Volume Flow Anatomy [Kodexius]Volume Flow Anatomy is a dynamic, multi-dimensional volume map that reconstructs how buy, sell, and “stealth” activity is distributed across price rather than just across time. Instead of relying on a static, session-based volume profile, it uses an exponentially decaying memory of recent bars to build a constantly evolving “anatomy” of the auction, where each price level carries an adaptive history of order flow.
The script separates buy vs. sell pressure, adds a third “Stealth Flow” dimension for low-volume price movement (ease of movement / divergence), and automatically derives POC, Value Area, imbalances, absorption zones, and classic profile shapes (D, P, b, B). This gives the trader a compact but highly information-dense map on the right side of the chart to read control (buyers vs. sellers), structure (balanced vs. trending vs. double distribution), and key reaction levels (support/resistance born from flow, not just wicks).
🔹 Features
🔸 Dynamic Lookback with Decay
- The script computes an effective lookback N from the Decay Factor and caps it with Max Lookback.
- Higher decay keeps more history; lower decay emphasizes the most recent flow.
- The profile continuously adapts as new bars are printed.
🔸 Price-Bucketed Flow Map
Each bucket accumulates:
- Sell Flow (sell pressure)
- Buy Flow (buy pressure)
- Stealth Flow (low-volume price movement)
- Box width at each bucket is proportional to the relative intensity of that component.
🔸 Stealth Flow (Low-Volume Price Movement)
- Measures close to close movement relative to volume, emphasizing price movement that occurs on comparatively low volume.
- Helps reveal hidden participation, inefficient moves, and areas that may be vulnerable to re-tests or reversions.
🔸 POC & 70% Value Area (VA)
- Identifies the Point of Control (price bucket with the highest total volume) over the effective lookback.
- Builds a 70% Value Area by expanding from POC towards the nearest high volume neighbors until 70% of the total volume is included.
- POC is drawn as a line over the analyzed range; VA is displayed as a shaded band in the profile area.
🔸 Market Profile Shape Detection
Splits the profile vertically into three zones (bottom / middle / top) and compares their volume distribution.
Classifies structure as:
- D-Shape (Balanced)
- P-Shape (Short Covering)
- b-Shape (Long Liquidation)
- B-Shape (Double Distribution)
Displays a shape label with color coded bias for quick auction context interpretation.
🔸 Imbalance Zones & Absorption
Imbalance: detects buckets where Buy Flow or Sell Flow exceeds the opposite side by at least Imbalance Ratio.
Absorption: flags zones with high volume but low price “ease”, where price is not moving much despite significant volume.
Extends these levels into horizontal zones, marking potential support/resistance and trap areas.
Bullish Imbalance Zone :
Bearish Imbalance Zone :
Absorption Zone :
🔸 Range Context & On-Chart Legend
Draws a Range Box covering the dynamically determined lookback (N bars), with a label displaying the effective bar count.
A bottom-right legend summarizes:
- Color keys for Buy / Sell / Stealth
- POC / VA status
- Bullish vs. Bearish dominance percentage
- Profile shape classification
- Imbalance and Absorption conventions
🔹 Calculations
1. Dynamic Lookback & Price Buckets
int N = math.min(int(4 / (1 - decayFactor) - 1), maxHistory)
float priceHigh = ta.highest(high, N)
float priceLow = ta.lowest(low, N)
float bucketSize = (priceHigh - priceLow) / bucketCount
The effective lookback N is derived from the Decay Factor, using the approximation 4 / (1 - decay) to capture roughly 99% of the decayed influence, then capped with maxHistory to control performance. Over that adaptive range, the script finds the highest and lowest prices and divides the band into bucketCount equal slices (bucketSize). Each slice is a price bucket that will accumulate volume-flow information.
2. Exponentially Decayed Volume Allocation
addValue(array profile, float weight, float minPrice, float maxPrice) =>
for j = 0 to bucketCount - 1
float bucketMin = priceLow + j * bucketSize
float bucketMax = bucketMin + bucketSize
float overlapMin = math.max(minPrice, bucketMin)
float overlapMax = math.min(maxPrice, bucketMax)
float overlapRange = overlapMax - overlapMin
if overlapRange > 0
profile.set(j, profile.get(j) * decayFactor + weight * overlapRange)
This function is the core engine of the indicator. For a given price span and intensity, it checks every bucket for overlap, distributes the weight proportionally to the overlapping range, and before adding new value, decays the existing bucket content by decayFactor. This results in an exponentially weighted profile: recent activity dominates, while older levels retain a gradually fading footprint.
3. POC and 70% Value Area
array totalProfile = array.new(bucketCount, 0)
for j = 0 to bucketCount - 1
float total = sellProfile.get(j) + buyProfile.get(j)
totalProfile.set(j, total)
if total > eaMax
eaMax := total
int pocIdx = 0
float pocVal = 0.0
for j = 0 to bucketCount - 1
if totalProfile.get(j) > pocVal
pocVal := totalProfile.get(j)
pocIdx := j
float totalSum = totalProfile.sum()
float targetSum = totalSum * 0.70
int vaLow = pocIdx
int vaHigh = pocIdx
float currentSum = pocVal
while currentSum < targetSum and (vaLow > 0 or vaHigh < bucketCount - 1)
float lowVal = vaLow > 0 ? totalProfile.get(vaLow - 1) : 0.0
float highVal = vaHigh < bucketCount - 1 ? totalProfile.get(vaHigh + 1) : 0.0
First, totalProfile is built as the sum of buy and sell flow per bucket, and eaMax (the maximum total) is tracked for later normalization. The POC bucket (pocIdx) is simply the index with the highest totalProfile value.
To compute the 70% Value Area, the algorithm starts at the POC bucket and expands outward, each step adding either the upper or lower neighbor depending on which has more volume. This continues until the cumulative volume reaches 70% of totalSum. The result is a volume-driven VA, not necessarily symmetric around POC, which more accurately represents where the market has truly traded.
4. Market Profile Shape Classification
float volTopThird = 0.0
float volMidThird = 0.0
float volBotThird = 0.0
int thirdIdx = int(bucketCount / 3)
for j = 0 to bucketCount - 1
float val = totalProfile.get(j)
if j < thirdIdx
volBotThird += val
else if j < thirdIdx * 2
volMidThird += val
else
volTopThird += val
float totalVolShape = totalProfile.sum()
string shapeStr = "D-Shape (Balanced)"
if (volTopThird > totalVolShape * 0.20) and (volBotThird > totalVolShape * 0.20) and (volMidThird < totalVolShape * 0.50)
shapeStr := "B-Shape (Double Dist)"
else
if pocIdx > bucketCount * 0.5 and volTopThird > volBotThird * 1.3
shapeStr := "P-Shape (Short Covering)"
else if pocIdx < bucketCount * 0.5 and volBotThird > volTopThird * 1.3
shapeStr := "b-Shape (Long Liquidation)"
else
shapeStr := "D-Shape (Balanced)"
The profile is split into bottom, middle, and top thirds. The script compares how much volume is concentrated in each and combines that with the relative location of POC. If both extremes are heavy and the middle light, it labels a B-Shape (double distribution). If the POC is high and the top dominates the bottom, it’s a P-Shape (short covering). If the POC is low and the bottom dominates, it’s a b-Shape (long liquidation). Otherwise, it defaults to a D-Shape (balanced). This provides a quick, at-a-glance assessment of auction structure.
5. Imbalances, Absorption & Zones
bool isBuyImb = showImb and sVal > 0 and (bVal / sVal >= imbRatio)
bool isSellImb = showImb and bVal > 0 and (sVal / bVal >= imbRatio)
float volRatio = eaMax > 0 ? tVal / eaMax : 0
float stRatio = esmRange > 0 ? (stVal - esmMin) / esmRange : 1.0
bool isAbsorp = showAbsorp and volRatio > 0.6 and stRatio < 0.25
if showImbZone
if isSellImb
zoneBoxes.push(box.new(bar_index - N + 1, bucketHi, bar_index + 1, bucketLo, ...))
if isBuyImb
zoneBoxes.push(box.new(bar_index - N + 1, bucketHi, bar_index + 1, bucketLo, ...))
if isAbsorp
zoneBoxes.push(box.new(bar_index - N + 1, bucketHi, bar_index + 1, bucketLo, ...))
Imbalances are identified where one side’s volume (buy or sell) exceeds the other by at least Imbalance Ratio. These buckets are marked as buy or sell imbalance zones, indicating aggressive participation from one side.
Absorption is detected by combining a high volume ratio (volRatio) with a low normalized stealth ratio (stRatio). High volume with limited price movement suggests that opposing orders are absorbing flow at that level. Both imbalance and absorption buckets are extended into horizontal zones from the start of the lookback to the current bar, visually emphasizing key support/resistance and liquidity areas.
6. Building Buy, Sell & Stealth Profiles
sellProfile := array.new(bucketCount, 0)
buyProfile := array.new(bucketCount, 0)
stealthProfile := array.new(bucketCount, 0)
Three arrays are used to store Sell Flow, Buy Flow, and Stealth Flow. Bars are processed from oldest to newest so that decay is applied in correct chronological order. For each bar, a volume density (volume / range) is calculated and distributed across the candle range. Bull candles feed buyProfile, bear candles feed sellProfile.
Stealth Flow computes the close-to-close move between consecutive bars, scaled by 1 / (1 + volume). Big moves on low volume produce high stealth values, which are then allocated across the move’s price span into stealthProfile. This yields a three-layer profile per price level: directional volume and stealthy price movement.
Cerca negli script per "support resistance"
⭐ Silver HUD v15.1 — Full Notes Version (3-Column HUD)Silver HUD v15.1 is a comprehensive Pine Script v5 indicator designed for micro silver futures (SIL) trading on TradingView. It overlays a 3-column HUD table displaying real-time analysis across multiple engines including trend, flow, momentum, pullback, turbo (breakout), divergence, volume, and 2H structure. The system generates weighted BUY/SELL scores and final signals with risk warnings, optimized for 5m charts with 30m support/resistance levels.
Core Components
Support/Resistance & Trade Levels
Pulls 30m lowest low (support) and highest high (resistance) for entry/stop/TP calculation. Entry defaults to support, stop loss at support - 0.10, with ATR-based TPs (1x/2x/3x). Risk per lot factors SIL contract specs (1000oz, $5/tick). Alerts when price nears support within 0.05.
Multi-Engine Analysis
TREND: EMA20/50 + VWAP direction (UP/DOWN/MIXED).
FLOW: CCIOBV (CCI+OBV) + QQE momentum sync.
MOMENTUM: RSI/MFI >55 (UP) or <45 (DOWN).
PB (Pullback): EMA20 deviation (-0.4% to +1.2% = OK; flags CHASE/DEEP).
TURBO: ATR percentile + BB width squeeze for BREAKOUT/EXHAUST.
Scores weight flow (30%), momentum (25%), PB (25%), trend/turbo (10-20%). BUY ≥75, SELL ≥72 triggers raw signals.
Advanced Features
2H Structure: Detects HH/HL/LL/LH swings for macro bias (UP/DOWN/MIXED).
SELL System: Distinguishes SELL-ALERT (exhaustion) vs full SELL-REVERSAL (multi-condition bear flip).
Divergence & Volume: RSI-based bear/bull div on swing highs/lows; surge detection (>2x vol MA or 80th percentile).
Final Signal: Combines raw scores with filters (no DEEP PB for BUY, 2H tiebreaker); RISK flags conflicts like div or trend mismatches.
HUD Display & Usage
Renders a bottom-right table with metric, status (color-coded), and Chinese explanations. Stars rate scores (★★★★★=90+). Ideal for high-frequency SIL traders monitoring multi-timeframe confluence on 5m charts.
BB Breakout-Momentum + Reversion Strategies# BB Breakout-Momentum + Reversion Strategies
## Overview
This indicator combines two complementary Bollinger Band trading strategies that automatically adapt to market conditions. Strategy 1 capitalizes on trending markets with breakout-pullback-momentum setups, while Strategy 2 exploits mean reversion in ranging markets. Advanced filtering using ADX and BB Width ensures each strategy only fires in its optimal market environment.
---
## Strategy 1: Breakout → Pullback → Renewed Momentum (Long B / Short B)
### Best Market Conditions
- **Trending Markets**: ADX ≥ 25
- **High Volatility**: BB Width ≥ 1.0× average
- Directional price action with sustained momentum
### Entry Logic
**Long B (Bullish Breakout):**
1. **Initial Breakout**: Price breaks above upper Bollinger Band with strong momentum
2. **Controlled Pullback**: Price pulls back 1-12 bars but holds above lower band (stays in trend)
3. **Defended Zone**: Pullback creates a support zone based on swing lows (validated by multiple touches)
4. **Renewed Momentum**: Price reclaims with green candle, volume confirmation, bullish MACD
5. **Position Check**: Entry must have cushion below upper band and room to reach targets
**Short B (Bearish Breakdown):**
- Mirror logic for downtrends: breakdown below lower band, pullback stays below upper band, renewed selling pressure
### Risk Management
- **Stop Loss**: Lower of (zone floor/previous low) OR (1.5 × ATR from entry)
- **Targets**:
- T1: Entry + 0.85R (0.85 × 1.5 ATR)
- T2: Entry + 1.40R (1.40 × 1.5 ATR)
- T3: Entry + 2.50R (2.50 × 1.5 ATR)
- T4: Entry + 4.50R (4.50 × 1.5 ATR)
- Risk is calculated using ATR (ATRX = 1.5 ATR), stop uses tighter of structural level (ATRL) or ATRX
---
## Strategy 2: Bollinger Band Mean Reversion (Long R / Short R)
### Best Market Conditions
- **Ranging Markets**: ADX ≤ 20
- **Low Volatility**: BB Width ≤ 0.8× average
- Price oscillating around the mean without sustained trend
### Entry Logic
**Long R (Long Reversion):**
1. **Overextension**: Price breaks below lower Bollinger Band (2 consecutive closes)
2. **Snap Back**: Price crosses back above lower band (re-enters the range)
3. **Entry Window**: Within 2 candles of re-entry, look for:
- **Green candle** (close > open) confirming bullish strength
- Close above previous candle (close > close )
4. **Trigger**: First qualifying candle within 2-bar window executes the trade
**Short R (Short Reversion):**
1. **Overextension**: Price breaks above upper Bollinger Band (2 consecutive closes)
2. **Snap Back**: Price crosses back below upper band (re-enters the range)
3. **Entry Window**: Within 2 candles of re-entry, look for:
- **Red candle** (close < open) confirming bearish pressure
- Close below previous candle (close < close )
4. **Trigger**: First qualifying candle within 2-bar window executes the trade
### Risk Management
- **Stop Loss**: Lower of (previous high/low) OR (1.5 × ATR from entry)
- **Targets**: Same as Strategy 1 (0.85R, 1.4R, 2.5R, 4.5R based on 1.5 ATR)
- Betting on return to Bollinger Band basis (mean)
---
## Advanced Filtering System
### ADX Filter (Average Directional Index)
- **Purpose**: Measures trend strength vs choppy/ranging conditions
- **Trending**: ADX ≥ 25 → Enables Strategy 1 (Breakout)
- **Ranging**: ADX ≤ 20 → Enables Strategy 2 (Reversion)
- **Neutral**: ADX 20-25 → No signals (indecisive market)
### BB Width Filter
- **Purpose**: Confirms volatility expansion/contraction
- **Wide Bands**: Current width ≥ 1.0× 50-bar average → Trending environment
- **Narrow Bands**: Current width ≤ 0.8× 50-bar average → Ranging environment
- **Logic**: Both ADX and BB Width must agree on market state before signaling
### Combined Logic
- **Strategy 1 fires**: When BOTH ADX shows trending AND bands are wide
- **Strategy 2 fires**: When BOTH ADX shows ranging AND bands are narrow
- **Visual Display**: Table at bottom-right shows ADX value, BB Width ratio, and current market state
---
## Visual Elements
### Bollinger Bands
- **Gray line**: 20-period SMA (basis/mean)
- **Green line**: Upper band (basis + 2 standard deviations)
- **Red line**: Lower band (basis - 2 standard deviations)
### Strategy 1 Markers
- **Long B**: Green triangle below bar with "Long B" text
- **Short B**: Orange triangle above bar with "Short B" text
- **Defended Zones**: Green/red boxes showing pullback support/resistance areas
- **Targets**: Green/orange crosses showing T1-T4 and stop loss levels
### Strategy 2 Markers
- **Long R**: Blue label below bar with "Long R" text
- **Short R**: Purple label above bar with "Short R" text
- **Trade Levels**: Horizontal lines extending 50 bars forward
- Blue solid = Entry price
- Red dashed = Stop loss
- Green/Orange dotted = Targets (T1-T4)
### Market State Table
- **ADX**: Current value with color coding (green=trending, orange=ranging, gray=neutral)
- **BB Width**: Ratio vs 50-bar average (e.g., "1.15x" = 15% wider than average)
- **State**: TREND / RANGE / NEUTRAL classification
---
## Settings & Customization
### Bollinger Bands
- **BB Length**: 20 (default) - period for moving average
- **BB Std Dev**: 2.0 (default) - standard deviation multiplier
### ATR & Risk
- **ATR Length**: 14 (default) - period for Average True Range calculation
- All stop losses and targets are derived from 1.5 × ATR
### Trend/Range Filters
- **ADX Length**: 14 (default)
- **ADX Trending Threshold**: 25 (higher = stronger trend required)
- **ADX Ranging Threshold**: 20 (lower = tighter ranging condition)
- **BB Width Average Length**: 50 (period for comparing current width)
- **BB Width Trend Multiplier**: 1.0 (width must be ≥ this × average)
- **BB Width Range Multiplier**: 0.8 (width must be ≤ this × average)
- **Use ADX Filter**: Toggle on/off
- **Use BB Width Filter**: Toggle on/off
### Strategy 1 (Breakout-Momentum)
- **Breakout Lookback**: 15 bars (how far back to search for initial breakout)
- **Min Pullback Bars**: 1 (minimum consolidation period)
- **Max Pullback Bars**: 12 (maximum consolidation period)
- **Show Defended Zone**: Display support/resistance boxes
- **Show Signals**: Display Long B / Short B markers
- **Show Targets**: Display stop loss and target levels
### Strategy 2 (Reversion)
- **Show Signals**: Display Long R / Short R markers
- **Show Trade Levels**: Display entry, stop, and target lines
---
## How to Use This Indicator
### Step 1: Identify Market State
- Check the table in bottom-right corner
- **TREND**: Look for Strategy 1 signals (Long B / Short B)
- **RANGE**: Look for Strategy 2 signals (Long R / Short R)
- **NEUTRAL**: Wait for clearer conditions
### Step 2: Wait for Signal
- Signals only fire when ALL conditions are met (structural + momentum + filters + room-to-target)
- Signals are relatively rare but high-probability
### Step 3: Execute Trade
- **Entry**: Close of signal candle
- **Stop Loss**: Shown as red cross (Strategy 1) or red dashed line (Strategy 2)
- **Targets**: Scale out at T1, T2, T3, T4 or hold for maximum R:R
### Step 4: Management
- Consider moving stop to breakeven after T1
- Trail stop using swing lows/highs in Strategy 1
- Exit full position at T2-T3 in Strategy 2 (mean reversion has limited upside)
---
## Key Principles
### Why This Works
1. **Market Adaptation**: Uses right strategy for right conditions (trend vs range)
2. **Confluence**: Multiple confirmations required (structure + momentum + volatility + room)
3. **Risk-Defined**: Every trade has pre-calculated stop and targets based on ATR
4. **Probability**: Filters reduce noise and increase win rate by waiting for ideal setups
### Common Pitfalls to Avoid
- ❌ Taking signals in NEUTRAL market state (indicators disagree)
- ❌ Overriding the stop loss (it's calculated for a reason)
- ❌ Expecting signals on every swing (quality over quantity)
- ❌ Using Strategy 1 in ranging markets or Strategy 2 in trending markets
- ❌ Ignoring the room-to-target check (signal won't fire if targets are blocked)
### Complementary Analysis
This indicator works best when combined with:
- Higher timeframe trend analysis
- Key support/resistance levels
- Volume analysis
- Market structure (swing highs/lows)
- Risk management rules (position sizing, max daily loss, etc.)
---
## Technical Details
### Indicators Used
- **Bollinger Bands**: 20-period SMA ± 2 standard deviations
- **ATR**: 14-period Average True Range for volatility measurement
- **ADX**: 14-period Average Directional Index for trend strength
- **EMA**: 10 and 20-period exponential moving averages (Strategy 1 filter)
- **MACD**: 12/26/9 settings (Strategy 1 momentum confirmation)
- **Volume**: Compared to 15-bar average (Strategy 1 confirmation)
### Calculation Methodology
- **ATRL** (Structural Risk): Previous swing high/low or defended zone boundary
- **ATRX** (ATR Risk): 1.5 × 14-period ATR from entry price
- **Stop Loss**: Minimum of ATRL and ATRX (tightest protection)
- **Targets**: Always calculated from ATRX (consistent R-multiples)
- **BB Width Ratio**: Current BB width ÷ 50-period SMA of BB width
---
## Performance Notes
### Strengths
- Adapts to changing market conditions automatically
- Clear, objective entry and exit criteria
- Pre-defined risk on every trade
- Filters reduce false signals significantly
- Works across multiple timeframes and instruments
### Limitations
- Signals are infrequent (by design - quality over quantity)
- Requires patience to wait for all conditions to align
- May miss explosive moves if pullback doesn't form properly (Strategy 1)
- Ranging markets can transition to trending (Strategy 2 risk)
- Filters may delay entry in fast-moving markets
### Best Timeframes
- **Strategy 1**: 1H, 4H, Daily (needs time for proper pullback structure)
- **Strategy 2**: 15M, 30M, 1H (mean reversion works best intraday)
- Both strategies can work on any timeframe if market conditions are right
### Best Instruments
- **Liquid markets**: Major stocks, indices, forex pairs, liquid crypto
- **Sufficient volatility**: ATR should be meaningful relative to price
- **Clear trend/range cycles**: Markets that respect technical levels
---
## IMPORTANT DISCLAIMER
### Risk Warning
**TRADING INVOLVES SUBSTANTIAL RISK OF LOSS AND IS NOT SUITABLE FOR ALL INVESTORS.**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment advice, trading advice, or any other sort of advice. You should not treat any of the indicator's content as such.
### No Guarantee of Profit
Past performance is not indicative of future results. No trading strategy, including this indicator, can guarantee profits or protect against losses. The market is inherently unpredictable and all trading involves risk.
### User Responsibility
- **Do Your Own Research**: Always conduct your own analysis before making trading decisions
- **Test First**: Backtest and paper trade this strategy before risking real capital
- **Risk Management**: Never risk more than you can afford to lose
- **Position Sizing**: Use appropriate position sizes relative to your account
- **Stop Losses**: Always use stop losses and respect them
- **Market Conditions**: Understand that market conditions change and past behavior may not repeat
### No Liability
The creator of this indicator accepts no liability for any financial losses incurred through the use of this tool. All trading decisions are made at your own risk. You are solely responsible for evaluating the merits and risks associated with the use of any trading systems, signals, or content provided.
### Not Financial Advice
This indicator does not take into account your personal financial situation, investment objectives, risk tolerance, or specific needs. You should consult with a licensed financial advisor before making any investment decisions.
### Technical Limitations
- Indicators can repaint or lag in real-time
- Past signals may look different than real-time signals
- Code bugs or errors may exist despite testing
- TradingView platform limitations may affect functionality
### Market Risks
- Markets can gap, causing stops to be executed at worse prices
- Slippage and commissions can significantly impact results
- High volatility can cause unexpected losses
- Counterparty risk exists in all leveraged products
---
## Version History
- **v1.0**: Initial release combining breakout-momentum and mean reversion strategies
- Includes ADX and BB Width filtering
- ATRL/ATRX risk calculation system
- 2-candle entry window for reversion trades
---
## Credits & License
This indicator combines concepts from classical technical analysis including Bollinger Bands (John Bollinger), ATR (Welles Wilder), and ADX (Welles Wilder). The specific implementation and combination of filters is original work.
**Use at your own risk. Trade responsibly.**
---
*For questions, suggestions, or to report bugs, please comment below or contact the author.*
**Remember: The best indicator is the one between your ears. Use this tool as part of a comprehensive trading plan, not as a standalone solution.**
White Crow**White Crow — cluster reversal signals + market structure**
> Indicator that helps you read market structure (pivots, trend, last extremes) and spot potential reversals through CCI/RSI signal clusters. This is *not* a standalone trading system and does not guarantee any result — it is a tool for filtering and confirming your own market ideas.
---
## 1. Concept
White Crow combines three core blocks:
1. **Pivots & market structure**
Automatically detects **local tops/bottoms** and derives a *Bullish / Bearish / Sideways* bias from them.
In the top-right corner you see a compact panel with current trend and **Last Bottom / Last Top** prices.
2. **Momentum & overbought/oversold zones**
Inside, the indicator uses:
* **CCI** with fixed levels `+100 / -100`;
* an optional **RSI filter** with overbought/oversold levels (`80 / 20`).
These generate basic *Buy / Close* signals.
3. **Cluster signals Buy X / CloseV**
The script tracks **clusters of signals inside a 4-bar window** and highlights rarer, “amplified” events:
* **Buy X** — cluster buy signal (multiple buy conditions in a row);
* **CloseV** — cluster signal for exit/reversal.
**Buy X and CloseV are the strongest and most reliable signals in this indicator** because they are based on repeated conditions rather than a single bar. They work **best on higher timeframes (1H–4H)**, where they reflect meaningful shifts in order flow instead of noise.
> ⚠️ Important: Buy X and CloseV are *only signals*. They must be used as **one of several confirmation factors** for your own view of market structure (support/resistance, trend, price action, volume, etc.), not as standalone reasons to enter or exit trades.
---
## 2. How it works
### 2.1. Pivots and trend detection
* The indicator builds a **zigzag-like structure**:
after a local high, once price retraces down by a given percentage (`pivotSigma`), a **Top** is marked;
after a local low, once price retraces up by the same percentage, a **Bottom** is marked.
* Using the sequence of recent tops and bottoms, the script determines the trend:
* *Bullish* — the last low is higher than the previous one (HL);
* *Bearish* — the last high is lower than the previous one (LH);
* otherwise — *Sideways*.
* The info table shows:
* **Market Trend** — Bullish / Bearish / Sideways;
* **Last Bottom / Last Top** with adaptive decimal precision (works for crypto, FX, stocks, etc.).
### 2.2. Base Buy / Close signals
* **Long condition (Buy):**
* `CCI < -100` (oversold),
* if RSI filter is enabled — `RSI < 20`.
* **Short/Exit condition (Close):**
* `CCI > +100` (overbought),
* if RSI filter is enabled — `RSI > 80`.
These conditions generate the regular **Buy** and **Close** labels on the chart.
### 2.3. Clusters: Buy X and CloseV
To reduce noise, the indicator evaluates not only the current bar, but also the **last 4 bars**:
* `buy_count` — how many times the long condition was true within the last 4 bars;
* `sell_count` — how many times the short condition was true within the last 4 bars.
Then:
* **Buy X** appears when:
* `buy_count ≥ 2` (conditions for Buy were met on at least 2 of the last 4 bars),
* the time filter between two Buy X signals is satisfied (`Min Bars Between Signals`).
* **CloseV** appears when:
* `sell_count ≥ 2`,
* the required number of bars has passed since the previous CloseV.
> ✅ This is why **Buy X / CloseV are stronger and more trustworthy than single Buy/Close signals**, especially on **1H–4H** timeframes: the market confirms the same overbought/oversold condition several times in a row.
### 2.4. Order Blocks
* When `Show Order Blocks` is enabled, the indicator highlights **impulsive candles** whose body exceeds a threshold based on ATR.
* Colored rectangles mark **potential order blocks** (areas where strong buying or selling previously occurred).
## 3. Inputs and customization
Inputs are grouped in TradingView-friendly categories.
### 3.1. Pivot Settings
* `Show Pivots` — enable/disable **Top / Bottom** markers.
* `Sigma (% retracement)` — pivot sensitivity (minimum retracement in % required to confirm a pivot).
* Colors for Top/Bottom — for visual tuning.
**Tip:**
On H1–H4 you can keep near-default values.
On lower timeframes, reduce `Sigma` if you want more detailed local structure.
### 3.2. CCI / RSI Settings
* `CCI Period` — CCI length (short by default for faster reaction).
* `Enable RSI Filter` / `RSI Period` — toggle and length for RSI filter.
* RSI levels are fixed at **20 / 80** to mark strong oversold/overbought zones.
**Usage:**
* For more conservative entries — keep the RSI filter enabled.
* For more frequent signals (e.g. scalping) — you can disable the RSI filter.
### 3.3. Order Blocks
* `Show Order Blocks` — display order block zones.
* `Block Threshold (ATR multiplier)` — how large a candle must be (vs ATR) to be considered significant.
### 3.4. Signals & Filters
* `Show Buy / Show Buy X / Show Close / Show CloseV` — choose which labels you want to see.
* `Enable Time Filter` — enable minimum spacing between amplified signals.
* `Min Bars Between Signals` — how many bars must pass between two Buy X or two CloseV signals.
**Tip:**
If you see too many amplified signals, increase `Min Bars Between Signals`.
If you want more activity, decrease it.
### 3.5. Alerts
* `Buy Alerts / Buy X Alerts / Close Alerts / CloseV Alerts` — choose which signal types should trigger alerts.
* `One Alert Per Bar` — when enabled, alerts are triggered only once per bar (recommended for H1–H4).
Alerts are generated via `alert()`, with messages that include signal type, ticker, timeframe and current price.
---
## 4. How to trade with White Crow
### 4.1. Recommended timeframes
* 📌 **Main focus: 1H–4H.**
On these timeframes:
* pivots and trend are more stable;
* CCI/RSI reflect meaningful swings;
* **Buy X / CloseV clusters** filter out a lot of intrabar noise.
You can still experiment on M1–M15, but expect more signals and more sensitivity to noise.
### 4.2. Reading the signals step by step
1. **Start with context**
* Look at **Market Trend / Last Bottom / Last Top** in the info panel.
* See where price is relative to these points: near resistance, near support, inside a range, etc.
2. **Identify zones of interest**
* Use pivots and order blocks as potential support/resistance areas.
* Wait for price to approach these zones.
3. **Watch the signals**
* **Buy** — early sign of local oversold conditions.
* **Buy X** — amplified cluster signal; more weight than a single Buy.
* **Close** — early warning of potential exhaustion in the current move.
* **CloseV** — amplified cluster exit/reversal signal.
4. **Practical approach**
* In a *Bullish* trend:
* focus on **Buy / Buy X** near bottoms and demand blocks;
* use **Close / CloseV** for partial profit-taking or tightening stops.
* In a *Bearish* trend:
* focus on **Close / CloseV** near tops and supply blocks;
* use **Buy / Buy X** mainly for countertrend scalps with strict risk control.
---
## 5. Important notes and disclaimer
1. **Buy X / CloseV are stronger — but not “magic” signals.**
They are statistically more meaningful than single Buy/Close signals because:
* they require multiple confirmations within a cluster;
* they are time-filtered.
However, **false signals are still possible**, especially in news spikes and low-liquidity conditions.
2. **Best performance on higher timeframes (1H–4H).**
Here, Buy X and CloseV usually reflect genuine shifts in supply/demand rather than micro noise.
3. **This is a confirmation tool, not a complete system.**
Pro Trading White Crow:
* does not manage risk;
* does not define position size or stop-loss;
* does not replace your own analysis.
Always use its signals as **one of several confluence factors** together with structure, trend, price action, volume, and your trading plan.
4. **Educational purpose only.**
This script and description are for educational and analytical purposes only.
They **do not constitute investment advice or a guarantee of profit**.
You are fully responsible for all trading decisions and risk management.
---
---
## White Crow — кластерные сигналы разворота + структура рынка
> Индикатор помогает читать рыночную структуру (пивоты, тренд, последние экстремумы) и находить потенциальные развороты через кластеры сигналов CCI/RSI. Это *не* готовая торговая система и *не* гарантия результата — а инструмент для фильтрации и подтверждения ваших собственных идей по рынку.
---
## 1. Концепция
White Crow объединяет три ключевых блока:
1. **Пивоты и структура рынка**
Автоматически находит **локальные вершины и впадины** и на их основе формирует трендовое смещение: *Bullish / Bearish / Sideways*.
В правом верхнем углу — компактная панель с текущим трендом и ценами **Last Bottom / Last Top**.
2. **Моментум и зоны перегрева**
Внутри используются:
* **CCI** с фиксированными уровнями `+100 / -100`;
* опциональный **фильтр RSI** с уровнями перепроданности/перекупленности (`20 / 80`).
По ним строятся базовые сигналы *Buy / Close*.
3. **Кластерные сигналы Buy X / CloseV**
Скрипт отслеживает **кластеры сигналов внутри окна в 4 бара** и выделяет более редкие, «усиленные» события:
* **Buy X** — кластерный сигнал покупки (несколько buy-условий подряд);
* **CloseV** — кластерный сигнал выхода/разворота.
Именно **Buy X и CloseV являются наиболее сильными и достоверными сигналами индикатора**, так как возникают при повторяющемся выполнении условий, а не на одном баре. Лучше всего они работают **на старших таймфреймах (1–4 часа)**, где отражают реальное смещение баланса спроса/предложения, а не рыночный шум.
> ⚠️ Важно: Buy X и CloseV — *это всего лишь сигналы*. Они должны использоваться **как один из факторов подтверждения** вашего видения структуры рынка (уровни, тренд, price action, объём и т.д.), а не как единственная причина для входа или выхода.
---
## 2. Как это работает
### 2.1. Пивоты и определение тренда
* Индикатор строит **структуру в стиле зигзага**:
после локального максимума, когда цена откатывает вниз на заданный процент (`pivotSigma`), отмечается **Top**;
после локального минимума, когда цена откатывает вверх на тот же процент, отмечается **Bottom**.
* По последовательности последних вершин и впадин определяется тренд:
* *Bullish* — последний минимум выше предыдущего (HL);
* *Bearish* — последний максимум ниже предыдущего (LH);
* иначе — *Sideways*.
* В информационной таблице отображаются:
* **Market Trend** — Bullish / Bearish / Sideways;
* **Last Bottom / Last Top** с адаптивным количеством знаков (подходит под крипту, форекс, акции и т.д.).
### 2.2. Базовые сигналы Buy / Close
* **Условие для Buy (лонг):**
* `CCI < -100` (зона перепроданности),
* при включённом фильтре — `RSI < 20`.
* **Условие для Close (шорт/выход):**
* `CCI > +100` (зона перекупленности),
* при включённом фильтре — `RSI > 80`.
По этим условиям индикатор рисует обычные метки **Buy** и **Close**.
### 2.3. Кластеры: Buy X и CloseV
Чтобы отсеять лишний шум, индикатор оценивает не только текущий бар, но и **4 последних бара**:
* `buy_count` — сколько раз условие на покупку выполнялось за последние 4 бара;
* `sell_count` — сколько раз условие на продажу/выход выполнялось за последние 4 бара.
Далее:
* **Buy X** появляется, когда:
* `buy_count ≥ 2` (минимум на 2 из 4 баров были условия для покупки),
* соблюдён фильтр по времени между усиленными сигналами (`Min Bars Between Signals`).
* **CloseV** появляется, когда:
* `sell_count ≥ 2`,
* прошло достаточно баров с момента предыдущего CloseV.
> ✅ Поэтому **Buy X и CloseV заметно сильнее и надёжнее одиночных Buy/Close**, особенно на **таймфреймах 1–4 часа**: рынок несколько раз подряд подтверждает один и тот же перегрев/разрядку момента.
### 2.4. Order Blocks
* При включённом `Show Order Blocks` индикатор выделяет **импульсные свечи**, чьё тело больше заданного множителя ATR.
* По таким свечам строятся цветные прямоугольники — **потенциальные блоки ордеров** (области поддержек/сопротивлений, где ранее проходил крупный объём).
---
## 3. Настройки и кастомизация
Настройки сгруппированы в привычные разделы TradingView.
### 3.1. Pivot Settings
* `Show Pivots` — включить/выключить метки **Top / Bottom**.
* `Sigma (% retracement)` — чувствительность к пивотам (минимальная глубина отката в процентах).
* Цвета Top/Bottom — визуальная настройка.
**Совет:**
На H1–H4 можно оставить значения близкие к стандартным.
На младших ТФ уменьшайте `Sigma`, если нужна более детальная структура.
### 3.2. CCI / RSI Settings
* `CCI Period` — период CCI (по умолчанию короткий, для более быстрой реакции).
* `Enable RSI Filter` / `RSI Period` — включение и длина RSI-фильтра.
* Уровни RSI фиксированы: **20 / 80**, выделяя сильную перепроданность/перекупленность.
**Использование:**
* Для более консервативной торговли — держите фильтр RSI включённым.
* Для более частых сигналов (скальпинг и т.п.) — можно фильтр отключить.
### 3.3. Order Blocks
* `Show Order Blocks` — отображение блоков ордеров.
* `Block Threshold (ATR multiplier)` — насколько большой должна быть свеча относительно ATR, чтобы считаться значимой.
### 3.4. Signals & Filters
* `Show Buy / Show Buy X / Show Close / Show CloseV` — выбор типов отображаемых меток.
* `Enable Time Filter` — включение минимального интервала между усиленными сигналами.
* `Min Bars Between Signals` — сколько баров должно пройти между двумя Buy X или двумя CloseV.
**Совет:**
Если усиленных сигналов слишком много — увеличьте `Min Bars Between Signals`.
Если хотите больше активности — уменьшите это значение.
### 3.5. Alerts
* `Buy Alerts / Buy X Alerts / Close Alerts / CloseV Alerts` — выбор типов сигналов для алертов.
* `One Alert Per Bar` — при включении алерты отправляются один раз на бар (рекомендуется для H1–H4).
Алерты формируются через `alert()` с сообщением, включающим тип сигнала, тикер, таймфрейм и текущую цену.
---
## 4. Как использовать White Crow в торговле
### 4.1. Рекомендуемые таймфреймы
* 📌 **Основной фокус: 1–4 часа.**
На этих ТФ:
* структура по пивотам и тренд более стабильны;
* CCI/RSI отражают существенные ценовые колебания;
* кластеры **Buy X / CloseV** лучше отсеивают шум.
На M1–M15 индикатор тоже можно применять, но нужно быть готовым к большему количеству сигналов и чувствительности к микродвижениям.
### 4.2. Пошаговое чтение сигналов
1. **Начните с контекста**
* Посмотрите на **Market Trend / Last Bottom / Last Top** в панели.
* Определите, где находитесь относительно этих уровней: у сопротивления, у поддержки, внутри диапазона и т.п.
2. **Найдите зоны интереса**
* Используйте пивоты и order blocks как потенциальные области спроса/предложения.
* Ждите подхода цены к этим зонам.
3. **Отслеживайте сигналы**
* **Buy** — ранний признак локальной перепроданности.
* **Buy X** — усиленный кластерный сигнал, более значимый, чем одиночный Buy.
* **Close** — ранний сигнал возможного ослабления текущего движения.
* **CloseV** — усиленный кластерный сигнал выхода/разворота.
4. **Практическое применение**
* В *бычьем* тренде:
* фокус на **Buy / Buy X** возле впадин и зон спроса;
* **Close / CloseV** использовать для частичной фиксации и подтягивания стопа.
* В *медвежьем* тренде:
* фокус на **Close / CloseV** возле вершин и зон предложения;
* **Buy / Buy X** — для аккуратных контртрендовых входов с жестким риском.
---
## 5. Важные замечания и дисклеймер
1. **Buy X / CloseV сильнее, но не «волшебные» сигналы.**
Они статистически более значимы, чем одиночные Buy/Close, потому что:
* требуют нескольких подтверждений в кластере;
* фильтруются по времени.
Однако **ложные срабатывания всё равно возможны**, особенно на новостях и в условиях низкой ликвидности.
2. **Оптимальная область применения — старшие ТФ (1–4 часа).**
Здесь Buy X и CloseV обычно отражают реальное изменение баланса спроса/предложения, а не шум.
3. **Это инструмент подтверждения, а не полноценная система.**
Pro Trading White Crow:
* не управляет рисками;
* не считает размер позиции и уровень стоп-лосса;
* не заменяет ваше собственное видение рынка.
Всегда используйте его сигналы **как один из факторов согласованности** вместе со структурой, трендом, price action, объёмом и персональным торговым планом.
4. **Образовательный характер.**
Скрипт и описание предназначены для обучения и анализа графиков.
Они **не являются инвестиционной рекомендацией и не гарантируют прибыль**.
Вы самостоятельно принимаете все торговые решения и несёте полную ответственность за риск.
---
SMC Fib Range Signals [@gyanapravah]SMC Fib Range Signals
This indicator blends Smart Money Concepts (SMC) with a Range Filter Trend System and Fibonacci Retracement & Extensions to generate high-probability automated Buy/Sell signals.
Designed to avoid noise and focus on market structure + trend + price confluence, this tool is ideal for:
1. Intraday traders
2. Swing traders
3. Index & stock traders
4. Crypto & Forex traders
CORE FEATURES
Range Filter Trend Detection
Smooth adaptive filter identifies true trend direction
Visual confirmation:
🟢 Green filter = bullish pressure
🔴 Red filter = bearish pressure
🟡 Yellow filter = neutral
Upper & Lower Bands act as dynamic support/resistance zones
Smart Money Order Blocks (SMC)
Automatically detects important pivot highs & lows
Marks:
OB High → supply / resistance zone
OB Low → demand / support zone
Continuously tracks latest OB levels for live price interaction
Fibonacci Engine
Detects the current swing zone and plots:
Retracement levels
0.236 – 0.382 – 0.500 – 0.618 – 0.786 (editable)
Extension targets
1.272 – 1.618
All levels update dynamically on new market structure and pivots.
SIGNAL ENGINE
This indicator generates signals from three independent confirmation systems:
BUY SIGNALS trigger when:
1. Trend flips bullish (price crosses above the Filter)
2.Bullish trend + price reacts near:
Order Block support
Fibonacci 0.382 / 0.618 levels
Bounce from the Lower Band with trend support
All setups require volume confirmation to filter fake breakouts.
SELL SIGNALS trigger when:
1. Trend flips bearish (price crosses below the Filter)
2. Bearish trend + price reacts near:
Order Block resistance
Fibonacci 0.382 / 0.618 levels
Rejection from the Upper Band with trend support
ALERTS READY
Two built-in alerts:
BUY Alert — fires on bullish signal
SELL Alert — fires on bearish signal
INPUT SETTINGS
Trend Engine
1.Source
2.Sampling Period
3.Range Multiplier
Smart Money
Pivot detection sensitivity (Left / Right bars)
Fibonacci
1.Swing lookback length
2.Editable Fib retracement and extension values
3.Toggle show/hide Fib levels
BEST USE CASE
Works extremely well on:
⏱️ 3M – 15M Intraday scalping
⏱️ 30M – 1H positional entries
⏱️ 4H – D1 swing trading
Tested on:
NIFTY / BANKNIFTY / FINNIFTY
Stocks
Crypto
Forex
DISCLAIMER
This indicator is for educational purposes only.
It does NOT guarantee profits.
Always use:
Proper risk management
Stop-loss rules
Your own confirmation before entering trades.
AUTHOR
Built & shared by @gyanapravah (Odisha, India)
Open-source for learning and community improvement.
All Macro LevelsA comprehensive overlay indicator that displays key macro-level support and resistance zones using widely-followed moving averages across multiple timeframes.
Features
Bull Market Support Band (BMSB)
- Weekly 20 SMA and 21 EMA with customizable fill
- A popular indicator for identifying bull market trends - price holding above the band typically signals strength
Daily 12/21/25 EMA Bands
- Three daily EMAs (12, 21, 25) with fill between the outer bands
- Useful for tracking short-term momentum and trend direction
Long-Term Weekly Moving Averages
- 100-Week MA - Intermediate cycle support
- 200-Week MA - Major cycle support level
- 300-Week MA - Deep value zone
- Each MA can be configured as SMA or EMA
Customization
- Toggle each indicator group on/off independently
- Full color customization for lines, fills, and labels
- Adjustable line widths
- Optional custom symbol input to display levels from a different asset
- Real-time labels showing current values at chart edge
Use Cases
- Identify macro support/resistance levels
- Spot potential buy zones during corrections
- Confirm bull/bear market conditions
- Multi-timeframe analysis on a single chart
⚔️ The Scalpel⚔️ THE SCALPEL v2.0
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Surgical-Grade Market Structure Detection System
🔬 WHAT IS THE SCALPEL?
The Scalpel is a precision-engineered market structure analyzer that identifies and tracks critical support and resistance zones with surgical accuracy. Unlike conventional S&R tools that flood your chart with noise, The Scalpel cuts through the clutter to reveal only the most significant price structures.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ CORE TECHNOLOGY
▸ Pivot-Based Detection Engine
Advanced pivot analysis calibrated by user-defined precision settings
▸ Tissue Integrity Validation
Filters structures based on candle body-to-range ratios
▸ Dynamic Stress Analysis
Tracks zone interactions and removes exhausted levels automatically
▸ Volatility-Adaptive Zones
Zone width scales with ATR for consistent performance across all markets
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎨 VISUAL SPECTRUM
💜 STERILE ZONES (Electric Violet)
Fresh, untested structures with maximum potential
🔴 COMPRESSION ZONES (Magenta Fire)
Tested resistance ceilings under selling pressure
🩵 FOUNDATION ZONES (Neon Teal)
Tested support floors with proven buyer interest
✨ PLASMA AURA EFFECT
Multi-layered glow effect for enhanced visibility
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📐 PARAMETERS
🔪 Blade Precision (1-10)
Higher = fewer but sharper pivots detected
🩺 Tissue Integrity % (30-90)
Minimum candle body percentage required
📏 Incision Depth (0.1-2.0 ATR)
Controls zone thickness based on volatility
💉 Stress Threshold (1-10)
Maximum touches before zone invalidation
📐 Projection Range (10-200)
How far zones extend into the future
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💡 HOW TO USE
1. Fresh sterile zones (violet) are your highest-probability setups
2. Watch for price reaction at zone boundaries
3. Tested zones confirm structure but may have diminished strength
4. Zones auto-remove after stress threshold is reached
5. Use projection range to anticipate future tests
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 BEST FOR
✓ Scalping & Day Trading
✓ Swing Trade Entries
✓ Stop Loss Placement
✓ Take Profit Targeting
✓ Multi-Timeframe Analysis
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ DISCLAIMER
This indicator is for educational purposes only. Always conduct your own analysis and use proper risk management. Past performance does not guarantee future results.
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🏷️ TAGS
support resistance zones SNR pivot points market structure scalping day trading swing trading price action order blocks smart money supply demand technical analysis
Pivot Hourly x EMA RibbonHourly Fibonacci Pivot + EMA is an intraday analysis tool that combines hourly Fibonacci-based pivot levels with exponential moving averages (EMAs). It is designed to help traders visualize potential intraday support/resistance zones and short-term trend direction on any timeframe.
The indicator calculates pivot levels from hourly price data and then projects Fibonacci extensions and retracements around a central pivot. These levels can be used to see where price has previously reacted and where future reactions may occur. The EMAs provide an additional layer of context by highlighting the prevailing short-term trend and momentum.
Key features:
Hourly Fibonacci pivot levels (support and resistance zones derived from hourly ranges)
Multiple Fibonacci bands to show potential reaction areas above and below the central pivot
One or more configurable EMAs to show short-term trend direction and dynamic support/resistance
Works on all symbols and intraday timeframes supported by TradingView
Typical use:
Monitor how price behaves when approaching or rejecting Fibonacci pivot levels
Look for confluence between pivot zones and EMA direction or EMA bounces
Use the levels as potential areas of interest for trade planning, stop placement, or partial profit zones within your own trading system
Also have "C" Label it's mean Candle for example C1 is First Candle of the source timeframe, if the source timeframe set to 4 Hour it will be the first 4h candle, the C2 is the second 4h candle of the day.
This script is intended purely as a technical analysis tool and does not generate buy/sell signals or guarantee any particular outcome. It is not financial advice. Always combine it with your own analysis, risk management, and trading plan before making any trading decisions.
Linear Trajectory & Volume StructureThe Linear Trajectory & Volume Structure indicator is a comprehensive trend-following system designed to identify market direction, volatility-adjusted channels, and high-probability entry points. Unlike standard Moving Averages, this tool utilizes Linear Regression logic to calculate the "best fit" trajectory of price, encased within volatility bands (ATR) to filter out market noise.
It integrates three core analytical components into a single interface:
Trend Engine: A Linear Regression Curve to determine the mean trajectory.
Volume Verification: Filters signals to ensure price movement is backed by market participation.
Market Structure: Identifies previous high-volume supply and demand zones for support and resistance analysis.
2. Core Components and Logic
The Trajectory Engine
The backbone of the system is a Linear Regression calculation. This statistical method fits a straight line through recent price data points to determine the current slope and direction.
The Baseline: Represents the "fair value" or mean trajectory of the asset.
The Cloud: Calculated using Average True Range (ATR). It expands during high volatility and contracts during consolidation.
Trend Definition:
Bullish: Price breaks above the Upper Deviation Band.
Bearish: Price breaks below the Lower Deviation Band.
Neutral/Chop: Price remains inside the cloud.
Smart Volume Filter
The indicator includes a toggleable volume filter. When enabled, the script calculates a Simple Moving Average (SMA) of the volume.
High Volume: Current volume is greater than the Volume SMA.
Signal Validation: Reversal signals and structure zones are only generated if High Volume is present, reducing the likelihood of trading false breakouts on low liquidity.
Volume Structure (Smart Liquidity)
The script automatically plots Support (Demand) and Resistance (Supply) boxes based on pivot points.
Creation: A box is drawn only if a pivot high or low is formed with High Volume (if the volume filter is active).
Mitigation: The boxes extend to the right. If price breaks through a zone, the box turns gray to indicate the level has been breached.
3. Signal Guide
Trend Reversals (Buy/Sell Labels)
These are the primary signals indicating a potential change in the macro trend.
BUY Signal: Appears when price closes above the upper volatility band after previously being in a downtrend.
SELL Signal: Appears when price closes below the lower volatility band after previously being in an uptrend.
Pullbacks (Small Circles)
These are continuation signals, useful for adding to positions or entering an existing trend.
Long Pullback: The trend is Bullish, but price dips momentarily below the baseline (into the "discount" area) and closes back above it.
Short Pullback: The trend is Bearish, but price rallies momentarily above the baseline (into the "premium" area) and closes back below it.
4. Configuration and Settings
Trend Engine Settings
Trajectory Length: The lookback period for the Linear Regression. This is the most critical setting for tuning sensitivity.
Channel Multiplier: Controls the width of the cloud.
1.0: Aggressive. Results in narrower bands and earlier signals, but more false positives.
1.5: Balanced (Default).
2.0+: Conservative. Creates a wide channel, filtering out significant noise but delaying entry signals.
Signal Logic
Show Trend Reversals: Toggles the main Buy/Sell labels.
Show Pullbacks: Toggles the re-entry circle signals.
Smart Volume Filter: If checked, signals require above-average volume. Unchecking this yields more signals but removes the volume confirmation requirement.
Volume Structure
Show Smart Liquidity: Toggles the Support/Resistance boxes.
Structure Lookback: Defines how many bars constitute a pivot. Higher numbers identify only major market structures.
Max Active Zones: Limits the number of boxes on the chart to prevent clutter.
5. Timeframe Optimization Guide
To maximize the effectiveness of the Linear Trajectory, you must adjust the Trajectory Length input based on your trading style and timeframe.
Scalping (1-Minute to 5-Minute Charts)
Recommended Length: 20 to 30
Multiplier: 1.2 to 1.5
Logic: Fast-moving markets require a shorter lookback to react quickly to micro-trend changes.
Day Trading (15-Minute to 1-Hour Charts)
Recommended Length: 55 (Default)
Multiplier: 1.5
Logic: A balance between responsiveness and noise filtering. The default setting of 55 is standard for identifying intraday sessions.
Swing Trading (4-Hour to Daily Charts)
Recommended Length: 89 to 100
Multiplier: 1.8 to 2.0
Logic: Swing trading requires filtering out intraday noise. A longer length ensures you stay in the trade during minor retracements.
6. Dashboard (HUD) Interpretation
The Head-Up Display (HUD) provides a summary of the current market state without needing to analyze the chart visually.
Bias: Displays the current trend direction (BULLISH or BEARISH).
Momentum:
ACCELERATING: Price is moving away from the baseline (strong trend).
WEAKENING: Price is compressing toward the baseline (potential consolidation or reversal).
Volume: Indicates if the current candle's volume is HIGH or LOW relative to the average.
Disclaimer
*Trading cryptocurrencies, stocks, forex, and other financial instruments involves a high level of risk and may not be suitable for all investors. This indicator is a technical analysis tool provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profit. Past performance of any trading system or methodology is not necessarily indicative of future results.
Advanced ICC Multi-Timeframe 1.0Advanced ICC Multi-Timeframe Trading System
A comprehensive implementation and interpretation of the Indication, Correction, Continuation (ICC) trading methodology made popular by Trades by Sci, enhanced with advanced multi-timeframe analysis and automation features.
⚠️ CRITICAL TRADING WARNINGS:
DO NOT blindly follow BUY/SELL signals from this indicator
This indicator shows potential entry points but YOU must validate each trade
PAPER TRADE EXTENSIVELY before risking real capital
BACKTEST THOROUGHLY on your chosen instruments and timeframes
The ICC methodology requires understanding and discretion - automated signals are guidance only
This tool aids analysis but does not replace proper trade planning, risk management, or trader judgment
⚠️ Important Disclaimers:
This indicator is not endorsed by or affiliated with Trades by Sci
This is an early implementation and interpretation of the ICC methodology
May not work exactly as Trades by Sci executes his trades and entries
Requires further debugging, backtesting, and real-world validation
Completely free to use - no purchase required
I'm just one person obsessed with this method and wanted some better visualization of the chart/entries
About ICC:
The ICC method identifies complete market cycles through three phases: Indication (breakout), Correction (pullback), and Continuation (entry). This indicator automates the identification of these phases and adds powerful features for modern traders.
Key Features:
Multi-Timeframe Capabilities:
Automatic timeframe detection with optimized settings for 5m, 15m, 30m, 1H, 4H, and Daily charts
Higher timeframe overlay to view HTF ICC levels on lower timeframe charts for precise entry timing
Smart defaults that adjust swing length and consolidation detection based on your timeframe
Advanced Phase Tracking:
Complete ICC cycle tracking: Indication, Correction, Consolidation, Continuation, and No Setup phases
Live structure detection shows potential peaks/troughs before full confirmation
Intelligent invalidation logic detects failed setups when market structure reverses
Dynamic phase backgrounds for instant visual confirmation
Three Types of Entry Signals:
Traditional Entries - Price crosses back through the original indication level (strongest signals)
"BUY" (green) / "SELL" (red)
Breakout Entries - Price breaks out of consolidation range in the same direction
"BUY" (green) / "SELL" (red)
Reversal Entries (Optional, can be toggled off) - Price breaks consolidation in opposite direction, indicating failed setup
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
More aggressive, counter-trend signals
Can be disabled for more conservative trading
Professional Features:
Volatility-based support/resistance zones (ATR-adjusted) that adapt to market conditions
Historical zone tracking (0-3 configurable) with visual hierarchy
Comprehensive real-time info table displaying all key metrics
Full alert system for entries, indications, and consolidation detection
Visual distinction between high-confidence trend entries and cautionary reversal entries
📖 USAGE GUIDE
Entry Signal Types:
The indicator provides three types of entry signals with visual distinction:
Strong Entries (High Confidence):
"BUY" (bright green) / "SELL" (bright red)
Includes traditional entries (crossing back through indication level) and breakout entries (breaking consolidation in trend direction)
These are trend continuation or breakout signals with higher probability
Recommended for all traders
Reversal Entries (Caution - Counter-Trend):
"⚠ BUY" (yellow) / "⚠ SELL" (orange)
Triggered when price breaks out of correction/consolidation in the OPPOSITE direction
Indicates a failed setup and potential trend reversal
More aggressive, counter-trend plays
Can be toggled off in settings for more conservative trading
Recommended only for experienced traders or after thorough backtesting
Swing Length Settings:
The swing length determines how many bars on each side are needed to confirm a swing high/low. This is the most important setting for tuning the indicator to your style.
Auto Mode (Recommended for beginners): Toggle "Use Auto Timeframe Settings" ON
5-minute: 30 bars
15-minute: 20 bars
30-minute: 12 bars
1-hour: 7 bars
4-hour: 5 bars
Daily: 3 bars
Manual Mode: Toggle "Use Auto Timeframe Settings" OFF
Lower values (3-7): More aggressive, detects smaller swings
Pros: More signals, faster entries, catches smaller moves
Cons: More noise, more false signals, requires tighter stops
Best for: Scalping, active day trading, volatile markets
Higher values (12-20): More conservative, only major swings
Pros: More reliable signals, fewer false breakouts, clearer structure
Cons: Fewer signals, delayed entries, might miss smaller opportunities
Best for: Swing trading, position trading, trending markets
Default Manual Setting: 7 bars (balanced for 1H charts)
Minimum: 3 bars
Consolidation Bars Setting:
Determines how many bars without new structure are needed before flagging consolidation.
Lower values (3-10): Faster detection, catches brief pauses, more sensitive
Best for: Lower timeframes, volatile markets, avoiding any chop
Higher values (20-40): More reliable, only flags true extended consolidation
Best for: Higher timeframes, trending markets, patient traders
Current defaults scale with timeframe (more bars needed on shorter timeframes)
Historical S/R Zones:
Shows previous support and resistance levels to provide context.
Default: 2 historical zones (shows current + 2 previous)
Range: 0-3 zones
Visual Hierarchy: Older zones are more transparent with dashed borders
Usage: Higher numbers (2-3) show more historical context but can clutter the chart. Start with 2 and adjust based on your preference.
Live Structure Feature (Yellow Warning ⚠):
Provides early warning of potential structure changes before full confirmation.
What it does: Detects potential swing highs/lows after just 2 bars instead of waiting for full swing_length confirmation
Live Peak: Shows when a high is followed by 2 lower closes (potential top forming)
Live Trough: Shows when a low is followed by 2 higher closes (potential bottom forming)
Important: These are UNCONFIRMED - they may be invalidated if price reverses
Use case: Get early awareness of potential reversals while waiting for confirmation
Displayed in: Info table only (no visual markers on chart to reduce clutter)
Only shows: Peaks higher than last swing high, or troughs lower than last swing low (filters out noise)
Higher Timeframe (HTF) Analysis:
View higher timeframe ICC structure while trading on lower timeframes.
How to enable: Toggle "Show Higher Timeframe ICC" ON
Setup: Set "Higher Timeframe" to your reference timeframe
Example: Trading on 15-minute? Set HTF to 240 (4-hour) or 60 (1-hour)
Example: Trading on 5-minute? Set HTF to 60 (1-hour) or 15 (15-minute)
What it shows:
HTF indication levels displayed as dashed lines
Blue = HTF Bullish Indication
Purple = HTF Bearish Indication
HTF phase and levels shown in info table
Trading workflow:
Check HTF phase for overall market direction
Wait for HTF correction phase
Drop to lower timeframe to find precise entries
Enter when lower TF shows continuation in alignment with HTF
Best practice: HTF should be 3-4x your trading timeframe for best results
Reversal Entries Toggle:
Default: ON (shows all signal types)
Toggle OFF for more conservative trading (only trend continuation signals)
Recommended: Backtest with both settings to see which works better for your style
New traders should consider disabling reversal entries initially
Volatility-Based Zones:
When enabled, support/resistance zones automatically adjust their height based on ATR (Average True Range).
More volatile = wider zones
Less volatile = tighter zones
Toggle OFF for fixed-width zones
Community Feedback Welcome:
This is an evolving project and your input is valuable! Please share:
Bug reports and issues you encounter
Feature requests and suggestions for improvement
Results from your backtesting and live trading experience
Feedback on the reversal entry feature (too aggressive? working well?)
Ideas for better aligning with the ICC methodology
Perfect for traders learning or implementing the ICC methodology with the benefit of modern automation, multi-timeframe analysis, and flexible entry signal options.
Institutional Moving Averages (50/100/200)A streamlined Moving Average suite designed for institutional-style trend analysis. This indicator plots the three most critical trend baselines used by traders and funds:
50 MA (Blue): Short-term trend and momentum.
100 MA (Orange): Medium-term support/resistance.
200 MA (Purple): Long-term trend definition (Bull/Bear line).
Features:
Fully Customizable: Switch between SMA, EMA, WMA, RMA, or HMA.
Clean Visuals: Optimized colors for dark and light themes.
Native Performance: Uses standard TradingView plotting for maximum speed and compatibility with the "Style" tab visibility settings.
Equal Highs/Lows Multi-Pivot [Julio]Equal Highs/Lows Multi-Pivot
Description
A sophisticated multi-timeframe pivot analysis tool that detects and highlights equal highs and equal lows across four different pivot lengths simultaneously. This indicator identifies price levels where the market creates identical extremes, a powerful signal of institutional support/resistance and potential reversal or breakout zones.
How It Works
Four Independent Pivot Streams
Pivot 1 (Intraday - 2 bars): Ultra-fast level detection for scalpers
Pivot 2 (Session - 4 bars): Short-term swing levels
Pivot 3 (Daily - 6 bars): Medium-term structural levels
Pivot 4 (Weekly - 9 bars): Long-term institutional levels
Equal High (EQH) Detection
Compares consecutive swing highs and draws a line when two highs are nearly identical within a defined threshold. The indicator uses ATR-based confluence to determine "equality," filtering out noise while catching true market structure.
Equal Low (EQL) Detection
Same logic applied to swing lows, identifying support zones where price repeatedly fails to break below previous lows.
Key Features
Four Simultaneous Timeframes: Analyze intraday, session, daily, and weekly structures all on one chart
ATR-Based Confluence Threshold: Automatically adjusts sensitivity based on current volatility (no fake signals)
Color-Coded Levels: Each pivot length has distinct colors for instant visual identification
Highs: Red, Orange, Yellow, Fuchsia
Lows: Green, Blue, Aqua, Purple
Confirmation Mode: Optional setting to wait for full pivot confirmation before marking levels
Customizable Alert Zones: Toggle individual pivot lengths on/off to reduce clutter
Smart Label Positioning: Labels auto-center between the two equal pivots for clarity
Ideal For
Swing traders tracking support/resistance across multiple timeframes
Scalpers identifying micro-structure for quick entries and exits
Market structure analysts studying institutional price action patterns
Multi-timeframe traders needing confluence from intraday to weekly levels
Anyone trading 1-minute to 4-hour charts
Trading Applications
Identify strong support/resistance zones: Equal levels = confirmed institutional levels
Confirm trend reversals: Multiple equal lows = strong accumulation zone; multiple equal highs = distribution
Plan entries with precision: Enter near equal levels for higher probability setups
Detect liquidity concentration: Where price repeatedly tests the same level
Multi-timeframe confluence: Look for equal levels across multiple pivot lengths for ultra-strong zones
How to Use
Identify the equal levels: Color-coded lines instantly show where price creates matching extremes
Check for confluence: Strong setups occur where multiple pivot lengths align
Wait for price action: Watch for breakouts through equal levels or reversals at these zones
Enter with structure: Use equal levels as entry/exit triggers combined with your trading methodology
Manage with confidence: These levels mark institutional decision points
Customization Options
Adjust pivot lengths to match your preferred timeframe structure
Set ATR threshold sensitivity (lower = stricter equality, higher = more signals)
Toggle confirmation mode for additional filter
Enable/disable individual pivot streams to reduce visual clutter
Customize colors to match your chart theme
Default Settings Optimized For
NASDAQ futures and liquid forex pairs
Intraday and swing trading (1-minute to 4-hour charts)
Smart Money / ICT trading methodologies
Volatility-adjusted confluence detection
Asia & London Session Boxes (NY Time) + 4H SwingsAsia & London Session Boxes + 4H Swings
Description
A multi-timeframe session analysis tool designed for forex and futures traders operating on NY time. This indicator visualizes major trading sessions with automatic high/low range boxes while simultaneously tracking 4-hour swing levels, giving you a complete picture of institutional trading activity and key price levels.
How It Works
Session Boxes (NY Time Zone)
Asia Session (20:00 – 00:00 NY): Blue-shaded box marking the complete range from open to close
London Session (02:00 – 06:00 NY): Yellow-shaded box capturing the high-volatility London open
Each session box automatically records the highest high and lowest low during that timeframe, providing instant reference for session extremes and potential supply/demand zones.
4-Hour Swing Levels
Detects swing highs and lows on a 30-minute timeframe for ultra-responsive level identification
Red lines: Swing highs (resistance levels)
Green lines: Swing lows (support levels)
Lines extend to the right for continuous monitoring
Auto-removes touched levels: When price breaches a swing, it automatically deletes that level to keep your chart clean and focused on active levels
Key Features
Session-Based Trading Analysis: Identify which session created important price levels and ranges
Multi-Timeframe Architecture: Analyzes 30-minute swings while tracking 4-hour patterns on your current chart
Smart Level Cleanup: Touched swings automatically remove themselves, eliminating clutter
NY Time Conversion: All times automatically adjust to your NY timezone for consistency
Institutional Perspective: View exactly where institutions are trading during major session hours
Zero Lag Detection: Real-time identification of swing extremes
Ideal For
Forex traders (especially EUR/USD, GBP/USD) targeting session breakouts
Scalpers and swing traders needing precise support/resistance levels
Market structure traders analyzing institutional price action
Session traders looking to trade Asia/London opens
1-minute to 4-hour timeframe charts
Trading Applications
Trade Asia session breakouts into London
Identify liquidity zones from previous sessions
Detect swing extremes for entry/exit planning
Confirm trend direction using multi-session structure
Find support/resistance on intraday pullbacks
Default Settings Optimized For
NASDAQ futures and forex pairs
Scalping and short-term swing trading
NY timezone trading (automatically converts UTC-4)
30-minute swing detection for precise level identification
Simulateur Carnet d'Ordres & Liquidité [Sese] - Custom🔹 Indicator Name
Order Book & Liquidity Simulator - Custom
🔹 Concept and Functionality
This indicator is a technical analysis tool designed to visually simulate market depth (Order Book) and potential liquidity zones.
It is important to adhere to TradingView's transparency rules: This script does not access real Level 2 data (the actual exchange order book). Instead, it uses a deductive algorithm based on historical Price Action to estimate where Buy Limit (Bid) and Sell Limit (Ask) orders might be resting.
Methodology used by the script:
Pivot Detection: The indicator scans for significant Swing Highs and Swing Lows over a user-defined lookback period (Length).
Level Projection: These pivots are projected to the right as horizontal lines.
Red Lines (Ask): Represent potential resistance zones (sellers).
Blue Lines (Bid): Represent potential support zones (buyers).
Liquidity Management (Absorption): The script is dynamic. If the current price crosses a line, the indicator assumes the liquidity at that level has been consumed (orders filled). The line is then automatically deleted from the chart.
Density Profile (Right Side): Horizontal bars appear to the right of the current price. These approximate a "Time Price Opportunity" or Volume Profile, showing where the market has spent the most time recently.
🔹 User Manual (Settings)
Here is how to configure the inputs to match your trading style:
1. Detection Algorithm
Lookback Length (Candles): Determines the sensitivity of the pivots.
Low value (e.g., 10): Shows many lines (scalping/short term).
High value (e.g., 50): Shows only major structural levels (swing trading).
Volume Factor: (Technical note: In this specific code version, this variable is calculated but the lines are primarily drawn based on geometric pivots).
2. Visual Settings
Show Price Lines (Bid/Ask): Toggles the horizontal Support/Resistance lines on or off.
Show Volume Profile: Toggles the heatmap-style bars on the right side of the chart.
Extend Lines: If checked, untouched lines will extend to the right towards the current price bar.
3. Colors and Transparency Management
Customize the aesthetics to keep your chart clean:
Bid / Ask Colors: Choose your base colors (Default is Blue and Red).
Line Transparency (%): Crucial for chart visibility.
0% = Solid, bright colors.
80-90% = Very subtle, faint lines (recommended if you overlay this on other tools).
Text Size: Adjusts the size of the price labels ("BUY LIMIT" / "SELL LIMIT").
🔹 How to Read the Indicator
Rejections: Unbroken lines act as potential walls. Watch for price reaction when approaching a blue line (support) or red line (resistance).
Breakouts/Absorption: When a line disappears, it means the level has been breached. The market may then seek the next liquidity level (the next line).
Density (Right-side boxes): More opaque/visible boxes indicate a price zone "accepted" by the market (consolidation). Empty gaps suggest an imbalance where price might move through quickly.
⚠️ Disclaimer
This script is for educational and technical analysis purposes only. It is a simulation based on price history, not real-time order book data. Past performance is not indicative of future results. Trading involves risk.
DANCE WITH WOLVES VN ALL TO 1DANCE WITH WOLVES VN is a smart-money volume indicator designed for stocks and crypto.
Main features:
• logic to detect Distribution, No Demand, Absorption and Exhaustion.
• Automatically builds smart Support/Resistance zones from high-volume price leaders.
• Regression trend channel to see the short-term trend and trading range.
• Dashboard table that shows the top high/low price bars with buy/sell volume and group labels.
• Alert conditions for Breakout above resistance and At Support Area so you don’t need to watch the chart all the time.
You can use it on any symbol and timeframe. Just add the script to your chart and follow the zones (red = resistance, green = support) together with the P/L labels and the status line.
Vietnamese note: Indicator dùng volume + để vẽ vùng hỗ trợ/kháng cự thông minh, label phân phối / hấp thụ / cạn lực bán và kênh xu hướng. Dùng được cho cả stock và crypto. tot nhat dung khung 5 den 15 phut
Symmetrical Geometric MandalaSymmetrical Geometric Mandala
Overview
The Symmetrical Geometric Mandala is an advanced geometric trading tool that applies phi (φ) harmonic relationships to price-time analysis. This indicator automatically detects swing ranges and constructs a scale-invariant geometric framework based on the square root of phi (√φ), revealing natural support/resistance zones and harmonic price-time balance points.
Core Concept
Traditional technical analysis often treats price and time as separate dimensions. This indicator harmonizes them using the mathematical constant √φ (approximately 1.272), creating a geometric "squaring" of price and time that remains proportionally consistent across different chart scales.
The Mathematics
When you select a price range (from swing low to swing high or vice versa), the indicator calculates:
PBR (Price-to-Bar Ratio) = Range / Number of Bars
Harmonic PBR = PBR × √φ (1.272019649514069)
Phi Extension = Range × φ (1.618033988749895)
The Harmonic PBR is the critical value - this is the chart scaling factor that creates perfect geometric harmony between price and time for your selected range.
Visual Components
1. Horizontal Boundary Lines
Two horizontal lines extend from the selected range at a distance of Range × φ (golden ratio extension):
Upper line: Extended above the swing high (for uplegs) or swing low (for downlegs)
Lower line: Extended below the swing low (for uplegs) or swing high (for downlegs)
These lines mark the natural harmonic boundaries of the price movement.
2. Rectangle Diagonal Lines
Two diagonal lines that create a "rectangle" effect, connecting:
Overlap points on horizontal boundaries to swing extremes
These lines go in the opposite direction of the price leg (creating the symmetrical mandala pattern)
When extended, they reveal future geometric support/resistance zones
3. Phi Harmonic Circles (Optional)
Two precisely calculated circles (drawn as smooth polylines):
Circle A: Centered at the first swing extreme (Nodal A)
Circle B: Centered at the second swing extreme (Nodal B)
Radius = Range × φ, causing them to perfectly touch the horizontal boundary lines
These circles visualize the geometric harmony and create a mandala-like pattern that reveals natural price zones.
How to Use
Step 1: Select Your Range
Set the Start Date at your swing low or swing high
Set the End Date at the opposite extreme
The indicator automatically detects whether it's an upleg or downleg
Step 2: Read the Harmonic PBR
Check the highlighted yellow row in the table: "PBR × √φ"
This is your chart scaling value
Step 3: Apply Chart Scaling (Optional)
For perfect geometric visualization:
Right-click on your chart's price axis
Select "Scale price chart only"
Enter the PBR × √φ value
The geometry will now display in perfect harmonic proportion
Step 4: Interpret the Geometry
Horizontal lines: Key support/resistance zones at phi extensions
Diagonal lines: Dynamic trend channels and future price-time balance points
Circle intersections: Natural harmonic turning points
Central diamond area: Core price-time equilibrium zone
Key Features
✅ Automatic swing detection - identifies upleg/downleg automatically
✅ Scale-invariant geometry - maintains proportions across timeframes
✅ Phi harmonic calculations - based on golden ratio mathematics
✅ Professional color scheme - clean, non-intrusive visuals
✅ Customizable display - toggle circles, lines, and table independently
✅ Smooth circle rendering - adjustable segments (16-360) for optimal smoothness
Settings
Show Horizontal Boundary Lines: Display phi extension levels
Show Rectangle Diagonal Lines: Display the geometric framework
Show Phi Harmonic Circles: Display circular geometry (optional)
Circle Smoothness: Adjust polyline segments (default: 96)
Colors: Fully customizable color scheme for all elements
Theory Background
This indicator draws inspiration from:
W.D. Gann's price-time squaring techniques
Bradley Cowan's geometric market analysis
Phi/golden ratio harmonic theory
Mathematical constants in market structure
Unlike traditional Fibonacci retracements, this tool uses √φ instead of φ as the primary scaling constant, creating a unique geometric relationship that "squares" price movement with time passage.
Best Practices
Use on significant swings - Works best on major swing highs/lows
Multiple timeframe analysis - Apply to different timeframes for confluence
Combine with other tools - Use alongside support/resistance and trend analysis
Respect the geometry - Pay attention when price interacts with geometric elements
Chart scaling optional - The geometry works at any scale, but scaling enhances visualization
Notes
The indicator draws geometry from left to right (from Nodal A to Nodal B)
All lines extend infinitely for future projections
The table shows real-time calculations for the selected range
Date range selection uses confirm dialogs to prevent accidental changes
The Trade Plan 9 & 15 EMA⭐ What Are EMAs?
An Exponential Moving Average (EMA) gives more weight to recent prices, making it more responsive than a simple moving average.
9-EMA = very fast, reacts quickly to price changes
15-EMA = slightly slower, smooths short-term noise
Together they help identify momentum shifts.
📈 How the 9/15 EMA Strategy Works
1. Buy Signal (Bullish Crossover)
You enter a long (buy) trade when:
➡ 9 EMA crosses above the 15 EMA
This suggests momentum is shifting upward and a new uptrend may be forming.
2. Sell Signal (Bearish Crossover)
You enter a short (sell) trade or exit long positions when:
➡ 9 EMA crosses below the 15 EMA
This suggests momentum is turning downward.
🔧 How Traders Typically Use It
Entry
Wait for a clear crossover.
Confirm with price closing on the same side of EMAs.
Some traders add confirmation using RSI, MACD, or support/resistance.
Exit
Several options:
Exit when the opposite crossover occurs.
Exit at predetermined risk-reward levels (e.g., 1:2).
Use trailing stop below/above EMAs.
👍 Strengths
Easy to follow
Good for fast-moving markets
Works well on trending markets
Minimal indicators needed
👎 Weaknesses
Whipsaws in sideways markets
Many false signals on very low timeframes
Works best with additional filters
🕒 Common Timeframes
Scalping: 1m, 5m
Day trading: 5m, 15m
Swing trading: 1H, 4H
SuperTrend Zone Rejection [STRZ] CONCEPT -
This indicator identifies trend-continuation setups by combining the Super Trend with dynamic Average True Range (ATR) value zones. It highlights specific price action behaviour's—specifically wick rejections and momentum closes—that occur during pullbacks into the trend baseline.
HOW IT WORKS -
The script operates on three logic gates:
>> Trend Filter: Uses a standard Super Trend (Factor 3, Period 10 default) to define market direction.
>> Dynamic Zones: Projects a volatility-based zone (default 2.0x ATR) above or below the Super Trend line to define a valid pullback area.
>> Signal Detection: Identifies specific candle geometries occurring within these zones.
>> Rejection: Candles with significant wicks testing the zone support/resistance.
>> Momentum: Candles that open within the zone and close in the upper/lower quartile of their range.
FEATURES -
>> Dynamic Channel: Visualizes the active buy/sell zone using a continuous, non-repainting box.
>> Volatile Filtering: Filters out low-volatility candles (doji's/noise) based on minimum ATR size.
>> Visuals: Color-coded trend visualization with distinct signal markers for qualified entries.
SETTINGS -
>> Super Trend: Adjustable Factor and ATR Period.
>> Zone Multiplier: Controls the width of the pullback zone relative to ATR.
>> Visuals: Customizable colours for zones and signals to fit light/dark themes.
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.
Pivot Reversal Signals - Multi ConfirmationPivot Reversal Signals - Multi-Confirmation System
Overview
A comprehensive reversal detection indicator designed for daytraders that combines six independent technical signals to identify high-probability pivot points. The indicator uses a scoring system to classify signal strength as Weak, Medium, or Strong based on the number of confirmations present.
How It Works
The indicator monitors six key reversal signals simultaneously:
1. RSI Divergence - Detects when price makes new highs/lows but RSI shows weakening momentum
2. MACD Divergence - Identifies divergence between price action and MACD histogram
3. Key Level Touch - Confirms price is at significant support/resistance (previous day high/low, premarket high/low, VWAP, 50 SMA)
4. Reversal Candlestick Patterns - Recognizes bullish/bearish engulfing, hammers, and shooting stars
5. Moving Average Confluence - Validates bounces/rejections at stacked moving averages (9/20/50)
6. Volume Spike - Confirms increased participation (default: 1.5x average volume)
Signal Strength Classification
• Weak (3/6 confirmations) - Small circles for situational awareness only
• Medium (4/6 confirmations) - Regular triangles, viable entry signals
• Strong (5-6/6 confirmations) - Large triangles with background highlight, highest probability setups
Visual Features
• Entry Signals: Green triangles (up) for long entries, red triangles (down) for short entries
• Exit Warnings: Orange X markers when opposing signals appear
• Signal Labels: Show confirmation score (e.g., "5/6") and strength level
• Key Levels Displayed:
o Previous Day High/Low - Solid green/red lines (uses actual daily data)
o Premarket High/Low - Blue/orange circles (4:00 AM - 9:30 AM EST)
o VWAP - Purple line
o Moving Averages - 9 EMA (blue), 20 EMA (orange), 50 SMA (red)
• Background Tinting: Subtle color on strongest reversal zones
Key Level Detection
The indicator uses request.security() to accurately fetch previous day's high/low from daily timeframe data, ensuring precise level placement. Premarket high/low levels are dynamically tracked during premarket sessions (4:00 AM - 9:30 AM EST) and plotted throughout the trading day, providing critical support/resistance zones that often influence price action during regular hours.
Customizable Parameters
• Signal strength thresholds (adjust required confirmations)
• RSI settings (length, overbought/oversold levels)
• MACD parameters (fast/slow/signal lengths)
• Moving average periods
• Volume spike multiplier
• Toggle individual display elements (levels, MAs, labels)
Best Practices
• Use on 5-minute charts for entries, confirm on 15-minute for direction
• Focus on Medium and Strong signals; Weak signals provide context only
• Strong signals (5-6 confirmations) have the highest win rate
• Pay special attention to reversals at premarket high/low - these levels frequently hold
• Previous day high/low often acts as major support/resistance
• Always use proper risk management and stop losses
• Works best in moderately trending markets
Alert Capabilities
Set custom alerts for:
• Strong long/short signals
• All entry signals (medium + strong)
• Exit warnings for open positions
Ideal For
• Daytraders and scalpers (especially SPY, QQQ, and liquid equities)
• Swing traders seeking precise entries
• Traders who prefer confirmation-based systems
• Anyone looking to reduce false signals with multi-factor validation
• Traders who utilize premarket levels in their strategy
Technical Notes
• Uses Pine Script v6
• Premarket hours: 4:00 AM - 9:30 AM EST
• Previous day levels pulled from daily timeframe for accuracy
• Maximum 500 labels to maintain chart performance
• All key levels update dynamically in real-time
________________________________________
Note: This indicator provides signal analysis only and should be used as part of a complete trading strategy. Past performance does not guarantee future results. Always practice proper risk management.
Orderbook Table1. Indicator Name
Orderbook Table
This is an order book style trading volume map
that upgraded the price from my first script to label
2. One-line Introduction
A visual heatmap-style orderbook simulator that displays volume and delta clustering across price levels.
3. Overall Description
Orderbook Table is a powerful visual tool designed to replicate an on-chart approximation of a traditional order book.
It scans historical candles within a specified lookback window and accumulates traded volume into price "bins" or levels.
Each level is color-coded based on total volume and directional bias (delta), offering a layered view of where market interest was concentrated.
The indicator approximates order flow by analyzing each candle's directional volume, separating bullish and bearish volume.
With adjustable parameters such as level depth, price bin density, delta sensitivity, and opacity, it provides a highly customizable visualization.
Displayed directly on the chart, each level shows the volume at that price zone, along with a price label, offset to the right of the current bar.
Traders can use this tool to detect high liquidity zones, support/resistance clusters, and volume imbalances that may precede future price movements.
4. Key Benefits (Title + Description)
✅ On-Chart Volume Heatmap
Shows volume distribution across price levels in real-time directly on the price chart, creating a live “orderbook” view.
✅ Delta-Based Bias Coloring
Color changes based on net buying/selling pressure (delta), making aggressive demand/supply zones easy to spot.
✅ High Customizability
Users can adjust lookback bars, price bins, opacity levels, and delta usage to fit any market condition or asset class.
✅ Lightweight Simulation
Approximates orderbook depth using candle data without needing L2 feed access—works on all assets and timeframes.
✅ Clear Visual Anchoring
Volume quantities and price levels are offset to the right for easy viewing without cluttering the active chart area.
✅ Fast Market Context Recognition
Quickly identify price levels where volume concentrated historically, improving decision-making for entries/exits.
5. Indicator User Guide
📌 Basic Concept
Orderbook Table analyzes a configurable number of past bars and distributes traded volume into price "bins."
Each bin shows how much volume occurred around that price level, optionally adjusted for bullish/bearish candle direction.
⚙️ Settings Overview
Lookback Bars: Number of candles to scan for volume history
Levels (Total): Number of price levels to display around the current price
Price Bins: Granularity of price segmentation for volume distribution
Shift Right: How far to offset labels to the right of the current bar
Max/Min Opacity: Controls visual strength of volume coloring
Use Candle Delta Approx.: If enabled, colors the volume based on candle direction (green for up, red for down)
📈 Example Timing
Look for green clusters (bullish bias) below current price → possible strong demand zones
Price enters a high-volume level with previously aggressive buyers (green), suggesting support
📉 Example Timing
Red clusters (bearish bias) above current price can act as resistance or supply zones
Price stalling at a red-heavy volume band may indicate exhaustion or reversal opportunity
🧪 Recommended Use
Use as a support/resistance mapping tool in ranging and trending markets
Pair with candlestick analysis or momentum indicators for refined entry/exit points
Combine with VWAP or volume profile for multi-dimensional volume insight
🔒 Cautions
This is an approximation, not a true L2 orderbook—volume is based on historical candles, not actual limit order data
In low-volume markets or higher timeframes, bin granularity may be too coarse—adjust "Price Bins" accordingly
Delta calculation is based on open-close direction and does not reflect true buy/sell volume splits
Avoid overinterpreting low-opacity (light color) zones—they may indicate low interest rather than true resistance/support
+++
CVD [able0.1]# CVD Overlay iOS Style - Complete User Guide
## 📖 Table of Contents
1. (#what-is-cvd)
2. (#installation-guide)
3. (#understanding-the-display)
4. (#reading-the-info-table)
5. (#settings--customization)
6. (#trading-strategies)
7. (#common-mistakes-to-avoid)
---
## 🎯 What is CVD?
**CVD (Cumulative Volume Delta)** tracks the **difference between buying and selling pressure** over time.
### Simple Explanation:
- **Positive CVD** (Orange) = More buying than selling = Bulls winning
- **Negative CVD** (Gray) = More selling than buying = Bears winning
- **Rising CVD** = Increasing buying pressure = Potential uptrend
- **Falling CVD** = Increasing selling pressure = Potential downtrend
### Why It Matters:
CVD helps you see **who's really in control** of the market - not just price movement, but actual buying/selling volume.
---
## 🚀 Installation Guide
### Step 1: Open Pine Editor
1. Go to TradingView
2. Click the **"Pine Editor"** tab at the bottom of the screen
3. Click **"New"** or open an existing script
### Step 2: Copy & Paste the Code
1. Select all existing code (Ctrl+A / Cmd+A)
2. Delete it
3. Copy the entire CVD iOS Style code
4. Paste it into Pine Editor
### Step 3: Add to Chart
1. Click **"Save"** button (or Ctrl+S / Cmd+S)
2. Click **"Add to Chart"** button
3. The indicator will appear on your chart!
### Step 4: Initial Setup
- The indicator appears as an **overlay** on your price chart
- You'll see an **orange/gray line** following price
- An **info table** appears in the top-right corner
---
## 📊 Understanding the Display
### Main Chart Elements:
#### 1. **CVD Line** (Orange/Gray)
- **Orange Line** = Positive CVD (buying pressure)
- **Gray Line** = Negative CVD (selling pressure)
- This line moves with your price chart but shows volume delta
#### 2. **CVD Zone** (Shaded Area)
- Light shaded box around the CVD line
- Shows the "range" of CVD movement
- Helps visualize CVD boundaries
#### 3. **Center Line** (Dotted)
- Gray dotted line in the middle of the zone
- Represents the "neutral" point
- CVD crossing this = shift in market control
#### 4. **Reference Asset Line** (Light Gray)
- Shows Bitcoin (BTC) price movement for comparison
- Helps you see if your asset moves with or against BTC
- Can be changed to any asset you want
#### 5. **CVD Label**
- Shows current CVD value
- Positioned above/below zone to avoid overlap
- Updates in real-time
#### 6. **Reset Background** (Very Light Gray)
- Appears when CVD resets
- Indicates a new calculation period
---
## 📋 Reading the Info Table
The info table (top-right) shows **8 key metrics**:
### Row 1: **Header**
```
╔═ CVD able ═╗ | 15m | ████████ | able
```
- **CVD able** = Indicator name + creator
- **15m** = Current timeframe
- **████████** = Visual decoration
- **able** = Creator signature
### Row 2: **CVD Value**
```
CVD▲ | 7.39K | ████████ | █
█
█
```
- **CVD▲** = CVD with trend arrow
- ▲ = CVD increasing
- ▼ = CVD decreasing
- ► = CVD unchanged
- **7.39K** = Actual CVD number
- **Progress Bar** = Visual strength (darker = stronger)
- **Vertical Bars** = Height shows intensity
### Row 3: **Delta**
```
◆DELTA | -1.274K | ████░░░░ | ░
░
```
- **Delta** = Volume change THIS BAR ONLY
- **Negative** = More selling this bar
- **Positive** = More buying this bar
- Shows **immediate** pressure (not cumulative)
### Row 4: **UP Volume**
```
UP↑ | -1.263K | ████████ | █
█
█
```
- Total **buying volume** this bar
- Higher = Stronger buying pressure
- Green/Orange vertical bars = Bullish strength
### Row 5: **DOWN Volume**
```
DN↓ | 2.643K | ████████ | ░
░
░
```
- Total **selling volume** this bar
- Higher = Stronger selling pressure
- Gray vertical bars = Bearish strength
### Row 6-7: **Reference Asset** (if enabled)
```
══ REF ══ | ══════ | ████████ | █
█
PRICE▲ | 4130.300 | ████████ | █
█
```
- **REF** = Reference asset header
- **PRICE▲** = Reference price with trend
- Shows if BTC (or chosen asset) is rising/falling
- Compare with your chart to see correlation
### Row 8: **Market Status**
```
◄STATUS► | NEUT | ████░░░░ | ▒
▒
```
- **BULL** = CVD positive + Delta positive = Strong buying
- **BEAR** = CVD negative + Delta negative = Strong selling
- **NEUT** = Mixed signals = Wait for clarity
**Status Colors:**
- **Orange background** = Bullish (good for long)
- **Gray background** = Bearish (good for short)
- **White background** = Neutral (no clear signal)
---
## ⚙️ Settings & Customization
### Main Settings (⚙️)
#### **CVD Reset**
- **None** = CVD never resets (from beginning of data)
- **On Higher Timeframe** = Resets when HTF candle closes
- 15m chart → Resets hourly
- 1h chart → Resets daily
- Recommended for most traders
- **On Session Start** = Resets at market open
- **On Visible Chart** = Resets from leftmost visible bar
#### **Precision**
- **Low (Fast)** = Uses 1m data, faster but less accurate
- **Medium** = Uses 5m data, balanced (recommended)
- **High** = Uses 15m data, most accurate but slower
#### **Cumulative**
- ✅ On = CVD accumulates over time (recommended)
- ❌ Off = Shows only current bar delta
#### **Show Labels**
- ✅ On = Shows CVD value label on chart
- ❌ Off = Cleaner chart, no label
#### **Show Info Table**
- ✅ On = Shows info table (recommended for beginners)
- ❌ Off = Hide table for minimalist view
---
### 🎨 iOS Style Colors
You can customize **every color** to match your chart theme:
#### **Primary Colors**
- **Primary (Orange)** = Main bullish color (#FF9500)
- **Secondary (Gray)** = Main bearish color (#8E8E93)
- **Background** = Table background (#FFFFFF)
- **Text** = Text color (#1C1C1E)
#### **Bullish/Bearish**
- **Bullish (Orange)** = Positive CVD color
- **Bearish (Gray)** = Negative CVD color
- **Opacity** = Zone transparency (0-100%)
- **Show Zone** = Enable/disable shaded area
#### **Table Colors** (📋)
- **Header Background** = Top row background
- **Header Text** = Top row text color
- **Cell Background** = Data cells background
- **Cell Text** = Data cells text color
- **Border** = Table border color
- **Accent Background** = Special rows background
- **Alert Background** = Warning/status background
---
### 📊 Reference Asset Settings
#### **Enable**
- ✅ On = Shows reference asset line
- ❌ Off = Hide reference asset
#### **Symbol**
- Default: `BINANCE:BTCUSDT`
- Can change to any asset:
- `BINANCE:ETHUSDT` (Ethereum)
- `SPX` (S&P 500)
- `DXY` (US Dollar Index)
- Any ticker symbol
#### **Color & Width**
- Customize line appearance
- Width: 1-4 (thickness)
---
## 💡 Trading Strategies
### Strategy 1: CVD Divergence (Beginner-Friendly)
**What to Look For:**
- Price making **higher highs** but CVD making **lower highs** = Bearish divergence
- Price making **lower lows** but CVD making **higher lows** = Bullish divergence
**How to Trade:**
1. Wait for divergence to form
2. Look for confirmation (price reversal, candlestick pattern)
3. Enter trade in divergence direction
4. Stop loss beyond recent high/low
**Example:**
```
Price: /\ /\ /\ (higher highs)
CVD: /\ / \/ (lower highs) = Bearish signal
```
### Strategy 2: CVD Trend Following (Intermediate)
**What to Look For:**
- **Strongly rising CVD** + **rising price** = Strong uptrend
- **Strongly falling CVD** + **falling price** = Strong downtrend
**How to Trade:**
1. Wait for CVD and price moving in same direction
2. Enter on pullbacks to support/resistance
3. Stay in trade while CVD trend continues
4. Exit when CVD trend breaks
**Signals:**
- CVD ▲▲▲ + Price ↑ = Go LONG
- CVD ▼▼▼ + Price ↓ = Go SHORT
### Strategy 3: CVD + Reference Asset (Advanced)
**What to Look For:**
- Your asset **rising** but BTC (reference) **falling** = Relative strength
- Your asset **falling** but BTC (reference) **rising** = Relative weakness
**How to Trade:**
1. Compare CVD movement with BTC
2. If your CVD rises faster than BTC = Buy signal
3. If your CVD falls faster than BTC = Sell signal
4. Use for **pair trading** or **asset selection**
### Strategy 4: Volume Delta Confirmation
**What to Look For:**
- **Large positive Delta** = Strong buying this bar
- **Large negative Delta** = Strong selling this bar
**How to Trade:**
1. Price breaks resistance + Large positive Delta = Confirmed breakout
2. Price breaks support + Large negative Delta = Confirmed breakdown
3. Use Delta to **confirm** price moves, not predict them
**Rules:**
- Delta > 2x average = Very strong pressure
- Delta near zero at key level = Weak move, likely false breakout
---
## 🎓 Reading Real Scenarios
### Scenario 1: Strong Buying Pressure
```
Table Shows:
CVD▲ | 12.5K | ████████ | ████ (CVD rising)
◆DELTA | +2.8K | ████████ | ▲ (Positive delta)
UP↑ | 3.1K | ████████ | ████ (High buy volume)
DN↓ | 0.3K | ██░░░░░░ | ░ (Low sell volume)
◄STATUS► | BULL | ████████ | ████ (Orange background)
```
**Interpretation:** Strong buying, good for LONG trades
### Scenario 2: Distribution (Hidden Selling)
```
Table Shows:
CVD► | 8.2K | ████░░░░ | ▒▒ (CVD flat)
◆DELTA | -1.5K | ████████ | ▼ (Negative delta)
UP↑ | 0.8K | ███░░░░░ | ░ (Low buy volume)
DN↓ | 2.3K | ████████ | ████ (High sell volume)
◄STATUS► | BEAR | ████████ | ░░░░ (Gray background)
```
**Interpretation:** Price may look stable, but selling increasing = Prepare for drop
### Scenario 3: Neutral/Choppy Market
```
Table Shows:
CVD► | 5.1K | ████░░░░ | ▒ (CVD sideways)
◆DELTA | +0.2K | ██░░░░░░ | ─ (Small delta)
UP↑ | 1.2K | ████░░░░ | ▒ (Medium buy)
DN↓ | 1.0K | ████░░░░ | ▒ (Medium sell)
◄STATUS► | NEUT | ████░░░░ | ▒▒ (White background)
```
**Interpretation:** No clear direction = Stay out or reduce position size
---
## ⚠️ Common Mistakes to Avoid
### Mistake 1: Trading on CVD Alone
- ❌ **Wrong:** "CVD is rising, I'll buy immediately"
- ✅ **Right:** "CVD is rising, let me check price structure, support/resistance, and wait for confirmation"
### Mistake 2: Ignoring Delta
- ❌ **Wrong:** Looking only at cumulative CVD
- ✅ **Right:** Watch both CVD (trend) and Delta (momentum)
- Delta shows **immediate** pressure changes
### Mistake 3: Wrong Timeframe
- ❌ **Wrong:** Using 1m chart with High Precision (too slow)
- ✅ **Right:** Match precision to timeframe:
- 1m-5m → Low Precision
- 15m-1h → Medium Precision
- 4h+ → High Precision
### Mistake 4: Not Using Reset
- ❌ **Wrong:** Using "None" reset for intraday trading
- ✅ **Right:** Use "On Higher Timeframe" to see fresh CVD each session
### Mistake 5: Overtrading Neutral Status
- ❌ **Wrong:** Forcing trades when STATUS = NEUT
- ✅ **Right:** Only trade clear BULL or BEAR status
### Mistake 6: Ignoring Reference Asset
- ❌ **Wrong:** Trading altcoin without checking BTC
- ✅ **Right:** Always check if BTC CVD agrees with your asset
---
## 🔥 Pro Tips
### Tip 1: Multi-Timeframe Analysis
- Check CVD on **3 timeframes**:
- Lower TF (15m) = Entry timing
- Current TF (1h) = Trade direction
- Higher TF (4h) = Overall trend
### Tip 2: Volume Confirmation
- Big price move + Small Delta = **Weak move** (likely reversal)
- Small price move + Big Delta = **Strong accumulation** (continuation)
### Tip 3: CVD Reset Zones
- Pay attention to **reset backgrounds** (light gray)
- Often marks **session starts** = High volatility periods
### Tip 4: Divergence + Status
- Bearish divergence + STATUS = BEAR = **Strongest short signal**
- Bullish divergence + STATUS = BULL = **Strongest long signal**
### Tip 5: Color Psychology
- **Orange** (Bullish) is **warm** = Buying energy
- **Gray** (Bearish) is **cool** = Selling pressure
- Train your eye to read colors instantly
### Tip 6: Table as Quick Scan
- Glance at table without reading numbers:
- **All orange** = Bullish
- **All gray** = Bearish
- **Mixed** = Wait
---
## 📱 Quick Reference Card
| Signal | CVD | Delta | Status | Action |
|--------|-----|-------|--------|--------|
| **Strong Buy** | ▲▲ High | ++ Positive | BULL | Long Entry |
| **Strong Sell** | ▼▼ Low | -- Negative | BEAR | Short Entry |
| **Divergence Buy** | ▲ Rising | Price ▼ | → BULL | Long Setup |
| **Divergence Sell** | ▼ Falling | Price ▲ | → BEAR | Short Setup |
| **Neutral** | → Flat | ~0 Near Zero | NEUT | Stay Out |
| **Accumulation** | → Flat | ++ Positive | NEUT→BULL | Watch for Breakout |
| **Distribution** | → Flat | -- Negative | NEUT→BEAR | Watch for Breakdown |
---
## 🆘 Troubleshooting
### Issue: "Indicator not showing"
- **Solution:** Make sure overlay=true in code, re-add to chart
### Issue: "Table overlaps with price"
- **Solution:** Change table position in code or use TradingView's "Move" feature
### Issue: "CVD line too far from price"
- **Solution:** This is normal! CVD is volume-based, not price-based. Focus on CVD direction, not position
### Issue: "Too many lines on chart"
- **Solution:** Disable "Show Zone" and "Show Labels" in settings for cleaner view
### Issue: "Calculations too slow"
- **Solution:** Change Precision to "Low (Fast)" or use higher timeframe
### Issue: "Reference asset not showing"
- **Solution:** Check if "Enable" is ON and symbol is valid (e.g., BINANCE:BTCUSDT)
---
## 🎬 Getting Started Checklist
- Install indicator on TradingView
- Set precision to "Medium"
- Set reset to "On Higher Timeframe"
- Enable info table
- Add reference asset (BTC)
- Practice reading the table on demo account
- Test on different timeframes (15m, 1h, 4h)
- Compare CVD with your current strategy
- Paper trade for 1 week before going live
- Keep a trading journal of CVD signals
---
## 📚 Summary
**CVD shows WHO is winning: Buyers or Sellers**
**Key Points:**
1. **Orange/Rising CVD** = Buying pressure = Bullish
2. **Gray/Falling CVD** = Selling pressure = Bearish
3. **Delta** = Immediate momentum THIS BAR
4. **Status** = Overall market condition
5. **Always confirm** with price action & other indicators
**Remember:**
- CVD is a **tool**, not a crystal ball
- Use with proper risk management
- Practice makes perfect
- Stay disciplined!
---
**Created by: able**
**Version:** iOS Style v1.0
**Contact:** For questions, refer to TradingView community
Happy Trading! 🚀📈
Pso VP 2.0This indicator provides an advanced volume analysis tool that visualizes trading activity across different price levels and automatically identifies key support and resistance zones.
How It Works:
The Volume Profile analyzes historical price and volume data within a specified lookback period, distributing volume across horizontal price levels. Unlike traditional volume indicators that show volume over time, this tool displays volume at price, revealing where the most significant trading activity has occurred.
The algorithm:
Divides the price range into customizable horizontal bars (bins)
Calculates and accumulates volume for each price level
Identifies high-volume nodes that often act as support or resistance levels
Uses percentile filtering to highlight the most significant trading areas
Key Features:
Automatic S/R Detection: Uses volume percentile filtering to identify the most significant price levels
Dynamic Support/Resistance Lines: Automatically draws horizontal black lines at high-volume areas that typically act as price magnets or barriers
Customizable Parameters: Full control over lookback period, number of price bars, percentile thresholds, profile width, opacity, and line projections
Clean Aesthetic: Monochrome design for professional chart presentation
