ADR [KasTrades]This ADR indicator has 2 options: a Range of ADR, such as 7 and 14 which is typically used for indexes, index futures and equities, or a single ADR such as a 5 day which is typically used for forex.
The session start time is 17:00 ET (NY Time) by default, this is adjustable.
You can adjust the ADR days to different ranges such as 5 and 10, or a single ADR day such as 7.
Colors of the ADR high and low are also adjustable.
Volatilità
ADR - Average Daily Range [KasTrades]This is an Average Daily Range (ADR) indicator.
There are two settings for ADR:
Two Look back period ADR range (e.g. 7 and 14 days)
One Look back period ADR (e.g. 5 days only)
Two day ADR ranges are typically used in equities and index futures whereas one day ADR is typically used in forex.
The opening time by default is 17:00 New York (Eastern) time. The ranges are always calculated from the opening price of the first bar on the respected timeframe.
ASR - Average Session Range [KasTrades]This indicator displays the Average Session Range based on the session of your choice.
You can turn the tables off if you don't want to see a table version of the ASR levels. There is also a momentum table showing the current momentum, which you can also turn off.
Adaptive Trend CatcherAdaptive Trend Catcher is an original indicator that combines Hull Moving Average smoothing, ATR-based volatility bands, and a CCI filter within an adaptive logic framework. It’s built to react intelligently to changing market conditions rather than applying fixed parameters.
The system uses hysteresis to confirm trend flips only after several consistent signals, minimizing noise and false reversals. During strong momentum bursts, it automatically tightens its internal deadzone and step size to stay responsive while maintaining stability in quieter periods.
The result is a dynamic trend engine that plots a color-shifting adaptive line — green for bullish, red for bearish — that adjusts smoothly with volatility. Optional upper/lower ATR bands can be displayed for added context.
How to use: Watch for confirmed trend color flips with supporting momentum. Bullish flips occur when price regains the lower band and CCI turns positive; bearish flips when price falls below the upper band and CCI turns negative.
Includes alert conditions for both reversals.
For educational purposes only. Not financial advice.
Opening Range Fibonacci Extensions (ATR Adjusted)this script displays daily, weekly, or monthly range extensions as a function of ATR in a Fibonacci retracement
Squeeze Hour Frequency [CHE]Squeeze Hour Frequency (ATR-PR) — Standalone — Tracks daily squeeze occurrences by hour to reveal time-based volatility patterns
Summary
This indicator identifies periods of unusually low volatility, defined as squeezes, and tallies their frequency across each hour of the day over historical trading sessions. By aggregating counts into a sortable table, it helps users spot hours prone to these conditions, enabling better scheduling of trading activity to avoid or target specific intraday regimes. Signals gain robustness through percentile-based detection that adapts to recent volatility history, differing from fixed-threshold methods by focusing on relative lowness rather than absolute levels, which reduces false positives in varying market environments.
Motivation: Why this design?
Traders often face uneven intraday volatility, with certain hours showing clustered low-activity phases that precede or follow breakouts, leading to mistimed entries or overlooked calm periods. The core idea of hourly squeeze frequency addresses this by binning low-volatility events into 24 hourly slots and counting distinct daily occurrences, providing a historical profile of when squeezes cluster. This reveals time-of-day biases without relying on real-time alerts, allowing proactive adjustments to session focus.
What’s different vs. standard approaches?
- Reference baseline: Classical volatility tools like simple moving average crossovers or fixed ATR thresholds, which flag squeezes uniformly across the day.
- Architecture differences:
- Uses persistent arrays to track one squeeze per hour per day, preventing overcounting within sessions.
- Employs custom sorting on ratio arrays for dynamic table display, prioritizing top or bottom performers.
- Handles timezones explicitly to ensure consistent binning across global assets.
- Practical effect: Charts show a persistent table ranking hours by squeeze share, making intraday patterns immediately visible—such as a top hour capturing over 20 percent of total events—unlike static overlays that ignore temporal distribution, which matters for avoiding low-liquidity traps in crypto or forex.
How it works (technical)
The indicator first computes a rolling volatility measure over a specified lookback period. It then derives a relative ranking of the current value against recent history within a window of bars. A squeeze is flagged when this ranking falls below a user-defined cutoff, indicating the value is among the lowest in the recent sample.
On each bar, the local hour is extracted using the selected timezone. If a squeeze occurs and the bar has price data, the count for that hour increments only if no prior mark exists for the current day, using a persistent array to store the last marked day per hour. This ensures one tally per unique trading day per slot.
At the final bar, arrays compile counts and ratios for all 24 hours, where the ratio represents each hour's share of total squeezes observed. These are sorted ascending or descending based on display mode, and the top or bottom subset populates the table. Background shading highlights live squeezes in red for visual confirmation. Initialization uses zero-filled arrays for counts and negative seeds for day tracking, with state persisting across bars via variable declarations.
No higher timeframe data is pulled, so there is no repaint risk from external fetches; all logic runs on confirmed bars.
Parameter Guide
ATR Length — Controls the lookback for the volatility measure, influencing sensitivity to short-term fluctuations; shorter values increase responsiveness but add noise, longer ones smooth for stability — Default: 14 — Trade-offs/Tips: Use 10-20 for intraday charts to balance quick detection with fewer false squeezes; test on historical data to avoid over-smoothing in trending markets.
Percentile Window (bars) — Sets the history depth for ranking the current volatility value, affecting how "low" is defined relative to past; wider windows emphasize long-term norms — Default: 252 — Trade-offs/Tips: 100-300 bars suit daily cycles; narrower for fast assets like crypto to catch recent regimes, but risks instability in sparse data.
Squeeze threshold (PR < x) — Defines the cutoff for flagging low relative volatility, where values below this mark a squeeze; lower thresholds tighten detection for rarer events — Default: 10.0 — Trade-offs/Tips: 5-15 percent for conservative signals reducing false positives; raise to 20 for more frequent highlights in high-vol environments, monitoring for increased noise.
Timezone — Specifies the reference for hourly binning, ensuring alignment with market sessions — Default: Exchange — Trade-offs/Tips: Set to "America/New_York" for US assets; mismatches can skew counts, so verify against chart timezone.
Show Table — Toggles the results display, essential for reviewing frequencies — Default: true — Trade-offs/Tips: Disable on mobile for performance; pair with position tweaks for clean overlays.
Pos — Places the table on the chart pane — Default: Top Right — Trade-offs/Tips: Bottom Left avoids candle occlusion on volatile charts.
Font — Adjusts text readability in the table — Default: normal — Trade-offs/Tips: Tiny for dense views, large for emphasis on key hours.
Dark — Applies high-contrast colors for visibility — Default: true — Trade-offs/Tips: Toggle false in light themes to prevent washout.
Display — Filters table rows to focus on extremes or full list — Default: All — Trade-offs/Tips: Top 3 for quick scans of risky hours; Bottom 3 highlights safe low-squeeze periods.
Reading & Interpretation
Red background shading appears on bars meeting the squeeze condition, signaling current low relative volatility. The table lists hours as "H0" to "H23", with columns for daily squeeze counts, percentage share of total squeezes (summing to 100 percent across hours), and an arrow marker on the top hour. A summary row above details the peak count, its share, and the leading hour. A label at the last bar recaps total days observed, data-valid days, and top hour stats. Rising shares indicate clustering, suggesting regime persistence in that slot.
Practical Workflows & Combinations
- Trend following: Scan for hours with low squeeze shares to enter during stable regimes; confirm with higher highs or lower lows on the 15-minute chart, avoiding top-share hours post-news like tariff announcements.
- Exits/Stops: Tighten stops in high-share hours to guard against sudden vol spikes; use the table to shift to conservative sizing outside peak squeeze times.
- Multi-asset/Multi-TF: Defaults work across crypto pairs on 5-60 minute timeframes; for stocks, widen percentile window to 500 bars. Combine with volume oscillators—enter only if squeeze count is below average for the asset.
Behavior, Constraints & Performance
Logic executes on closed bars, with live bars updating counts provisionally but finalizing on confirmation; table refreshes only at the last bar, avoiding intrabar flicker. No security calls or higher timeframes, so no repaint from external data. Resources include a 5000-bar history limit, loops up to 24 iterations for sorting and totals, and arrays sized to 24 elements; labels and table are capped at 500 each for efficiency. Known limits: Skips hours without bars (e.g., weekends), assumes uniform data availability, and may undercount in sparse sessions; timezone shifts can alter profiles without warning.
Sensible Defaults & Quick Tuning
Start with ATR Length at 14, Percentile Window at 252, and threshold at 10.0 for broad crypto use. If too many squeezes flag (noisy table), raise threshold to 15.0 and narrow window to 100 for stricter relative lowness. For sluggish detection in calm markets, drop ATR Length to 10 and threshold to 5.0 to capture subtler dips. In high-vol assets, widen window to 500 and threshold to 20.0 for stability.
What this indicator is—and isn’t
This is a historical frequency tracker and visualization layer for intraday volatility patterns, best as a filter in multi-tool setups. It is not a standalone signal generator, predictive model, or risk manager—pair it with price action, news filters, and position sizing rules.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Thanks to Duyck
for the ma sorter
Volume BubblesVolume Bubbles Indicator
Introduction
The Volume Bubbles indicator is a powerful tool designed to visually highlight significant volume spikes on your TradingView charts. It helps traders identify potential areas of whale accumulation (large buying activity) or dumping (large selling activity) by displaying colored bubbles on candles where volume exceeds a customizable threshold. Green bubbles indicate bullish (buy) volume on up candles, suggesting possible accumulation, while red bubbles signal bearish (sell) volume on down candles, indicating potential dumping. The bubble size scales with the volume magnitude, making it easy to spot major market moves at a glance.
This indicator is particularly useful for crypto, forex, and stock traders looking to gauge market sentiment and large player involvement without cluttering the chart. It's built in Pine Script v5 and overlays directly on your price action.
How It Works
The indicator calculates a moving average of volume (default: 20-period SMA) and detects spikes when current volume exceeds this average by a multiplier (default: 2x).
Buy Bubbles (Green): Appear on bullish candles (close >= open) at the low wick, representing potential whale buying or accumulation zones.
Sell Bubbles (Red): Appear on bearish candles (close < open) at the high wick, indicating potential whale selling or dumping zones.
Bubble Size: Dynamically sized based on volume thresholds – huge for >1M, large for 500K-1M, normal for <500K.
Transparency: Increases with volume ratio for better visibility on extreme spikes.
Tooltip:
Hover over a bubble to see detailed info like total volume, average volume, and ratio.
By focusing on these high-volume events, traders can spot key support/resistance levels where whales might be active.
How to Use for Whale Accumulation and Dumping
Whales (large holders) often move markets with high-volume trades. This indicator helps spot them:
Accumulation (Buying): Look for clusters of large green bubbles at price lows or during consolidations. This suggests whales are buying dips, potentially signaling a reversal or uptrend start. Combine with support levels for confirmation.
Dumping (Selling): Watch for big red bubbles at price highs or after rallies. This indicates whales unloading positions, which could lead to downtrends or corrections. Pair with resistance levels.
Tips:
Use on higher timeframes (e.g., 1H+) for reliable signals.
Confirm with other indicators like RSI or MACD to avoid false positives.
In trending markets, buy bubbles in uptrends confirm strength; sell bubbles in downtrends signal continuation.
Credits and Disclaimer
Inspired by volume analysis techniques. This is free to use; feedback welcome! Not financial advice – trade at your own risk.
Multiple Symbol Trend Screener [Pineify]Multiple Symbol Trend Screener Pineify – Ultimate Multi-Indicator Scanner for TradingView
Empower your trading with deep market insights across multiple symbols using this feature-rich Pine Script screener. The Multiple Symbol Trend Screener Pineify enables traders to monitor and compare trends, reversals, and consolidations in real-time across the biggest equity symbols on TradingView, through a synergistic blend of popular technical indicators.
Key Features
Monitor up to 15 symbols and their trends simultaneously
Integrates 7 professional-grade indicators: MA Distance, Aroon, Parabolic SAR (PSAR), ADX, Supertrend, Keltner Channel, and BBTrend
Color-coded table display for instant visual assessment
Customizable lookback periods, indicator types, and calculation methods
SEO optimized for multi-symbol trend detection, screener, and advanced TradingView indicator
How It Works
This indicator leverages TradingView’s Pine Script v6 and request.security() to process multiple symbols across selected timeframes. Data populates a dynamic table, updating each cell based on the calculated value of every underlying indicator. MA Distance highlights deviation from moving averages; Aroon flags emerging trend strength; PSAR marks potential trend reversals; ADX assesses trend momentum; Supertrend detects bullish/bearish phases; Keltner Channel and BBTrend offer volatility and power insights.
Set up your preferred symbols and timeframes
Each indicator runs its calculation per symbol using its parameter group
All results are displayed in a table for a comprehensive dashboard view
Trading Ideas and Insights
Traders can use this screener for cross-market comparison, directional bias, entry/exit filtering, and comprehensive trend evaluation. The screener is excellent for swing trading, day trading, and portfolio tracking. It enables confirmation across multiple frameworks — for example, spotting momentum with ADX before confirming direction with Supertrend and PSAR.
Identify correlated movements or divergences across selected assets
Spot synchronized trend changes for basket trading ideas
Filter symbols by volatility, strength, or trend status for precise trade selection
How Multiple Indicators Work Together
The screener’s edge lies in its intelligent correlation of popular indicators. MA Distance measures the proximity to chosen moving averages, ideal for spotting overbought/oversold conditions. Aroon reveals the strength of new price trends, PSAR indicates reversal signals, and ADX quantifies the momentum of these trends. Supertrend provides a directional phase, while Keltner Channel & BBTrend analyze volatility shifts and band compressions. This amalgamation allows for a robust, multi-dimensional market snapshot, capturing details missed by single-indicator tools.
By displaying all key metrics side-by-side, the screener enables holistic decision-making, revealing confluence zones and contradiction areas across multiple tickers and timeframes.
Unique Aspects
Original implementation combining seven independent trend and momentum indicators for each symbol
Rich customization for symbols, timeframes, and all indicator parameters
Intuitive color-coding for quick reading of bullish/bearish/neutral signals
Comprehensive dashboard for instant actionable insights
How to Use
Load the indicator onto your TradingView chart
Go to the script’s settings and input your preferred symbols and relevant timeframes
Set your desired parameters for each indicator group: Moving Average type, Aroon length, PSAR values, ADX smoothing, etc.
Observe the results in the top-right table, then use it to filter candidates and validate trade setups
The screener is suitable for all timeframes and asset classes available on TradingView. Make sure your chart’s timeframe matches the one used in the scanner for optimal accuracy.
Customization
Choose up to 15 symbols to monitor in a single dashboard
Customize lookback periods, indicator types, colors, and display settings
Configure alerting options and thresholds for advanced trade automation
Conclusion
The Multiple Symbol Trend Screener Pineify sets a new standard for multi-asset screening on TradingView. By elegantly merging seven proven technical indicators, the screener delivers powerful trend detection, reversal analysis, and volatility monitoring — all in one dashboard. Take your trading to new heights with in-depth, customizable market surveillance.
Smart Dip & Spike Finder v6Dip and Spike Finder
What This Adds
✅ Finds dips (for buying)
✅ Finds spikes (for selling)
✅ Works with your existing RSI & MA filters
✅ Shows BUY and SELL labels on the chart
✅ Triggers separate alerts for dip and spike conditions
Market Regime (w/ Adaptive Thresholds)Logic Behind This Indicator
This indicator identifies market regimes (trending vs. mean-reverting) using adaptive thresholds that adjust to recent market conditions.
Core Components
1. Regime Score Calculation (0-100 scale)
Starts at 50 (neutral) and adjusts based on two factors:
A. Trend Strength
Compares fast EMA (5) vs. slow EMA (10)
If fast > slow by >1% → +60 points (strong uptrend)
If fast < slow by >1% → -60 points (strong downtrend)
B. RSI Momentum
Uses 7-period RSI smoothed with 3-period EMA
RSI > 70 → +20 points (overbought/trending)
RSI < 30 → -20 points (oversold/mean-reverting)
The score is then smoothed and clamped between 0-100.
2. Adaptive Thresholds
Instead of fixed levels, thresholds adjust to recent market behavior:
Looks back 100 bars to find the min/max regime score
High threshold = 80% of the range (trending regime)
Low threshold = 20% of the range (mean-reverting regime)
This prevents false signals in different volatility environments.
3. Regime Classification
Regime Score Classification Meaning
Above high threshold STRONG TREND Market is trending strongly (follow momentum)
Below low threshold STRONG MEAN REVERSION Market is choppy/oversold (fade moves)
Between thresholds NEUTRAL No clear regime (stay out or wait)
4. Regime Persistence Filter
Requires the regime to hold for a minimum number of bars (default: 1) before confirming
Prevents whipsaws from brief score fluctuations
What It Aims to Detect
When to use trend-following strategies (green = buy breakouts, ride momentum)
When to use mean-reversion strategies (red = buy dips, sell rallies)
When to stay out (gray = unclear conditions, high risk of false signals)
Visual Cues
Green background = Strong trend (momentum strategies work)
Red background = Strong mean reversion (contrarian strategies work)
Table = Shows current regime, color, and score
Alerts = Notifies when regime changes
ATR% Multiple From MA - Overextensions trackingATR% Multiple From MA - Quantifiable Profit Taking Indicator
This overlay indicator identifies overextended price moves by calculating how many ATR% multiples price is away from a moving average, providing objective profit-taking signals.
Formula:
A = ATR% = (ATR / Price) × 100
B = % Gain from MA = ((Price - MA) / MA) × 100
ATR% Multiple = B / A
Signals:
Yellow circle at 7x: Start scaling out partial profits
Red circle at 10x+: Heavily overextended, aggressive profit taking recommended
Stats table: Real-time ATR% Multiple, % Gain from MA, ATR%, and action status
For very volatile markets I usually go for 10x and 15x extension instead of 7x and 10x.
This method normalizes moves across different volatility environments, eliminating emotional decision-making. Historical examples include PLTR, SOFI, TSLA, NVDA which stalled after exceeding 10x.
Customizable Settings:
ATR Length (default: 14)
MA Length (default: 50)
Profit Zone thresholds (7x, 10x)
Toggle circles and MA display
RSI Donchian Channel [DCAUT]█ RSI Donchian Channel
📊 ORIGINALITY & INNOVATION
The RSI Donchian Channel represents an important synthesis of two complementary analytical frameworks: momentum oscillators and breakout detection systems. This indicator addresses a common limitation in traditional RSI analysis by replacing fixed overbought/oversold thresholds with adaptive zones derived from historical RSI extremes.
Key Enhancement:
Traditional RSI analysis relies on static threshold levels (typically 30/70), which may not adequately reflect changing market volatility regimes. This indicator adapts the reference zones dynamically based on the actual RSI behavior over the lookback period, helping traders identify meaningful momentum extremes relative to recent price action rather than arbitrary fixed levels.
The implementation combines the proven momentum measurement capabilities of RSI with Donchian Channel's breakout detection methodology, creating a framework that identifies both momentum exhaustion points and potential continuation signals through the same analytical lens.
📐 MATHEMATICAL FOUNDATION
Core Calculation Process:
Step 1: RSI Calculation
The Relative Strength Index measures momentum by comparing the magnitude of recent gains to recent losses:
Calculate price changes between consecutive periods
Separate positive changes (gains) from negative changes (losses)
Apply selected smoothing method (RMA standard, also supports SMA, EMA, WMA) to both gain and loss series
Compute Relative Strength (RS) as the ratio of smoothed gains to smoothed losses
Transform RS into bounded 0-100 scale using the formula: RSI = 100 - (100 / (1 + RS))
Step 2: Donchian Channel Application
The Donchian Channel identifies the highest and lowest RSI values within the specified lookback period:
Upper Channel: Highest RSI value over the lookback period, represents the recent momentum peak
Lower Channel: Lowest RSI value over the lookback period, represents the recent momentum trough
Middle Channel (Basis): Average of upper and lower channels, serves as equilibrium reference
Channel Width Dynamics:
The distance between upper and lower channels reflects RSI volatility. Wide channels indicate high momentum variability, while narrow channels suggest momentum consolidation and potential breakout preparation. The indicator monitors channel width over a 100-period window to identify squeeze conditions that often precede significant momentum shifts.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Primary Signal Categories:
Breakout Signals:
Upper Breakout: RSI crosses above the upper channel, indicates momentum reaching new relative highs and potential trend continuation, particularly significant when accompanied by price confirmation
Lower Breakout: RSI crosses below the lower channel, suggests momentum reaching new relative lows and potential trend exhaustion or reversal setup
Breakout strength is enhanced when the channel is narrow prior to the breakout, indicating a transition from consolidation to directional movement
Mean Reversion Signals:
Upper Touch Without Breakout: RSI reaches the upper channel but fails to break through, may indicate momentum exhaustion and potential reversal opportunity
Lower Touch Without Breakout: RSI reaches the lower channel without breakdown, suggests potential bounce as momentum reaches oversold extremes
Return to Basis: RSI moving back toward the middle channel after touching extremes signals momentum normalization
Trend Strength Assessment:
Sustained Upper Channel Riding: RSI consistently remains near or above the upper channel during strong uptrends, indicates persistent bullish momentum
Sustained Lower Channel Riding: RSI stays near or below the lower channel during strong downtrends, reflects persistent bearish pressure
Basis Line Position: RSI position relative to the middle channel helps identify the prevailing momentum bias
Channel Compression Patterns:
Squeeze Detection: Channel width narrowing to 100-period lows indicates momentum consolidation, often precedes significant directional moves
Expansion Phase: Channel widening after a squeeze confirms the initiation of a new momentum regime
Persistent Narrow Channels: Extended periods of tight channels suggest market indecision and accumulation/distribution phases
🎯 STRATEGIC APPLICATIONS
Trend Continuation Strategy:
This approach focuses on identifying and trading momentum breakouts that confirm established trends:
Identify the prevailing price trend using higher timeframe analysis or trend-following indicators
Wait for RSI to break above the upper channel in uptrends (or below the lower channel in downtrends)
Enter positions in the direction of the breakout when price action confirms the momentum shift
Place protective stops below the recent swing low (long positions) or above swing high (short positions)
Target profit levels based on prior swing extremes or use trailing stops to capture extended moves
Exit when RSI crosses back through the basis line in the opposite direction
Mean Reversion Strategy:
This method capitalizes on momentum extremes and subsequent corrections toward equilibrium:
Monitor for RSI reaching the upper or lower channel boundaries
Look for rejection signals (price reversal patterns, volume divergence) when RSI touches the channels
Enter counter-trend positions when RSI begins moving back toward the basis line
Use the basis line as the initial profit target for mean reversion trades
Implement tight stops beyond the channel extremes to limit risk on failed reversals
Scale out of positions as RSI approaches the basis line and closes the position when RSI crosses the basis
Breakout Preparation Strategy:
This approach positions traders ahead of potential volatility expansion from consolidation phases:
Identify squeeze conditions when channel width reaches 100-period lows
Monitor price action for consolidation patterns (triangles, rectangles, flags) during the squeeze
Prepare conditional orders for breakouts in both directions from the consolidation
Enter positions when RSI breaks out of the narrow channel with expanding width
Use the channel width expansion as a confirmation signal for the breakout's validity
Manage risk with stops just inside the opposite channel boundary
Multi-Timeframe Confluence Strategy:
Combining RSI Donchian Channel analysis across multiple timeframes can improve signal reliability:
Identify the primary trend direction using a higher timeframe RSI Donchian Channel (e.g., daily or weekly)
Use a lower timeframe (e.g., 4-hour or hourly) to time precise entry points
Enter long positions when both timeframes show RSI above their respective basis lines
Enter short positions when both timeframes show RSI below their respective basis lines
Avoid trades when timeframes provide conflicting signals (e.g., higher timeframe below basis, lower timeframe above)
Exit when the higher timeframe RSI crosses its basis line in the opposite direction
Risk Management Guidelines:
Effective risk management is essential for all RSI Donchian Channel strategies:
Position Sizing: Calculate position sizes based on the distance between entry point and stop loss, limiting risk to 1-2% of capital per trade
Stop Loss Placement: For breakout trades, place stops just inside the opposite channel boundary; for mean reversion trades, use stops beyond the channel extremes
Profit Targets: Use the basis line as a minimum target for mean reversion trades; for trend trades, target prior swing extremes or use trailing stops
Channel Width Context: Increase position sizes during narrow channels (lower volatility) and reduce sizes during wide channels (higher volatility)
Correlation Awareness: Monitor correlations between traded instruments to avoid over-concentration in similar setups
📋 DETAILED PARAMETER CONFIGURATION
RSI Source:
Defines the price data series used for RSI calculation:
Close (Default): Standard choice providing end-of-period momentum assessment, suitable for most trading styles and timeframes
High-Low Average (HL2): Reduces the impact of closing auction dynamics, useful for markets with significant end-of-day volatility
High-Low-Close Average (HLC3): Provides a more balanced view incorporating the entire period's range
Open-High-Low-Close Average (OHLC4): Offers the most comprehensive price representation, helpful for identifying overall period sentiment
Strategy Consideration: Use Close for end-of-period signals, HL2 or HLC3 for intraday volatility reduction, OHLC4 for capturing full period dynamics
RSI Length:
Controls the number of periods used for RSI calculation:
Short Periods (5-9): Highly responsive to recent price changes, produces more frequent signals with increased false signal risk, suitable for short-term trading and volatile markets
Standard Period (14): Widely accepted default balancing responsiveness with stability, appropriate for swing trading and intermediate-term analysis
Long Periods (21-28): Produces smoother RSI with fewer signals but more reliable trend identification, better for position trading and reducing noise in choppy markets
Optimization Approach: Test different lengths against historical data for your specific market and timeframe, consider using longer periods in ranging markets and shorter periods in trending markets
RSI MA Type:
Determines the smoothing method applied to price changes in RSI calculation:
RMA (Relative Moving Average - Default): Wilder's original smoothing method providing stable momentum measurement with gradual response to changes, maintains consistency with classical RSI interpretation
SMA (Simple Moving Average): Treats all periods equally, responds more quickly to changes than RMA but may produce more whipsaws in volatile conditions
EMA (Exponential Moving Average): Weights recent periods more heavily, increases responsiveness at the cost of potential noise, suitable for traders prioritizing early signal generation
WMA (Weighted Moving Average): Applies linear weighting favoring recent data, offers a middle ground between SMA and EMA responsiveness
Selection Guidance: Maintain RMA for consistency with traditional RSI analysis, use EMA or WMA for more responsive signals in fast-moving markets, apply SMA for maximum simplicity and transparency
DC Length:
Specifies the lookback period for Donchian Channel calculation on RSI values:
Short Periods (10-14): Creates tight channels that adapt quickly to changing momentum conditions, generates more frequent trading signals but increases sensitivity to short-term RSI fluctuations
Standard Period (20): Balances channel responsiveness with stability, aligns with traditional Bollinger Bands and moving average periods, suitable for most trading styles
Long Periods (30-50): Produces wider, more stable channels that better represent sustained momentum extremes, reduces signal frequency while improving reliability, appropriate for position traders and higher timeframes
Calibration Strategy: Match DC length to your trading timeframe (shorter for day trading, longer for swing trading), test channel width behavior during different market regimes, consider using adaptive periods that adjust to volatility conditions
Market Adaptation: Use shorter DC lengths in trending markets to capture momentum shifts earlier, apply longer periods in ranging markets to filter noise and focus on significant extremes
Parameter Combination Recommendations:
Scalping/Day Trading: RSI Length 5-9, DC Length 10-14, EMA or WMA smoothing for maximum responsiveness
Swing Trading: RSI Length 14, DC Length 20, RMA smoothing for balanced analysis (default configuration)
Position Trading: RSI Length 21-28, DC Length 30-50, RMA or SMA smoothing for stable signals
High Volatility Markets: Longer RSI periods (21+) with standard DC length (20) to reduce noise
Low Volatility Markets: Standard RSI length (14) with shorter DC length (10-14) to capture subtle momentum shifts
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Adaptive Threshold Mechanism:
Unlike traditional RSI analysis with fixed 30/70 thresholds, this indicator's Donchian Channel approach provides several improvements:
Context-Aware Extremes: Overbought/oversold levels adjust automatically based on recent momentum behavior rather than arbitrary fixed values
Volatility Adaptation: In low volatility periods, channels narrow to reflect tighter momentum ranges; in high volatility, channels widen appropriately
Market Regime Recognition: The indicator implicitly adapts to different market conditions without manual threshold adjustments
False Signal Reduction: Adaptive channels help reduce premature reversal signals that often occur with fixed thresholds during strong trends
Signal Quality Characteristics:
The indicator's dual-purpose design provides distinct advantages for different trading objectives:
Breakout Trading: Channel boundaries offer clear, objective breakout levels that update dynamically, eliminating the ambiguity of when momentum becomes "too high" or "too low"
Mean Reversion: The basis line provides a natural profit target for reversion trades, representing the midpoint of recent momentum extremes
Trend Strength: Persistent channel boundary riding offers an objective measure of trend strength without additional indicators
Consolidation Detection: Channel width analysis provides early warning of potential volatility expansion from compression phases
Comparative Analysis:
When compared to traditional RSI implementations and other momentum frameworks:
vs. Fixed Threshold RSI: Provides market-adaptive reference levels rather than static values, helping to reduce false signals during trending markets where RSI can remain "overbought" or "oversold" for extended periods
vs. RSI Bollinger Bands: Offers clearer breakout signals and more intuitive extreme identification through actual high/low boundaries rather than statistical standard deviations
vs. Stochastic Oscillator: Maintains RSI's momentum measurement advantages (unbounded calculation avoiding scale compression) while adding the breakout detection capabilities of Donchian Channels
vs. Standard Donchian Channels: Applies breakout methodology to momentum space rather than price, providing earlier signals of potential trend changes before price breakouts occur
Performance Characteristics:
The indicator exhibits specific behavioral patterns across different market conditions:
Trending Markets: Excels at identifying momentum continuation through channel breakouts, RSI tends to ride one channel boundary during strong trends, providing trend confirmation
Ranging Markets: Channel width narrows during consolidation, offering early preparation signals for potential breakout trading opportunities
High Volatility: Channels widen to reflect increased momentum variability, automatically adjusting signal sensitivity to match market conditions
Low Volatility: Channels contract, making the indicator more sensitive to subtle momentum shifts that may be significant in calm market environments
Transition Periods: Channel squeezes often precede major trend changes, offering advance warning of potential regime shifts
Limitations and Considerations:
Users should be aware of certain operational characteristics:
Lookback Dependency: Channel boundaries depend entirely on the lookback period, meaning the indicator has no predictive element beyond identifying current momentum relative to recent history
Lag Characteristics: As with all moving average-based indicators, RSI calculation introduces lag, and channel boundaries update only as new extremes occur within the lookback window
Range-Bound Sensitivity: In extremely tight ranges, channels may become very narrow, potentially generating excessive signals from minor momentum fluctuations
Trending Persistence: During very strong trends, RSI may remain at channel extremes for extended periods, requiring patience for mean reversion setups or commitment to trend-following approaches
No Absolute Levels: Unlike traditional RSI, this indicator provides no fixed reference points (like 50), making it less suitable for strategies that depend on absolute momentum readings
USAGE NOTES
This indicator is designed for technical analysis and educational purposes to help traders understand momentum dynamics and identify potential trading opportunities. The RSI Donchian Channel has limitations and should not be used as the sole basis for trading decisions.
Important considerations:
Performance varies significantly across different market conditions, timeframes, and instruments
Historical signal patterns do not guarantee future results, as market behavior continuously evolves
Effective use requires understanding of both RSI momentum principles and Donchian Channel breakout concepts
Risk management practices (stop losses, position sizing, diversification) are essential for any trading application
Consider combining with additional analytical tools such as volume analysis, price action patterns, or trend indicators for confirmation
Backtest thoroughly on your specific instruments and timeframes before live trading implementation
Be aware that optimization on historical data may lead to curve-fitting and poor forward performance
The indicator performs best when used as part of a comprehensive trading methodology that incorporates multiple forms of market analysis, sound risk management, and realistic expectations about win rates and drawdowns.
Uptrick: Volatility Adjusted TrailIntroduction
The "Uptrick: Volatility Adjusted Trail" is a dynamic trailing band indicator. It adapts in real time to changing market conditions by adjusting both to volatility and trend consistency. Inspired by Supertrend-style logic, it enhances traditional approaches by introducing adaptive mechanisms for more context-sensitive behavior in both trending and consolidating environments.
Overview
This indicator combines an exponential moving average (EMA) as its basis with an Average True Range (ATR)-derived multiplier that adjusts dynamically. Unlike fixed-multiplier tools, this indicator modifies its band distances in real time according to volatility expansion and trend persistence. The result is a trailing system that adapts to the prevailing market regime, providing traders with clearer signals for trend bias, stop placement, and potential momentum shifts.
Originality
The script’s originality lies in its multi-layered approach to trail calculation. It introduces a real-time ATR multiplier adjustment driven by two factors: a volatility expansion ratio and a trend persistence model. The expansion ratio compares the current ATR to its moving average, making the indicator more sensitive during volatile conditions and less sensitive during quieter periods. The trend persistence model assesses directional consistency to widen the bands during sustained trends. This dual adjustment method creates a system that evolves with market behavior, making it more responsive and adaptive than static-band or fixed-multiplier alternatives.
Components & Inspiration
This indicator was designed with specific components that work together:
Exponential Moving Average (EMA): Chosen as the central baseline because it responds faster to recent price changes than a simple moving average, providing a more current reference for trailing bands.
Average True Range (ATR): Used as the volatility measure because it accounts for both intraday and gap movement, making it a robust and widely accepted standard for market volatility.
Dynamic Multiplier: The multiplier is adjusted by both volatility expansion and trend persistence to produce bands that tighten during low volatility and widen during consistent trends. This combination was chosen to give the indicator the ability to self-regulate across different market regimes.
Trend Persistence Model: Integrated to assess directional consistency, ensuring the bands expand during strong trends, which can prevent premature stop-outs.
Flip Confirmation Logic: Added to filter out noise by requiring multiple bar closes beyond a band before confirming a state change, reducing false reversals.
For inspiration, the indicator draws on the core idea behind Supertrend—using a baseline and volatility-derived bands to define trailing stop levels. However, while Supertrend uses a fixed ATR multiplier, this indicator introduces a dynamic multiplier system and persistence weighting, making it more adaptive and suited for varying conditions.
Inputs and Parameters
Basis EMA Length
Defines the period for the EMA that serves as the core price reference.
ATR Length
Sets the lookback period for the Average True Range calculation used in band spacing.
Base ATR Mult
The base multiplier applied to ATR before adjustments. Forms the starting scale of the band offset.
Volatility Expansion Sensitivity
Controls how strongly the band spacing reacts to short-term volatility bursts. Higher values create more pronounced band expansions or contractions.
Trend Persistence Window
Determines how many bars are used to calculate directional trend consistency using a smoothed step function.
Persistence Impact
Scales how much influence the trend persistence has on band widening. Values range from 0 (no effect) to 1 (maximum effect).
Min Effective Mult
Sets the minimum value that the adjusted multiplier can reach. Prevents the bands from becoming too narrow.
Max Effective Mult
Sets the maximum value the adjusted multiplier can reach. Prevents the bands from over-expanding during high volatility.
Bars Above/Below to Confirm Flip
Number of consecutive bars required to close above or below the opposing trail before confirming a bullish or bearish flip. Helps reduce noise and false signals.
Show Flip Labels
Enables or disables the display of flip markers on the chart.
Label Size
Allows users to adjust the size of flip labels from Tiny to Huge.
Label ATR Offset
Adjusts the vertical placement of flip labels in relation to the trail using an ATR-based offset.
Features and Logic
EMA Basis: All calculations stem from an EMA that tracks the centerline of price action.
Dynamic ATR Multiplier: The ATR multiplier adjusts in real time based on volatility expansion and trend persistence.
Clamped Multiplier: The adjusted multiplier is limited between user-defined minimum and maximum values to keep the band scale practical.
Upper and Lower Bands: Bands are plotted above and below the EMA using the dynamic multiplier and ATR values.
Trailing Logic: The script uses Supertrend-style trailing logic, updating the active band in the current trend direction and resetting the opposite band.
Trend State Detection: A state variable tracks the current market regime (bullish, bearish, or neutral). Transitions are confirmed only after a user-specified number of bars close beyond the respective bands.
Visual Elements: Trail lines and fill zones are color-coded (bullish cyan, bearish magenta). Candlestick and bar colors match the trend state. Optional flip labels mark confirmed transitions.
Alerts: Built-in alert conditions allow users to receive real-time notifications for bullish or bearish flips.
Usage Guidelines
This indicator can be used for:
Defining context-aware dynamic stop levels that adjust with market behavior.
Identifying trend direction and reversal points based on adaptive logic.
Filtering entry or exit signals during trending vs. consolidating conditions.
Supplementing trade management strategies with responsive visual markers.
Entering long or short positions based on the appearance of flip labels and managing stop losses by following the adaptive trail.
Traders may tune the parameters to suit different trading styles or timeframes. For example, lower ATR and EMA values may suit intraday setups, while longer settings may benefit swing or positional trading.
Summary
The "Uptrick: Volatility Adjusted Trail" provides a flexible, adaptive trailing band system that accounts for both volatility and directional consistency. By combining an EMA baseline with a dynamic ATR multiplier influenced by volatility expansion and trend persistence, it creates a context-sensitive trailing system that aligns with changing market conditions. Customizable confirmation, flip labels, alerts, and dynamic visual cues make it a versatile tool for trend-following, breakout filtering, and trailing stop logic.
Disclaimer
This indicator is provided for educational and research purposes only. It does not constitute financial advice. Trading involves risk, and past performance does not guarantee future results. Always conduct your own analysis and risk management before making trading decisions.
Stochastic %K Colored by VolumeDescription:
"Stochastic %K Colored by Volume is a technical indicator that combines the traditional Stochastic %K oscillator with volume-based coloring. It highlights periods of high, low, and neutral trading volume by changing the color of the %K line. Additionally, it identifies bullish and bearish divergences between price and the %K oscillator, helping traders spot potential reversals and trend changes. The indicator also includes key levels for overbought, oversold, and extreme zones to guide trading decisions."
- Standardized Money Flow Index with Multi-MA and BB OverlayThis custom Money Flow Index (MFI) script enhances the standard MFI by introducing multiple layers of configurability, statistical normalization, and visual clarity. It begins with the traditional MFI calculation using the average price, hlc3, and a user-defined length, then offers the option to standardize the output. Standardization transforms the MFI into a z-score by subtracting a rolling mean and dividing by a rolling standard deviation, making the indicator statistically interpretable across different assets, timeframes, and volatility regimes. When standardization is active, the overbought and oversold thresholds shift from the conventional 80 and 20 to +2 and –2, aligning them with standard deviation boundaries and improving signal clarity in volatile environments.
Beyond standardization, the script introduces a robust smoothing engine. Users can choose from several moving average types, including SMA, EMA, SMMA (RMA), WMA, and VWMA, to reduce noise and highlight trend shifts. A particularly advanced option is the “SMA + Bollinger Bands” mode, which overlays volatility envelopes around the smoothed MFI using a user-defined standard deviation multiplier. This feature helps traders identify when the MFI is unusually high or low relative to its recent behaviour, adding a volatility-adjusted layer of insight, especially useful in momentum or mean-reversion setups.
Visually, the script is designed for clarity, modularity, and flexibility. It plots the raw or standardized MFI in purple, overlays the smoothed version in yellow if enabled, and adds green Bollinger Bands when selected. It also includes horizontal reference lines for overbought, oversold, and midpoint levels, which dynamically adjust based on whether standardization is active. A shaded background between the overbought and oversold lines further enhances readability, helping traders quickly assess momentum extremes and potential inflection zones.
Compared to the standard MFI, which offers a fixed calculation, limited visual feedback, and no statistical context, this enhanced version is modular, customizable, and statistically grounded. It allows traders to tailor the indicator to their strategy, whether they prefer raw signals, smoothed trends, or volatility-adjusted extremes. These enhancements make it a powerful building block for more sophisticated signal engines, especially when combined with filter gating, persistent state logic, or multi-indicator overlays.
Arisa RSI Rebound Alert (v6.2)Short description:
Simple RSI-based rebound detection with ATR confirmation — designed for traders who prefer a clean and intuitive signal.
Full description:
This indicator detects oversold and rebound phases using RSI and confirms the strength of each rebound with ATR slope analysis.
It is optimized for deep correction phases (e.g. RSI 25→35 cross), helping traders catch early reversal signals while avoiding unnecessary noise.
💡 Recommended use:
• Timeframes: 30min–4h
• Ideal for short- to mid-term rebound trades
• Combine with Heikin-Ashi or volume expansion for higher accuracy
✨ Key Features:
• Clear oversold/rebound thresholds (default RSI <25 / cross-up >35)
• Background highlight for deep oversold conditions
• Visual markers for strong vs. weak rebounds (ATR slope filter)
• Alert-ready (three conditions included)
🪶 Concept:
This script is designed for traders who value simplicity and intuition — focusing on meaningful signals rather than automation overload.
It’s for those who still want to see and feel the market before taking action.
⸻
Author:
Arisa Sanjo (Japan)
Created with the support of GPT-5, based on live trading insights from October 2025.
License:
Free to use and modify with proper attribution.
If you redistribute or enhance this script, please mention “Based on Arisa RSI Rebound Alert (v6.2)” in your description.
Keltner Channel Enhanced [DCAUT]█ Keltner Channel Enhanced
📊 ORIGINALITY & INNOVATION
The Keltner Channel Enhanced represents an important advancement over standard Keltner Channel implementations by introducing dual flexibility in moving average selection for both the middle band and ATR calculation. While traditional Keltner Channels typically use EMA for the middle band and RMA (Wilder's smoothing) for ATR, this enhanced version provides access to 25+ moving average algorithms for both components, enabling traders to fine-tune the indicator's behavior to match specific market characteristics and trading approaches.
Key Advancements:
Dual MA Algorithm Flexibility: Independent selection of moving average types for middle band (25+ options) and ATR smoothing (25+ options), allowing optimization of both trend identification and volatility measurement separately
Enhanced Trend Sensitivity: Ability to use faster algorithms (HMA, T3) for middle band while maintaining stable volatility measurement with traditional ATR smoothing, or vice versa for different trading strategies
Adaptive Volatility Measurement: Choice of ATR smoothing algorithm affects channel responsiveness to volatility changes, from highly reactive (SMA, EMA) to smoothly adaptive (RMA, TEMA)
Comprehensive Alert System: Five distinct alert conditions covering breakouts, trend changes, and volatility expansion, enabling automated monitoring without constant chart observation
Multi-Timeframe Compatibility: Works effectively across all timeframes from intraday scalping to long-term position trading, with independent optimization of trend and volatility components
This implementation addresses key limitations of standard Keltner Channels: fixed EMA/RMA combination may not suit all market conditions or trading styles. By decoupling the trend component from volatility measurement and allowing independent algorithm selection, traders can create highly customized configurations for specific instruments and market phases.
📐 MATHEMATICAL FOUNDATION
Keltner Channel Enhanced uses a three-component calculation system that combines a flexible moving average middle band with ATR-based (Average True Range) upper and lower channels, creating volatility-adjusted trend-following bands.
Core Calculation Process:
1. Middle Band (Basis) Calculation:
The basis line is calculated using the selected moving average algorithm applied to the price source over the specified period:
basis = ma(source, length, maType)
Supported algorithms include EMA (standard choice, trend-biased), SMA (balanced and symmetric), HMA (reduced lag), WMA, VWMA, TEMA, T3, KAMA, and 17+ others.
2. Average True Range (ATR) Calculation:
ATR measures market volatility by calculating the average of true ranges over the specified period:
trueRange = max(high - low, abs(high - close ), abs(low - close ))
atrValue = ma(trueRange, atrLength, atrMaType)
ATR smoothing algorithm significantly affects channel behavior, with options including RMA (standard, very smooth), SMA (moderate smoothness), EMA (fast adaptation), TEMA (smooth yet responsive), and others.
3. Channel Calculation:
Upper and lower channels are positioned at specified multiples of ATR from the basis:
upperChannel = basis + (multiplier × atrValue)
lowerChannel = basis - (multiplier × atrValue)
Standard multiplier is 2.0, providing channels that dynamically adjust width based on market volatility.
Keltner Channel vs. Bollinger Bands - Key Differences:
While both indicators create volatility-based channels, they use fundamentally different volatility measures:
Keltner Channel (ATR-based):
Uses Average True Range to measure actual price movement volatility
Incorporates gaps and limit moves through true range calculation
More stable in trending markets, less prone to extreme compression
Better reflects intraday volatility and trading range
Typically fewer band touches, making touches more significant
More suitable for trend-following strategies
Bollinger Bands (Standard Deviation-based):
Uses statistical standard deviation to measure price dispersion
Based on closing prices only, doesn't account for intraday range
Can compress significantly during consolidation (squeeze patterns)
More touches in ranging markets
Better suited for mean-reversion strategies
Provides statistical probability framework (95% within 2 standard deviations)
Algorithm Combination Effects:
The interaction between middle band MA type and ATR MA type creates different indicator characteristics:
Trend-Focused Configuration (Fast MA + Slow ATR): Middle band uses HMA/EMA/T3, ATR uses RMA/TEMA, quick trend changes with stable channel width, suitable for trend-following
Volatility-Focused Configuration (Slow MA + Fast ATR): Middle band uses SMA/WMA, ATR uses EMA/SMA, stable trend with dynamic channel width, suitable for volatility trading
Balanced Configuration (Standard EMA/RMA): Classic Keltner Channel behavior, time-tested combination, suitable for general-purpose trend following
Adaptive Configuration (KAMA + KAMA): Self-adjusting indicator responding to efficiency ratio, suitable for markets with varying trend strength and volatility regimes
📊 COMPREHENSIVE SIGNAL ANALYSIS
Keltner Channel Enhanced provides multiple signal categories optimized for trend-following and breakout strategies.
Channel Position Signals:
Upper Channel Interaction:
Price Touching Upper Channel: Strong bullish momentum, price moving more than typical volatility range suggests, potential continuation signal in established uptrends
Price Breaking Above Upper Channel: Exceptional strength, price exceeding normal volatility expectations, consider adding to long positions or tightening trailing stops
Price Riding Upper Channel: Sustained strong uptrend, characteristic of powerful bull moves, stay with trend and avoid premature profit-taking
Price Rejection at Upper Channel: Momentum exhaustion signal, consider profit-taking on longs or waiting for pullback to middle band for reentry
Lower Channel Interaction:
Price Touching Lower Channel: Strong bearish momentum, price moving more than typical volatility range suggests, potential continuation signal in established downtrends
Price Breaking Below Lower Channel: Exceptional weakness, price exceeding normal volatility expectations, consider adding to short positions or protecting against further downside
Price Riding Lower Channel: Sustained strong downtrend, characteristic of powerful bear moves, stay with trend and avoid premature covering
Price Rejection at Lower Channel: Momentum exhaustion signal, consider covering shorts or waiting for bounce to middle band for reentry
Middle Band (Basis) Signals:
Trend Direction Confirmation:
Price Above Basis: Bullish trend bias, middle band acts as dynamic support in uptrends, consider long positions or holding existing longs
Price Below Basis: Bearish trend bias, middle band acts as dynamic resistance in downtrends, consider short positions or avoiding longs
Price Crossing Above Basis: Potential trend change from bearish to bullish, early signal to establish long positions
Price Crossing Below Basis: Potential trend change from bullish to bearish, early signal to establish short positions or exit longs
Pullback Trading Strategy:
Uptrend Pullback: Price pulls back from upper channel to middle band, finds support, and resumes upward, ideal long entry point
Downtrend Bounce: Price bounces from lower channel to middle band, meets resistance, and resumes downward, ideal short entry point
Basis Test: Strong trends often show price respecting the middle band as support/resistance on pullbacks
Failed Test: Price breaking through middle band against trend direction signals potential reversal
Volatility-Based Signals:
Narrow Channels (Low Volatility):
Consolidation Phase: Channels contract during periods of reduced volatility and directionless price action
Breakout Preparation: Narrow channels often precede significant directional moves as volatility cycles
Trading Approach: Reduce position sizes, wait for breakout confirmation, avoid range-bound strategies within channels
Breakout Direction: Monitor for price breaking decisively outside channel range with expanding width
Wide Channels (High Volatility):
Trending Phase: Channels expand during strong directional moves and increased volatility
Momentum Confirmation: Wide channels confirm genuine trend with substantial volatility backing
Trading Approach: Trend-following strategies excel, wider stops necessary, mean-reversion strategies risky
Exhaustion Signs: Extreme channel width (historical highs) may signal approaching consolidation or reversal
Advanced Pattern Recognition:
Channel Walking Pattern:
Upper Channel Walk: Price consistently touches or exceeds upper channel while staying above basis, very strong uptrend signal, hold longs aggressively
Lower Channel Walk: Price consistently touches or exceeds lower channel while staying below basis, very strong downtrend signal, hold shorts aggressively
Basis Support/Resistance: During channel walks, price typically uses middle band as support/resistance on minor pullbacks
Pattern Break: Price crossing basis during channel walk signals potential trend exhaustion
Squeeze and Release Pattern:
Squeeze Phase: Channels narrow significantly, price consolidates near middle band, volatility contracts
Direction Clues: Watch for price positioning relative to basis during squeeze (above = bullish bias, below = bearish bias)
Release Trigger: Price breaking outside narrow channel range with expanding width confirms breakout
Follow-Through: Measure squeeze height and project from breakout point for initial profit targets
Channel Expansion Pattern:
Breakout Confirmation: Rapid channel widening confirms volatility increase and genuine trend establishment
Entry Timing: Enter positions early in expansion phase before trend becomes overextended
Risk Management: Use channel width to size stops appropriately, wider channels require wider stops
Basis Bounce Pattern:
Clean Bounce: Price touches middle band and immediately reverses, confirms trend strength and entry opportunity
Multiple Bounces: Repeated basis bounces indicate strong, sustainable trend
Bounce Failure: Price penetrating basis signals weakening trend and potential reversal
Divergence Analysis:
Price/Channel Divergence: Price makes new high/low while staying within channel (not reaching outer band), suggests momentum weakening
Width/Price Divergence: Price breaks to new extremes but channel width contracts, suggests move lacks conviction
Reversal Signal: Divergences often precede trend reversals or significant consolidation periods
Multi-Timeframe Analysis:
Keltner Channels work particularly well in multi-timeframe trend-following approaches:
Three-Timeframe Alignment:
Higher Timeframe (Weekly/Daily): Identify major trend direction, note price position relative to basis and channels
Intermediate Timeframe (Daily/4H): Identify pullback opportunities within higher timeframe trend
Lower Timeframe (4H/1H): Time precise entries when price touches middle band or lower channel (in uptrends) with rejection
Optimal Entry Conditions:
Best Long Entries: Higher timeframe in uptrend (price above basis), intermediate timeframe pulls back to basis, lower timeframe shows rejection at middle band or lower channel
Best Short Entries: Higher timeframe in downtrend (price below basis), intermediate timeframe bounces to basis, lower timeframe shows rejection at middle band or upper channel
Risk Management: Use higher timeframe channel width to set position sizing, stops below/above higher timeframe channels
🎯 STRATEGIC APPLICATIONS
Keltner Channel Enhanced excels in trend-following and breakout strategies across different market conditions.
Trend Following Strategy:
Setup Requirements:
Identify established trend with price consistently on one side of basis line
Wait for pullback to middle band (basis) or brief penetration through it
Confirm trend resumption with price rejection at basis and move back toward outer channel
Enter in trend direction with stop beyond basis line
Entry Rules:
Uptrend Entry:
Price pulls back from upper channel to middle band, shows support at basis (bullish candlestick, momentum divergence)
Enter long on rejection/bounce from basis with stop 1-2 ATR below basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Downtrend Entry:
Price bounces from lower channel to middle band, shows resistance at basis (bearish candlestick, momentum divergence)
Enter short on rejection/reversal from basis with stop 1-2 ATR above basis
Aggressive: Enter on first touch; Conservative: Wait for confirmation candle
Trend Management:
Trailing Stop: Use basis line as dynamic trailing stop, exit if price closes beyond basis against position
Profit Taking: Take partial profits at opposite channel, move stops to basis
Position Additions: Add to winners on subsequent basis bounces if trend intact
Breakout Strategy:
Setup Requirements:
Identify consolidation period with contracting channel width
Monitor price action near middle band with reduced volatility
Wait for decisive breakout beyond channel range with expanding width
Enter in breakout direction after confirmation
Breakout Confirmation:
Price breaks clearly outside channel (upper for longs, lower for shorts), channel width begins expanding from contracted state
Volume increases significantly on breakout (if using volume analysis)
Price sustains outside channel for multiple bars without immediate reversal
Entry Approaches:
Aggressive: Enter on initial break with stop at opposite channel or basis, use smaller position size
Conservative: Wait for pullback to broken channel level, enter on rejection and resumption, tighter stop
Volatility-Based Position Sizing:
Adjust position sizing based on channel width (ATR-based volatility):
Wide Channels (High ATR): Reduce position size as stops must be wider, calculate position size using ATR-based risk calculation: Risk / (Stop Distance in ATR × ATR Value)
Narrow Channels (Low ATR): Increase position size as stops can be tighter, be cautious of impending volatility expansion
ATR-Based Risk Management: Use ATR-based risk calculations, position size = 0.01 × Capital / (2 × ATR), use multiples of ATR (1-2 ATR) for adaptive stops
Algorithm Selection Guidelines:
Different market conditions benefit from different algorithm combinations:
Strong Trending Markets: Middle band use EMA or HMA, ATR use RMA, capture trends quickly while maintaining stable channel width
Choppy/Ranging Markets: Middle band use SMA or WMA, ATR use SMA or WMA, avoid false trend signals while identifying genuine reversals
Volatile Markets: Middle band and ATR both use KAMA or FRAMA, self-adjusting to changing market conditions reduces manual optimization
Breakout Trading: Middle band use SMA, ATR use EMA or SMA, stable trend with dynamic channels highlights volatility expansion early
Scalping/Day Trading: Middle band use HMA or T3, ATR use EMA or TEMA, both components respond quickly
Position Trading: Middle band use EMA/TEMA/T3, ATR use RMA or TEMA, filter out noise for long-term trend-following
📋 DETAILED PARAMETER CONFIGURATION
Understanding and optimizing parameters is essential for adapting Keltner Channel Enhanced to specific trading approaches.
Source Parameter:
Close (Most Common): Uses closing price, reflects daily settlement, best for end-of-day analysis and position trading, standard choice
HL2 (Median Price): Smooths out closing bias, better represents full daily range in volatile markets, good for swing trading
HLC3 (Typical Price): Gives more weight to close while including full range, popular for intraday applications, slightly more responsive than HL2
OHLC4 (Average Price): Most comprehensive price representation, smoothest option, good for gap-prone markets or highly volatile instruments
Length Parameter:
Controls the lookback period for middle band (basis) calculation:
Short Periods (10-15): Very responsive to price changes, suitable for day trading and scalping, higher false signal rate
Standard Period (20 - Default): Represents approximately one month of trading, good balance between responsiveness and stability, suitable for swing and position trading
Medium Periods (30-50): Smoother trend identification, fewer false signals, better for position trading and longer holding periods
Long Periods (50+): Very smooth, identifies major trends only, minimal false signals but significant lag, suitable for long-term investment
Optimization by Timeframe: 1-15 minute charts use 10-20 period, 30-60 minute charts use 20-30 period, 4-hour to daily charts use 20-40 period, weekly charts use 20-30 weeks.
ATR Length Parameter:
Controls the lookback period for Average True Range calculation, affecting channel width:
Short ATR Periods (5-10): Very responsive to recent volatility changes, standard is 10 (Keltner's original specification), may be too reactive in whipsaw conditions
Standard ATR Period (10 - Default): Chester Keltner's original specification, good balance between responsiveness and stability, most widely used
Medium ATR Periods (14-20): Smoother channel width, ATR 14 aligns with Wilder's original ATR specification, good for position trading
Long ATR Periods (20+): Very smooth channel width, suitable for long-term trend-following
Length vs. ATR Length Relationship: Equal values (20/20) provide balanced responsiveness, longer ATR (20/14) gives more stable channel width, shorter ATR (20/10) is standard configuration, much shorter ATR (20/5) creates very dynamic channels.
Multiplier Parameter:
Controls channel width by setting ATR multiples:
Lower Values (1.0-1.5): Tighter channels with frequent price touches, more trading signals, higher false signal rate, better for range-bound and mean-reversion strategies
Standard Value (2.0 - Default): Chester Keltner's recommended setting, good balance between signal frequency and reliability, suitable for both trending and ranging strategies
Higher Values (2.5-3.0): Wider channels with less frequent touches, fewer but potentially higher-quality signals, better for strong trending markets
Market-Specific Optimization: High volatility markets (crypto, small-caps) use 2.5-3.0 multiplier, medium volatility markets (major forex, large-caps) use 2.0 multiplier, low volatility markets (bonds, utilities) use 1.5-2.0 multiplier.
MA Type Parameter (Middle Band):
Critical selection that determines trend identification characteristics:
EMA (Exponential Moving Average - Default): Standard Keltner Channel choice, Chester Keltner's original specification, emphasizes recent prices, faster response to trend changes, suitable for all timeframes
SMA (Simple Moving Average): Equal weighting of all data points, no directional bias, slower than EMA, better for ranging markets and mean-reversion
HMA (Hull Moving Average): Minimal lag with smooth output, excellent for fast trend identification, best for day trading and scalping
TEMA (Triple Exponential Moving Average): Advanced smoothing with reduced lag, responsive to trends while filtering noise, suitable for volatile markets
T3 (Tillson T3): Very smooth with minimal lag, excellent for established trend identification, suitable for position trading
KAMA (Kaufman Adaptive Moving Average): Automatically adjusts speed based on market efficiency, slow in ranging markets, fast in trends, suitable for markets with varying conditions
ATR MA Type Parameter:
Determines how Average True Range is smoothed, affecting channel width stability:
RMA (Wilder's Smoothing - Default): J. Welles Wilder's original ATR smoothing method, very smooth, slow to adapt to volatility changes, provides stable channel width
SMA (Simple Moving Average): Equal weighting, moderate smoothness, faster response to volatility changes than RMA, more dynamic channel width
EMA (Exponential Moving Average): Emphasizes recent volatility, quick adaptation to new volatility regimes, very responsive channel width changes
TEMA (Triple Exponential Moving Average): Smooth yet responsive, good balance for varying volatility, suitable for most trading styles
Parameter Combination Strategies:
Conservative Trend-Following: Length 30/ATR Length 20/Multiplier 2.5, MA Type EMA or TEMA/ATR MA Type RMA, smooth trend with stable wide channels, suitable for position trading
Standard Balanced Approach: Length 20/ATR Length 10/Multiplier 2.0, MA Type EMA/ATR MA Type RMA, classic Keltner Channel configuration, suitable for general purpose swing trading
Aggressive Day Trading: Length 10-15/ATR Length 5-7/Multiplier 1.5-2.0, MA Type HMA or EMA/ATR MA Type EMA or SMA, fast trend with dynamic channels, suitable for scalping and day trading
Breakout Specialist: Length 20-30/ATR Length 5-10/Multiplier 2.0, MA Type SMA or WMA/ATR MA Type EMA or SMA, stable trend with responsive channel width
Adaptive All-Conditions: Length 20/ATR Length 10/Multiplier 2.0, MA Type KAMA or FRAMA/ATR MA Type KAMA or TEMA, self-adjusting to market conditions
Offset Parameter:
Controls horizontal positioning of channels on chart. Positive values shift channels to the right (future) for visual projection, negative values shift left (past) for historical analysis, zero (default) aligns with current price bars for real-time signal analysis. Offset affects only visual display, not alert conditions or actual calculations.
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Keltner Channel Enhanced provides improvements over standard implementations while maintaining proven effectiveness.
Response Characteristics:
Standard EMA/RMA Configuration: Moderate trend lag (approximately 0.4 × length periods), smooth and stable channel width from RMA smoothing, good balance for most market conditions
Fast HMA/EMA Configuration: Approximately 60% reduction in trend lag compared to EMA, responsive channel width from EMA ATR smoothing, suitable for quick trend changes and breakouts
Adaptive KAMA/KAMA Configuration: Variable lag based on market efficiency, automatic adjustment to trending vs. ranging conditions, self-optimizing behavior reduces manual intervention
Comparison with Traditional Keltner Channels:
Enhanced Version Advantages:
Dual Algorithm Flexibility: Independent MA selection for trend and volatility vs. fixed EMA/RMA, separate tuning of trend responsiveness and channel stability
Market Adaptation: Choose configurations optimized for specific instruments and conditions, customize for scalping, swing, or position trading preferences
Comprehensive Alerts: Enhanced alert system including channel expansion detection
Traditional Version Advantages:
Simplicity: Fewer parameters, easier to understand and implement
Standardization: Fixed EMA/RMA combination ensures consistency across users
Research Base: Decades of backtesting and research on standard configuration
When to Use Enhanced Version: Trading multiple instruments with different characteristics, switching between trending and ranging markets, employing different strategies, algorithm-based trading systems requiring customization, seeking optimization for specific trading style and timeframe.
When to Use Standard Version: Beginning traders learning Keltner Channel concepts, following published research or trading systems, preferring simplicity and standardization, wanting to avoid optimization and curve-fitting risks.
Performance Across Market Conditions:
Strong Trending Markets: EMA or HMA basis with RMA or TEMA ATR smoothing provides quicker trend identification, pullbacks to basis offer excellent entry opportunities
Choppy/Ranging Markets: SMA or WMA basis with RMA ATR smoothing and lower multipliers, channel bounce strategies work well, avoid false breakouts
Volatile Markets: KAMA or FRAMA with EMA or TEMA, adaptive algorithms excel by automatic adjustment, wider multipliers (2.5-3.0) accommodate large price swings
Low Volatility/Consolidation: Channels narrow significantly indicating consolidation, algorithm choice less impactful, focus on detecting channel width contraction for breakout preparation
Keltner Channel vs. Bollinger Bands - Usage Comparison:
Favor Keltner Channels When: Trend-following is primary strategy, trading volatile instruments with gaps, want ATR-based volatility measurement, prefer fewer higher-quality channel touches, seeking stable channel width during trends.
Favor Bollinger Bands When: Mean-reversion is primary strategy, trading instruments with limited gaps, want statistical framework based on standard deviation, need squeeze patterns for breakout identification, prefer more frequent trading opportunities.
Use Both Together: Bollinger Band squeeze + Keltner Channel breakout is powerful combination, price outside Bollinger Bands but inside Keltner Channels indicates moderate signal, price outside both indicates very strong signal, Bollinger Bands for entries and Keltner Channels for trend confirmation.
Limitations and Considerations:
General Limitations:
Lagging Indicator: All moving averages lag price, even with reduced-lag algorithms
Trend-Dependent: Works best in trending markets, less effective in choppy conditions
No Direction Prediction: Indicates volatility and deviation, not future direction, requires confirmation
Enhanced Version Specific Considerations:
Optimization Risk: More parameters increase risk of curve-fitting historical data
Complexity: Additional choices may overwhelm beginning traders
Backtesting Challenges: Different algorithms produce different historical results
Mitigation Strategies:
Use Confirmation: Combine with momentum indicators (RSI, MACD), volume, or price action
Test Parameter Robustness: Ensure parameters work across range of values, not just optimized ones
Multi-Timeframe Analysis: Confirm signals across different timeframes
Proper Risk Management: Use appropriate position sizing and stops
Start Simple: Begin with standard EMA/RMA before exploring alternatives
Optimal Usage Recommendations:
For Maximum Effectiveness:
Start with standard EMA/RMA configuration to understand classic behavior
Experiment with alternatives on demo account or paper trading
Match algorithm combination to market condition and trading style
Use channel width analysis to identify market phases
Combine with complementary indicators for confirmation
Implement strict risk management using ATR-based position sizing
Focus on high-quality setups rather than trading every signal
Respect the trend: trade with basis direction for higher probability
Complementary Indicators:
RSI or Stochastic: Confirm momentum at channel extremes
MACD: Confirm trend direction and momentum shifts
Volume: Validate breakouts and trend strength
ADX: Measure trend strength, avoid Keltner signals in weak trends
Support/Resistance: Combine with traditional levels for high-probability setups
Bollinger Bands: Use together for enhanced breakout and volatility analysis
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. Keltner Channel Enhanced has limitations and should not be used as the sole basis for trading decisions. While the flexible moving average selection for both trend and volatility components provides valuable adaptability across different market conditions, algorithm performance varies with market conditions, and past characteristics do not guarantee future results.
Key considerations:
Always use multiple forms of analysis and confirmation before entering trades
Backtest any parameter combination thoroughly before live trading
Be aware that optimization can lead to curve-fitting if not done carefully
Start with standard EMA/RMA settings and adjust only when specific conditions warrant
Understand that no moving average algorithm can eliminate lag entirely
Consider market regime (trending, ranging, volatile) when selecting parameters
Use ATR-based position sizing and risk management on every trade
Keltner Channels work best in trending markets, less effective in choppy conditions
Respect the trend direction indicated by price position relative to basis line
The enhanced flexibility of dual algorithm selection provides powerful tools for adaptation but requires responsible use, thorough understanding of how different algorithms behave under various market conditions, and disciplined risk management.
SPYDER ORBITSPYDER ORBIT is an adaptation of the original Kaiser Windowed Sinc Moving Average by The_Peaceful_Lizard.
This version adds the dynamic standard deviation bands with the precision of a Kaiser windowed sinc filter for ultra-smooth, low-lag trend extraction — ideal for identifying dominant directional bias while minimizing market noise.
Around this smoothed orbit, SPYDER ORBIT adds multi-level deviation envelopes (1σ, 2σ, 3σ) to visualize volatility expansion and contraction zones. These act like adaptive shells, helping identify exhaustion, breakout volatility, and mean-reversion opportunities.
Credits:
Sinc MA © The_Peaceful_Lizard
Parabolic SAR MTF LinesThe indicator shows the Parabolic SAR sign (price above or below the indicator) for several timeframes at once. You can see at a glance how the price is trending across higher and lower timeframes.
Note that, for lower timeframes, the line becomes yellow to the left because history is limited and there are not enough bars to calculate.
Other features (can be enabled in settings):
* each line can be enabled or disabled individually, so that unused ones can be hidden.
* simple trend detection based on the number of bullish and bearish timeframes; threshold can be changed in Settings.
* "Score" output: counting the net number of bullish and bearish timeframes
* "Trend" output: changes to bullish or bearish as the score goes over or under the threshold
* background color (green or red according to trend).
* alert for trend change.
* another alert with a separate threshold score for flexibility.
* score weights for further customization of trend detection and alerts. Input parameters are set in terms of score values instead of number of lines.
* input options to choose alert modes for trend and extra alerts. The options are "once per bar close" (default), "once per bar", "every time".
This indicator was based on MACD MTF Lines where all the logic and features came from.
Crypto Mean Reversion System (Pullback & Bounce)Mean Reversion Theory
The indicator operates on the principle that extreme price movements in crypto markets tend to revert toward their mean over time.
Consider this a valuable aid for your dollar-cost averaging strategy, effectively identifying periods ripe for accumulating or divesting from the market.
Research shows that:
Short-term momentum often persists briefly after surges, but extreme moves trigger mean reversion
Sharp drops exhibit strong bounce patterns, especially after capitulation events
Longer timeframes (7-day) show stronger mean reversion tendencies than shorter ones (1-day)
Timeframe Analysis
1-Day Timeframe
Pullback probabilities: 45-85% depending on surge magnitude
Bounce probabilities: 55-95% depending on drop severity
Captures immediate overextension and panic selling
More volatile but faster signal generation
7-Day Timeframe
Pullback probabilities: 50-90% (higher confidence)
Bounce probabilities: 50-90% (slightly moderated)
Filters out noise and identifies sustained trends
Stronger mean reversion signals due to extended moves
Probability Tiers
Pullback Risk (After Surges)
Moderate (45-60%): 5-10% surge → Expected -3% to -12% pullback
High (55-70%): 10-15% surge → Expected -5% to -18% pullback
Very High (65-80%): 15-25% surge → Expected -10% to -25% pullback
Extreme (75-90%): 25%+ surge → Expected -15% to -40% pullback
Bounce Probability (After Drops)
Moderate (55-65%): -5% to -10% drop → Expected +3% to +10% bounce
High (65-75%): -10% to -15% drop → Expected +6% to +18% bounce
Very High (75-85%): -15% to -25% drop → Expected +10% to +30% bounce
Extreme (85-95%): -25%+ drop → Expected +18% to +45% bounce
The probability ranges are derived from:
Crypto volatility patterns: Higher volatility than traditional assets creates stronger mean reversion
Behavioral finance: Extreme moves trigger emotional trading (FOMO/panic) that reverses
Historical backtesting: Probability estimates based on typical reversion patterns in crypto markets
Timeframe correlation: Longer timeframes show increased reversion probability due to reduced noise
Key Features
Dual-direction signals: Identifies both overbought (pullback) and oversold (bounce) conditions
Multi-timeframe confirmation: 1D and 7D analysis for different trading styles
Customizable thresholds: Adjust sensitivity based on asset volatility
Visual alerts: Color-coded labels and table for quick assessment
Risk categorization: Clear severity levels for position sizing
Total Info Indicator by MikePenzin
Install & Add to Chart
• Copy the script into Pine Editor → click Add to Chart .
• Open the ⚙️ Settings → Inputs to customize.
What It Does
• Displays key info in a floating table — trend, volume, ATR, RSI, stop loss, and more.
• Detects breakouts , smart SELL signals , and opening strength .
• Uses emojis and colours to make trends easy to read: 🟢 good, 🟡 neutral, 🔴 risky.
For Swing Traders
• Works best on Daily or 4H charts.
• Watch for 🟢 Uptrend + ⚡BUY / 🔥BUY breakout signals.
• Use ATR-based Stop Loss (shown in table).
• Avoid new entries a few days before earnings.
Suggested Setup
• 20/50/150 MA Lines: ON
• 200 MA Line: optional
• ATR Multiplier: 1.3
• Breakout Detection: ON (Volume + RSI + Trend filters)
• Smart SELLs: ON (RSI 70, EMA 20)
• Pivots: ON for quick swing levels
How to Read
• MA Row: 🟢 = price above MA (bullish).
• ATR/Stop Loss: Suggests where to place protective stop.
• Volume Info: Today’s vs 20-day average, plus pace.
• RSI & CCI: Shows momentum and overbought/oversold levels.
• Breakouts: ⚡BUY (early), 🔥BUY (confirmed).
• Smart SELLs: RSI🔴 / DIV🟣 / EMA🔵 mean potential exit zones.
Example Use
1️⃣ Find stocks with Uptrend 🟢 , rising volume, and ⚡BUY signal.
2️⃣ Enter near breakout; set Stop = shown level.
3️⃣ Take profits or trail when Smart SELLs appear or RSI peaks.
Tips
• Choose table corner under “Table Visualization.”
• Reduce clutter on small timeframes (turn off Pivots/200 MA).
• Use “Volume speed” to spot surging interest before breakouts.
• Compatible with most equities and ETFs.
Disclaimer
This script is for education & analysis only .
Not financial advice — always manage your own risk.
Wilder's ADX/DIワイルダー氏が作ったトレンドの強弱を計るインジケーターです。証券会社のものは微妙に計算式が違うため、ワイルダー氏のオリジナルの計算式で作りました。
It’s an indicator created by Mr. Wilder to measure the strength of a trend.
Since the calculation formulas used by brokerage firms vary slightly, this version is built using Mr. Wilder’s original formula.
Commodity Pulse Matrix (CPM) [WavesUnchained] [Strategy]Commodity Pulse Matrix (CPM) - Strategy Version
⚠️ Development Status
ACTIVE DEVELOPMENT - This strategy is currently under heavy development and optimization. The risk management settings, entry/exit logic, and parameter tuning are still being refined and are NOT yet satisfactory for live trading.
Current development areas:
Stop-loss and take-profit optimization
Position sizing and risk management
Entry timing and signal filtering
Backtest validation across different market conditions
⚠️ Use for testing and backtesting only - NOT recommended for live trading yet!
For detailed information about the underlying indicator logic, signals, and analysis methods, please refer to the Commodity Pulse Matrix (CPM) indicator description.
Overview
The CPM Strategy is an automated trading system based on the Commodity Pulse Matrix indicator. It converts the indicator's multi-timeframe confluence signals into executable trades with dynamic ATR-based risk management.
Strategy Core Features
Signal Sources
The strategy trades based on:
Strong Buy/Sell signals from the CPM indicator
Multi-timeframe alignment (configurable: 3/3, 2/3, or score-only)
EMA-200 trend filter (prevents counter-trend entries)
Dynamic signal cooldown (5-8 bars)
Optional reversal zone signals (triple-confirmed)
Risk Management (ATR-Based)
Stop-Loss & Take-Profit
Stop-Loss: 2.5x ATR (default) - Dynamic distance based on volatility
Take-Profit: 4.0x ATR (default) - Risk/Reward ratio of 1.6:1
ATR Length: 14 periods (adjustable)
Both SL and TP adjust to current market volatility
Trailing Stop (Optional)
Enabled by default
Trails at 2.5x ATR distance
Protects profits in trending moves
Can be disabled for fixed SL/TP only
Position Management
Trade Direction Filter
Both Directions (default) - Trade both Long and Short
Long Only - Only enter long positions
Short Only - Only enter short positions
Cooldown After Exit
Default: 3 bars minimum after closing a position
Prevents immediate re-entry (whipsaw protection)
Adjustable from 0 (disabled) to any number of bars
Signal Filtering
Signal Mode (Timeframe Consensus)
Strict (3/3 TFs): All 3 timeframes must agree - Most conservative
Majority (2/3 TFs): At least 2 of 3 timeframes agree - Balanced (default)
Flexible (Score Only): Overall score threshold only - Most signals
Optional Filters
Min ABS(overallScore): Only trade when confluence score meets minimum (default: 0 = disabled)
Confirmed Bar Only: Wait for bar close before entry (prevents repainting) - Recommended ON
Strategy Settings Guide
For Conservative Trading (Lower Risk)
Signal Mode: "Strict (3/3 TFs)"
Stop-Loss: 3.0x ATR or higher
Take-Profit: 5.0x ATR or higher
Trailing Stop: Enabled
Cooldown: 5-10 bars
Min Score: 8.0 or higher
For Aggressive Trading (More Signals)
Signal Mode: "Flexible (Score Only)"
Stop-Loss: 2.0x ATR
Take-Profit: 3.0x ATR
Trailing Stop: Optional
Cooldown: 0-3 bars
Min Score: 4.0 or disabled
For Balanced Trading (Recommended Starting Point)
Signal Mode: "Majority (2/3 TFs)"
Stop-Loss: 2.5x ATR
Take-Profit: 4.0x ATR
Trailing Stop: Enabled
Cooldown: 3 bars
Min Score: 6.0-8.0
TradingView Strategy Tester Settings
Essential Settings to Configure:
Properties Tab
Initial Capital: Set to realistic account size
Order Size: Use "% of Equity" (e.g., 10-25% per trade)
Commission: Set realistic commission (e.g., 0.05% for crypto, 0.1% for stocks)
Slippage: Add realistic slippage (1-3 ticks for liquid markets)
Verify "Recalculate: On Every Tick" is DISABLED (for realistic backtests)
Inputs Tab
Adjust ATR multipliers for your market
Set appropriate cooldown period
Choose signal mode based on desired trade frequency
Enable/disable trailing stop
Configure directional filter if needed
Backtesting Recommendations
Before Using This Strategy:
Test across multiple markets - What works for one commodity may not work for another
Test different timeframes - Strategy behavior changes significantly with TF
Test different market conditions - Trending vs ranging markets
Validate performance metrics - Win rate, profit factor, max drawdown, Sharpe ratio
Forward test on paper account - Before risking real capital
Key Metrics to Monitor:
Win Rate (aim for >40% minimum)
Profit Factor (aim for >1.5)
Max Drawdown (should be acceptable for your risk tolerance)
Sharpe Ratio (higher is better, >1.0 is good)
Average Trade (should be positive after commissions/slippage)
Known Limitations
Range-bound markets: May produce more whipsaws despite filters
Low volatility: ATR-based stops may be too tight
High volatility: ATR-based stops may be too wide
News events: Strategy cannot account for fundamental shocks
Signal timing: Entry timing is still being optimized
Indicator vs Strategy
When to use the Indicator:
- Manual trading with discretion
- Confluence analysis and timing
- Multiple signal validation
- Learning market structure
When to use the Strategy:
- Automated backtesting
- System validation
- Parameter optimization
- Performance measurement
⚠️ The indicator provides richer information and context than the strategy can execute!
Technical Details
Pine Script v6
Non-repainting: Uses confirmed bars for HTF data
Strategy type: Long/Short with dynamic stops
Risk management: ATR-based (adaptive to volatility)
Position sizing: Configured in Strategy Tester
Pyramiding: Default 1 (no adding to positions)
Important Notes
⚠️ Strategy parameters are still under optimization - Current settings may not be optimal for all markets or timeframes
⚠️ Backtest thoroughly before live trading - Test across different market conditions and timeframes
⚠️ Risk management is critical - Use appropriate position sizing (1-2% risk per trade recommended)
⚠️ Market conditions change - A strategy that works in trending markets may fail in ranging markets
⚠️ Commission and slippage matter - Always include realistic costs in backtests
✅ Start with conservative settings and optimize gradually
✅ Paper trade before going live
✅ Monitor performance and adjust as needed
✅ Never risk more than you can afford to lose
Disclaimer
Educational and testing purposes only. Not financial advice.
This strategy is provided as-is for backtesting and educational purposes. Past performance is not indicative of future results. Trading involves substantial risk of loss. The developer is not responsible for any losses incurred from using this strategy. Always do your own research, backtest thoroughly, and consult with a qualified financial advisor before making trading decisions.
NEVER use this strategy with real money until:
You have thoroughly backtested it on your specific market and timeframe
You understand all parameters and their impact
You have forward tested it on a paper account
You are comfortable with the maximum drawdown and risk profile
The strategy has been marked as production-ready by the developer
Version
v1.2 - Strategy Adapter (Active Development)
Based on: Commodity Pulse Matrix v1.2 Indicator
Last Updated: 2025-10-10
For detailed indicator documentation, see the Commodity Pulse Matrix (CPM) indicator description.
