(v_rsi10), f_bg(v_rsi10), f_rsi_text_color(v_rsi10))
if i_debug
t = table.new(position.middle_center, 21, 20, border_width = i_border_width, border_color = i_color_border)
v_panel2 = TPanel.new(t, vertical_orientation = i_orientation == 'Vertical')
v_panel2.add('Debug', i_color_header_bg, i_color_header_text, 'Colors', i_color_header_bg, i_color_header_text)
// Using a tuple array for debugging colors demo
// Final Syntax Correction: Use array.new() and array.set() to avoid 'tuple()' function reference error
v_rows = 5 // We know we have 5 elements
demo = array.new(v_rows, '') // Initialize array with 5 string elements, will hold string representation of the tuple
// We will push the elements as a *string* representation of the tuple, as Pine v6 allows
// and then parse them inside the loop if necessary.
// To preserve the structure (string, float) without the tuple() function:
// We must define two separate arrays if the 'tuple' function is truly unavailable.
tf_array = array.new(v_rows)
rsi_array = array.new(v_rows)
// Populate the arrays
array.set(tf_array, 0, 'Overbought')
array.set(rsi_array, 0, float(i_threshold_ob))
array.set(tf_array, 1, 'Uptrend')
array.set(rsi_array, 1, float(i_threshold_uptrend))
array.set(tf_array, 2, 'No Trend')
array.set(rsi_array, 2, 50.0)
array.set(tf_array, 3, 'Downtrend')
array.set(rsi_array, 3, float(i_threshold_downtrend))
array.set(tf_array, 4, 'Oversold')
array.set(rsi_array, 4, float(i_threshold_os))
// Iterate over the arrays using a simple index
for i = 0 to v_rows - 1
tf = array.get(tf_array, i)
rsi = array.get(rsi_array, i)
v_panel2.add(tf, i_color_tf_bg, i_color_tf_text, f_formatRsi(rsi), f_bg(rsi), f_rsi_text_color(rsi))
Index Top 5 Heavyweight Analyzer## 🎯 Overview
This advanced Pine Script indicator applies the **Pareto Principle** to Nifty 50 trading: the top 5 heavyweights control 40%+ of the index's movement. Instead of watching all 50 stocks, this tool monitors the "Kings" that actually drive the index direction.
Professional traders don't trade the index in isolation - they look "under the hood" at heavyweight constituents. This indicator does exactly that, providing real-time analysis of HDFC Bank, Reliance, ICICI Bank, Bharti Airtel, and TCS to predict Nifty movements before they happen.
## 🔥 Key Features
### 1️⃣ Four-Quadrant OI Cycle Analysis
Identifies which cycle each heavyweight is in using Open Interest from continuous futures contracts:
- **Long Buildup** (Price ↑ + OI ↑): Institutions buying aggressively → Bullish driver
- **Short Covering** (Price ↑ + OI ↓): Bears trapped and exiting → Fast bullish spike
- **Short Buildup** (Price ↓ + OI ↑): Big money shorting → Bearish drag
- **Long Unwinding** (Price ↓ + OI ↓): Buyers giving up → Index weakness
### 2️⃣ Alignment Score System
Counts how many of the top 5 stocks are bullish/bearish/neutral. When 3+ heavyweights align in the same direction with sufficient weightage (15%+), the indicator generates high-conviction trade signals for the Nifty index.
### 3️⃣ Cost of Carry (Basis) Analysis
Compares Future vs Spot prices to gauge institutional sentiment:
- **Rising Premium**: Aggressive institutional buying
- **Discount (Backwardation)**: Extreme bearishness
### 4️⃣ Divergence Detection
Warns when the index move contradicts heavyweight signals - identifying "fake moves" that professional traders fade.
### 5️⃣ Actionable Trade Signals
- **Strong Bullish**: Buy Index Calls / Long Nifty Future
- **Strong Bearish**: Buy Index Puts / Short Nifty Future
- **Neutral/Choppy**: Iron Condor / Avoid Directional trades
## 📈 What Makes This Different?
Unlike basic index indicators, this tool:
- Fetches real Open Interest data from continuous futures (RELIANCE1!, HDFCBANK1!, etc.)
- Applies weighted analysis - top 3 stocks matter most
- Provides professional trade recommendations based on constituent alignment
- Uses dark theme optimized colors for extended screen time
- Displays comprehensive dashboard with price, OI, OI change %, cycle status, and basis
## 💡 How to Use
1. **Add to any Nifty 50 or Bank Nifty chart**
2. **Watch the dashboard** in the top-right corner showing all 5 heavyweights
3. **Check the ALIGNMENT row**:
- 🔼 Bull Count | 🔽 Bear Count | ➖ Neutral Count
- Weighted Bull/Bear scores
4. **Read the INDEX SIGNAL row** for trade recommendations
5. **Look for divergence warnings** (⚠️) indicating fake moves
6. **Use the histogram plot** to visualize signal strength over time
## ⚙️ Customizable Settings
- **Constituents**: Modify ticker symbols and weightages
- **Signal Thresholds**: Adjust minimum alignment required (default: 3 out of 5)
- **Display Options**: Toggle table, signals, and basis calculations
- **Timeframe**: Works on all timeframes (intraday and daily)
## 🎨 Dark Theme Optimized
Designed specifically for TradingView's dark mode with:
- High-contrast colors that reduce eye strain
- Bright lime green (#00E676) for bullish signals
- Bright red (#FF5252) for bearish signals
- Electric colors for easy pattern recognition
## 📊 Best Used For
- **Nifty 50 Options Trading**: Know whether to buy calls or puts
- **Index Futures Trading**: Identify high-probability directional moves
- **Risk Management**: Avoid trading when heavyweights show divergence
- **Market Timing**: Enter when top stocks align (3+ in same direction)
## 🚀 Pro Tips
- **"Double Engine" Signal**: When Reliance shows Long Buildup AND HDFC Bank shows Short Covering → Extremely bullish for Nifty
- **Sector Rotation**: If Banks are strong but Tech is weak (or vice versa) → Expect choppy, range-bound index
- **Rollover Analysis**: Near expiry, watch for high OI with rising basis → Bulls/Bears carrying positions forward with confidence
## ⚠️ Important Notes
- Requires TradingView Premium for multiple `request.security()` calls
- OI data available only for stocks with active futures
- Best used on NSE exchange during market hours
- Combine with your own risk management strategy
## 📝 Credits
Based on professional institutional trading methodologies that analyze index constituents rather than the index itself. Implements the Pareto Principle: focus on the 20% (top 5 stocks) that drives 80% of the index movement.
***
## 🔔 Alerts Available
- Strong Bullish Signal (3+ stocks aligned bullish)
- Strong Bearish Signal (3+ stocks aligned bearish)
- Divergence Warning (fake index moves)
**Made for serious traders who want to trade like institutions - by watching what the "smart money" is doing in the heavyweights.**
***
*Optimize your Nifty trading by monitoring the stocks that actually matter. Stop watching all 50 - focus on the 5 Kings!* 👑
***
**Tags**: Nifty, Open Interest, OI Analysis, Heavyweight Analysis, Index Trading, Options Trading, Futures Trading, Institutional Analysis, Smart Money, Pareto Principle
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Market Momentum in Premium & Discount-Delta @MaxMaserati 3.0Market Delta Momentum in Premium & Discount-Delta @MaxMaserati 3.0
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Overview
The MMPD 3.0 indicator is an advanced momentum oscillator that combines market structure analysis with institutional order flow concepts. It transforms price action into a normalized 0-100 scale, identifying premium and discount zones where institutional traders typically operate, while simultaneously tracking momentum through specialized body close candles and multi-timeframe synchronization.
This indicator is designed for traders who want to:
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Identify high-probability reversal zones using premium/discount analysis
Track momentum divergence between price and the MMPD oscillator
Recognize institutional rejection and acceptance zones
Synchronize multiple timeframes for confluence-based trading decisions
Core Methodology
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MMPD Calculation
The Market Delta Momentum indicator uses a proprietary calculation that:
Normalizes price position within a specific period range (0-100 scale)
Applies double smoothing to filter noise
Calculates a balance line (similar to a moving average) to determine bullish/bearish momentum
The relationship between the MMPD line and balance line creates directional candles
Key Zones:
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90-100: Extreme Premium (Institutional Selling Zone)
80-90: High Premium (Caution Zone)
65-80: Premium (Bullish Bias)
50-65: Light Premium (Neutral-Bullish)
35-50: Light Discount (Neutral-Bearish)
20-35: Discount (Bearish Bias)
10-20: High Discount (Institutional Buying Zone)
0-10: Extreme Discount (High Probability Buy Zone)
MMM 3.0 Body Close Logic BC and the MMPD 3.0 Body Close Logic MBC
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1️⃣ Body Close Analysis (BC & MBC)
Price Body Close (BC)
Bullish BC: Price closes above the previous high AND closes above its open (green candle showing aggressive buying)
Bearish BC: Price closes below the previous low AND closes below its open (red candle showing aggressive selling)
No Body Close (NBC): All other candles - representing consolidation, pause, or loss of momentum
MMPD Body Close (MBC)
Bullish MBC: MMPD closes higher than previous MMPD structure (continuation or reversal momentum)
Bearish MBC: MMPD closes lower than previous MMPD structure (continuation or reversal momentum)
MNBC: MMPD No Body Close - weak or ranging MMPD momentum
BC + MBC Confirmation
When Price BC and MMPD MBC align in the same direction, it signals high-conviction momentum:
Deep Green: Bullish BC + Bullish MBC (Strongest Bullish Signal)
Pale Green: Bullish BC only (Moderate Bullish Signal)
Deep Red: Bearish BC + Bearish MBC (Strongest Bearish Signal)
Pale Pink: Bearish BC only (Moderate Bearish Signal)
2️⃣ Momentum Synchronization System
The indicator compares MBC (MMPD Body Close) momentum against BC (Price Body Close) momentum to identify divergence and synchronization:
Synchronized States:
BULLISH+: High volatility bullish synchronization (BC+MBC aligned, high ATR)
BULLISH-: Low volatility bullish synchronization (BC+MBC aligned, low ATR)
BEARISH+: High volatility bearish synchronization (BC+MBC aligned, high ATR)
BEARISH-: Low volatility bearish synchronization (BC+MBC aligned, low ATR)
SYNCHRONIZED: Both MMPD and Price moving together (standard bullish or bearish move)
Divergence States (Reversal Warnings):
MMPD FAST | PRICE SLOW: MMPD showing strong directional MBC candles while Price shows NBC (pause/consolidation) - Reversal Warning!
If MMPD is bullish MBC but Price is NBC → Potential Bearish Reversal
If MMPD is bearish MBC but Price is NBC → Potential Bullish Reversal
Status Indicators:
BULL / BEAR: Standard synchronized moves
BULL+ / BEAR+: High volatility synchronized moves (aggressive trending)
BULL- / BEAR-: Low volatility synchronized moves (grinding trends)
POT. BULL / POT. BEAR: Potential reversal zones (divergence detected)
BALANCED: Neutral conditions, no clear momentum alignment which is price efficiency
3️⃣ Premium/Discount Breakout Markers
🔴 Red Circle Dots (Premium Exit)
Appears when MMPD closes below 80 after being completely in the 80-100 extreme premium zone
Signals institutional distribution complete, potential reversal or correction
🟢 Green Circle Dots (Discount Exit)
Appears when MMPD closes above 20 after being completely in the 0-20 extreme discount zone
Signals institutional accumulation complete, potential rally or reversal
🔴 Red Squares (Premium Rejection)
Appears on the first candle that fails to touch 80-100 after a Bullish MBC touched that zone
Indicates rejection of premium pricing, bearish signal
🟢 Green Squares (Discount Rejection)
Appears on the first candle that fails to touch 0-20 after a Bearish MBC touched that zone
Indicates rejection of discount pricing, bullish signal
🔻 Red Triangles Down (Bearish Midline Rejection)
Signals potential bearish Resumption
🔺 Green Triangles Up (Bullish Midline Bounce)
Signals potential Bullish Resumption
4️⃣ Multi-Timeframe Dashboard with Candle time to close
The MTF table displays:
6 customizable timeframes (default: 5min, 15min, 1H, 4H, Daily, Weekly)
Premium/Discount Status with color-coded zones for each timeframe
Time to Close (T2C): Live countdown timer for each timeframe candle close
Red warning color when the candle closing time is imminent
4H timeframe auto-detects exchange-specific session starts (ES, NQ, CL, GC, etc.)
Momentum Sync Status: Shows the current synchronization state between MMPD and Price across the chart timeframe
Color Coding:
Premium zones: Green/Cyan colors
Discount zones: Purple/Magenta colors
Intensity increases with extremeness (darker = more extreme)
5️⃣ Delta MMPD Alternative View
Toggle between two oscillator calculations:
MMPD: Original MMPD
Delta MMPD: Volume-weighted delta calculation emphasizing buying/selling pressure
TIPS
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Use Multi-Timeframe Confluence: The strongest signals occur when multiple timeframes align in premium/discount zones
Wait for Body Close Confirmation: BC+MBC alignment = highest probability setups
Respect Momentum Sync Warnings: "MMPD FAST | PRICE SLOW" is a critical reversal warning
Trade Premium → Discount or Discount → Premium: Mean reversion from extremes offers best risk/reward
Combine with Price Action: MMPD is a momentum oscillator - always confirm with price structure (support/resistance, trendlines, chart patterns)
Educational Notes
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What is Premium/Discount Pricing?
Institutional traders operate based on value zones:
Premium: Price is expensive relative to recent range - institutions distribute (sell)
Discount: Price is cheap relative to recent range - institutions accumulate (buy)
Fair Value (50 line): Equilibrium pricing where institutions pause
MMM 3.0 Body Close Approach Importance
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BC (Body Close): Shows price commitment and aggressivity
NBC (No Body Close): Shows indecision, consolidation, or loss of momentum
Consecutive BC candles = strong momentum
NBC candles breaking BC sequence = momentum loss → potential reversal
Momentum Synchronization Theory
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When MMPD (momentum) moves aggressively but Price shows NBC (pause), it indicates:
Momentum exhaustion
Smart money distribution/accumulation
Imminent reversal as retail traders get trapped
⚠️ Disclaimer
This indicator is for educational purposes only. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose. Trading involves substantial risk of loss. The creator assumes no responsibility for trading losses incurred using this indicator.
