Dskyz Adaptive Futures Elite (DAFE)Dskyz Adaptive Futures Edge (DAFE)
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A Dynamic Futures Trading Strategy
DAFE adapts to market volatility and price action using technical indicators and advanced risk management. It’s built for high-stakes futures trading (e.g., MNQ, BTCUSDT.P), offering modular logic for scalpers and swing traders alike.
Key Features
Adaptive Moving Averages
Dynamic Logic: Fast and slow SMAs adjust lengths via ATR, reacting to momentum shifts and smoothing in calm markets.
Signals: Long entry on fast SMA crossing above slow SMA with price confirmation; short on cross below.
RSI Filtering (Optional)
Momentum Check: Confirms entries with RSI crossovers (e.g., above oversold for longs). Toggle on/off with custom levels.
Fine-Tuning: Adjustable lookback and thresholds (e.g., 60/40) for precision.
Candlestick Pattern Recognition
Eng|Enhanced Detection: Identifies strong bullish/bearish engulfing patterns, validated by volume and range strength (vs. 10-period SMA).
Conflict Avoidance: Skips trades if both patterns appear in the lookback window, reducing whipsaws.
Multi-Timeframe Trend Filter
15-Minute Alignment: Syncs intrabar trades with 15-minute SMA trends; optional for flexibility.
Dollar-Cost Averaging (DCA) New!
Scaling: Adds up to a set number of entries (e.g., 4) on pullbacks/rallies, spaced by ATR multiples.
Control: Caps exposure and resets on exit, enhancing trend-following potential.
Trade Execution & Risk Management
Entry Rules: Prioritizes moving averages or patterns (user choice), with volume, volatility, and time filters.
Stops & Trails:
Initial Stop: ATR-based (2–3.5x, volatility-adjusted).
Trailing Stop: Locks profits with configurable ATR offset and multiplier.
Discipline
Cooldown: Pauses post-exit (e.g., 0–5 minutes).
Min Hold: Ensures trades last a set number of bars (e.g., 2–10).
Visualization & Tools
Charts: Overlays MAs, stops, and signals; trend shaded in background.
Dashboard: Shows position, P&L, win rate, and more in real-time.
Debugging: Logs signal details for optimization.
Input Parameters
Parameter Purpose Suggested Use
Use RSI Filter - Toggle RSI confirmation *Disable 4 price-only
trading
RSI Length - RSI period (e.g., 14) *7–14 for sensitivity
RSI Overbought/Oversold - Adjust for market type *Set levels (e.g., 60/40)
Use Candlestick Patterns - Enables engulfing signals *Disable for MA focus
Pattern Lookback - Pattern window (e.g., 19) *10–20 bars for balance
Use 15m Trend Filter - Align with 15-min trend *Enable for trend trades
Fast/Slow MA Length - Base MA lengths (e.g., 9/19) *10–25 / 30–60 per
timeframe
Volatility Threshold - Filters volatile spikes *Max ATR/close (e.g., 1%)
Min Volume - Entry volume threshold *Avoid illiquid periods
(e.g., 10)
ATR Length - ATR period (e.g., 14) *Standard volatility
measure
Trailing Stop ATR Offset - Trail distance (e.g., 0.5) *0.5–1.5 for tightness
Trailing Stop ATR Multi - Trail multiplier (e.g., 1.0) *1–3 for trend room
Cooldown Minutes - Post-exit pause (e.g., 0–5) *Prevents overtrading
Min Bars to Hold - Min trade duration (e.g., 2) *5–10 for intraday
Trading Hours - Active window (e.g., 9–16) *Focus on key sessions
Use DCA - Toggle DCA *Enable for scaling
Max DCA Entries - Cap entries (e.g., 4) *Limit risk exposure
DCA ATR Multiplier Entry spacing (e.g., 1.0) *1–2 for wider gaps
Compliance
Realistic Testing: Fixed quantities, capital, and slippage for accurate backtests.
Transparency: All logic is user-visible and adjustable.
Risk Controls: Cooldowns, stops, and hold periods ensure stability.
Flexibility: Adapts to various futures and timeframes.
Summary
DAFE excels in volatile futures markets with adaptive logic, DCA scaling, and robust risk tools. Currently in prop account testing, it’s a powerful framework for precision trading.
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
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Multi-Timeframe MACD Strategy ver 1.0Multi-Timeframe MACD Strategy: Enhanced Trend Trading with Customizable Entry and Trailing Stop
This strategy utilizes the Moving Average Convergence Divergence (MACD) indicator across multiple timeframes to identify strong trends, generate precise entry and exit signals, and manage risk with an optional trailing stop loss. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trade accuracy, reduce exposure to false signals, and capture larger market moves.
Key Features:
Dual Timeframe Analysis: Calculates and analyzes the MACD on both the current chart's timeframe and a user-selected higher timeframe (e.g., Daily MACD on a 1-hour chart). This provides a broader market context, helping to confirm trends and filter out short-term noise.
Configurable MACD: Fine-tune the MACD calculation with adjustable Fast Length, Slow Length, and Signal Length parameters. Optimize the indicator's sensitivity to match your trading style and the volatility of the asset.
Flexible Entry Options: Choose between three distinct entry types:
Crossover: Enters trades when the MACD line crosses above (long) or below (short) the Signal line.
Zero Cross: Enters trades when the MACD line crosses above (long) or below (short) the zero line.
Both: Combines both Crossover and Zero Cross signals, providing more potential entry opportunities.
Independent Timeframe Control: Display and trade based on the current timeframe MACD, the higher timeframe MACD, or both. This allows you to focus on the information most relevant to your analysis.
Optional Trailing Stop Loss: Implements a configurable trailing stop loss to protect profits and limit potential losses. The trailing stop is adjusted dynamically as the price moves in your favor, based on a user-defined percentage.
No Repainting: Employs lookahead=barmerge.lookahead_off in the request.security() function to prevent data leakage and ensure accurate backtesting and real-time signals.
Clear Visual Signals (Optional): Includes optional plotting of the MACD and Signal lines for both timeframes, with distinct colors for easy visual identification. These plots are for visual confirmation and are not required for the strategy's logic.
Suitable for Various Trading Styles: Adaptable to swing trading, day trading, and trend-following strategies across diverse markets (stocks, forex, cryptocurrencies, etc.).
Fully Customizable: All parameters are adjustable, including timeframes, MACD Settings, Entry signal type and trailing stop settings.
How it Works:
MACD Calculation: The strategy calculates the MACD (using the standard formula) for both the current chart's timeframe and the specified higher timeframe.
Trend Identification: The relationship between the MACD line, Signal line, and zero line is used to determine the current trend for each timeframe.
Entry Signals: Buy/sell signals are generated based on the selected "Entry Type":
Crossover: A long signal is generated when the MACD line crosses above the Signal line, and both timeframes are in agreement (if both are enabled). A short signal is generated when the MACD line crosses below the Signal line, and both timeframes are in agreement.
Zero Cross: A long signal is generated when the MACD line crosses above the zero line, and both timeframes agree. A short signal is generated when the MACD line crosses below the zero line and both timeframes agree.
Both: Combines Crossover and Zero Cross signals.
Trailing Stop Loss (Optional): If enabled, a trailing stop loss is set at a specified percentage below (for long positions) or above (for short positions) the entry price. The stop-loss is automatically adjusted as the price moves favorably.
Exit Signals:
Without Trailing Stop: Positions are closed when the MACD signals reverse according to the selected "Entry Type" (e.g., a long position is closed when the MACD line crosses below the Signal line if using "Crossover" entries).
With Trailing Stop: Positions are closed if the price hits the trailing stop loss.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to assess its performance and optimize parameters for different assets and timeframes.
Example Use Cases:
Confirming Trend Strength: A trader on a 1-hour chart sees a bullish MACD crossover on the current timeframe. They check the MTF MACD strategy and see that the Daily MACD is also bullish, confirming the strength of the uptrend.
Filtering Noise: A trader using a 15-minute chart wants to avoid false signals from short-term volatility. They use the strategy with a 4-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and enables the trailing stop loss. As the price rises, the trailing stop is automatically adjusted upwards, protecting profits. The trade is exited either when the MACD reverses or when the price hits the trailing stop.
Disclaimer:
The MACD is a lagging indicator and can produce false signals, especially in ranging markets. This strategy is for educational and informational purposes only and should not be considered financial advice. Backtest and optimize the strategy thoroughly, combine it with other technical analysis tools, and always implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Awesome Oscillator (AO) with Signals [AIBitcoinTrend]👽 Multi-Scale Awesome Oscillator (AO) with Signals (AIBitcoinTrend)
The Multi-Scale Awesome Oscillator transforms the traditional Awesome Oscillator (AO) by integrating multi-scale wavelet filtering, enhancing its ability to detect momentum shifts while maintaining responsiveness across different market conditions.
Unlike conventional AO calculations, this advanced version refines trend structures using high-frequency, medium-frequency, and low-frequency wavelet components, providing traders with superior clarity and adaptability.
Additionally, it features real-time divergence detection and an ATR-based dynamic trailing stop, making it a powerful tool for momentum analysis, reversals, and breakout strategies.
👽 What Makes the Multi-Scale AO – Wavelet-Enhanced Momentum Unique?
Unlike traditional AO indicators, this enhanced version leverages wavelet-based decomposition and volatility-adjusted normalization, ensuring improved signal consistency across various timeframes and assets.
✅ Wavelet Smoothing – Multi-Scale Extraction – Captures short-term fluctuations while preserving broader trend structures.
✅ Frequency-Based Detail Weights – Separates high, medium, and low-frequency components to reduce noise and improve trend clarity.
✅ Real-Time Divergence Detection – Identifies bullish and bearish divergences for early trend reversals.
✅ Crossovers & ATR-Based Trailing Stops – Implements intelligent trade management with adaptive stop-loss levels.
👽 The Math Behind the Indicator
👾 Wavelet-Based AO Smoothing
The indicator applies multi-scale wavelet decomposition to extract high-frequency, medium-frequency, and low-frequency trend components, ensuring an optimal balance between reactivity and smoothness.
sma1 = ta.sma(signal, waveletPeriod1)
sma2 = ta.sma(signal, waveletPeriod2)
sma3 = ta.sma(signal, waveletPeriod3)
detail1 = signal - sma1 // High-frequency detail
detail2 = sma1 - sma2 // Intermediate detail
detail3 = sma2 - sma3 // Low-frequency detail
advancedAO = weightDetail1 * detail1 + weightDetail2 * detail2 + weightDetail3 * detail3
Why It Works:
Short-Term Smoothing: Captures rapid fluctuations while minimizing noise.
Medium-Term Smoothing: Balances short-term and long-term trends.
Long-Term Smoothing: Enhances trend stability and reduces false signals.
👾 Z-Score Normalization
To ensure consistency across different markets, the Awesome Oscillator is normalized using a Z-score transformation, making overbought and oversold levels stable across all assets.
normFactor = ta.stdev(advancedAO, normPeriod)
normalizedAO = advancedAO / nz(normFactor, 1)
Why It Works:
Standardizes AO values for comparison across assets.
Enhances signal reliability, preventing misleading spikes.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence
Price makes a lower low, while AO forms a higher low.
A buy signal is confirmed when AO starts rising.
Bearish Divergence
Price makes a higher high, while AO forms a lower high.
A sell signal is confirmed when AO starts declining.
👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
✅AO crosses above the bullish trigger level → Buy Signal.
✅Trailing stop placed at Low - (ATR × Multiplier).
✅Exit if price crosses below the stop.
Bearish Setup:
✅AO crosses below the bearish trigger level → Sell Signal.
✅Trailing stop placed at High + (ATR × Multiplier).
✅Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Wavelet-Enhanced Filtering – Retains essential trend details while eliminating excessive noise.
Multi-Scale Momentum Analysis – Separates different trend frequencies for enhanced clarity.
Real-Time Divergence Alerts – Identifies early reversal signals for better entries and exits.
ATR-Based Risk Management – Ensures stops dynamically adapt to market conditions.
Works Across Markets & Timeframes – Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
AO Short Period – Defines the short-term moving average for AO calculation.
AO Long Period – Defines the long-term moving average for AO smoothing.
Wavelet Smoothing – Adjusts multi-scale decomposition for different market conditions.
Divergence Detection – Enables or disables real-time divergence analysis. Normalization Period – Sets the lookback period for standard deviation-based AO normalization.
Cross Signals Sensitivity – Controls crossover signal strength for buy/sell signals.
ATR Trailing Stop Multiplier – Adjusts the sensitivity of the trailing stop.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Enhanced ROC - Savitzky–Golay [AIBitcoinTrend]👽 Adaptive ROC - Savitzky–Golay (AIBitcoinTrend)
The Adaptive ROC - Savitzky–Golay redefines traditional Rate of Change (ROC) analysis by integrating Savitzky–Golay smoothing with volatility-adaptive normalization, allowing it to dynamically adjust across different market conditions. Unlike the standard ROC, which reacts rigidly to price changes, this advanced version refines trend signals while maintaining responsiveness to volatility.
Additionally, this indicator features real-time divergence detection and an ATR-based trailing stop system, equipping traders with a powerful toolset for momentum analysis, reversals, and trend-following strategies.
👽 What Makes the Adaptive ROC - Savitzky–Golay Unique?
Unlike conventional ROC indicators, this enhanced version leverages volatility-adjusted scaling and Z-score normalization to improve signal consistency across different timeframes and assets.
✅ Savitzky–Golay Smoothing – Reduces noise while preserving trend structure for clearer signals.
✅ Volatility-Adaptive Normalization – Ensures that overbought and oversold thresholds remain consistent across different markets.
✅ Real-Time Divergence Detection – Identifies early bullish and bearish divergence signals for potential reversals.
✅ Crossovers & ATR-Based Trailing Stops – Implements intelligent trade management with dynamic stop levels.
👽 The Math Behind the Indicator
👾 Savitzky–Golay Smoothing
The indicator applies a Savitzky–Golay filter to the raw ROC data, creating a smoother curve while preserving key inflection points. This technique prevents excessive lag while maintaining the integrity of price movements.
sg_roc = (roc_raw + 3*roc_raw + 5*roc_raw + 7*roc_raw + 5*roc_raw + 3*roc_raw + roc_raw ) / 25
👾 Volatility-Adaptive Scaling
By dynamically adjusting the smoothed ROC using standard deviation, the indicator ensures that momentum readings remain relative to the market’s current volatility.
volatility = ta.stdev(close, rocLength)
dynamicFactor = 1 / (1 + volatility / 100)
advanced_sg_roc = sg_roc * dynamicFactor
👾 Z-Score Normalization
To maintain a stable Overbought/Oversold structure across different markets, the ROC is normalized using a Z-score transformation, ensuring its values remain statistically relevant.
rocMean = ta.wma(advanced_sg_roc, lenZ)
rocStdev = ta.stdev(advanced_sg_roc, lenZ)
zRoc = (advanced_sg_roc - rocMean) / rocStdev
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence Setup:
Price makes a lower low, while the ROC forms a higher low.
A buy signal is confirmed when the ROC starts rising.
Bearish Divergence Setup:
Price makes a higher high, while the ROC forms a lower high.
A sell signal is confirmed when the ROC starts declining.
👾 Buy & Sell Signals with Trailing Stop
Bullish Setup:
✅ ROC crosses above the bullish trigger level → Buy Signal.
✅ A bullish trailing stop is placed at Low - (ATR × Multiplier).
✅ Exit if price crosses below the stop.
Bearish Setup:
✅ ROC crosses below the bearish trigger level → Sell Signal.
✅ A bearish trailing stop is placed at High + (ATR × Multiplier).
✅ Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Savitzky–Golay Filtering – Retains essential trend details while eliminating excessive noise.
Volatility-Adjusted Normalization – Makes overbought/oversold levels universally reliable across markets.
Real-Time Divergence Alerts – Identifies early reversal signals for optimal entries and exits.
ATR-Based Risk Management – Ensures stops dynamically adapt to market conditions.
Works Across Markets & Timeframes - Suitable for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
ROC Period – Defines the number of bars used for ROC calculation.
Smoothing Strength – Adjusts the degree of Savitzky–Golay filtering.
Volatility Scaling – Enables or disables the adaptive volatility factor.
Enable Divergence Analysis – Turns on real-time divergence detection.
Lookback Period – Specifies the pivot detection period for divergences.
Enable Crosses Signals – Activates trade signals based on ROC crossovers.
ATR Multiplier – Controls the sensitivity of the trailing stop.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Volatility-Enhanced Williams %R [AIBitcoinTrend]👽 Volatility-Enhanced Williams %R (AIBitcoinTrend)
The Volatility-Enhanced Williams %R takes the classic Williams %R oscillator to the next level by incorporating volatility-adaptive smoothing, making it significantly more responsive to market dynamics. Unlike the traditional version, which uses a fixed calculation method, this indicator dynamically adjusts its smoothing factor based on market volatility, helping traders capture trends more effectively while filtering out noise.
Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, providing traders with enhanced risk management tools and early reversal signals.
👽 What Makes the Volatility-Enhanced Williams %R Unique?
Unlike the standard Williams %R, which applies a simple lookback-based formula, this version integrates adaptive smoothing and volatility-based filtering to refine its signals and reduce false breakouts.
✅ Volatility-Adaptive Smoothing – Adjusts dynamically based on standard deviation, enhancing signal accuracy.
✅ Real-Time Divergence Detection – Identifies bullish and bearish divergences for early trend reversal signals.
✅ Crossovers & Trailing Stops – Implements Williams %R crossovers with ATR-based trailing stops for intelligent trade management.
👽 The Math Behind the Indicator
👾 Volatility-Adaptive Smoothing
The indicator smooths the Williams %R calculation by applying an adaptive filtering mechanism, which adjusts its responsiveness based on market conditions. This helps to eliminate whipsaws and makes trend-following strategies more reliable.
The smoothing function is defined as:
clamp(x, lo, hi) => math.min(math.max(x, lo), hi)
adaptive(src, prev, len, divisor, minAlpha, maxAlpha) =>
vol = ta.stdev(src, len)
alpha = clamp(vol / divisor, minAlpha, maxAlpha)
prev + alpha * (src - prev)
Where:
Volatility Factor (vol) measures price dispersion using standard deviation.
Adaptive Alpha (alpha) dynamically adjusts smoothing strength.
Clamped Output ensures that the smoothing factor remains within a stable range.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence Setup:
Price makes a lower low, while Williams %R forms a higher low.
Buy signal is confirmed when Williams %R reverses upward.
Bearish Divergence Setup:
Price makes a higher high, while Williams %R forms a lower high.
Sell signal is confirmed when Williams %R reverses downward.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅ Williams %R crosses above trigger level → Buy signal.
✅ A bullish trailing stop is placed at Low - (ATR × Multiplier).
✅ Exit if price crosses below the stop.
Bearish Setup:
✅ Williams %R crosses below trigger level → Sell signal.
✅ A bearish trailing stop is placed at High + (ATR × Multiplier).
✅ Exit if price crosses above the stop.
👽 Why It’s Useful for Traders
Adaptive Filtering Mechanism – Avoids excessive noise while maintaining responsiveness.
Real-Time Divergence Alerts – Helps traders anticipate market reversals before they occur.
ATR-Based Risk Management – Stops dynamically adjust based on market volatility.
Multi-Market Compatibility – Works effectively across stocks, forex, crypto, and futures.
👽 Indicator Settings
Smoothing Factor – Controls how aggressively the indicator adapts to volatility.
Enable Divergence Analysis – Activates real-time divergence detection.
Lookback Period – Defines the number of bars for detecting pivot points.
Enable Crosses Signals – Turns on Williams %R crossover-based trade signals.
ATR Multiplier – Adjusts trailing stop sensitivity.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
CCI with Signals & Divergence [AIBitcoinTrend]👽 CCI with Signals & Divergence (AIBitcoinTrend)
The Hilbert Adaptive CCI with Signals & Divergence takes the traditional Commodity Channel Index (CCI) to the next level by dynamically adjusting its calculation period based on real-time market cycles using Hilbert Transform Cycle Detection. This makes it far superior to standard CCI, as it adapts to fast-moving trends and slow consolidations, filtering noise and improving signal accuracy.
Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, helping traders identify potential reversals and manage risk effectively.
👽 What Makes the Hilbert Adaptive CCI Unique?
Unlike the traditional CCI, which uses a fixed-length lookback period, this version automatically adjusts its lookback period using Hilbert Transform to detect the dominant cycle in the market.
✅ Hilbert Transform Adaptive Lookback – Dynamically detects cycle length to adjust CCI sensitivity.
✅ Real-Time Divergence Detection – Instantly identifies bullish and bearish divergences for early reversal signals.
✅ Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management
👽 The Math Behind the Indicator
👾 Hilbert Transform Cycle Detection
The Hilbert Transform estimates the dominant market cycle length based on the frequency of price oscillations. It is computed using the in-phase and quadrature components of the price series:
tp = (high + low + close) / 3
smooth = (tp + 2 * tp + 2 * tp + tp ) / 6
detrender = smooth - smooth
quadrature = detrender - detrender
inPhase = detrender + quadrature
outPhase = quadrature - inPhase
instPeriod = 0.0
deltaPhase = math.abs(inPhase - inPhase ) + math.abs(outPhase - outPhase )
instPeriod := nz(3.25 / deltaPhase, instPeriod )
dominantCycle = int(math.min(math.max(instPeriod, cciMinPeriod), 500))
Where:
In-Phase & Out-Phase Components are derived from a detrended version of the price series.
Instantaneous Frequency measures the rate of cycle change, allowing the CCI period to adjust dynamically.
The result is bounded within a user-defined min/max range, ensuring stability.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Bullish Divergence Setup:
Price makes a lower low, while CCI forms a higher low.
Buy signal is confirmed when CCI shows upward momentum.
Bearish Divergence Setup:
Price makes a higher high, while CCI forms a lower high.
Sell signal is confirmed when CCI shows downward momentum.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅ CCI crosses above -100 → Buy signal.
✅ A bullish trailing stop is placed at Low - (ATR × Multiplier).
✅ Exit if the price crosses below the stop.
Bearish Setup:
✅ CCI crosses below 100 → Sell signal.
✅ A bearish trailing stop is placed at High + (ATR × Multiplier).
✅ Exit if the price crosses above the stop.
👽 Why It’s Useful for Traders
Hilbert Adaptive Period Calculation – No more fixed-length periods; the indicator dynamically adapts to market conditions.
Real-Time Divergence Alerts – Helps traders anticipate market reversals before they occur.
ATR-Based Risk Management – Stops automatically adjust based on volatility.
Works Across Multiple Markets & Timeframes – Ideal for stocks, forex, crypto, and futures.
👽 Indicator Settings
Min & Max CCI Period – Defines the adaptive range for Hilbert-based lookback.
Smoothing Factor – Controls the degree of smoothing applied to CCI.
Enable Divergence Analysis – Toggles real-time divergence detection.
Lookback Period – Defines the number of bars for detecting pivot points.
Enable Crosses Signals – Turns on CCI crossover-based trade signals.
ATR Multiplier – Adjusts trailing stop sensitivity.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Milvetti_Pineconnector_LibraryLibrary "Milvetti_Pineconnector_Library"
This library has methods that provide practical signal transmission for Pineconnector.Developed By Milvetti
buy(licenseId, symbol, risk, sl, tp, beTrigger, beOffset, trailTrig, trailDist, trailStep, atrTimeframe, atrTrigger, atrPeriod, atrMultiplier, atrShift, spread, accFilter, secret, comment)
Create a buy order message
Parameters:
licenseId (string) : License Id. This is a unique identifier found in the Pineconnector Licensing Dashboard.
symbol (string) : Symbol. Default is syminfo.ticker
risk (float) : Risk. Function depends on the “Volume Type” selected in the EA
sl (float) : StopLoss. Place stop-loss. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
tp (float) : TakeProfit. Place take-profit. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
beTrigger (float) : Breakeven will be activated after the position gains this number of pips. Ensure > 0
beOffset (float) : Offset from entry price. 0 means the SL will be placed exactly at entry price. 1 means 1 pip above the entry price for buy trades and 1 pip below for sell trades.
trailTrig (int) : Trailing stop-loss will be activated after a trade gains this number of pips. Default is 0(inactive)
trailDist (int) : SL will be opened at traildist after trailtrig is met, even if you do not have a SL placed.. Default is 0(inactive)
trailStep (int) : Moves trailing stop-loss once price moves to favourable by a specified number of pips. Default is 0(inactive)
atrTimeframe (string) : ATR Trailing Stop will be based on the specified timeframe in minutes and will only update once per bar close. Default is Timeframe.Period
atrTrigger (float) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default is 0(inactive)
atrPeriod (int) : ATR averaging period. Default is 0
atrMultiplier (float) : Multiple of ATR to utilise in the new SL computation. Default is 1
atrShift (float) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default is 0
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips. Default is 0(inactive)
accFilter (float) : Enter the position only if the account requirement is met. Default is 0(inactive)
secret (string)
comment (string) : Comment. Add a string into the order’s comment section. Default is "Symbol+Timeframe"
sell(licenseId, symbol, risk, sl, tp, beTrigger, beOffset, trailTrig, trailDist, trailStep, atrTimeframe, atrTrigger, atrPeriod, atrMultiplier, atrShift, spread, accFilter, secret, comment)
Create a buy order message
Parameters:
licenseId (string) : License Id. This is a unique identifier found in the Pineconnector Licensing Dashboard.
symbol (string) : Symbol. Default is syminfo.ticker
risk (float) : Risk. Function depends on the “Volume Type” selected in the EA
sl (float) : StopLoss. Place stop-loss. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
tp (float) : TakeProfit. Place take-profit. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
beTrigger (float) : Breakeven will be activated after the position gains this number of pips. Ensure > 0
beOffset (float) : Offset from entry price. 0 means the SL will be placed exactly at entry price. 1 means 1 pip above the entry price for buy trades and 1 pip below for sell trades.
trailTrig (int) : Trailing stop-loss will be activated after a trade gains this number of pips. Default is 0(inactive)
trailDist (int) : SL will be opened at traildist after trailtrig is met, even if you do not have a SL placed.. Default is 0(inactive)
trailStep (int) : Moves trailing stop-loss once price moves to favourable by a specified number of pips. Default is 0(inactive)
atrTimeframe (string) : ATR Trailing Stop will be based on the specified timeframe in minutes and will only update once per bar close. Default is Timeframe.Period
atrTrigger (float) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default is 0(inactive)
atrPeriod (int) : ATR averaging period. Default is 0
atrMultiplier (float) : Multiple of ATR to utilise in the new SL computation. Default is 1
atrShift (float) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default is 0
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips. Default is 0(inactive)
accFilter (float) : Enter the position only if the account requirement is met. Default is 0(inactive)
secret (string)
comment (string) : Comment. Add a string into the order’s comment section. Default is "Symbol+Timeframe"
buyLimit(licenseId, symbol, pending, risk, sl, tp, beTrigger, beOffset, trailTrig, trailDist, trailStep, atrTimeframe, atrTrigger, atrPeriod, atrMultiplier, atrShift, spread, accFilter, secret, comment)
Create a buy limit order message
Parameters:
licenseId (string) : License Id. This is a unique identifier found in the Pineconnector Licensing Dashboard.
symbol (string) : Symbol. Default is syminfo.ticker
pending (float) : Computing pending order entry price. EA Options: Pips, Specified Price, Percentage
risk (float) : Risk. Function depends on the “Volume Type” selected in the EA
sl (float) : StopLoss. Place stop-loss. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
tp (float) : TakeProfit. Place take-profit. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
beTrigger (float) : Breakeven will be activated after the position gains this number of pips. Ensure > 0
beOffset (float) : Offset from entry price. 0 means the SL will be placed exactly at entry price. 1 means 1 pip above the entry price for buy trades and 1 pip below for sell trades.
trailTrig (int) : Trailing stop-loss will be activated after a trade gains this number of pips. Default is 0(inactive)
trailDist (int) : SL will be opened at traildist after trailtrig is met, even if you do not have a SL placed.. Default is 0(inactive)
trailStep (int) : Moves trailing stop-loss once price moves to favourable by a specified number of pips. Default is 0(inactive)
atrTimeframe (string) : ATR Trailing Stop will be based on the specified timeframe in minutes and will only update once per bar close. Default is Timeframe.Period
atrTrigger (float) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default is 0(inactive)
atrPeriod (int) : ATR averaging period. Default is 0
atrMultiplier (float) : Multiple of ATR to utilise in the new SL computation. Default is 1
atrShift (float) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default is 0
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips. Default is 0(inactive)
accFilter (float) : Enter the position only if the account requirement is met. Default is 0(inactive)
secret (string)
comment (string) : Comment. Add a string into the order’s comment section. Default is "Symbol+Timeframe"
buyStop(licenseId, symbol, pending, risk, sl, tp, beTrigger, beOffset, trailTrig, trailDist, trailStep, atrTimeframe, atrTrigger, atrPeriod, atrMultiplier, atrShift, spread, accFilter, secret, comment)
Create a buy stop order message
Parameters:
licenseId (string) : License Id. This is a unique identifier found in the Pineconnector Licensing Dashboard.
symbol (string) : Symbol. Default is syminfo.ticker
pending (float) : Computing pending order entry price. EA Options: Pips, Specified Price, Percentage
risk (float) : Risk. Function depends on the “Volume Type” selected in the EA
sl (float) : StopLoss. Place stop-loss. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
tp (float) : TakeProfit. Place take-profit. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
beTrigger (float) : Breakeven will be activated after the position gains this number of pips. Ensure > 0
beOffset (float) : Offset from entry price. 0 means the SL will be placed exactly at entry price. 1 means 1 pip above the entry price for buy trades and 1 pip below for sell trades.
trailTrig (int) : Trailing stop-loss will be activated after a trade gains this number of pips. Default is 0(inactive)
trailDist (int) : SL will be opened at traildist after trailtrig is met, even if you do not have a SL placed.. Default is 0(inactive)
trailStep (int) : Moves trailing stop-loss once price moves to favourable by a specified number of pips. Default is 0(inactive)
atrTimeframe (string) : ATR Trailing Stop will be based on the specified timeframe in minutes and will only update once per bar close. Default is Timeframe.Period
atrTrigger (float) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default is 0(inactive)
atrPeriod (int) : ATR averaging period. Default is 0
atrMultiplier (float) : Multiple of ATR to utilise in the new SL computation. Default is 1
atrShift (float) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default is 0
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips. Default is 0(inactive)
accFilter (float) : Enter the position only if the account requirement is met. Default is 0(inactive)
secret (string)
comment (string) : Comment. Add a string into the order’s comment section. Default is "Symbol+Timeframe"
sellLimit(licenseId, symbol, pending, risk, sl, tp, beTrigger, beOffset, trailTrig, trailDist, trailStep, atrTimeframe, atrTrigger, atrPeriod, atrMultiplier, atrShift, spread, accFilter, secret, comment)
Create a sell limit order message
Parameters:
licenseId (string) : License Id. This is a unique identifier found in the Pineconnector Licensing Dashboard.
symbol (string) : Symbol. Default is syminfo.ticker
pending (float) : Computing pending order entry price. EA Options: Pips, Specified Price, Percentage
risk (float) : Risk. Function depends on the “Volume Type” selected in the EA
sl (float) : StopLoss. Place stop-loss. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
tp (float) : TakeProfit. Place take-profit. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
beTrigger (float) : Breakeven will be activated after the position gains this number of pips. Ensure > 0
beOffset (float) : Offset from entry price. 0 means the SL will be placed exactly at entry price. 1 means 1 pip above the entry price for buy trades and 1 pip below for sell trades.
trailTrig (int) : Trailing stop-loss will be activated after a trade gains this number of pips. Default is 0(inactive)
trailDist (int) : SL will be opened at traildist after trailtrig is met, even if you do not have a SL placed.. Default is 0(inactive)
trailStep (int) : Moves trailing stop-loss once price moves to favourable by a specified number of pips. Default is 0(inactive)
atrTimeframe (string) : ATR Trailing Stop will be based on the specified timeframe in minutes and will only update once per bar close. Default is Timeframe.Period
atrTrigger (float) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default is 0(inactive)
atrPeriod (int) : ATR averaging period. Default is 0
atrMultiplier (float) : Multiple of ATR to utilise in the new SL computation. Default is 1
atrShift (float) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default is 0
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips. Default is 0(inactive)
accFilter (float) : Enter the position only if the account requirement is met. Default is 0(inactive)
secret (string)
comment (string) : Comment. Add a string into the order’s comment section. Default is "Symbol+Timeframe"
sellStop(licenseId, symbol, pending, risk, sl, tp, beTrigger, beOffset, trailTrig, trailDist, trailStep, atrTimeframe, atrTrigger, atrPeriod, atrMultiplier, atrShift, spread, accFilter, secret, comment)
Create a sell stop order message
Parameters:
licenseId (string) : License Id. This is a unique identifier found in the Pineconnector Licensing Dashboard.
symbol (string) : Symbol. Default is syminfo.ticker
pending (float) : Computing pending order entry price. EA Options: Pips, Specified Price, Percentage
risk (float) : Risk. Function depends on the “Volume Type” selected in the EA
sl (float) : StopLoss. Place stop-loss. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
tp (float) : TakeProfit. Place take-profit. Computation is based on the Target Type selected in the EA. Default is 0(inactive)
beTrigger (float) : Breakeven will be activated after the position gains this number of pips. Ensure > 0
beOffset (float) : Offset from entry price. 0 means the SL will be placed exactly at entry price. 1 means 1 pip above the entry price for buy trades and 1 pip below for sell trades.
trailTrig (int) : Trailing stop-loss will be activated after a trade gains this number of pips. Default is 0(inactive)
trailDist (int) : SL will be opened at traildist after trailtrig is met, even if you do not have a SL placed.. Default is 0(inactive)
trailStep (int) : Moves trailing stop-loss once price moves to favourable by a specified number of pips. Default is 0(inactive)
atrTimeframe (string) : ATR Trailing Stop will be based on the specified timeframe in minutes and will only update once per bar close. Default is Timeframe.Period
atrTrigger (float) : Activate the trigger of ATR Trailing after market moves favourably by a number of pips. Default is 0(inactive)
atrPeriod (int) : ATR averaging period. Default is 0
atrMultiplier (float) : Multiple of ATR to utilise in the new SL computation. Default is 1
atrShift (float) : Relative shift of price information, 0 uses latest candle, 1 uses second last, etc. Default is 0
spread (float) : Enter the position only if the spread is equal or less than the specified value in pips. Default is 0(inactive)
accFilter (float) : Enter the position only if the account requirement is met. Default is 0(inactive)
secret (string)
comment (string) : Comment. Add a string into the order’s comment section. Default is "Symbol+Timeframe"
Volatility System by W. WilderVolatility System (Volatility Stops) Similarity
Most traders adjust their stops over time in the direction of the trend in order to lock in profits. Apart from moving averages, one of the most popular techniques is trailing stops using a multiple of Average True Range. There are several variations:
The original Volatility System(Volatility Stops), introduced by Welles Wilder in his 1978 book: New Concepts in Technical Trading Systems
Chandelier exits introduced by Alexander Elder in Come Into My Trading Room (2002) trail the stops from Highs or Lows rather than Closing Price
Average True Range Trailing Stops are similar to the above, but include a ratchet mechanism to prevent stops moving down during an up-trend or rising during a down-trend, as ATR increases
WillTrend intoduced by Larry Williams in 1988
Comparison of systems
All the systems under consideration have one common ingredient - ATR. ATR was developed by Welles Wilder and described in his book in 1978, also in this book the Volatility System was described, which in the future became known as Volatility Stops.
In fact, Wilder is the father of such systems due to the presence of ATR in the calculation of this type of indicator.
The main difference of Volatility System
Followers such as Larry Williams and Alexander Elder made minor changes to the value based on the ATR, mainly focusing on changing the base to which this value is added or subtracted.
Larry Williams uses the square root of 5 as a multiplier and calculates the ATR with a period of 66, and Alexander Elder uses a multiplier of 2.5-3.5 applying it to the ATR with a period of 22. Both authors changed the original value for ATR and multiplier calculations. Alexander Elder is closest to the original Welles Wilder calculation, which used a multiplier of 2.8.-3.1 applying it to an ATR with a period of 7.
As a reference, Elder took the Highest High(22) from which he subtracts ATR*Multiplier in an uptrend or the Lowest Low(22) to which he adds ATR*Multiplier to obtain the turning point (SAR).
Larry Williams uses the average price of extremes (Highest High(10) + Lowest Low(10)) / 2 as a reference base to which he adds or subtracts the ATR*Multilpyer values.
Both systems differ from the original, because Wilder used Significan Close(SIC) in his calculations. SIC is the maximum closing price during an uptrend and the minimum closing price during a downtrend, which
does not go beyond the current trade, as in other systems. To calculate the base when a trend changes, bars that are outside the current trend will be used when calculating WillTrend and Chandelier Exit, in contrast to the Volatility System, which takes SIC values only within the current trade. This is the main difference from subsequent developments of similar systems.
Improvements made
The original Volatility System is present as an indicator on TradingView, but it is an improved version with the addition of a ratchet and works differently from the original Weilder system.
List of improvements:
Added the ability to remove the ratchet. You need to turn off the "Trail one way" checkbox in the setting menu. When this function is turned off, the system will operate in the author-inventor mode. On some instruments, the original system works much better than the improved ratchet system, which cannot be turned off.
Added the ability to use Highest High and Lowest Low as a base instead of the closing price.
Volatility Stops Formula Description
Welles Wilder's system uses Closing Price and incorporates a stop-and-reverse feature (as with his Parabolic SAR).
Determine the initial trend direction
Calculate the Significant Close ("SIC"): the highest close reached in an up-trend or the lowest close in a down-trend
Calculate Average True Range ("ATR") for the selected period (7 days in this example)
Multiply ATR by the Multiple (3.0 in this example, best values author describes as 2.8-3.1)
The first stop is calculated in day 7 and plotted for day 8
If an up-trend, the first stop is SIC - 3 * ATR, otherwise SIC + 3 * ATR for a down-trend
Repeat each day until price closes below the stop (or above in a down-trend)
Set SIC equal to the latest Close, reverse the trend and continue.
Chandelier Exit Description
Chandelier Exits subtract a multiple of Average True Range ("ATR") from the highest high for the selected period. Using the default settings as an example:
Highest High in last 22 days - 3 * ATR for 22 days
In a down-trend the formula is reversed:
Lowest Low in last 22 days + 3 * ATR for 22 days
The time period must be long enough to capture the highest point of the recent up-trend: too short and the stops move downward; too long and the high may be taken from a previous down-trend.
It is not essential to use the same period for up and down trends; down-trends are notoriously faster than up-trends and may benefit from a shorter time period.
The multiple of 3 may be varied, but most traders settle between 2.5 and 3.5.
WillTrend Description
Larry Williams is prefer to used the Square Root from 5 as a multiplayer for ATR. SQRT(5) = 2.236
WillTrend subtract a multiple of Average True Range ("ATR") from the Middle Price (Highest High for the selected period + Lowest Low for the selected period / 2).
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 - 2.236 * ATR for 66 days
In a down-trend the formula is reversed:
(Highest High in last 10 days + Lowest Low in last 10 days) / 2 + 2.236 * ATR for 66 days
Qullamaggie Breakout V2After publishing the Qullamaggie Breakout script and seeing that it had some decent results, I wanted to explore it a bit further. There were a few things I didn't like about that methodology that didn't really jive with the way I like to trade. So what I did was combined the Breakout Trend Follower strategy I had been using for entries with the Qullamaggie strategy for trailing stops once in profit. The results seem pretty good to me and an approach that fits my personality and something I can actually trade. Typically better profit than the Breakout Trend Follower by giving more room for your winners to run, while still protecting your entries by moving up the trailing stop until you are in profit, all while taking less trades, so that's great.
Everything is done with stop orders. So you set your buy stop at the recent swing high point and wait for a breakout. Once in a position you set your sell stop at the recent swing low point. The most recent swing high and low are shown on the chart for easy reference with the blue and orange horizontal lines. Once in a trade, trail your sell stop after a new swing low is registered (shown by the thicker orange stop line). Once you are in profit, leave that hard stop level there (the orange line will stay there helping you). Now, you wait for price to cross a Moving Average of your choosing (default is Daily 10 MA). Once the bar crosses that moving average, you move your stop to the low of that candle (shown by the blue stop line) and trail your stop along every crossing of the moving average until the trend changes and takes out your stop. So managing this trade is pretty easy...just wait for the stop lines to move and move your stop with them. It's a great way to trade when you can't be at your computer all the time because the stop orders take care of execution on both buy and sell side. If you use a daily timeframe for your moving averages (the default), you really only need to move stops around about once a day, so is a good part time trader's strategy in my opinion.
The best opportunities will come by scanning for stocks in the longer term timeframe of your moving averages. Wait for a consolidation on that timeframe so the anticipated breakout has some room to run. Once you've identified a good candidate, zoom in to your lower timeframe where the swing highs/lows will act as your entry and exit points, all while keeping the moving averages consistent between timeframes.
Hope you guys find it useful.
A few options available:
- Choose any timeframe for your moving averages, while using swing high/low points on intraday charts.
- Choose one of two moving averages shown for your trailing stops (default 10 and 20 MA).
- Choose to use the third moving average as a filter for keeping you out of trades that are below it (trading with the trend).
- Use the charts resolution candle or the moving average resolution candle for the moving average trailing stop.
- Only take trades where your buy level minus stop level is below a % of the Average Daily Range (ADR). This allows you to potentially have better risk/reward. I added a little table that shows the ADR of the stock/ticker as well as the range between the recent buy and sell levels (shown by the orange and blue horizontal lines) for easy reference.
Stoploss indicatorGood for setting trailing stops and stoplosses when your taking a scalp etc, most recommended for manual trailing stops
Cowabunga System from babypips.comPlease do read the information below as well, especially if you are new to Forex.
The Cowabunga System is a type of Mechanical Trading System that filters trades based on the trend of the 4 hour chart with EMAs and some other familiar indicators (RSI, Stochastics and MACD) while entering trades base on 15 minute chart.
I have coded (quite amateurishly) the basic system onto a 15 minute chart (the 4 hour settings are coded as well). The author says the system is to be traded off the 15 minute chart with the 4 hour chart only as a reference for trend direction.
4 Hour Chart Settings
5 EMA
10 EMA
Stochastics (10,3,3)
RSI (9)
Then we move onto the 15 minute chart, where he gives us the trade entry rules.
15 Minute Chart Settings
5 EMA
10 EMA
Stochastics (10,3,3)
RSI (9)
MACD (12,26,9)
Entry Rules - long entry rules used, obviously reverse these for shorting.
1. EMA must cross above the 10 EMA.
2. RSI must be greater than 50 and not overbought.
3. Stochastic must be headed up and not be in overbought territory.
4. MACD histogram must go from negative to positive OR be negative and start to increase in value.
What I did.
1. Set the RSI and Stochastic levels to avoid entries when they indicate overbought conditions for long and oversold conditions for short (80 and 20 levels).
2. Users can input specific times they want to backtest.
3. User's can configure profit targets, trailing stops and stops. Default is set it to was 100 pips profit target with a 40 pip trailing stop. (Note, when you are changing these values, please note that each pip is worth 10, so 100 pips is entered as 1000.)
The Cowabunga System from babypips.com is another popular and active system. The author, Pip Surfer, continues to post wins and losses with this system. It shows there is a lot of honesty and integrity with this system if the author keeps up to date even 10 years later and is not afraid of sharing the times the system causes losses.
As an example of this, here is post he shared just last week . It's almost like a journal, he gives specific times and reasons why he entered, lets the readers know when he was stopped out, etc. I think that what he does is equally important as his system.
To read more about this system, visit the thread on babypips.com, click here.
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.
Opening Range IndicatorComplete Trading Guide: Opening Range Breakout Strategy
What Are Opening Ranges?
Opening ranges capture the high and low prices during the first few minutes of market open. These levels often act as key support and resistance throughout the trading day because:
Heavy volume occurs at market open as overnight orders execute
Institutional activity is concentrated during opening minutes
Price discovery happens as market participants react to overnight news
Psychological levels are established that traders watch all day
Understanding the Three Timeframes
OR5 (5-Minute Range: 9:30-9:35 AM)
Most sensitive - captures immediate market reaction
Quick signals but higher false breakout rate
Best for scalping and momentum trading
Use for early entry when conviction is high
OR15 (15-Minute Range: 9:30-9:45 AM)
Balanced approach - most popular among day traders
Moderate sensitivity with better reliability
Good for swing trades lasting several hours
Primary timeframe for most strategies
OR30 (30-Minute Range: 9:30-10:00 AM)
Most reliable but slower signals
Lower false breakout rate
Best for position trades and trend following
Use when looking for major moves
Core Trading Strategies
Strategy 1: Basic Breakout
Setup:
Wait for price to break above OR15 high or below OR15 low
Enter on the breakout candle close
Stop loss: Opposite side of the range
Target: 2-3x the range size
Example:
OR15 range: $100.00 - $102.00 (Range = $2.00)
Long entry: Break above $102.00
Stop loss: $99.50 (below OR15 low)
Target: $104.00+ (2x range size)
Strategy 2: Multiple Confirmation
Setup:
Wait for OR5 break first (early signal)
Confirm with OR15 break in same direction
Enter on OR15 confirmation
Stop: Below OR30 if available, or OR15 opposite level
Why it works:
Multiple timeframe confirmation reduces false signals and increases probability of sustained moves.
Strategy 3: Failed Breakout Reversal
Setup:
Price breaks OR15 level but fails to hold
Wait for re-entry into the range
Enter reversal trade toward opposite OR level
Stop: Recent breakout high/low
Target: Opposite side of range + extension
Key insight: Failed breakouts often lead to strong moves in the opposite direction.
Advanced Techniques
Range Quality Assessment
High-Quality Ranges (Trade these):
Range size: 0.5% - 2% of stock price
Clean boundaries (not choppy)
Volume spike during range formation
Clear rejection at range levels
Low-Quality Ranges (Avoid these):
Very narrow ranges (<0.3% of stock price)
Extremely wide ranges (>3% of stock price)
Choppy, overlapping candles
Low volume during formation
Volume Confirmation
For Breakouts:
Look for volume spike (2x+ average) on breakout
Declining volume often signals false breakout
Rising volume during range formation shows interest
Market Context Filters
Best Conditions:
Trending market days (SPY/QQQ with clear direction)
Earnings reactions or news-driven moves
High-volume stocks with good liquidity
Volatility above average (VIX considerations)
Avoid Trading When:
Extremely low volume days
Major economic announcements pending
Holidays or half-days
Choppy, sideways market conditions
Risk Management Rules
Position Sizing
Conservative: Risk 0.5% of account per trade
Moderate: Risk 1% of account per trade
Aggressive: Risk 2% maximum per trade
Stop Loss Placement
Inside the range: Quick exit but higher stop-out rate
Outside opposite level: More room but larger risk
ATR-based: 1.5-2x Average True Range below entry
Profit Taking
Target 1: 1x range size (take 50% off)
Target 2: 2x range size (take 25% off)
Runner: Trail remaining 25% with moving stops
Specific Entry Techniques
Breakout Entry Methods
Method 1: Immediate Entry
Enter as soon as price closes above/below range
Fastest entry but highest false signal rate
Best for strong momentum situations
Method 2: Pullback Entry
Wait for breakout, then pullback to range level
Enter when price bounces off former resistance/support
Better risk/reward but may miss some moves
Method 3: Volume Confirmation
Wait for breakout + volume spike
Enter after volume confirmation candle
Reduces false signals significantly
Multiple Timeframe Entries
Aggressive: OR5 break → immediate entry
Conservative: OR5 + OR15 + OR30 all align → enter
Balanced: OR15 break with OR30 support → enter
Common Mistakes to Avoid
1. Trading Poor-Quality Ranges
❌ Don't trade ranges that are too narrow or too wide
✅ Focus on clean, well-defined ranges with good volume
2. Ignoring Volume
❌ Don't chase breakouts without volume confirmation
✅ Always check for volume spike on breakouts
3. Over-Trading
❌ Don't force trades when ranges are unclear
✅ Wait for high-probability setups only
4. Poor Risk Management
❌ Don't risk more than planned or use tight stops in volatile conditions
✅ Stick to predetermined risk levels
5. Fighting the Trend
❌ Don't fade breakouts in strongly trending markets
✅ Align trades with overall market direction
Daily Trading Routine
Pre-Market (8:00-9:30 AM)
Check overnight news and earnings
Review major indices (SPY, QQQ, IWM)
Identify potential opening range candidates
Set alerts for range breakouts
Market Open (9:30-10:00 AM)
Watch opening range formation
Note volume and price action quality
Mark key levels on charts
Prepare for breakout signals
Trading Session (10:00 AM - 4:00 PM)
Execute breakout strategies
Manage existing positions
Trail stops as profits develop
Look for additional setups
Post-Market Review
Analyze winning and losing trades
Review range quality vs. outcomes
Identify improvement areas
Prepare for next session
Best Stocks/ETFs for Opening Range Trading
Large Cap Stocks (Best for beginners):
AAPL, MSFT, GOOGL, AMZN, TSLA
High liquidity, predictable behavior
Good range formation most days
ETFs (Consistent patterns):
SPY, QQQ, IWM, XLF, XLE
Excellent liquidity
Clear range boundaries
Mid-Cap Growth (Advanced traders):
Stocks with good volume (1M+ shares daily)
Recent news catalysts
Clean technical patterns
Performance Optimization
Track These Metrics:
Win rate by range type (OR5 vs OR15 vs OR30)
Average R/R (risk vs reward ratio)
Best performing market conditions
Time of day performance
Continuous Improvement:
Keep detailed trade journal
Review failed breakouts for patterns
Adjust position sizing based on win rate
Refine entry timing based on backtesting
Final Tips for Success
Start small - Paper trade or use tiny positions initially
Focus on quality - Better to miss trades than take bad ones
Stay disciplined - Stick to your rules even during losing streaks
Adapt to conditions - What works in trending markets may fail in choppy conditions
Keep learning - Markets evolve, so should your approach
The opening range strategy is powerful because it captures natural market behavior, but like all strategies, it requires practice, discipline, and proper risk management to be profitable long-term.
Clarix Trailing MasterClarix Trailing Master
Advanced Manual Entry Trailing Stop Strategy
Purpose :
Clarix Trailing Master is designed to give traders precise control over trade exits with a customizable trailing stop system. It combines manual entry inputs with dynamic and static trailing stop options, empowering users to protect profits while minimizing premature stop-outs.
How It Works:
You manually input your trade entry price and specify the trade direction (Long or Short).
The strategy activates the trailing stop only after the price moves favorably by a configurable profit threshold. This helps avoid early stop losses during initial market noise.
You can choose between a dynamic trailing stop based on Average True Range (ATR) or a fixed static trailing distance. The ATR can also be computed on a higher timeframe for enhanced stability.
Once active, the trailing stop updates live with price movements, ensuring your gains are locked in progressively.
If the price crosses the trailing stop, a clear alert triggers, and the stop-hit status displays visually on the chart.
Key Features:
Manual entry with exact price and timestamp input for precise trade tracking.
Supports both Long and Short trades.
Choice between dynamic ATR-based trailing or static trailing stops.
Configurable profit threshold before trailing stop activation to avoid early exits.
Visual markers for entry and stop-hit points (yellow and red respectively).
Live dashboard displaying entry details, trade status, trailing mode, and current stop level.
Works on all asset classes and timeframes, adaptable to various trading styles.
Built-in audio alert notifies you immediately when the trailing stop is hit.
Usage Tips:
Adjust the profit threshold and ATR settings based on your asset’s volatility and timeframe. For example, use higher ATR multipliers for more volatile markets like crypto.
Consider using higher timeframe ATR values for smoother trailing stops in fast-moving markets.
Ideal for swing trading or position trading where precise stop management is crucial.
Always backtest and paper trade before applying to live markets.
Commodity Trend Reactor [BigBeluga]
🔵 OVERVIEW
A dynamic trend-following oscillator built around the classic CCI, enhanced with intelligent price tracking and reversal signals.
Commodity Trend Reactor extends the traditional Commodity Channel Index (CCI) by integrating trend-trailing logic and reactive reversal markers. It visualizes trend direction using a trailing stop system and highlights potential exhaustion zones when CCI exceeds extreme thresholds. This dual-level system makes it ideal for both trend confirmation and mean-reversion alerts.
🔵 CONCEPTS
Based on the CCI (Commodity Channel Index) oscillator, which measures deviation from the average price.
Trend bias is determined by whether CCI is above or below user-defined thresholds.
Trailing price bands are used to lock in trend direction visually on the main chart.
Extreme values beyond ±200 are treated as potential reversal zones.
🔵 FEATURES\
CCI-Based Trend Shifts:
Triggers a bullish bias when CCI crosses above the upper threshold, and bearish when it crosses below the lower threshold.
Adaptive Trailing Stops:
In bullish mode, a trailing stop tracks the lowest price; in bearish mode, it tracks the highest.
Top & Bottom Markers:
When CCI surpasses +200 or drops below -200, it plots colored squares both on the oscillator and on price, marking potential reversal zones.
Background Highlights:
Each time a trend shift occurs, the background is softly colored (lime for bullish, orange for bearish) to highlight the change.
🔵 HOW TO USE
Use the oscillator to monitor when CCI crosses above or below threshold values to detect trend activation.
Enter trades in the direction of the trailing band once the trend bias is confirmed.
Watch for +200 and -200 square markers as warnings of potential mean reversals.
Use trailing stop areas as dynamic support/resistance to manage stop loss and exit strategies.
The background color changes offer clean confirmation of trend transitions on chart.
🔵 CONCLUSION
Commodity Trend Reactor transforms the simple CCI into a complete trend-reactive framework. With real-time trailing logic and clear reversal alerts, it serves both momentum traders and contrarian scalpers alike. Whether you’re trading breakouts or anticipating mean reversions, this indicator provides clarity and structure to your decision-making.
nineLivesUtilLibLibrary "nineLivesUtilLib"
isDateInRange(currentTime, useTimeFilter, startDate, endDate)
Checks if the current time is within the specified date range.
Parameters:
currentTime (int) : The current bar's time (time).
useTimeFilter (bool) : Bool 📅: Enable the date range filter.
startDate (int) : Timestamp 📅: The start date for the filter.
endDate (int) : Timestamp 📅: The end date for the filter.
Returns: True if the current time is within the range or filtering is disabled, false otherwise.
@example
inDateRange = nineLivesUtilLib.isDateInRange(time, useTimeFilter, startDate, endDate)
if inDateRange
// Execute trading logic
checkVolumeCondition(currentVolume, useVolumeFilter, volumeThresholdMultiplier, volumeLength)
Checks if the current volume meets the threshold condition.
Parameters:
currentVolume (float) : The current bar's volume (volume).
useVolumeFilter (bool) : Bool 📊: Enable the volume filter.
volumeThresholdMultiplier (float) : Float 📊: Volume threshold relative to average (e.g., 1.5 for 1.5x average).
volumeLength (int) : Int 📊: Lookback length for the volume average.
Returns: True if the volume condition is met or filtering is disabled, false otherwise.
@example
volumeOk = nineLivesUtilLib.checkVolumeCondition(volume, useVolumeFilter, volumeThreshold, volumeLength)
if volumeOk
// Proceed with trading logic
checkMultiTimeframeCondition(currentClose, currentOpen, htfClose, htfOpen, useMultiTimeframe, alignment)
Checks alignment with higher timeframe direction.
Parameters:
currentClose (float) : Float: The current bar's closing price (close).
currentOpen (float) : Float: The current bar's opening price (open).
htfClose (float) : Float: The closing price from the higher timeframe (must be fetched by the calling script using request.security).
htfOpen (float) : Float: The opening price from the higher timeframe (must be fetched by the calling script using request.security).
useMultiTimeframe (bool) : Bool ⏱️: Enable multi-timeframe analysis.
alignment (string) : String ⏱️: Desired alignment ("same", "opposite", "any").
Returns: True if the timeframe alignment condition is met or analysis is disabled, false otherwise.
@example
// In the calling script:
= request.security(syminfo.tickerid, higherTimeframe, )
tfOk = nineLivesUtilLib.checkMultiTimeframeCondition(close, open, htfClose, htfOpen, useMultiTimeframe, tfAlignment)
if tfOk
// Proceed with trading logic
checkMarketRegime(useMarketRegime, regimeIndicator, regimeThreshold, regimeLength, regimeMode)
Detects the market regime (trending or ranging) and checks if trading is allowed.
Parameters:
useMarketRegime (bool) : Bool 🔍: Enable market regime detection.
regimeIndicator (string) : String 🔍: Indicator to use ("ADX" or "Volatility").
regimeThreshold (int) : Int 🔍: Threshold for trend strength/volatility.
regimeLength (simple int) : Int 🔍: Lookback length for the indicator.
regimeMode (string) : String 🔍: Trading mode based on regime ("trend_only", "range_only", "adaptive").
Returns: A tuple containing:
: conditionMet (bool) - True if trading is allowed based on the regime mode and detection, false otherwise.
: inTrendingRegime (bool) - True if the current regime is trending based on the indicator and threshold.
@example
= nineLivesUtilLib.checkMarketRegime(useMarketRegime, regimeIndicator, regimeThreshold, regimeLength, regimeMode)
if regimeOk
// Proceed with trading logic
applyCooldown(buySignal, sellSignal, cooldownBars)
Applies a cooldown period after a signal.
Parameters:
buySignal (bool) : Bool: Buy signal (potentially after primary entry logic).
sellSignal (bool) : Bool: Sell signal (potentially after primary entry logic).
cooldownBars (int) : Int ⏳: The number of bars to wait after a signal before allowing another.
Returns: A tuple containing:
: cooldownFilteredBuy (bool) - Buy signal after cooldown filter.
: cooldownFilteredSell (bool) - Sell signal after cooldown filter.
@example
= nineLivesUtilLib.applyCooldown(rawBuySignal, rawSellSignal, iCool)
applyAllFilters(rawBuy, rawSell, inDateRange, tradeDirection, volumeOk, tfOk, regimeOk, drawdownOk, cooldownOkBuy, cooldownOkSell)
Applies all filtering conditions to the buy and sell signals.
Parameters:
rawBuy (bool) : Bool: The initial buy signal candidate (from primary entry logic, e.g., after cooldown).
rawSell (bool) : Bool: The initial sell signal candidate (from primary entry logic, e.g., after cooldown).
inDateRange (bool) : Bool 📅: Result from isDateInRange.
tradeDirection (string) : String 🔄: Overall trade direction preference ("longs_only", "shorts_only", "both").
volumeOk (bool) : Bool 📊: Result from checkVolumeCondition.
tfOk (bool) : Bool ⏱️: Result from checkMultiTimeframeCondition.
regimeOk (bool) : Bool 🔍: Result from checkMarketRegime.
drawdownOk (bool) : Bool 📉: Result from checkDrawdownExceeded (or equivalent).
cooldownOkBuy (bool) : Bool ⏳: Result from applyCooldown for buy.
cooldownOkSell (bool) : Bool ⏳: Result from applyCooldown for sell.
Returns: A tuple containing:
: finalBuySignal (bool) - The final buy signal after all filters.
: finalSellSignal (bool) - The final sell signal after all filters.
@example
= nineLivesUtilLib.applyAllFilters(cooldownBuy, cooldownSell, inDateRange, tradeDirection, volumeOk, tfOk, regimeOk, !drawdownExceeded, cooldownBuy, cooldownSell)
NOTE: This function filters signals generated by your primary entry logic (e.g., EMA crossover).
checkDrawdownExceeded(currentEquity, useMaxDrawdown, maxDrawdownPercent)
Tracks maximum equity and checks if current drawdown exceeds a threshold.
Parameters:
currentEquity (float) : Float: The strategy's current equity (strategy.equity).
useMaxDrawdown (bool) : Bool 📉: Enable max drawdown protection.
maxDrawdownPercent (float) : Float 📉: The maximum allowed drawdown as a percentage.
Returns: True if drawdown protection is enabled and the current drawdown exceeds the threshold, false otherwise.
@example
drawdownExceeded = nineLivesUtilLib.checkDrawdownExceeded(strategy.equity, useMaxDrawdown, maxDrawdownPercent)
if drawdownExceeded
// Consider stopping entries or exiting positions in the strategy script
calculateExitPrice(positionAvgPrice, percentage, isStop, isLong)
Calculates a stop loss or take profit price based on a percentage from the average entry price.
Parameters:
positionAvgPrice (float) : Float: The average price of the current position (strategy.position_avg_price).
percentage (float) : Float: The stop loss or take profit percentage (e.g., 2.0 for 2%).
isStop (bool) : Bool: True if calculating a stop loss price, false if calculating a take profit price.
isLong (bool) : Bool: True if the position is long, false if short.
Returns: The calculated stop price or take profit price, or na if no position or percentage is invalid.
@example
longSL = nineLivesUtilLib.calculateExitPrice(strategy.position_avg_price, stopLossPercent, true, true)
shortTP = nineLivesUtilLib.calculateExitPrice(strategy.position_avg_price, takeProfitPercent, false, false)
calculateTrailingStopLevel(positionAvgPrice, trailOffsetPercent, trailPercent, currentHigh, currentLow, isLong)
Calculates the current trailing stop level for a position.
Parameters:
positionAvgPrice (float) : Float: The average price of the current position (strategy.position_avg_price).
trailOffsetPercent (float) : Float 🔄: The percentage price movement to activate the trailing stop.
trailPercent (float) : Float 🔄: The percentage distance the stop trails behind the price.
currentHigh (float) : Float: The current bar's high (high).
currentLow (float) : Float: The current bar's low (low).
isLong (bool) : Bool: True if the position is long, false if short.
Returns: The calculated trailing stop price if active, otherwise na.
@example
longTrailStop = nineLivesUtilLib.calculateTrailingStopLevel(strategy.position_avg_price, trailOffset, trailPercent, high, low, true)
shortTrailStop = nineLivesUtilLib.calculateTrailingStopLevel(strategy.position_avg_price, trailOffset, trailPercent, high, low, false)
if not na(longTrailStop)
strategy.exit("Long Trail", from_entry="Long", stop=longTrailStop)
DEMA Trend Oscillator Strategy📌 Overview
The DEMA Trend Oscillator Strategy is a dynamic trend-following approach based on the Normalized DEMA Oscillator SD.
It adapts in real-time to market volatility with the goal of improving entry accuracy and optimizing risk management.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main goal of this strategy is to respond quickly to sudden price movements and trend reversals,
by combining momentum-based signals with volatility filters.
It is designed to be user-friendly for traders of all experience levels.
✨ Key Features
Normalized DEMA Oscillator: A momentum indicator that normalizes DEMA values on a 0–100 scale, allowing intuitive identification of trend strength
Two-Bar Confirmation Filter: Requires two consecutive bullish or bearish candles to reduce noise and enhance entry reliability
ATR x2 Trailing Stop: In addition to fixed stop-loss levels, a trailing stop based on 2× ATR is used to maximize profits during strong trends
📊 Trading Rules
Long Entry:
Normalized DEMA > 55 (strong upward momentum)
Candle low is above the upper SD band
Two consecutive bullish candles appear
Short Entry:
Normalized DEMA < 45 (downward momentum)
Candle high is below the lower SD band
Two consecutive bearish candles appear
Exit Conditions:
Take-profit at a risk-reward ratio of 1.5
Stop-loss triggered if price breaks below (long) or above (short) the SD band
Trailing stop activated based on 2× ATR to secure and extend profits
💰 Risk Management Parameters
Symbol & Timeframe: Any (AUDUSD 5M example)
Account size (virtual): $3000
Commission: 0.4PIPS(0.0004)
Slippage: 2 pips
Risk per trade: 5%
Number of trades (backtest):534
All parameters can be adjusted based on broker specifications and individual trading profiles.
⚙️ Trading Parameters & Considerations
Indicator: Normalized DEMA Oscillator SD
Parameter settings:
DEMA Period (len_dema): 40
Base Length: 20
Long Threshold: 55
Short Threshold: 45
Risk-Reward Ratio: 1.5
ATR Multiplier for Trailing Stop: 2.0
🖼 Visual Support
The chart displays the following visual elements:
Upper and lower SD bands (±2 standard deviations)
Entry signals shown as directional arrows
🔧 Strategy Improvements & Uniqueness
This strategy is inspired by “Normalized DEMA Oscillator SD” by QuantEdgeB,
but introduces enhancements such as a two-bar confirmation filter and an ATR-based trailing stop.
Compared to conventional trend-following strategies, it offers superior noise filtering and profit optimization.
✅ Summary
The DEMA Trend Oscillator Strategy is a responsive and practical trend-following method
that combines momentum detection with adaptive risk management.
Its visual clarity and logical structure make it a powerful and repeatable tool
for traders seeking consistent performance in trending markets.
⚠️ Always apply appropriate risk management. This strategy is based on historical data and does not guarantee future results.
Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
Reversal Trading Bot Strategy[BullByte]Overview :
The indicator Reversal Trading Bot Strategy is crafted to capture potential market reversal points by combining momentum, volatility, and trend alignment filters. It uses a blend of technical indicators to identify both bullish and bearish reversal setups, ensuring that multiple market conditions are met before entering a trade.
Core Components :
Technical Indicators Used :
RSI (Relative Strength Index) :
Purpose : Detects divergence conditions by comparing recent lows/highs in price with the RSI.
Parameter : Length of 8.
Bollinger Bands (BB) :
Purpose : Measures volatility and identifies price levels that are statistically extreme.
Parameter : Length of 20 and a 2-standard deviation multiplier.
ADX (Average Directional Index) & DMI (Directional Movement Index) :
Purpose : Quantifies the strength of the trend. The ADX threshold is set at 20, and additional filters check for the alignment of the directional indicators (DI+ and DI–).
ATR (Average True Range) :
Purpose : Provides a volatility measure used to set stop levels and determine risk through trailing stops.
Volume SMA (Simple Moving Average of Volume ):
Purpose : Helps confirm strength by comparing the current volume against a 20-period average, with an optional filter to ensure volume is at least twice the SMA.
User-Defined Toggle Filters :
Volume Filter : Confirms that the volume is above average (or twice the SMA) before taking trades.
ADX Trend Alignment Filter : Checks that the ADX’s directional indicators support the trade direction.
BB Close Confirmation : Optionally refines the entry by requiring price to be beyond the upper or lower Bollinger Band rather than just above or below.
RSI Divergence Exit : Allows the script to close positions if RSI divergence is detected.
BB Mean Reversion Exit : Closes positions if the price reverts to the Bollinger Bands’ middle line.
Risk/Reward Filter : Ensures that the potential reward is at least twice the risk by comparing the distance to the Bollinger Band with the ATR.
Candle Movement Filter : Optional filter to require a minimum percentage move in the candle to confirm momentum.
ADX Trend Exit : Closes positions if the ADX falls below the threshold and the directional indicators reverse.
Entry Conditions :
Bullish Entry :
RSI Divergence : Checks if the current close is lower than a previous low while the RSI is above the previous low, suggesting bullish divergence.
Bollinger Confirmation : Requires that the price is above the lower (or upper if confirmation is toggled) Bollinger Band.
Volume & Trend Filters : Combines volume condition, ADX strength, and an optional candle momentum condition.
Risk/Reward Check : Validates that the trade meets a favorable risk-to-reward ratio.
Bearish Entry :
Uses a mirror logic of the bullish entry by checking for bearish divergence, ensuring the price is below the appropriate Bollinger level, and confirming volume, trend strength, candle pattern, and risk/reward criteria.
Trade Execution and Exit Strateg y:
Trade Execution :
Upon meeting the entry conditions, the strategy initiates a long or short position.
Stop Loss & Trailing Stops :
A stop-loss is dynamically set using the ATR value, and trailing stops are implemented as a percentage of the close price.
Exit Conditions :
Additional exit filters can trigger early closures based on RSI divergence, mean reversion (via the middle Bollinger Band), or a weakening trend as signaled by ADX falling below its threshold.
This multi-layered exit strategy is designed to lock in gains or minimize losses if the market begins to reverse unexpectedly.
How the Strategy Works in Different Market Conditions :
Trending Markets :
The ADX filter ensures that trades are only taken when the trend is strong. When the market is trending, the directional movement indicators help confirm the momentum, making the reversal signal more reliable.
Ranging Markets :
In choppy markets, the Bollinger Bands expand and contract, while the RSI divergence can highlight potential turning points. The optional filters can be adjusted to avoid false signals in low-volume or low-volatility conditions.
Volatility Management :
With ATR-based stop-losses and a risk/reward filter, the strategy adapts to current market volatility, ensuring that risk is managed consistently.
Recommendation on using this Strategy with a Trading Bot :
This strategy is well-suited for high-frequency trading (HFT) due to its ability to quickly identify reversal setups and execute trades dynamically with automated stop-loss and trailing exits. By integrating this script with a TradingView webhook-based bot or an API-driven execution system, traders can automate trade entries and exits in real-time, reducing manual execution delays and capitalizing on fast market movements.
Disclaimer :
This script is provided for educational and informational purposes only. It is not intended as investment advice. Trading involves significant risk, and you should always conduct your own research and analysis before making any trading decisions. The author is not responsible for any losses incurred while using this script.
Penny King**Penny King Trend Indicator**
The **Penny King** is a powerful and versatile trend-following indicator designed to assist traders in identifying market trends and dynamic support/resistance levels. This tool effectively leverages Adaptive True Range (ATR) and Exponential Moving Average (EMA) or a Delta Price method to establish a trailing stop level, ensuring traders can capture strong trends while minimizing risk.
### **Key Features:**
1. **Dual Calculation Modes:**
- **ATR & EMA-Based Mode (Mode 0)**: Uses ATR (Average True Range) and EMA (Exponential Moving Average) to determine the trailing stop level dynamically.
- **Delta Price Mode (Mode 1)**: Utilizes a fixed price change threshold (Delta Price) to define stop levels based on market volatility.
2. **Adjustable Parameters for Customization:**
- **Range (akk_range)**: Defines the lookback period for the ATR calculation.
- **IMA Range (ima_range)**: Specifies the EMA smoothing factor applied to the ATR.
- **Factor (akk_factor)**: Multiplier applied to the ATR-based calculation to refine trailing stop sensitivity.
- **Delta Price (DeltaPrice)**: Fixed price-based stop level for an alternative trend calculation.
3. **Intelligent Trailing Stop Mechanism:**
- The trailing stop level dynamically adjusts based on price movement, following the trend while preventing premature exits.
- If the price moves in favor of the trend, the stop level is adjusted accordingly to lock in profits.
- If the price reverses against the trend, the stop level remains intact until a new trend direction is established.
4. **Efficient Market Adaptability:**
- The ATR-based method ensures adaptability to changing market conditions, expanding stop levels in high volatility and tightening them in low volatility periods.
- The Delta Price method offers a fixed approach, ideal for traders who prefer a non-ATR-based system for managing stop levels.
5. **Clean Visual Representation:**
- The indicator plots a clear, orange-colored trend stop line that dynamically follows the market movement.
- Provides a visual cue to determine potential entry and exit points efficiently.
### **How to Use:**
- **Trend Confirmation:**
- If the price remains above the trend stop line, it signals a bullish trend.
- If the price falls below the trend stop line, it indicates a bearish trend.
- **Trade Entries & Exits:**
- Consider long positions when the price remains above the trend stop.
- Consider short positions when the price stays below the trend stop.
- Utilize the trend stop line as a dynamic trailing stop-loss mechanism to protect gains and minimize losses.
- **Parameter Optimization:**
- Adjust the **Range**, **IMA Range**, and **Factor** to optimize settings based on the trading asset and time frame.
- Experiment with **Delta Price Mode** for assets where fixed price-based trailing stops are more effective.
### **Conclusion:**
The **Penny King Trend Indicator** is an essential tool for traders looking to capture market trends while ensuring effective risk management. Whether you prefer ATR-based adaptability or a fixed price stop approach, this indicator provides the flexibility needed to navigate different market conditions successfully. By integrating the **Penny King**, traders can enhance their trading strategy with a reliable and efficient trend-following system.
Adaptive Stochastic Oscillator with Signals [AIBitcoinTrend]👽 Adaptive Stochastic Oscillator with Signals (AIBitcoinTrend)
The Adaptive Stochastic Oscillator with Signals is a refined version of the traditional Stochastic Oscillator, dynamically adjusting its lookback period based on market volatility. This adaptive approach improves responsiveness to market conditions, reducing lag while maintaining trend sensitivity. Additionally, the indicator includes real-time divergence detection and an ATR-based trailing stop system, allowing traders to manage risk and optimize trade exits effectively.
👽 What Makes the Adaptive Stochastic Oscillator Unique?
Unlike the standard Stochastic Oscillator, which uses a fixed lookback period, this version dynamically adjusts the period length using an ATR-based fractal dimension. This makes it more responsive to market conditions, filtering out noise while capturing key price movements.
Key Features:
Adaptive Lookback Calculation – Stochastic period changes dynamically based on volatility.
Real-Time Divergence Detection – Identify bullish and bearish divergences instantly.
Implement Crossover/Crossunder signals tied to ATR-based trailing stops for risk management
👽 The Math Behind the Indicator
👾 Adaptive Lookback Period Calculation
Traditional Stochastic Oscillators use a fixed-length period for their calculations, which can lead to inaccurate signals in varying market conditions. This version automatically adjusts its lookback period based on market volatility using an ATR-based fractal dimension approach.
How it Works:
The fractal dimension (FD) is calculated using the ATR (Average True Range) over a defined period.
FD values dynamically adjust the Stochastic lookback period between a minimum and maximum range.
This results in a faster response in high-volatility conditions and smoother signals during low volatility.
👽 How Traders Can Use This Indicator
👾 Divergence Trading Strategy
Traders can anticipate trend reversals before they occur using real-time divergence detection.
Bullish Divergence Setup:
Identify price making a lower low while Stochastic %K makes a higher low.
Enter a long trade when Stochastic confirms upward momentum.
Bearish Divergence Setup:
Identify price making a higher high while Stochastic %K makes a lower high.
Enter a short trade when Stochastic confirms downward momentum.
👾 Trailing Stop & Signal-Based Trading
Bullish Setup:
✅Stochastic %K crosses above 90 → Buy signal.
✅A bullish trailing stop is placed at low - ATR × Multiplier.
✅Exit if the price crosses below the stop.
Bearish Setup:
✅Stochastic %K crosses below 10 → Sell signal.
✅A bearish trailing stop is placed at high + ATR × Multiplier.
✅Exit if the price crosses above the stop.
👽 Why It’s Useful for Traders
Adaptive Period Calculation: Dynamically adjusts to market volatility.
Real-Time Divergence Alerts: Helps traders identify trend reversals in advance.
ATR-Based Risk Management: Automatically adjusts stop levels based on price movements.
Works Across Multiple Markets & Timeframes: Useful for stocks, forex, crypto, and futures trading.
👽 Indicator Settings
Min & Max Lookback Periods – Define the range for the adaptive Stochastic period.
Enable Divergence Analysis – Toggle real-time divergence detection.
Lookback Period – Set the number of bars for detecting pivot points.
Enable Trailing Stop – Activate the dynamic trailing stop feature.
ATR Multiplier – Adjust stop-loss sensitivity.
Line Width & Colors – Customize stop-loss visualization.
Disclaimer: This indicator is designed for educational purposes and does not constitute financial advice. Please consult a qualified financial advisor before making investment decisions.
Strategy SuperTrend SDI WebhookThis Pine Script™ strategy is designed for automated trading in TradingView. It combines the SuperTrend indicator and Smoothed Directional Indicator (SDI) to generate buy and sell signals, with additional risk management features like stop loss, take profit, and trailing stop. The script also includes settings for leverage trading, equity-based position sizing, and webhook integration.
Key Features
1. Date-based Trade Execution
The strategy is active only between the start and end dates set by the user.
times ensures that trades occur only within this predefined time range.
2. Position Sizing and Leverage
Uses leverage trading to adjust position size dynamically based on initial equity.
The user can set leverage (leverage) and percentage of equity (usdprcnt).
The position size is calculated dynamically (initial_capital) based on account performance.
3. Take Profit, Stop Loss, and Trailing Stop
Take Profit (tp): Defines the target profit percentage.
Stop Loss (sl): Defines the maximum allowable loss per trade.
Trailing Stop (tr): Adjusts dynamically based on trade performance to lock in profits.
4. SuperTrend Indicator
SuperTrend (ta.supertrend) is used to determine the market trend.
If the price is above the SuperTrend line, it indicates an uptrend (bullish).
If the price is below the SuperTrend line, it signals a downtrend (bearish).
Plots visual indicators (green/red lines and circles) to show trend changes.
5. Smoothed Directional Indicator (SDI)
SDI helps to identify trend strength and momentum.
It calculates +DI (bullish strength) and -DI (bearish strength).
If +DI is higher than -DI, the market is considered bullish.
If -DI is higher than +DI, the market is considered bearish.
The background color changes based on the SDI signal.
6. Buy & Sell Conditions
Long Entry (Buy) Conditions:
SDI confirms an uptrend (+DI > -DI).
SuperTrend confirms an uptrend (price crosses above the SuperTrend line).
Short Entry (Sell) Conditions:
SDI confirms a downtrend (+DI < -DI).
SuperTrend confirms a downtrend (price crosses below the SuperTrend line).
Optionally, trades can be filtered using crossovers (occrs option).
7. Trade Execution and Exits
Market entries:
Long (strategy.entry("Long")) when conditions match.
Short (strategy.entry("Short")) when bearish conditions are met.
Trade exits:
Uses predefined take profit, stop loss, and trailing stop levels.
Positions are closed if the strategy is out of the valid time range.
Usage
Automated Trading Strategy:
Can be integrated with webhooks for automated execution on supported trading platforms.
Trend-Following Strategy:
Uses SuperTrend & SDI to identify trend direction and strength.
Risk-Managed Leverage Trading:
Supports position sizing, stop losses, and trailing stops.
Backtesting & Optimization:
Can be used for historical performance analysis before deploying live.
Conclusion
This strategy is suitable for traders who want to automate their trading using SuperTrend and SDI indicators. It incorporates risk management tools like stop loss, take profit, and trailing stop, making it adaptable for leverage trading. Traders can customize settings, conduct backtests, and integrate it with webhooks for real-time trade execution. 🚀
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
$TUBR: Stop Loss IndicatorATR-Based Stop Loss Indicator for TradingView by The Ultimate Bull Run Community: TUBR
**Overview**
The ATR-Based Stop Loss Indicator is a custom tool designed for traders using TradingView. It helps you determine optimal stop loss levels by leveraging the Average True Range (ATR), a popular measure of market volatility. By adapting to current market conditions, this indicator aims to minimize premature stop-outs and enhance your risk management strategy.
---
**Key Features**
- **Dynamic Stop Loss Levels**: Calculates stop loss prices based on the ATR, providing both long and short stop loss suggestions.
- **Customizable Parameters**: Adjust the ATR period, multiplier, and smoothing method to suit your trading style and the specific instrument you're trading.
- **Visual Aids**: Plots stop loss lines directly on your chart for easy visualization.
- **Alerts and Notifications** (Optional): Set up alerts to notify you when the price approaches or hits your stop loss levels.
---
**Understanding the Indicator**
1. **Average True Range (ATR)**:
- **What It Is**: ATR measures market volatility by calculating the average range between high and low prices over a specified period.
- **Why It's Useful**: A higher ATR indicates higher volatility, which can help you set stop losses that accommodate market fluctuations.
2. **ATR Multiplier**:
- **Purpose**: Determines how far your stop loss is placed from the current price based on the ATR.
- **Example**: An ATR multiplier of 1.5 means the stop loss is set at 1.5 times the ATR away from the current price.
3. **Smoothing Methods**:
- **Options**: Choose from RMA (default), SMA, EMA, WMA, or Hull MA.
- **Effect**: Different smoothing methods can make the ATR more responsive or smoother, affecting where the stop loss is placed.
---
**How the Indicator Works**
- **Long Stop Loss Calculation**:
- **Formula**: `Long Stop Loss = Close Price - (ATR * ATR Multiplier)`
- **Purpose**: For long positions, the stop loss is set below the current price to protect against downside risk.
- **Short Stop Loss Calculation**:
- **Formula**: `Short Stop Loss = Close Price + (ATR * ATR Multiplier)`
- **Purpose**: For short positions, the stop loss is set above the current price to protect against upside risk.
- **Plotting on the Chart**:
- **Green Line**: Represents the suggested stop loss level for long positions.
- **Red Line**: Represents the suggested stop loss level for short positions.
---
**How to Use the Indicator**
1. **Adding the Indicator to Your Chart**:
- **Step 1**: Copy the PineScript code of the indicator.
- **Step 2**: In TradingView, click on **Pine Editor** at the bottom of the platform.
- **Step 3**: Paste the code into the editor and click **Add to Chart**.
- **Step 4**: The indicator will appear on your chart with the default settings.
2. **Adjusting the Settings**:
- **ATR Period**:
- **Definition**: Number of periods over which the ATR is calculated.
- **Adjustment**: Increase for a smoother ATR; decrease for a more responsive ATR.
- **ATR Multiplier**:
- **Definition**: Factor by which the ATR is multiplied to set the stop loss distance.
- **Adjustment**: Increase to widen the stop loss (less likely to be hit); decrease to tighten the stop loss.
- **Smoothing Method**:
- **Options**: RMA, SMA, EMA, WMA, Hull MA.
- **Adjustment**: Experiment to see which method aligns best with your trading strategy.
- **Display Options**:
- **Show Long Stop Loss**: Toggle to display or hide the long stop loss line.
- **Show Short Stop Loss**: Toggle to display or hide the short stop loss line.
3. **Interpreting the Indicator**:
- **Long Positions**:
- **Action**: Set your stop loss at the value indicated by the green line when entering a long trade.
- **Short Positions**:
- **Action**: Set your stop loss at the value indicated by the red line when entering a short trade.
- **Adjusting Stop Losses**:
- **Trailing Stops**: You may choose to adjust your stop loss over time, moving it in the direction of your trade as the ATR-based stop loss levels change.
4. **Implementing in Your Trading Strategy**:
- **Risk Management**:
- **Position Sizing**: Use the stop loss distance to calculate your position size based on your risk tolerance.
- **Consistency**: Apply the same settings consistently to maintain discipline.
- **Combining with Other Indicators**:
- **Enhance Decision-Making**: Use in conjunction with trend indicators, support and resistance levels, or other technical analysis tools.
- **Alerts Setup** (If included in the code):
- **Purpose**: Receive notifications when the price approaches or hits your stop loss level.
- **Configuration**: Set up alerts in TradingView based on the alert conditions defined in the indicator.
---
**Benefits of Using This Indicator**
- **Adaptive Risk Management**: By accounting for current market volatility, the indicator helps prevent setting stop losses that are too tight or too wide.
- **Minimize Premature Stop-Outs**: Reduces the likelihood of being stopped out due to normal price fluctuations.
- **Flexibility**: Customizable settings allow you to tailor the indicator to different trading instruments and timeframes.
- **Visualization**: Clear visual representation of stop loss levels aids in quick decision-making.
---
**Things to Consider**
- **Market Conditions**:
- **High Volatility**: Be cautious as ATR values—and thus stop loss distances—can widen, increasing potential losses.
- **Low Volatility**: Tighter stop losses may increase the chance of being stopped out by minor price movements.
- **Backtesting and Optimization**:
- **Historical Analysis**: Test the indicator on past data to evaluate its effectiveness and adjust settings accordingly.
- **Continuous Improvement**: Regularly reassess and fine-tune the parameters to adapt to changing market conditions.
- **Risk Per Trade**:
- **Alignment with Risk Tolerance**: Ensure the stop loss level keeps potential losses within your acceptable risk per trade (e.g., 1-2% of your trading capital).
- **Emotional Discipline**:
- **Stick to Your Plan**: Avoid making impulsive changes to your stop loss levels based on emotions rather than analysis.
---
**Example Usage Scenario**
1. **Setting Up a Long Trade**:
- **Entry Price**: $100
- **ATR Value**: $2
- **ATR Multiplier**: 1.5
- **Calculated Stop Loss**: $100 - ($2 * 1.5) = $97
- **Action**: Place a stop loss order at $97.
2. **During the Trade**:
- **Price Increases to $105**
- **ATR Remains at $2**
- **New Stop Loss Level**: $105 - ($2 * 1.5) = $102
- **Action**: Move your stop loss up to $102 to lock in profits.
---
**Final Tips**
- **Documentation**: Keep a trading journal to record your trades, stop loss levels, and observations for future reference.
- **Education**: Continuously educate yourself on risk management and technical analysis to enhance your trading skills.
- **Support**: Engage with trading communities or seek professional advice if you're unsure about implementing the indicator effectively.
---
**Conclusion**
The ATR-Based Stop Loss Indicator is a valuable tool for traders looking to enhance their risk management by setting stop losses that adapt to market volatility. By integrating this indicator into your trading routine, you can improve your ability to protect capital and potentially increase profitability. Remember to use it as part of a comprehensive trading strategy, and always adhere to sound risk management principles.
---
**How to Access the Indicator**
To start using the ATR-Based Stop Loss Indicator, follow these steps:
1. **Obtain the Code**: Copy the PineScript code provided for the indicator.
2. **Create a New Indicator in TradingView**:
- Open TradingView and navigate to the **Pine Editor**.
- Paste the code into the editor.
- Click **Save** and give your indicator a name.
3. **Add to Chart**: Click **Add to Chart** to apply the indicator to your current chart.
4. **Customize Settings**: Adjust the input parameters to suit your preferences and start integrating the indicator into your trading strategy.
---
**Disclaimer**
Trading involves significant risk, and it's possible to lose all your capital. The ATR-Based Stop Loss Indicator is a tool to aid in decision-making but does not guarantee profits or prevent losses. Always conduct your own analysis and consider seeking advice from a financial professional before making trading decisions.
