Valuation MetricValuation Metric Indicator
The Valuation Metric Indicator provides a comprehensive tool for evaluating price dynamics in relation to a moving average and standard deviation. It combines the power of statistical analysis with clear visualizations to help traders assess market valuation levels and potential overbought or oversold conditions.
Key Features:
Z-Score Calculation:
Displays the Z-score of the price relative to the moving average, normalized by standard deviation.
Z-score is clamped within the range of -3 to +3 to focus on significant deviations.
Standard Deviation Bands:
Plots bands at 1x, 2x, and 3x standard deviations above and below the moving average.
Helps identify areas of extreme overvaluation or undervaluation.
Dynamic Valuation Table:
Displays the current Z-score and provides a textual assessment of the market's valuation:
Overvalued
Slightly Overvalued
Neutral
Slightly Undervalued
Undervalued
Background color dynamically changes based on the valuation.
Customizable Background Signals:
Optional background highlighting for "Top Signal" (overvaluation) and "Bottom Signal" (undervaluation).
Configurable Display:
Users can toggle the visibility of standard deviation bands and background signals to fit their preferences.
Color-Coded Visualization:
Uses gradient-based color coding for Z-scores and standard deviation bands, improving readability and decision-making.
Cerca negli script per "bands"
Momentum BBPCT Z-Score [QuantAlgo]Momentum BBPCT Z-Score 💫📈
The Momentum BBPCT Z-Score by QuantAlgo is an advanced indicator designed to identify statistical extremes and momentum shifts in price action across various timeframes and market conditions. This system combines Bollinger Bands percentage analysis with Z-score calculations and Statistical Momentum evaluation to help traders and investors identify overbought/oversold conditions and trend strength. By evaluating both statistical extremes and momentum together, this tool empowers users to make data-driven decisions, whether they aim to follow trends or capture mean reversion opportunities.
💫 Conceptual Foundation and Innovation
The Momentum BBPCT Z-Score by QuantAlgo provides a unique framework for assessing price action and momentum through a blend of statistical analysis and momentum evaluation. Unlike traditional Bollinger Band indicators that only reflect price position, this system incorporates Z-score normalization to reveal statistically significant deviations, helping users determine whether price movements are extreme relative to historical norms. By combining high-quality momentum analysis with Z-scores of Bollinger Band positioning, it evaluates both statistical probabilities and momentum quality, while Z-scores standardize deviations from historical trends, enabling traders and investors to spot extreme conditions. This dual approach allows users to better identify mean reversion opportunities while respecting strong momentum conditions, enhancing both counter-trend and trend-following strategies.
📊 Technical Composition and Calculation
The Momentum BBPCT Z-Score is composed of several statistical and momentum components that create a dynamic dual scoring model:
Bollinger Bands Percentage (BBPCT) : Measures the relative position of price between bands on a 0-100 scale, providing a normalized view of price extremes relative to the bands.
Z-Score Normalization : Applies statistical normalization to BBPCT values to identify significant deviations from historical means, helping traders and investors quantify the extremity of current market conditions.
Statistical Momentum Analysis : Evaluates price action across multiple periods to determine momentum strength and persistence, adding depth to the analysis beyond simple price positioning.
📈 Key Indicators and Features
The Momentum BBPCT Z-Score combines various statistical and technical tools to deliver a well-rounded analysis of market conditions.
The indicator utilizes dynamic Bollinger Bands with customizable length and standard deviation multipliers to adapt to market volatility. Z-score calculations are applied to normalize the percentage position within these bands, providing clear statistical context for price movements. The Statistical Momentum component evaluates price action across user-defined periods, helping validate trends and identify potential reversals.
The indicator also incorporates multi-layered visualization with gradient color coding to signal both statistical extremes and momentum conditions. These adaptive visual cues, combined with threshold-based alerts for overbought and oversold zones, help traders and investors track both statistical extremes and momentum shifts, adding reliability to both mean-reversion and trend-following strategies.
⚡️ Practical Applications and Examples
✅ Add the Indicator: Add the indicator to your TradingView chart by clicking on the star icon to add it to your favorites ⭐️
👀 Monitor Z-Scores and Momentum: Watch the Z-score values and momentum state to identify statistically significant price movements. During extreme readings, consider mean reversion opportunities, while strong momentum readings may signal trend-following opportunities.
🔔 Set Alerts: Configure alerts for Z-score extremes and momentum shifts, ensuring you can act on significant statistical and trend changes promptly.
🌟 Summary
The Momentum BBPCT Z-Score by QuantAlgo is a highly adaptable tool, designed to support both statistical and momentum analysis across different market environments. By combining Z-score normalized Bollinger Band positioning with Statistical Momentum Analysis, it helps traders and investors identify statistically significant price movements while measuring momentum quality, providing more reliable trading signals. The tool's flexibility across timeframes makes it ideal for both mean reversion and trend-following strategies, allowing users to capture opportunities while maintaining statistical rigor in their analysis.
Magic Linear Regression Channel [MW]Introduction
The Magic Linear Regression Channel indicator provides users with a way to quickly include a linear regression channel ANYWHERE on their chart, in order to find channel breakouts and bounces within any time period. It uses a novel method that allows users to adjust the start and end period of the regression channel in order to quickly make adjustments faster, with fewer steps, and with more precision than with any other linear regression channel tool. It includes Fibonacci bands AND a horizontal mode in order for users to quickly define significant price levels based on the high, low, open, and close prices defined by the start period.
Settings
Start Time: This is initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
End time: This is also initially MANUALLY SELECTED ON THE CHART when the indicator is first loaded.
Horizontal Line: This forces the baseline to be horizontal. The band distance is defined by the maximum price distance from the band.
Horizontal Line Type: This snaps the horizontal line to the close, high, low, or open price. Or, it can also use a regression calculation for the selected time period to define the y-position of the line.
Extend Line N Bars: How many bars to the left in which to extend the baseline and bands.
Show Baseline ONLY!!: Removes all lines except the baseline and it’s extension.
Add Half Band: Includes a band that is half the distance between the baseline and the top and bottom bands
Add Outer Fibonacci Band: Includes a band that is 1.618 (phi) times the default band distance
Add Inner Fibonacci Band - Upper: Includes a band that is 0.618 (1/phi) times the default band distance
Add Inner Fibonacci Band - Lower: Includes a band that is 0.382 (1 - 1/phi) times the default band distance
Calculations
This indicator uses the least squares approach for generating a straight regression line, which can be reviewed at Wikipedia’s “Simple Linear Regression” page. It sums all of the x-values, and y-values, as well as the sum of the product of corresponding x and y values, and the sum of the squares of the x-values. These values are used to calculate the slope and intercept using the following equations:
slope = (n * sum_xy - sum_x * sum_y) / (n * sum_xx - sum_x * sum_x)
And
intercept = (sum_y - slope * sum_x) / n
The slope and intercept are then used to generate the baseline and the corresponding bands using the user-selected offsets.
How to Use
When the Magic Linear Regression Channel indicator is first added to the chart, there will be a blue prompt behind the “Indicators, Metrics & Strategies” window. Close the window, then select a START POINT by clicking at a desired location on the chart. Next, you will be prompted to select an END POINT. The end point MUST be placed after the START POINT. At this time a channel will be generated. Once you’ve selected the START POINT and END POINT, you can adjust them by dragging them anywhere on the chart. Each adjustment will generate a new channel making it easier for you to quickly visualize and recognize any channel exits and bounces.
The Magic Linear Regression Channel indicator works great at identifying wave patterns. Place the start line at a top or bottom pivot point. Place the end line at the next respective top or bottom pivot. This will give you a complete wave form to work with. When price reaches a band and rejects, it can be a strong indication that price may move back to one of the bands in the channel. If price exits the channel with volume that supports the exit, it may be an indication of a breakout.
You can also use the horizontal mode to identify key levels, then add Fibonacci bands based on regression calculations for the given time period to provide more meaningful areas of support and resistance.
Other Usage Notes and Limitations
Occasionally, off-by-1 errors appear which makes the extended lines protrude at a slightly incorrect angle. This is a known bug and will be addressed in the next release.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
Uptrick: Bullish/Bearish Highlight -DEMO 1 Indicator Purpose:
• The indicator serves as a technical analysis tool for traders to identify potential bullish
and bearish trends in the market.
• It highlights periods where the closing price is above or below a 50-period simple
moving average (SMA), indicating potential bullish or bearish sentiment, respectively.
2 Moving Averages:
• The indicator calculates a 50-period SMA (sma50) to smooth out price fluctuations
and identify the overall trend direction.
• It also computes an 8-period exponential moving average (EMA), which responds
more quickly to recent price changes compared to the SMA.
3 Bollinger Bands:
• Bollinger Bands are plotted around the SMA, indicating volatility in the price
movement.
• The bands are typically set at two standard deviations above and below the SMA,
representing approximately 95% of the price data within that range.
4 Bullish and Bearish Conditions:
• The indicator defines conditions for identifying bullish and bearish market sentiments.
• When the closing price is above the SMA50, it indicates a bullish condition, and when
it's below, it suggests a bearish condition.
5 Plotting:
• The indicator visualizes the bullish and bearish conditions by changing the
background color accordingly.
• It also plots the SMA50, EMA, and Bollinger Bands to provide a graphical
representation of the market dynamics.
6 User Interface:
• The indicator is designed to be used as an overlay on price charts, allowing traders to
easily incorporate it into their analysis.
Overall, the "Uptrick: Bullish/Bearish Highlight" indicator offers traders a comprehensive view of market trends and potential reversal points, helping them make informed trading decisions.
TIP: When the white line, which is the EMA , crosses above the SMA (the orange line), it is usually a good idea to buy, but when the EMA crosses below the SMA it is a good idea to sell.
VOLD Ratio (Volume Difference Ratio) by TenozenAnother helpful indicator is here! VOLD Ratio is calculated by the net volume of a buying candle, divided by the net volume of a sell candle.
Formula:
buying net volume/selling net volume
It's a simple indicator, but don't underestimate this simplicity. It's a powerful indicator that would help you to decide whether the volume is getting interested in the direction that the market would take. So assume when the market is above the Bollinger Bands, it means that the volume is at a buying extreme, by that, we could expect the market to get back towards the mean, as there is a lot of buying demand that entered the market. How about below the Bollinger Bands? it means that the volume is at a selling extreme, we could expect that there is a lot of volume getting in toward the sellers, so we could take advantage of the opportunity to go for a long. Lastly, the Bollinger Bands would help you guys to determine the liquidity of the market, if the Bollinger Bands get smaller over time, it means there is no interest for the market to enter yet, and if the Bollinger Bands get bigger over time, it means there is interest for the market to enter in the session.
Tips & Reminder:
- We shouldn't use this indicator by itself, make sure to use an Indicator that would help you guys to determine the momentum and the liquidity of the market.
- The higher the timeframe, the slower this indicator would signal an entry, by that use a smaller timeframe... I suggest using a 15M chart for the execution.
- Always trade in the medium-longterm direction if you want to have a high probability trade.
- Be patient in your execution, it's more likely the market would go higher or lower after going in the extreme of the Bollinger Bands.
Well, that's it! Hope you guys enjoy using this indicator, let me know if there is any question or suggestion. Ciao...
Keltner Channel Width Oscillator (KingThies)Definition
The Keltner Channel Width oscillator is a technical analysis indicator derived originally from the same relationship the Bollinger Band Width indicator takes on Bollinger Bands.
Similar to the Bollinger Bands, Kelts measure volatility in relation to price, and factor in various range calculations to create three bands around the price of a given stock or digital asset. The Middle Line is typically a 20 Day Exponential Moving Average while the upper and lower bands highlight price at different range variations around its basis. Keltner Channel Width serve as a way to quantitatively measure the width between the Upper and Lower Bands and identify opportunities for entires and exits, based on the relative range price is experiencing that day.
Calculation
Kelt Channel Width = (Upper Band - Lower Band) / Middle Band
More on Keltner Channels
Keltner channel was first described by a Chicago grain trader called Chester W. Keltner in his 1960 book How to Make Money in Commodities. Though Keltner claimed no ownership of the original idea and simply called it the ten-day moving average trading rule, his name was applied by those who heard of this concept through his books.
Similarly to the Bollinger Bands, Keltner channel is a technical analysis tool based on three parallel lines. In fact, the Keltner indicator consists of a central moving average in addition to channel lines spread above and below it. The central line represents a 10-day simple moving average of what Chester W. Keltner called typical price. The typical price is defined as the average of the high, low and close. The distance between the central line and the upper, or lower line, is equivalent to the simple moving average of the preceding 10 days' trading ranges.
One way to interpret the Keltner Channel would be to consider the price breakouts outside of the channel. A trader would track price movement and consider any close above the upper line as a strong buy signal. Equivalently, any close below the lower line would be considered a strong sell signal. The trader would follow the trend emphasized by the indicator while complementing his analysis with the use of other indicators as well. However, the breakout method only works well when the market moves from a range-bound setting to an established trend. In a trend-less configuration, the Keltner Channel is better used as an overbought/oversold indicator. Thus, as the price breaks out below the lower band, a trader waits for the next close inside the Keltner Channel and considers this price behavior as an oversold situation indicating a potential buy signal. Similarly, as the price breaks out above the upper band, the trader waits for the next close inside the Keltner Channel and considers this price action as an overbought situation indicating a potential sell signal. By waiting for the price to close within the Channel, the trader avoids getting caught in a real upside or downside breakout.
MNQ Quant Oscillator Lab v2.1MNQ Quant Oscillator Lab v2.1 — Clean Namespaces
Adaptive LinReg Oscillator + Auto Regime Switching + MTF Confirmation + MOEP Gate + Research Harness
MNQ Quant Oscillator Lab is a research-grade oscillator framework designed for MNQ/NQ (and other liquid futures/indices) on 1-minute and intraday timeframes. It combines a linear-regression-based detrended oscillator with quant-style normalization, adaptive parameterization, regime switching, multi-timeframe confirmation, and an optional MOEP (Minimum Optimal Entry Point) gate. The goal is to provide a customizable signal laboratory that is stable in real time, non-repainting by default, and suitable for systematic experimentation.
What this indicator does
1) Core oscillator (quant-normalized)
The indicator computes a linear regression (LinReg) detrended signal and expresses it as a z-scored oscillator for portability across volatility regimes and assets. You can switch the oscillator “transform family” via Oscillator type:
LinReg Residual / Residual Z: detrended residual (mean-reversion sensitive)
LinReg Slope Z: regression slope (trend-derivative sensitive)
LogReturn Z: log-return oscillator (momentum-style)
VolNorm Return Z: volatility-normalized returns (risk-scaled)
This yields a single oscillator that is comparable over time, not tied to raw point values.
2) Adaptive length (dynamic calibration)
When enabled, the regression length is automatically adapted using a volatility-regime proxy (ATR% z-scored → logistic mapping). High volatility typically shortens the effective lookback; low volatility allows longer lookbacks. This helps the oscillator remain responsive during expansions while staying stable in compressions.
Important: the adaptive logic is implemented with safe warmup behavior, so it will not throw NaN errors on early bars.
3) Adaptive thresholds (dynamic bands)
Instead of static overbought/oversold levels, the indicator can compute dynamic upper/lower bands from the oscillator’s own distribution (rolling mean + sigma). This creates thresholds that adjust automatically to regime changes.
4) Auto regime switching (Trend vs Mean Reversion)
With Auto regime switch enabled, the indicator selects whether to behave as a Trend system or a Mean Reversion system using an interpretable heuristic:
Trend regime when EMA-spread is strong relative to ATR and ATR is rising
Otherwise defaults to Mean Reversion
This prevents running mean-reversion logic in trend breakouts and reduces “mode mismatch.”
5) Multi-timeframe (MTF) confirmation (optional)
MTF confirmation can be enabled to require that the higher timeframe oscillator sign aligns with the direction of the signal. This is useful for reducing noise on MNQ 1m by requiring higher-timeframe structure agreement (e.g., 5m or 15m).
6) MOEP Gate (optional “institutional” filter)
The MOEP gate is a confluence score filter intended to reduce low-quality signals. It aggregates multiple components into a 0–100 score:
BB/KC squeeze condition
Expansion proxy
Trend proxy
Momentum proxy (RSI-based)
Volume catalyst (volume z-score)
Structure break (highest/lowest break)
You can set:
Score threshold (minimum score required)
Minimum components required (forces diversity of evidence)
When enabled, a signal must satisfy both oscillator logic and MOEP confluence conditions.
7) Research harness (NON-CAUSAL, OFF by default)
A built-in research mode evaluates signals using future bars to compute basic forward excursion statistics:
MFE (max favorable excursion)
MAE (max adverse excursion)
Simple win-rate proxy based on MFE vs MAE
This feature is strictly for offline analysis and tuning. It is disabled by default and should not be considered “live-safe” because it uses future information for evaluation.
Signals and interpretation
Mean Reversion regime
Long: oscillator is below the lower band and turns back upward across it
Short: oscillator is above the upper band and turns back downward across it
Trend regime
Long: oscillator crosses above zero (optionally requires structure break confirmation)
Short: oscillator crosses below zero (optionally requires structure break confirmation)
Hybrid
When Hybrid is selected (manual mode), the indicator allows both trend and mean-reversion triggers, but still respects the filters and gates you enable.
Recommended starting configuration (MNQ 1m)
If you want stable, high-quality signals first, then expand into research:
Use RTH only: ON
Auto regime switch: ON
Adaptive length: ON
Adaptive bands: ON
MTF confirmation: OFF initially (turn ON later with 5m)
MOEP Gate: OFF initially (turn ON after you confirm base behavior)
Research harness: OFF (only enable for tuning studies)
Practical notes / transparency
The indicator is designed to be stable on live bars (optional confirmed-bar behavior reduces flicker).
No repainting logic is used for signals.
Any “performance” numbers shown under Research harness are not tradable metrics; they are forward-looking evaluation outputs intended strictly for experimentation.
Disclaimer
This script is provided for educational and research purposes only and does not constitute financial advice. Futures trading involves substantial risk, including the possibility of loss exceeding initial investment.
Exponential Moving Average + ATR MTF [YSFX]Description:
This indicator is a reupload of a previously published EMA + ATR tool, updated and enhanced after a house rule violation to provide additional features and a cleaner, more versatile experience for traders.
It combines trend analysis and volatility measurement into one intuitive tool, allowing traders to visualize market direction, dynamic support and resistance, and adaptive risk levels—all in a clean, minimal interface.
The indicator calculates a customizable moving average (MA) type—EMA, SMA, WMA, HMA, RMA, DEMA, TEMA, VWMA, LSMA, or KAMA—and surrounds it with ATR-based bands that expand and contract with market volatility. This creates a dynamic envelope around price, helping traders identify potential breakouts, pullbacks, or high-probability entry/exit zones.
Advanced Features:
Multiple MA types: Supports all major moving averages, including advanced options like KAMA, DEMA, and TEMA.
KAMA customization: Adjustable fast and slow lengths for precise tuning.
Dual timeframe support: Optionally use separate timeframes for the MA and ATR, or a global timeframe for both.
Dynamic ATR bands: Automatically adjust to market volatility, useful for setting adaptive stop-loss levels.
Optional fill: Shade the area between upper and lower ATR bands for a clear visual representation of volatility.
Flexible for all markets: Works across any timeframe or asset class.
Who It’s For:
This indicator is ideal for trend-following traders, swing traders, and volatility-focused analysts who want to:
Confirm trend direction while accounting for volatility
Identify high-probability trade entries and exits
Implement dynamic, ATR-based stop-loss strategies
Keep charts clean and uncluttered while still capturing key market information
This reuploaded version ensures compliance with platform rules while offering enhanced flexibility and clarity for modern trading workflows.
Adaptive Fear & Greed Index with ML-Enhanced SD - HOSSAM Adaptive Fear and Greed Index with ML-Enhanced Standard Deviation
📊 Overview
A sophisticated market sentiment indicator that combines traditional Fear and Greed Index methodology with machine learning-inspired adaptive algorithms. This tool dynamically adjusts to changing market conditions, providing more accurate sentiment readings and early warning signals.
🔥 Key Features
Adaptive Standard Deviation: Automatically adjusts volatility bands based on market conditions
VWAP Integration: Incorporates volume-weighted average price for better price context
Machine Learning Elements: Self-adjusting parameters that learn from recent market behavior
Multi-Regime Detection: Identifies high/low volatility environments
Dynamic Weighting: Automatically adjusts component weights based on market performance
Z-Score Analysis: Statistical significance measurement for deviations
📈 How It Works
The indicator combines four key market components:
Price Momentum with VWAP deviation
Volume-Weighted Volatility
RSI with Volume Confirmation
Market Structure Analysis
🎯 Interpretation
0-30: Extreme Fear (Potential Buying Opportunity)
30-40: Fear
40-60: Neutral
60-70: Greed
70-100: Extreme Greed (Potential Selling Opportunity)
⚡ Unique Advantages
Self-Adjusting Bands: SD bands expand during high volatility, contract during calm periods
Regime Awareness: Different signals for high/low volatility environments
Volume Validation: All components include volume confirmation
Statistical Significance: Z-scores show how extreme current readings are
🚨 Alert Conditions
Extreme greed/fear in high volatility regimes
Statistical outliers (Z-score > 2.5)
Trend acceleration signals
💡 Ideal For
Crypto traders seeking sentiment-based entries/exits
Swing traders looking for mean reversion opportunities
Risk management and position sizing decisions
Market regime identification
⚙️ Customization
Adjustable parameters include lookback period, SD multiplier, smoothing, and ML learning rate to match your trading style.
Category: Strategy & Sentiment Analysis
Tags: #FearAndGreed #MarketSentiment #Volatility #Cryptocurrency #Trading #Indicator #MachineLearning #VWAP
ORB + Session VWAP Pro (London & NY) — fixedORB + Session VWAP Pro (London & NY) — Listing copy (EN)
What it is
A clean, non-repainting intraday tool that fuses the classic Opening Range Breakout (ORB) with a session-anchored VWAP filter for London and New York. It highlights only the higher-quality breakouts (above/below session VWAP), adds an optional retest confirmation, and scores each signal with an intuitive Confidence metric (0–100).
Why it works
• ORB provides the day’s first actionable structure (range high/low).
• Session VWAP filters “cheap” breaks and favors flows aligned with session value.
• Optional retest reduces first-tick whipsaws.
• Confidence blends breakout depth (vs ATR), VWAP slope and band distance.
Key visuals
• LDN/NY OR High/Low (line break style) + optional OR boxes.
• Active Session VWAP (resets per signal window; falls back to daily VWAP outside).
• Optional VWAP bands (stdev or %).
• Session shading (London/NY windows).
• Signal markers (LDN BUY/SELL, NY BUY/SELL) fired with cooldown.
Signals
• London Long / Short: Break of LDN OR High/Low ± ATR buffer, aligned with VWAP side.
• NY Long / Short: Same logic during NY window.
• Retest (optional): Requires a tag back to the OR level ± tolerance before confirmation.
• Confidence: 0–100; gate via Min Confidence (default 55).
Inputs that matter
• Open Range Length (min): Default 15.
• London/NY times & timezones.
• ATR buffer & retest tolerance.
• Bands mode: Stdev (with lookback) or % (e.g., 1%).
• Signal cooldown: Avoids clutter on fast moves.
Non-repaint policy
• OR lines build within fixed time windows using the current bar’s timestamp.
• VWAP is cumulative within the session window; no lookahead.
• All ta.crossover/ta.crossunder are precomputed every bar (no conditional execution).
• Signals are based on live bar values, not future bars.
⸻
Quick start (examples)
1) EURUSD, London momentum
• Chart: 5m or 15m.
• OR: 15 min starting 08:00 Europe/London.
• Signals: Use defaults; keep ATR buffer = 0.2 and Retest = ON, Min Confidence ≥ 55.
• Play:
• BUY when price breaks LDN OR High + buffer and stays above VWAP; retest confirms.
• Trail behind VWAP or band #1; partials into band #2.
2) NAS100, New York breakout & run
• Chart: 5m.
• NY window: 09:30 America/New_York, OR = 15 min.
• Retest OFF on high momentum days; Min Confidence ≥ 60.
• Use band mode Stdev, bandLen=50, show ±1/±2.
• Momentum continuation: add on pullbacks that hold above VWAP after the breakout.
3) XAUUSD, London fake & VWAP fade
• Chart: 5m.
• Keep Retest ON; accept only shorts that break OR Low but retest fails back under VWAP.
• Confidence gate ≥ 50 to allow more mean-reversion setups.
⸻
Pro tips
• Adjust ATR buffer to the instrument: FX 0.15–0.25, indices 0.20–0.35, metals 0.20–0.30.
• Retest ON for choppy conditions; OFF for news momentum.
• Use VWAP bands: take partials at ±1; stretch targets at ±2/±3.
• Session timezones are explicit (London/New York). Ensure they match your instrument’s behavior.
• Pair with a higher-TF bias (e.g., 1H/4H trend) for directional filtering.
⸻
Alerts (ready to use)
• ORB+SVWAP — LDN Long, LDN Short, NY Long, NY Short
(Respect your cooldown; alerts fire only after confirmation and confidence gate.)
⸻
Known limits & notes
• Designed for intraday. On 1D+ charts, session windows compress.
• If your broker session differs from London/NY clocks on a holiday, adjust input times.
• Session-anchored VWAP uses the script’s signal window, not exchange sessions, by design.
APO Channel // SuperTrend Optimized📌 Complete Long Description (Final Version)
APO Channel – Adaptive Breakout Detection
🔹 How it works
The originality of this script lies in the combination of two complementary approaches:
An adaptive channel, whose responsiveness is based on fractal dimension and volatility.
A breakout & candle confirmation system, providing clear visual trade signals.
Unlike standard channels (e.g., Bollinger Bands), which use a fixed deviation or multiplier, the APO Channel dynamically adjusts its baseline (Filt) and bands (Filt1, Filt2) in real time. This ensures that signals are not only adaptive to market conditions but also reinforced when both indicators align simultaneously, filtering out false moves and highlighting stronger trade opportunities.
🔹 Why this combination matters
By merging an adaptive volatility channel with a breakout confirmation system, the script provides traders with a more reliable view of momentum shifts.
The channel identifies when markets are consolidating versus expanding.
The breakout signals confirm actual momentum surges.
When both conditions trigger together, the likelihood of a meaningful move increases, making signals clearer and more robust than using either tool alone.
🔹 Visual signals
The script offers optional candle coloring and breakout labels:
Bullish signals are shown when price breaks above the adaptive upper band.
Bearish signals appear when price breaks below the adaptive lower band.
For clearer visualization, traders can activate the blue, green, and gray candles by clicking on the channel bands.
👉 This makes simultaneous signals and the prevailing trend much more visible, helping traders quickly spot alignment between the adaptive channel and breakout confirmation.
🔹 Optimized Default Settings
Channel Length: 26
Bands Distance: 1
ATR Period: 1
Source: (High + Low)/2
ATR Multiplier: 2
These parameters have been optimized for balanced responsiveness across assets.
👉 Signals are particularly relevant for scalping entries on the 3-minute timeframe, where quick detection of breakouts provides a trading edge.
The indicator works seamlessly on futures, crypto, forex, stocks, and most other instruments, making it a versatile tool for traders across markets.
🔹 How to use
Use breakouts above the channel as a potential entry signal for bullish momentum trades.
Use breakouts below the channel as a potential entry signal for bearish momentum trades.
When both the breakout signal and candle confirmation occur simultaneously, consider it a stronger trading signal.
Activate candle coloring on the channel bands to make signals and trend more visible.
Combine with other tools (volume, higher timeframe bias) for additional confirmation.
✅ Why this script adds value
Most breakout tools rely on static measures (fixed standard deviation, moving average envelopes, etc.). The APO Channel introduces an adaptive filter based on fractal dimension analysis, while also reinforcing signals through dual confirmation (channel breakouts + candle regime).
This makes it a versatile tool for traders seeking adaptive, visually clear, and reliable breakout detection across multiple markets and timeframes.
DubleB_basic.verTitle:
Final Combo: Bollinger Bands + 5 SMAs + Cross Signals + Dual Pierce + Hammer Alerts
Description:
This indicator combines multiple technical tools into one comprehensive package:
Bollinger Bands:
• BB (Length 4, StdDev 4, source: Open, no midline)
• BB (Length 20, StdDev 2, source: Close, with SMA midline)
Moving Averages (5 lines):
• SMA 5, 20, 60, 120, 240
• Each line has customizable color, style, and visibility toggle
Cross Signals:
• 5/20, 60/120, 60/240, 120/240 crossovers
• Plot markers with customizable style and colors
• Alerts triggered instantly when the cross forms
Dual Bollinger Pierce:
• Signals when a candle pierces both the 4,4 and 20,2 Bollinger Bands simultaneously
• Alerts notify as “Double BB” event
Candlestick Patterns:
• Hammer and Inverted Hammer detection (with relaxed conditions)
• Signals only confirmed at bar close
• Alerts notify as “Hammer detected” or “Inverted Hammer detected”
Alerts:
• All signals (crosses, double BB pierce, hammers) come with built-in alertcondition()
• Alert messages include symbol name and timeframe automatically
How to Use:
Add the indicator to your chart
Configure moving averages, colors, and marker styles as needed
Set alerts directly from the chart using “Add Alert” → select the conditions you want
Ideal for traders who need combined volatility, trend, and candlestick reversal signals in one tool
BTC Evaluation IndicatorBTC Evaluation Indicator
The BTC Evaluation Indicator is a volatility-based tool designed to help traders evaluate Bitcoin’s price behavior relative to its moving average trend. It combines customizable moving averages with dynamic standard deviation bands to identify overbought and oversold conditions.
Key Features
Flexible Moving Averages: Choose between SMA, EMA, WMA, VWMA, HMA, or RMA for the baseline trend.
Dynamic Volatility Bands: Upper and lower bands are calculated using standard deviation, scaled by a user-defined multiplier.
Visual Clarity:
Orange line = central moving average (trend mean)
Green line = upper band (potential overbought zone)
Red line = lower band (potential oversold zone)
Shaded gray area = volatility range
Automatic Highlights: Background shading marks when price breaks above the upper band (overbought) or below the lower band (oversold).
How to Use
When price pushes above the upper band, it may indicate overextension or potential local overbought conditions.
When price falls below the lower band, it may signal undervaluation or potential oversold conditions.
The mean line acts as a dynamic equilibrium, often serving as short-term support/resistance.
This indicator is designed for Bitcoin evaluation, but it can be applied to any asset. By combining trend analysis with volatility context, it helps traders better understand when price may be stretched and when conditions are reverting to the mean.
Bitcoin Cycle Log-Curve (JDK-Analysis)Important: The standard parameters provided in the script are specifically tuned for the TradingView Bitcoin Index chart on a monthly timeframe on logarithmic scale, and will yield the most accurate visual alignment when applied to that dataset. (more below)
This very simple script visualizes Bitcoin’s long-term price behavior using a logarithmic regression model designed to reflect the cyclical nature of Bitcoin’s historical market trends. Unlike typical technical indicators that react to recent price movements, this tool is built on the assumption that Bitcoin follows an exponential growth path over time, shaped by its fixed supply structure and four-year halving cycles.
The calculation behind the curved bands:
An upper boundary, a lower boundary, and a central midline, are calculated based on logarithmic functions applied to the bar index (which serves as a proxy for time). The upper and lower bounds are defined using exponential formulas of the type y = exp(constant + coefficient * log(bar_index)), allowing the curves to evolve dynamically over time. These bands serve as a macro-level guide for identifying periods of historical overvaluation (upper red curve) and undervaluation (lower green curve), with a central black curve representing the geometric average of the two.
How to customize the parameters:
The lower1_const and upper1_const values vertically shift the respective lower and upper curves—more negative values push the curve downward, while higher values lift it.
The lower1_coef and upper1_coef control the steepness of the curves over time, with higher values resulting in faster growth relative to time.
The shift_factor allows for uniform vertical adjustment of all curves simultaneously.
Additionally, the channel_width setting determines how far the mirrored bands extend from the original curves, creating a visual “channel” that can highlight more conservative or aggressive valuation zones depending on preference.
How to use this indicator:
This indicator is not intended for short-term trading or intraday signals. Rather, it serves as a contextual framework for long-term investors to identify high-risk zones near the upper curve and potential long-term value opportunities near the lower curve. These areas historically align with cycle tops and bottoms, and the model helps to place current price action within that broader cyclical narrative. While the concept draws inspiration from Bitcoin’s halving-driven market cycles and exponential adoption curve, the implementation is original in its use of time-based logarithmic regression to define dynamic trend boundaries.
It is best used as a strategic tool for cycle analysis, macro positioning, and trend anchoring—rather than as a short-term signal provider.
Dynamic Range Filter with Trend Candlesticks (Zeiierman)█ Overview
Dynamic Range Filter with Trend Candlesticks (Zeiierman) is a volatility-responsive trend engine that adapts in real-time to market structure, offering a clean and intelligent visualization of directional bias. It blends dynamic range calculation with customizable smoothing techniques and layered trend confirmation logic, making it ideal for traders who rely on clear trend direction, structural range analysis, and momentum-based candlestick signals.
By measuring scaled volatility over configurable lengths and applying advanced moving average techniques, this indicator filters out market noise while preserving true directional intent. Complementing this, a dual-trend system (range-based and candle-based) enhances clarity and responsiveness, particularly during shifting market conditions.
█ How It Works
⚪ Scaled Volatility Band Calculation
At the core lies a volatility engine that constructs adaptive range bands around price using smoothed high/low calculations. The bands are dynamically adjusted using:
High/Low Smoothing – Applies a moving average to the raw high and low data before calculating the range.
Scaled Range Volatility – A 2.618 multiplier scales the distance between smoothed highs and lows, forming a responsive volatility envelope.
Band Multiplier – Controls how wide the upper/lower range bands extend from the mean.
This filtering process minimizes false signals and highlights only structurally meaningful moves.
⚪ Multi-Type Smoothing Engine
Users can choose from a wide array of smoothing algorithms for trend construction, including:
HMA (default), SMA, EMA, RMA
KAMA – Adapts to market volatility using efficiency ratios.
VIDYA – Momentum-sensitive smoothing using CMO logic.
FRAMA – Dynamically adjusts to fractal dimension in price.
Super Smoother – Ideal for eliminating aliasing in range signals.
This provides the trader with fine-tuned control over reactivity vs. smoothness.
⚪ Trend Detection (Dual Engine)
The indicator includes two independent trend tracking systems:
Main Trend Filter – Based on adaptive volatility band shifts.
Candle Trend Filter – A second-tier confirmation using smoothed candle data, ideal for directional candles and confirmation entries.
█ How to Use
⚪ Trend Confirmation
Use the Trend Line and colored candlesticks for high-probability entries in the trend direction. The more trend layers that align, the higher the confidence.
⚪ Reversal Zones
When the price reaches the outer bands or fails to break them, look for candle color shifts or a crossover in the range to anticipate possible reversals or consolidations.
█ Settings
Scaled Volatility Length – Controls the lookback used to stabilize the base volatility band.
MA Type & Length – Choose and fine-tune the smoothing method (HMA, EMA, KAMA, etc.)
High/Low Smoother – Pre-smoothing for structural high/low banding.
Band Multiplier – Adjusts the width of the dynamic bands.
Trend Length (Candles) – Length used for candle-based trend confirmation.
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Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
XAUUSD Multi-Timeframe Trend AnalyzerOverview
The "XAUUSD Multi-Timeframe Trend Analyzer" is an advanced script designed to provide a comprehensive analysis of the XAUUSD (Gold/US Dollar) trend across multiple timeframes simultaneously. By combining several key technical indicators, this tool helps traders quickly assess the market direction and trend strength for M15, M30, H1, H4, and D1 timeframes.
Multi-Timeframe Analysis: Displays the trend direction and strength across M15, M30, H1, H4, and D1 timeframes, allowing for a complete overview in a single glance.
Comprehensive Indicator Blend: Utilizes six popular technical indicators to determine the trend—Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR.
Trend Strength Scoring: Provides a numerical trend strength score (from -6 to 6) based on the alignment of the indicators, with positive values indicating uptrends and negative values for downtrends.
Visual Table Display: Displays results in a color-coded table (green for uptrend, red for downtrend, yellow for neutral) with a strength score for each timeframe, helping traders quickly assess market conditions.
How It Works
This script calculates the overall trend and its strength for each selected timeframe by analyzing six widely-used technical indicators:
Moving Averages (MA): The script uses a Fast and a Slow Moving Average. When the Fast MA crosses above the Slow MA, it indicates an uptrend. When the Fast MA crosses below, it signals a downtrend.
Relative Strength Index (RSI): The RSI is used to assess momentum. An RSI value above 50 suggests bullish momentum, while a value below 50 suggests bearish momentum.
Moving Average Convergence Divergence (MACD): MACD measures momentum and trend direction. When the MACD line crosses above the signal line, it signals bullish momentum; when it crosses below, it signals bearish momentum.
Bollinger Bands: These measure price volatility. When the price is above the middle Bollinger Band, the script considers the trend to be bullish, and when it's below, bearish.
Directional Movement Index (DMI): The DMI compares positive directional movement (DI+) and negative directional movement (DI-). A stronger DI+ over DI- signals an uptrend and vice versa.
Parabolic SAR: This indicator is used for determining potential trend reversals and setting stop-loss levels. If the price is above the Parabolic SAR, it indicates an uptrend, and if below, a downtrend.
Trend Strength Calculation
The script calculates a trend strength score for each timeframe:
Each indicator adds or subtracts 1 to the score based on whether it aligns with an uptrend or a downtrend.
A score of 6 indicates a Strong Uptrend, with all indicators aligned bullishly.
A score of -6 indicates a Strong Downtrend, with all indicators aligned bearishly.
Intermediate scores (e.g., 2 or -2) indicate Weak Uptrend or Weak Downtrend, suggesting that not all indicators are in agreement.
A score between 1 and -1 indicates a Neutral trend, suggesting uncertainty in the market.
How to Use
Assess Trend Direction and Strength: The table provides an easy-to-read summary of the trend and its strength on different timeframes. Look for timeframes where the strength is high (either 6 for a strong uptrend or -6 for a strong downtrend) to confirm the market’s overall direction.
Use in Conjunction with Other Strategies: This indicator is designed to provide a comprehensive view of the market. Traders should combine it with other strategies, such as price action analysis or candlestick patterns, to further confirm their trades.
Trend Reversal or Continuation: A weak trend (e.g., a strength of 2 or -2) could signal a possible reversal or a trend that has lost momentum. Strong trends (with a strength of 6 or -6) indicate higher confidence in trend continuation.
Multiple Timeframe Confirmation: Look for alignment across multiple timeframes to confirm the strength and direction of the trend before entering trades. For example, if M15, M30, and H1 are all showing a strong uptrend, it suggests a higher probability of the trend continuing.
Customization Options
- Adjustable Indicators: Users can modify the length and parameters of the Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR to suit their trading style.
- Flexible Timeframes: You can toggle between different timeframes (M15, M30, H1, H4, D1) to focus on the intervals most relevant to your strategy.
Ideal For
- Traders looking for a detailed, multi-timeframe trend analysis tool for XAUUSD.
- Traders who rely on trend-following strategies and need confirmation across multiple timeframes.
- Those who prefer a multi-indicator approach to avoid false signals and improve the accuracy of their trades.
Disclaimer
This indicator is for informational and educational purposes only. It is recommended to combine this with proper risk management strategies and your own analysis. Past performance does not guarantee future results. Always perform your own due diligence before making trading decisions.
Curved Price Channels (Zeiierman)█ Overview
The Curved Price Channels (Zeiierman) is designed to plot dynamic channels around price movements, much like the traditional Donchian Channels, but with a key difference: the channels are curved instead of straight. This curvature allows the channels to adapt more fluidly to price action, providing a smoother representation of the highest high and lowest low levels.
Just like Donchian Channels, the Curved Price Channels help identify potential breakout points and areas of trend reversal. However, the curvature offers a more refined approach to visualizing price boundaries, making it potentially more effective in capturing price trends and reversals in markets that exhibit significant volatility or price swings.
The included trend strength calculation further enhances the indicator by offering insight into the strength of the current trend.
█ How It Works
The Curved Price Channels are calculated based on the asset's average true range (ATR), scaled by the chosen length and multiplier settings. This adaptive size allows the channels to expand and contract based on recent market volatility. The central trendline is calculated as the average of the upper and lower curved bands, providing a smoothed representation of the overall price trend.
Key Calculations:
Adaptive Size: The ATR is used to dynamically adjust the width of the channels, making them responsive to changes in market volatility.
Upper and Lower Bands: The upper band is calculated by taking the maximum close value and adjusting it downward by a factor proportional to the ATR and the multiplier. Similarly, the lower band is calculated by adjusting the minimum close value upward.
Trendline: The trendline is the average of the upper and lower bands, representing the central tendency of the price action.
Trend Strength
The Trend Strength feature in the Curved Price Channels is a powerful feature designed to help traders gauge the strength of the current trend. It calculates the strength of a trend by analyzing the relationship between the price's position within the curved channels and the overall range of the channels themselves.
Range Calculation:
The indicator first determines the distance between the upper and lower curved channels, known as the range. This range represents the overall volatility of the price within the given period.
Range = Upper Band - Lower Band
Relative Position:
The next step involves calculating the relative position of the closing price within this range. This value indicates where the current price sits in relation to the overall range.
RelativePosition = (Close - Trendline) / Range
Normalization:
To assess the trend strength over time, the current range is normalized against the maximum and minimum ranges observed over a specified look-back period.
NormalizedRange = (Range - Min Range) / (Max Range - Min Range)
Trend Strength Calculation:
The final Trend Strength is calculated by multiplying the relative position by the normalized range and then scaling it to a percentage.
TrendStrength = Relative Position * Normalized Range * 100
This approach ensures that the Trend Strength not only reflects the direction of the trend but also its intensity, providing a more comprehensive view of market conditions.
█ Comparison with Donchian Channels
Curved Price Channels offer several advantages over Donchian Channels, particularly in their ability to adapt to changing market conditions.
⚪ Adaptability vs. Fixed Structure
Donchian Channels: Use a fixed period to plot straight lines based on the highest high and lowest low. This can be limiting because the channels do not adjust to volatility; they remain the same width regardless of how much or how little the price is moving.
Curved Price Channels: Adapt dynamically to market conditions using the Average True Range (ATR) as a measure of volatility. The channels expand and contract based on recent price movements, providing a more accurate reflection of the market's current state. This adaptability allows traders to capture both large trends and smaller fluctuations more effectively.
⚪ Sensitivity to Market Movements
Donchian Channels: Are less sensitive to recent price action because they rely on a fixed look-back period. This can result in late signals during fast-moving markets, as the channels may not adjust quickly enough to capture new trends.
Curved Price Channels: Respond more quickly to changes in market volatility, making them more sensitive to recent price action. The multiplier setting further allows traders to adjust the channel's sensitivity, making it possible to capture smaller price movements during periods of low volatility or filter out noise during high volatility.
⚪ Enhanced Trend Strength Analysis
Donchian Channels: Do not provide direct insight into the strength of a trend. Traders must rely on additional indicators or their judgment to gauge whether a trend is strong or weak.
Curved Price Channels: Includes a built-in trend strength calculation that takes into account the distance between the upper and lower channels relative to the trendline. A broader range between the channels typically indicates a stronger trend, while a narrower range suggests a weaker trend. This feature helps traders not only identify the direction of the trend but also assess its potential longevity and strength.
⚪ Dynamic Support and Resistance
Donchian Channels: Offer static support and resistance levels that may not accurately reflect changing market dynamics. These levels can quickly become outdated in volatile markets.
Curved Price Channels: Offer dynamic support and resistance levels that adjust in real-time, providing more relevant and actionable trading signals. As the channels curve to reflect price movements, they can help identify areas where the price is likely to encounter support or resistance, making them more useful in volatile or trending markets.
█ How to Use
Traders can use the Curved Price Channels in similar ways to Donchian Channels but with the added benefits of the adaptive, curved structure:
Breakout Identification:
Just like Donchian Channels, when the price breaks above the upper curved band, it may signal the start of a bullish trend, while a break below the lower curved band could indicate a bearish trend. The curved nature of the channels helps in capturing these breakouts more precisely by adjusting to recent volatility.
Volatility:
The width of the price channels in the Curved Price Channels indicator serves as a clear indicator of current market volatility. A wider channel indicates that the market is experiencing higher volatility, as prices are fluctuating more dramatically within the period. Conversely, a narrower channel suggests that the market is in a lower volatility state, with price movements being more subdued.
Typically, higher volatility is observed during negative trends, where market uncertainty or fear drives larger price swings. In contrast, lower volatility is often associated with positive trends, where prices tend to move more steadily and predictably. The adaptive nature of the Curved Price Channels reflects these volatility conditions in real time, allowing traders to assess the market environment quickly and adjust their strategies accordingly.
Support and Resistance:
The trend line act as dynamic support and resistance levels. Due to it's adaptive nature, this level is more reflective of the current market environment than the fixed level of Donchian Channels.
Trend Direction and Strength:
The trend direction and strength are highlighted by the trendline and the directional candle within the Curved Price Channels indicator. If the price is above the trendline, it indicates a positive trend, while a price below the trendline signals a negative trend. This directional bias is visually represented by the color of the directional candle, making it easy for traders to quickly identify the current market trend.
In addition to the trendline, the indicator also displays Max and Min values. These represent the highest and lowest trend strength values within the lookback period, providing a reference point for understanding the current trend strength relative to historical levels.
Max Value: Indicates the highest recorded trend strength during the lookback period. If the Max value is greater than the Min value, it suggests that the market has generally experienced more positive (bullish) conditions during this time frame.
Min Value: Represents the lowest recorded trend strength within the same period. If the Min value is greater than the Max value, it indicates that the market has been predominantly negative (bearish) over the lookback period.
By assessing these Max and Min values, traders gain an immediate understanding of the underlying trend. If the current trend strength is close to the Max value, it indicates a strong bullish trend. Conversely, if the trend strength is near the Min value, it suggests a strong bearish trend.
█ Settings
Trend Length: Defines the number of bars used to calculate the core trendline and adaptive size. A length of 200 will create a smooth, long-term trendline that reacts slowly to price changes, while a length of 20 will create a more responsive trendline that tracks short-term movements.
Multiplier: Adjusts the width of the curved price channels. A higher value tightens the channels, making them more sensitive to price movements, while a lower value widens the channels. A multiplier of 10 will create tighter channels that are more sensitive to minor price fluctuations, which is useful in low-volatility markets. A multiplier of 2 will create wider channels that capture larger trends and are better suited for high-volatility markets.
Trend Strength Length: Defines the period over which the maximum and minimum ranges are calculated to normalize the trend strength. A length of 200 will smooth out the trend strength readings, providing a stable indication of trend health, whereas a length of 50 will make the readings more reactive to recent price changes.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Abnormal value check1. indicator settings
BB Length: Sets the period used for the Bollinger Band calculation. The default is 20 periods.
BB Multiplier: Sets the multiplier to be used in the Bollinger Band calculation. The default is 2.5 multiplier.
Equilibrium volume reset: Selects whether or not the volume should be reset if it is out of equilibrium. The default setting is reset. 2.
2. bollinger band calculation
This indicator calculates Bollinger Bands (upper and lower bands and a reference line) from price and volume data.
Bollinger Bands are indicators used to measure price and volume volatility and are identified as anomalies when prices break through the bands.
3. display of abnormal prices
Abnormal Buying Price (ABP): The background color changes when the price significantly exceeds the upper limit of the Bollinger Band. The color is green.
Abnormal Selling Price (ASP): The background color changes when the price is significantly below the lower limit of the Bollinger Band. The color is red.
Abnormal High Volume (AHV): The background color changes when the volume is significantly above the upper Bollinger Band. The color is white.
Abnormal Low Volume (ALV): The background color changes when the volume is significantly below the lower limit of the Bollinger Band. The color is yellow. 4.
4. display of signals
Abnormal Price Signal: A triangle signal is displayed when the price rises or falls compared to the previous data. The color is orange for an increase and purple for a decrease.
Volume Abnormal Signal: A triangle signal is displayed when volume is up or down compared to the previous data. Rises are colored orange and falls are colored purple. 5.
5. price and volume history display
RSAB_P: Displays price anomaly history. Rising prices are displayed in green, and falling prices in red.
RSAB_V: Displays the volume anomaly history. Green indicates an increase and red indicates a decrease. 6.
6. display of equilibrium
PPE: Displays a line indicating the state of volume balance. A positive volume balance is displayed in orange, and a negative volume balance is displayed in purple.
Summary of usage
Add indicator to chart: Add this Pine Script™ code as an indicator in TradingView.
Set parameters: Based on the settings above, adjust the values to suit your trading strategy and analysis.
See signals and color changes on the chart: Visually identify price and volume anomalies to help you make trading decisions.
This indicator uses Bollinger Bands to identify abnormal price and volume movements to help you improve your trading timing and strategies.
ATR + Momentum Shifts w/Take ProfitThis script is a technical analysis indicator designed to assist in identifying potential entry points and setting take profit levels in trading. It combines the Average True Range (ATR) indicator, momentum shifts, and customizable take profit levels to provide insights into potential market movements.
Differences from Currently Published Ones:
This script is unique due to its use of a combination of elements:
ATR and Momentum: The script combines the ATR indicator to provide dynamic support and resistance levels with the momentum indicator to identify shifts in the underlying momentum.
Customizable Take Profit Levels: It offers the ability to set take profit levels based on customizable multipliers of the ATR, helping traders manage potential profits.
How to Use:
ATR Bands: The script plots upper and lower ATR bands as potential dynamic support and resistance levels.
Shift Arrows: Arrows are plotted below bars for potential long entry opportunities (green triangle) and above bars for potential short entry opportunities (yellow triangle).
Take Profit Levels: The script also plots take profit levels both above and below the source price based on the ATR multipliers set in the inputs.
Markets and Conditions:
This script can be used across various financial markets, including stocks, forex, commodities, and cryptocurrencies. It's most effective in trending markets where momentum shifts can signal potential reversals or continuation of trends. Traders should consider the following conditions:
Trend Confirmation: Look for momentum shifts in the direction of the prevailing trend for higher probability setups.
Volatility: Higher volatility can amplify ATR movements and subsequently affect the placement of ATR bands and take profit levels.
Risk Management: Always implement proper risk management strategies to protect your capital.
Additional Considerations:
Customization: Traders can adjust input parameters like ATR length, momentum length, and take profit multipliers to match their trading style and market conditions.
Combining with Other Indicators: Consider using this indicator in conjunction with other technical indicators or chart patterns for confirmation.
Mean ReversionThe "Mean Reversion" indicator in this script is a popular trading strategy that is based on the concept that over time, prices tend to move back towards their mean or average. This trading strategy seeks to identify instances where the price has deviated significantly from its mean and therefore presents an opportunity to profit from its eventual reversion to the mean.
The script calculates the distance between the current price and the EMA using the ATR, which is a measure of volatility. By multiplying the ATR by a specified factor, the script establishes a distance between the current price and the EMA. If the price falls below this distance, it triggers a potential buy signal, indicating that the price may be oversold and due for a rebound.
The script also uses Bollinger Bands to help identify potential buying and selling opportunities. The Bollinger Bands are a technical indicator that measures the volatility of an asset by plotting two standard deviations away from a moving average. When the price moves outside of the Bollinger Bands, it can indicate that the asset is overbought or oversold, potentially triggering a buy or sell signal.
The script's "buySignal" variable is triggered when the price is below the EMA by the specified ATR distance and also falls below the lower Bollinger Band. Conversely, the "sellSignal" variable is triggered when the price is above the EMA by the specified ATR distance and also rises above the upper Bollinger Band.
The script plots the EMA, Bollinger Bands, and the buy and sell signals on the chart for easy visualization. Additionally, the script includes alerts that can be set up to notify the user when a buy or sell signal is triggered, so that they can act on the information in a timely manner.
In summary, this script is a Mean Reversion indicator that aims to identify potential opportunities to buy or sell assets based on deviations from their mean price using a combination of the ATR, EMA, and Bollinger Bands.
Weekly/Monthly Golden ATR LevelsWeekly/Monthly Golden ATR Levels
This indicator is designed to give traders a clear, rule-based framework for identifying support and resistance zones anchored to prior period ranges and the market’s own volatility. It uses the Average True Range (ATR) as a measure of how far price can realistically stretch, then projects fixed levels from the midpoint of the prior week and prior month.
Rather than “moving targets” that repaint, these levels are frozen at the start of each new week and month and stay fixed until the next period begins. This makes them reliable rails for both intraday and swing trading.
What It Plots
Weekly Midpoint (last week’s High + Low ÷ 2)
From this mid, the script projects:
Weekly +1 / −1 ATR
Weekly +2 / −2 ATR
Monthly Midpoint (last month’s High + Low ÷ 2)
From this mid, the script projects:
Monthly +1 / −1 ATR
Monthly +2 / −2 ATR
Customization
Set ATR length & timeframe (default: 14 ATR on Daily bars).
Adjust multipliers for Level 1 (±1 ATR) and Level 2 (±2 ATR).
Choose line color, style, and width separately for weekly and monthly bands.
Toggle labels on/off.
How to Use
Context at the Open
If price opens above last week’s midpoint, bias favors upside toward +1 / +2.
If price opens below the midpoint, bias favors downside toward −1 / −2.
Weekly Bands = Short-Term Rails
+1 / −1 ATR: Rotation pivots. Expect intraday reaction.
+2 / −2 ATR: Extreme stretch zones. Reversals or breakouts often occur here.
Monthly Bands = Big Picture Rails
Use these for swing positioning, or as “outer guardrails” on intraday charts.
When weekly and monthly bands cluster → high-confluence zone.
Trade Playbook
Trend Day: Hold above +1 → target +2. Break below −1 → target −2.
Range Day: Fade first test of ±2, scalp toward ±1 or midpoint.
Catalyst/News Day: Use with caution—levels provide context, not barriers.
Risk Management
Place stops just outside the band you’re trading against.
Scale profits at the next inner level (e.g., short from +2, cover partial at +1).
Runners can trail to the midpoint or opposite side.
Why It Works
ATR measures volatility—how far price tends to travel in a given period.
Anchoring to prior highs and lows captures where real supply/demand last clashed.
Combining the two gives levels that are statistically relevant, widely observed, and psychologically sticky.
Trading books from Mark Douglas (Trading in the Zone), Jared Tendler (The Mental Game of Trading), and Oliver Kell (Victory in Stock Trading) all stress the importance of having objective, repeatable reference points. These levels deliver that discipline—removing guesswork and reducing emotional trading
Cubic Regression with Rainbow Grid (Adaptive StDev)Cubic Regression with Rainbow Channel
Description
The Cubic Regression with Rainbow Channel is an advanced technical analysis tool designed to identify trends and measure market volatility. It plots a cubic regression trendline surrounded by a "rainbow" of quantile bands.
Its primary feature is a unique adaptive volatility model. Instead of using a single period for standard deviation, it blends a long-term (stable) and a short-term (responsive) deviation. The user can control the weight between these two, allowing for fine-tuning of the channel's sensitivity to recent volatility changes.
How to Use and Recommendations
This indicator can be used for trend analysis, volatility assessment, and generating trading signals.
1. Trend Identification:
The central white line represents the calculated cubic regression trend.
Uptrend: The line curves upwards.
Downtrend: The line curves downwards.
Consolidation: The line moves sideways.
The curve's angle indicates the trend's strength.
2. Volatility Analysis:
The width of the rainbow is a direct measure of market volatility.
Wide Channel (High Volatility): Indicates significant price movement and uncertainty. Be cautious, as prices can swing wildly.
Narrow Channel (Low Volatility): Signals a period of consolidation or low market activity. Often, a "squeeze" (a very narrow channel) precedes a strong breakout.
3. Trading Signals:
Mean Reversion (Primary Strategy):
Sell Signal: When the price reaches the upper, "hot" bands (yellow, orange, red), it is considered overbought or overextended. Look for a potential reversal back towards the central white line.
Buy Signal: When the price touches the lower, "cold" bands (aqua, navy, purple), it is considered oversold. Look for a potential bounce back towards the central trendline.
Breakout Confirmation:
If the price consistently closes outside the outer bands (red or purple), especially as the channel is widening, it may signal the start of a very strong new trend, invalidating the mean-reversion signal.
4. Key Recommendations:
Always Use Confirmation: Do not use this indicator in isolation. Confirm its signals with other tools like RSI for momentum, MACD for trend confirmation, or Volume analysis.
Tune the Parameters:
Regression Period: Adjust this to fit the character of the asset. A longer period creates a smoother, more stable trendline suitable for long-term analysis. A shorter period makes it more responsive to recent price action.
Short StDev Weight (%): This is the most important setting. Start with a value around 20-40%.
Increase the weight to make the channel react faster to volatility spikes (good for short-term trading).
Decrease the weight for a smoother, more stable channel that filters out market noise (better for trend-following).
Context is King: The indicator is most reliable in markets that tend to revert to a mean. In a very strong, one-directional trend, mean-reversion signals may fail repeatedly.
The Ultimate ATR-BBW Market Volatility Indicator"The ATR-BBW Market Volatility Indicator combines the Average True Range (ATR) and Bollinger Bands Width (BBW) to provide a measure of market volatility. This indicator does not indicate bullish or bearish trends, but rather the magnitude of price fluctuations.
* Usage: When the indicator moves upward, it suggests increasing market volatility, indicating that prices are moving within a wider range. Conversely, a downward movement implies decreasing volatility, signifying that prices are moving within a narrower range.
* Note: This sub-indicator solely reflects market volatility and does not provide buy or sell signals.
Investing involves risk. Please conduct thorough research before making any investment decisions.
ATR and BBW Explained:
* Average True Range (ATR): ATR is a technical analysis indicator used to measure market volatility. It calculates the average of a series of true ranges, where the true range is the greatest of the following:
* The current high minus the current low
* The absolute value of the current high minus the previous close
* The absolute value of the current low minus the previous close
* A higher ATR value indicates higher volatility, while a lower value suggests lower volatility.
* Bollinger Bands Width (BBW): Bollinger Bands are plotted two standard deviations above and below a simple moving average. BBW measures the distance between the upper and lower bands. A wider BBW indicates higher volatility, as prices are moving further away from the moving average. Conversely, a narrower BBW suggests lower volatility.
Combining ATR and BBW:
By combining ATR and BBW, the ATR-BBW indicator provides a more comprehensive view of market volatility. ATR captures the overall volatility of the market, while BBW measures the volatility relative to the moving average. Together, they provide a more robust indicator of market conditions and can be used to identify potential trading opportunities.
Why ATR and BBW are Effective for Measuring Volatility:
* ATR directly measures the actual price movement, regardless of the direction.
* BBW shows how much prices are deviating from their average, indicating the strength of the current trend.
* Combined: By combining these two measures, the ATR-BBW indicator provides a more comprehensive and accurate assessment of market volatility.
In essence, the ATR-BBW indicator helps traders understand the magnitude of price fluctuations, allowing them to make more informed trading decisions.
