Tuga SupertrendDescription
This strategy uses the Supertrend indicator enhanced with commission and slippage filters to capture trends on the daily chart. It’s designed to work on any asset but is especially effective in markets with consistent movements.
Use the date inputs to set the backtest period (default: from January 1, 2018, through today, June 30, 2025).
The default input values are optimized for the daily chart. For other timeframes, adjust the parameters to suit the asset you’re testing.
Release Notes
June 30, 2025
• Updated default backtest period to end on June 30, 2025.
• Default commission adjusted to 0.1 %.
• Slippage set to 3 ticks.
• Default slippage set to 3 ticks.
• Simplified the strategy name to “Tuga Supertrend”.
Default Parameters
Parameter Default Value
Supertrend Period 10
Multiplier (Factor) 3
Commission 0.1 %
Slippage 3 ticks
Start Date January 1, 2018
End Date June 30, 2025
Indicators and strategies
AlgoChadLin's BITCOIN H1 Breakout Strategy No.545Strategy Overview
AlgoChadLin's BITCOIN H1 Breakout Strategy No.545 is a sophisticated breakout trading system designed for Bitcoin on the H1 timeframe. It integrates multiple volatility and price action indicators to identify high-probability breakout opportunities, aiming to capitalize on significant market movements.
Auther: @algochadlin
Strategy Logic
Breakout Confirmation: Utilizes a combination of Average True Range (ATR) and Bollinger Bands to identify periods of low volatility followed by sharp price movements.
Long: Initiated when the price breaks above the previous hour's upper Bollinger Band, with ATR confirming increased volatility.
Short: Triggered when the price breaks below the previous hour's lower Bollinger Band, with ATR indicating heightened volatility.
Parameters
Price Entry Multiplier: Adjusts the entry price relative to the breakout level.
Exit After Bars: Specifies the number of bars to hold the position before exiting.
Profit Target (%): Defines the percentage gain at which to take profit.
Stop Loss Coefficient: Multiplier for ATR to calculate stop-loss distance.
Trailing Stop Coefficients: Defines the trailing stop parameters.
Biggest Range Period: Determines the lookback period for identifying the largest price range.
Setup
Timeframe: 1-Hour (H1)
Asset: Bitcoin, also suitable for ETH
Options Strategy V1.3📈 Options Strategy V1.3 — EMA Crossover + RSI + ATR + Opening Range
Overview:
This strategy is designed for short-term directional trades on large-cap stocks or ETFs, especially when trading options. It combines classic trend-following signals with momentum confirmation, volatility-based risk management, and session timing filters to help identify high-probability entries with predefined stop-loss and profit targets.
🔍 Strategy Components:
EMA Crossover (Fast/Slow)
Entry signals are triggered by the crossover of a short EMA above or below a long EMA — a traditional trend-following method to detect shifts in momentum.
RSI Filter
RSI confirms the signal by avoiding entries in overbought/oversold zones unless certain momentum conditions are met.
Long entry requires RSI ≥ Long Threshold
Short entry requires RSI ≤ Short Threshold
ATR-Based SL & TP
Stop-loss is set dynamically as a multiple of ATR below (long) or above (short) the entry price.
Take-profit is placed as a ratio (TP/SL) of the stop distance, ensuring consistent reward/risk structure.
Opening Range Filter (Optional)
If enabled, the strategy only triggers trades after price breaks out of the 09:30–09:45 EST range, ensuring participation in directional moves.
Session Filters
No trades from 04:00 to 09:30 and from 16:00 to 20:00 EST, avoiding low-liquidity periods.
All open trades are closed at 15:55 EST, to avoid overnight risk or expiration issues for options.
⚙️ Built-in Presets:
You can choose one of the built-in ticker-specific presets for optimal conditions:
Ticker EMAs RSI (Long/Short) ATR SL×ATR TP/SL
SPY 8/28 56 / 26 14 1.4× 4.0×
TSLA 23/27 56 / 33 13 1.4× 3.6×
AAPL 6/13 61 / 26 23 1.4× 2.1×
MSFT 25/32 54 / 26 14 1.2× 2.2×
META 25/32 53 / 26 17 1.8× 2.3×
AMZN 28/32 55 / 25 16 1.8× 2.3×
You can also choose "Custom" to fully configure all parameters to your own market and strategy preferences.
📌 Best Use Case:
This strategy is especially suited for intraday options trading, where timing and risk control are critical. It works best on liquid tickers with strong trends or clear breakout behavior.
Operator Levels by Trade InsiderOperator Levels by Trade Insider
Overview
Operator Levels by Trade Insider is a breakout trading strategy designed for intraday trading on the Nifty 50 index using a 5-minute timeframe. It identifies high-probability trade setups based on the first 5-minute candle’s price range of the day, generating target levels for long and short positions. The strategy uses a customizable Simple Moving Average (SMA) for trend filtering and a strict 1:1.5 risk-to-reward validation, making it ideal for intraday traders in the Indian equity market.
Key Features
Dynamic Target Levels: Plots two sets of target levels above and below the first 5-minute candle’s range, calculated using a proprietary volatility-based multiplier to project realistic price objectives.
Trend Filtering: Uses a user-adjustable SMA (default: 24 periods) to ensure entries align with the prevailing market trend, reducing false breakouts.
Risk-to-Reward Validation: Only executes trades with a minimum 1:1.5 risk-to-reward ratio, promoting disciplined risk management.
Clean Visualization: Displays target levels as dashed lines with color-coded labels for easy identification of trade exits (Target 1, Target 2, Stop-Loss).
Customizable Settings: Allows adjustment of SMA period, position size, and risk parameters to suit different trading styles and market conditions.
What Makes It Unique?
Unlike standard breakout strategies, Operator Levels employs a proprietary multiplier derived from volatility analysis to optimize target levels for the Nifty 50’s intraday movements. The adjustable SMA period and strict 1:1.5 risk-to-reward filter enhance entry precision, reducing noise compared to traditional range breakout systems. The strategy’s minimalist design ensures actionable signals without overwhelming the chart, tailored specifically for the fast-paced 5-minute timeframe.
How to Use
Setup: Apply on a 5-minute chart for the Nifty 50 index (e.g., NSE:NIFTY). Recommended for intraday trading.
Default Settings:
Position Size: 5% of equity per trade (adjustable via default_qty_value).
SMA Period: 24 (adjustable; e.g., set to 12 for faster signals or 50 for smoother trends).
Risk-to-Reward: 1:1.5 minimum for all trades.
Trading Process:
Long Entry: Triggered when price breaks above the first 5-minute candle’s high, is above the SMA, and meets the 1:1.5 risk-to-reward ratio.
Short Entry: Triggered when price breaks below the first 5-minute candle’s low, is below the SMA, and meets the 1:1.5 risk-to-reward ratio.
Exits: Close positions at Target 1, Target 2, or Stop-Loss, with alerts set via TradingView for real-time notifications.
Integration: Combine with volume analysis or support/resistance indicators (e.g., RSI, pivot points) for confirmation of breakouts.
Example: On a Nifty 50 5-minute chart, enter a long trade when price breaks above the first candle’s high and is above the 24-period SMA, targeting the first dashed blue line (Target 1) with a stop-loss at the first candle’s low.
Backtesting Results
Test Parameters:
Symbol: NSE:NIFTY, 5-minute timeframe
Period: 6 months (January 2025–June 2025)
Initial Capital: $10,000
Commission: 0.1% per trade
Slippage: 5 ticks
Risk per Trade: 5% of equity
Results:
Total Trades: 150
Win Rate: 62%
Average Risk-to-Reward: 1.5:1
Notes: Results are based on standard candles to ensure realistic performance. Backtest on your preferred timeframe and symbol to validate suitability.
Limitations
Trade Frequency: The 5-minute timeframe generates more trades than daily charts but may still require active market sessions (e.g., 9:15 AM–3:30 PM IST) for optimal results.
Market Conditions: Breakouts may underperform in low-volatility or ranging markets; use additional confirmation (e.g., volume spikes or Nifty 50 futures data) to filter signals.
Risk Management: While the 1:1.5 risk-to-reward ratio is conservative, traders should back test and adjust position sizing and SMA period to match their risk tolerance.
HMA Crossover + ATR + Curvature (Long & Short)📏 Hull Moving Averages (Trend Filters)
- fastHMA = ta.hma(close, fastLength)
- slowHMA = ta.hma(close, slowLength)
These two HMAs act as dynamic trend indicators:
- A bullish crossover of fast over slow HMA signals a potential long setup.
- A bearish crossunder triggers short interest.
⚡️ Curvature (Acceleration Filter)
- curv = ta.change(ta.change(fastHMA))
This calculates the second-order change (akin to the second derivative) of the fast HMA — effectively the acceleration of the trend. It serves as a filter:
- For long entries: curv > curvThresh (positive acceleration)
- For short entries: curv < -curvThresh (negative acceleration)
It helps eliminate weak or stagnating moves by requiring momentum behind the crossover.
📈 Volatility-Based Risk Management (ATR)
- atr = ta.atr(atrLength)
- stopLoss = atr * atrMult
- trailStop = atr * trailMult
These define your:
- Initial stop loss: scaled to recent volatility using ATR and atrMult.
- Trailing stop: also ATR-scaled, to lock in gains dynamically as price moves favorably.
💰 Position Sizing via Risk Percent
- capital = strategy.equity
- riskCapital = capital * (riskPercent / 100)
- qty = riskCapital / stopLoss
This dynamically calculates the position size (qty) such that if the stop loss is hit, the loss does not exceed the predefined percentage of account equity. It’s a volatility-adjusted position sizing method, keeping your risk consistent regardless of market conditions.
📌 Execution Logic
- Long Entry: on bullish HMA crossover with rising curvature.
- Short Entry: on bearish crossover with falling curvature.
- Exits: use ATR-based trailing stops.
- Position is closed when trend conditions reverse (e.g., bearish crossover exits the long).
This framework gives you:
- Trend-following logic (via HMAs)
- Momentum confirmation (via curvature)
- Volatility-aware execution and exits (via ATR)
- Risk-controlled dynamic sizing
Want to get surgical and test what happens if we use curvature on the difference between HMAs instead? That might give some cool insights into trend strength transitions.
Long-Leg Doji Breakout StrategyThe Long-Leg Doji Breakout Strategy is a sophisticated technical analysis approach that capitalizes on market psychology and price action patterns.
Core Concept: The strategy identifies Long-Leg Doji candlestick patterns, which represent periods of extreme market indecision where buyers and sellers are in equilibrium. These patterns often precede significant price movements as the market resolves this indecision.
Pattern Recognition: The algorithm uses strict mathematical criteria to identify authentic Long-Leg Doji patterns. It requires the candle body to be extremely small (≤0.1% of the total range) while having long wicks on both sides (at least 2x the body size). An ATR filter ensures the pattern is significant relative to recent volatility.
Trading Logic: Once a Long-Leg Doji is identified, the strategy enters a "waiting mode," monitoring for a breakout above the doji's high (long signal) or below its low (short signal). This confirmation approach reduces false signals by ensuring the market has chosen a direction.
Risk Management: The strategy allocates 10% of equity per trade and uses a simple moving average crossover for exits. Visual indicators help traders understand the pattern identification and trade execution process.
Psychological Foundation: The strategy exploits the natural market cycle where uncertainty (represented by the doji) gives way to conviction (the breakout), creating high-probability trading opportunities.
The strength of this approach lies in its ability to identify moments when market sentiment shifts from confusion to clarity, providing traders with well-defined entry and exit points while maintaining proper risk management protocols.
How It Works
The strategy operates on a simple yet powerful principle: identify periods of market indecision, then trade the subsequent breakout when the market chooses direction.
Step 1: Pattern Detection
The algorithm scans for Long-Leg Doji candles, which have three key characteristics:
Tiny body (open and close prices nearly equal)
Long upper wick (significant rejection of higher prices)
Long lower wick (significant rejection of lower prices)
Step 2: Confirmation Wait
Once a doji is detected, the strategy doesn't immediately trade. Instead, it marks the high and low of that candle and waits for a definitive breakout.
Step 3: Trade Execution
Long Entry: When price closes above the doji's high
Short Entry: When price closes below the doji's low
Step 4: Exit Strategy
Positions are closed when price crosses back through a 20-period moving average, indicating potential trend reversal.
Market Psychology Behind It
A Long-Leg Doji represents a battlefield between bulls and bears that ends in a stalemate. The long wicks show that both sides tried to push price in their favor but failed. This creates a coiled spring effect - when one side finally gains control, the move can be explosive as trapped traders rush to exit and momentum traders jump aboard.
Key Parameters
Doji Body Threshold (0.1%): Ensures the body is truly small relative to the candle's range
Wick Ratio (2.0): Both wicks must be at least twice the body size
ATR Filter: Uses Average True Range to ensure the pattern is significant in current market conditions
Position Size: 10% of equity per trade for balanced risk management
Pros:
High Probability Setups: Doji patterns at key levels often lead to significant moves as they represent genuine shifts in market sentiment.
Clear Rules: Objective criteria for entry and exit eliminate emotional decision-making and provide consistent execution.
Risk Management: Built-in position sizing and exit rules help protect capital during losing trades.
Market Neutral: Works equally well for long and short positions, adapting to market direction rather than fighting it.
Visual Confirmation: The strategy provides clear visual cues, making it easy to understand when patterns are forming and trades are triggered.
Cons:
False Breakouts: In choppy or ranging markets, price may break the doji levels only to quickly reverse, creating whipsaws.
Patience Required: Traders must wait for both pattern formation and breakout confirmation, which can test discipline during active market periods.
Simple Exit Logic: The moving average exit may be too simplistic, potentially cutting profits short during strong trends or holding losers too long during reversals.
Volatility Dependent: The strategy relies on sufficient volatility to create meaningful doji patterns - it may underperform in extremely quiet markets.
Lagging Entries: Waiting for breakout confirmation means missing the very beginning of moves, reducing potential profit margins.
Best Market Conditions
The strategy performs optimally during periods of moderate volatility when markets are making genuine directional decisions rather than just random noise. It works particularly well around key support/resistance levels where the market's indecision is most meaningful.
Optimization Considerations
Consider combining with additional confluence factors like volume analysis, support/resistance levels, or other technical indicators to improve signal quality. The exit strategy could also be enhanced with trailing stops or multiple profit targets to better capture extended moves while protecting gains.
Best for Index option,
Enjoy !!
Multi-Confluence Swing Hunter V1# Multi-Confluence Swing Hunter V1 - Complete Description
Overview
The Multi-Confluence Swing Hunter V1 is a sophisticated low timeframe scalping strategy specifically optimized for MSTR (MicroStrategy) trading. This strategy employs a comprehensive point-based scoring system that combines optimized technical indicators, price action analysis, and reversal pattern recognition to generate precise trading signals on lower timeframes.
Performance Highlight:
In backtesting on MSTR 5-minute charts, this strategy has demonstrated over 200% profit performance, showcasing its effectiveness in capturing rapid price movements and volatility patterns unique to MicroStrategy's trading behavior.
The strategy's parameters have been fine-tuned for MSTR's unique volatility characteristics, though they can be optimized for other high-volatility instruments as well.
## Key Innovation & Originality
This strategy introduces a unique **dual scoring system** approach:
- **Entry Scoring**: Identifies swing bottoms using 13+ different technical criteria
- **Exit Scoring**: Identifies swing tops using inverse criteria for optimal exit timing
Unlike traditional strategies that rely on simple indicator crossovers, this system quantifies market conditions through a weighted scoring mechanism, providing objective, data-driven entry and exit decisions.
## Technical Foundation
### Optimized Indicator Parameters
The strategy utilizes extensively backtested parameters specifically optimized for MSTR's volatility patterns:
**MACD Configuration (3,10,3)**:
- Fast EMA: 3 periods (vs standard 12)
- Slow EMA: 10 periods (vs standard 26)
- Signal Line: 3 periods (vs standard 9)
- **Rationale**: These faster parameters provide earlier signal detection while maintaining reliability, particularly effective for MSTR's rapid price movements and high-frequency volatility
**RSI Configuration (21-period)**:
- Length: 21 periods (vs standard 14)
- Oversold: 30 level
- Extreme Oversold: 25 level
- **Rationale**: The 21-period RSI reduces false signals while still capturing oversold conditions effectively in MSTR's volatile environment
**Parameter Adaptability**: While optimized for MSTR, these parameters can be adjusted for other high-volatility instruments. Faster-moving stocks may benefit from even shorter MACD periods, while less volatile assets might require longer periods for optimal performance.
### Scoring System Methodology
**Entry Score Components (Minimum 13 points required)**:
1. **RSI Signals** (max 5 points):
- RSI < 30: +2 points
- RSI < 25: +2 points
- RSI turning up: +1 point
2. **MACD Signals** (max 8 points):
- MACD below zero: +1 point
- MACD turning up: +2 points
- MACD histogram improving: +2 points
- MACD bullish divergence: +3 points
3. **Price Action** (max 4 points):
- Long lower wick (>50%): +2 points
- Small body (<30%): +1 point
- Bullish close: +1 point
4. **Pattern Recognition** (max 8 points):
- RSI bullish divergence: +4 points
- Quick recovery pattern: +2 points
- Reversal confirmation: +4 points
**Exit Score Components (Minimum 13 points required)**:
Uses inverse criteria to identify swing tops with similar weighting system.
## Risk Management Features
### Position Sizing & Risk Control
- **Single Position Strategy**: 100% equity allocation per trade
- **No Overlapping Positions**: Ensures focused risk management
- **Configurable Risk/Reward**: Default 5:1 ratio optimized for volatile assets
### Stop Loss & Take Profit Logic
- **Dynamic Stop Loss**: Based on recent swing lows with configurable buffer
- **Risk-Based Take Profit**: Calculated using risk/reward ratio
- **Clean Exit Logic**: Prevents conflicting signals
## Default Settings Optimization
### Key Parameters (Optimized for MSTR/Bitcoin-style volatility):
- **Minimum Entry Score**: 13 (ensures high-conviction entries)
- **Minimum Exit Score**: 13 (prevents premature exits)
- **Risk/Reward Ratio**: 5.0 (accounts for volatility)
- **Lower Wick Threshold**: 50% (identifies true hammer patterns)
- **Divergence Lookback**: 8 bars (optimal for swing timeframes)
### Why These Defaults Work for MSTR:
1. **Higher Score Thresholds**: MSTR's volatility requires more confirmation
2. **5:1 Risk/Reward**: Compensates for wider stops needed in volatile markets
3. **Faster MACD**: Captures momentum shifts quickly in fast-moving stocks
4. **21-period RSI**: Reduces noise while maintaining sensitivity
## Visual Features
### Score Display System
- **Green Labels**: Entry scores ≥10 points (below bars)
- **Red Labels**: Exit scores ≥10 points (above bars)
- **Large Triangles**: Actual trade entries/exits
- **Small Triangles**: Reversal pattern confirmations
### Chart Cleanliness
- Indicators plotted in separate panes (MACD, RSI)
- TP/SL levels shown only during active positions
- Clear trade markers distinguish signals from actual trades
## Backtesting Specifications
### Realistic Trading Conditions
- **Commission**: 0.1% per trade
- **Slippage**: 3 points
- **Initial Capital**: $1,000
- **Account Type**: Cash (no margin)
### Sample Size Considerations
- Strategy designed for 100+ trade sample sizes
- Recommended timeframes: 4H, 1D for swing trading
- Optimal for trending/volatile markets
## Strategy Limitations & Considerations
### Market Conditions
- **Best Performance**: Trending markets with clear swings
- **Reduced Effectiveness**: Highly choppy, sideways markets
- **Volatility Dependency**: Optimized for moderate to high volatility assets
### Risk Warnings
- **High Allocation**: 100% position sizing increases risk
- **No Diversification**: Single position strategy
- **Backtesting Limitation**: Past performance doesn't guarantee future results
## Usage Guidelines
### Recommended Assets & Timeframes
- **Primary Target**: MSTR (MicroStrategy) - 5min to 15min timeframes
- **Secondary Targets**: High-volatility stocks (TSLA, NVDA, COIN, etc.)
- **Crypto Markets**: Bitcoin, Ethereum (with parameter adjustments)
- **Timeframe Optimization**: 1min-15min for scalping, 30min-1H for swing scalping
### Timeframe Recommendations
- **Primary Scalping**: 5-minute and 15-minute charts
- **Active Monitoring**: 1-minute for precise entries
- **Swing Scalping**: 30-minute to 1-hour timeframes
- **Avoid**: Sub-1-minute (excessive noise) and above 4-hour (reduces scalping opportunities)
## Technical Requirements
- **Pine Script Version**: v6
- **Overlay**: Yes (plots on price chart)
- **Additional Panes**: MACD and RSI indicators
- **Real-time Compatibility**: Confirmed bar signals only
## Customization Options
All parameters are fully customizable through inputs:
- Indicator lengths and levels
- Scoring thresholds
- Risk management settings
- Visual display preferences
- Date range filtering
## Conclusion
This scalping strategy represents a comprehensive approach to low timeframe trading that combines multiple technical analysis methods into a cohesive, quantified system specifically optimized for MSTR's unique volatility characteristics. The optimized parameters and scoring methodology provide a systematic way to identify high-probability scalping setups while managing risk effectively in fast-moving markets.
The strategy's strength lies in its objective, multi-criteria approach that removes emotional decision-making from scalping while maintaining the flexibility to adapt to different instruments through parameter optimization. While designed for MSTR, the underlying methodology can be fine-tuned for other high-volatility assets across various markets.
**Important Disclaimer**: This strategy is designed for experienced scalpers and is optimized for MSTR trading. The high-frequency nature of scalping involves significant risk. Past performance does not guarantee future results. Always conduct your own analysis, consider your risk tolerance, and be aware of commission/slippage costs that can significantly impact scalping profitability.
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Ticker Pulse Meter + Fear EKG StrategyDescription
The Ticker Pulse Meter + Fear EKG Strategy is a technical analysis tool designed to identify potential entry and exit points for long positions based on price action relative to historical ranges. It combines two proprietary indicators: the Ticker Pulse Meter (TPM), which measures price positioning within short- and long-term ranges, and the Fear EKG, a VIX-inspired oscillator that detects extreme market conditions. The strategy is non-repainting, ensuring signals are generated only on confirmed bars to avoid false positives. Visual enhancements, such as optional moving averages and Bollinger Bands, provide additional context but are not core to the strategy's logic. This script is suitable for traders seeking a systematic approach to capturing momentum and mean-reversion opportunities.
How It Works
The strategy evaluates price action using two key metrics:
Ticker Pulse Meter (TPM): Measures the current price's position within short- and long-term price ranges to identify momentum or overextension.
Fear EKG: Detects extreme selling pressure (akin to "irrational selling") by analyzing price behavior relative to historical lows, inspired by volatility-based oscillators.
Entry signals are generated when specific conditions align, indicating potential buying opportunities. Exits are triggered based on predefined thresholds or partial position closures to manage risk. The strategy supports customizable lookback periods, thresholds, and exit percentages, allowing flexibility across different markets and timeframes. Visual cues, such as entry/exit dots and a position table, enhance usability, while optional overlays like moving averages and Bollinger Bands provide additional chart context.
Calculation Overview
Price Range Calculations:
Short-Term Range: Uses the lowest low (min_price_short) and highest high (max_price_short) over a user-defined short lookback period (lookback_short, default 50 bars).
Long-Term Range: Uses the lowest low (min_price_long) and highest high (max_price_long) over a user-defined long lookback period (lookback_long, default 200 bars).
Percentage Metrics:
pct_above_short: Percentage of the current close above the short-term range.
pct_above_long: Percentage of the current close above the long-term range.
Combined metrics (pct_above_long_above_short, pct_below_long_below_short) normalize price action for signal generation.
Signal Generation:
Long Entry (TPM): Triggered when pct_above_long_above_short crosses above a user-defined threshold (entryThresholdhigh, default 20) and pct_below_long_below_short is below a low threshold (entryThresholdlow, default 40).
Long Entry (Fear EKG): Triggered when pct_below_long_below_short crosses under an extreme threshold (orangeEntryThreshold, default 95), indicating potential oversold conditions.
Long Exit: Triggered when pct_above_long_above_short crosses under a profit-taking level (profitTake, default 95). Partial exits are supported via a user-defined percentage (exitAmt, default 50%).
Non-Repainting Logic: Signals are calculated using data from the previous bar ( ) and only plotted on confirmed bars (barstate.isconfirmed), ensuring reliability.
Visual Enhancements:
Optional moving averages (SMA, EMA, WMA, VWMA, or SMMA) and Bollinger Bands can be enabled for trend context.
A position table displays real-time metrics, including open positions, Fear EKG, and Ticker Pulse values.
Background highlights mark periods of high selling pressure.
Entry Rules
Long Entry:
TPM Signal: Occurs when the price shows strength relative to both short- and long-term ranges, as defined by pct_above_long_above_short crossing above entryThresholdhigh and pct_below_long_below_short below entryThresholdlow.
Fear EKG Signal: Triggered by extreme selling pressure, when pct_below_long_below_short crosses under orangeEntryThreshold. This signal is optional and can be toggled via enable_yellow_signals.
Entries are executed only on confirmed bars to prevent repainting.
Exit Rules
Long Exit: Triggered when pct_above_long_above_short crosses under profitTake.
Partial exits are supported, with the strategy closing a user-defined percentage of the position (exitAmt) up to four times per position (exit_count limit).
Exits can be disabled or adjusted via enable_short_signal and exitPercentage settings.
Inputs
Backtest Start Date: Defines the start of the backtesting period (default: Jan 1, 2017).
Lookback Periods: Short (lookback_short, default 50) and long (lookback_long, default 200) periods for range calculations.
Resolution: Timeframe for price data (default: Daily).
Entry/Exit Thresholds:
entryThresholdhigh (default 20): Threshold for TPM entry.
entryThresholdlow (default 40): Secondary condition for TPM entry.
orangeEntryThreshold (default 95): Threshold for Fear EKG entry.
profitTake (default 95): Exit threshold.
exitAmt (default 50%): Percentage of position to exit.
Visual Options: Toggle for moving averages and Bollinger Bands, with customizable types and lengths.
Notes
The strategy is designed to work across various timeframes and assets, with data sourced from user-selected resolutions (i_res).
Alerts are included for long entry and exit signals, facilitating integration with TradingView's alert system.
The script avoids repainting by using confirmed bar data and shifted calculations ( ).
Visual elements (e.g., SMA, Bollinger Bands) are inspired by standard Pine Script practices and are optional, not integral to the core logic.
Usage
Apply the script to a chart, adjust input settings to suit your trading style, and use the visual cues (entry/exit dots, position table) to monitor signals. Enable alerts for real-time notifications.
Designed to work best on Daily timeframe.
Baseline TrendBaseline Trend Strategy Overview
Baseline Trend is a crypto-only trading strategy built on straightforward price-based logic: market direction is determined solely by the price’s position relative to a selected baseline open price. No technical indicators like RSI, MACD, or volume are used—this approach is purely focused on price action and position size manipulation.
This strategy is a genuine concept, developed from my own market analysis and logical theory, refined through extensive observation of crypto market behaviour.
While the strategy offers structure and adaptability, it’s important to recognise that no single trading system or indicator fits all market conditions. This tool is meant to support decision-making, not replace it—encouraging traders to stay flexible, informed, and in control of their risk.
Important Usage Note:
This system is intended for crypto markets only.
– When used as an indicator guide, it can be applied to both spot and futures markets.
– However, when used with web-hook automation, it is designed only for futures contracts.
Ensure compatibility with your trading setup before using automation features.
Core Logic: The Baseline
The strategy revolves around the concept of a “Baseline”, with three types available:
Main Baseline: Defines the primary trend direction. If the price is above, go long; if below, go short.
Second Baseline and Third Baseline: Used to measure buying/selling pressure and are key to certain take-profit logic options.
Baselines are customisable to different timeframes—Year, Month, Week, and more—based on available input settings. Structurally, the Main Baseline is the highest-level trend reference, followed by the Second, then Third.
Users can mix and match these baselines across timeframes to backtest crypto symbols and understand behaviour patterns, particularly when used with standard candlestick charts.
Entry & Exit Logic
Entry Signal: Triggered when price crosses over/under a defined distance (percentage) from the Main Baseline. This distance is the Trade Line, calculated based on the close price.
Exit Signal / Stop Loss: If price moves un-favorable and crosses over/under the Stop Loss Line (a defined distance from the Main Baseline), the open position will be force-closed according to user-defined settings.
LiqC (Liquidation Cut)
LiqC is a secondary stop-loss that activates when a leveraged position’s loss equals or exceeds the user-defined liquidation threshold. It forcefully closes the position to help prevent full liquidation before stop-loss, providing an extra layer of protection.
This LiqC is directly tied to the leverage level set by the user. Please ensure you understand how leverage affects liquidation risk, as different broker exchanges may use different liquidation ratio models. Using incorrect assumptions or mismatched leverage values may result in unexpected behaviour.
Position Sizing & Block Units
This strategy features a block-based position sizing system designed for flexibility and precision in trade management:
Block Range: Customisable from 1 to 10 blocks
Risk Allocation: Controlled through a user-defined ROE (Risk of Equity) value
For example, setting an ROE of 0.1% with 10 blocks allocates a total of 1% of account equity to the position. This structure supports both conservative and aggressive risk approaches, depending on user preference.
Block sizes are automatically calculated in alignment with exchange requirements, using Minimum Notional Value (MNV) and Minimum Trade Amount (MTA). These values are dynamically calculated based on the live market price, and scaled relative to the trader’s balance and selected risk percentage. This ensures accurate sizing with built-in adaptability for any account level and current market conditions.
Scalping Meets Trend Holding
This system blends short-term scalping with longer-term trend holding, offering a flexible and adaptive trading style.
Example:
Enter 10 blocks → take quick profits on 5 blocks → let the remaining 5 ride the trend.
This dual-layered approach allows traders to secure early gains while staying positioned for larger market moves. Think of it as:
5 Blocks to Protect: Capture quick wins and manage exposure.
5 Blocks to Pursue: Let profits run by following the broader trend.
By combining both protection and pursuit, the strategy supports risk control without sacrificing the potential for extended returns.
Flexible Take-Profit Logic
The strategy supports multiple, customisable take-profit mechanisms:
TP1–4 (Profit Percentage)
Triggers take profit of 1 block unit when unrealised gains reach defined percentage thresholds (TP1, TP2, TP3, TP4).
Buying/Selling Pressure-Based Take Profit
D1 – Pressure 1
Measures pressure between Second and Third Baselines.
If the distance between them exceeds a user-defined DPT (Decrease Post Threshold) and the price moves far enough from the Third Baseline, D1 activates to take profit or scale out one block.
D2 – Pressure 2
Measures pressure between the Main and Second Baselines.
Works similarly to D1, using a separate distance and pressure trigger.
Note: Both D1 and D2 deactivate in reversal or even trend conditions.
D3–5: High-High / Low-Low Logic
Based on bar index tracking after position entry:
For Long Positions: If after D3 bars the price doesn't exceed the previous bar's high, the system executes a take profit or scale-out.
For Short Positions: If the price doesn't drop below the previous low, the same logic applies.
This approach adds time-based and momentum-aware exit flexibility.
Leverage & Liquidation Risk
When backtesting with leverage enabled, the system checks whether historical candles exceed the liquidation range, calculated based on the average entry price and the leverage input. If the Liquidation Risk Count exceeds 1, profit and loss accuracy may be affected. Traders are encouraged to monitor this count closely to ensure realistic backtesting results.
Since the system cannot directly control or sync with your broker exchange’s actual leverage setting, it’s important to manually match the system’s leverage input with your broker’s configured leverage.
For example: If the system leverage input is set to 10, your exchange leverage setting must also be set to 10. Any mismatch will lead to inaccurate liquidation risk and PnL calculations.
Backtesting and Customisation
All TP1–4 and D1–5 functions are fully optional and customisable. Users are encouraged to backtest different crypto symbols to observe how price behaviour aligns with baseline structures and pressure metrics.
Each of the TP1–4 and D1–5 triggers is designed to execute only once per open position, ensuring controlled and predictable behaviour within each trade cycle.
Since backtesting is based on available historical bar data, please note that data availability varies depending on your TradingView subscription plan. For more reliable insights, it’s recommended to backtest across multiple time ranges, not just the full dataset, to assess the stability and consistency of the strategy’s performance over time.
Additionally, the time frame resolution interval in TradingView is customisable. For best results, use commonly supported time frames such as 30 minutes, 1 hour, 4 hours, 1 day, or 1 week. While the system is designed to support a broad range of intervals, non-standard resolutions may still cause calculation errors.
Currently, the system supports the following resolution ranges:
Intraday: from 1 minute to 720 minutes
(e.g., 60 minutes = 1 hour, 240 minutes = 4 hours, 720 minutes = 12 hours)
Daily: from 1 day to 6 days
Weekly: from 1 week to 3 weeks
Monthly: from 1 month to 4 months
Although the script is built to adapt to various resolutions, users should still monitor output behaviour closely, especially when testing less common or edge-case time frames.
System Usage Notice:
This system can be used as a standalone trading indicator or integrated with an exchange that supports web-hook signal execution. If you choose to automate trades via web-hook, please ensure you fully understand how to configure the setup properly. Web-hook integration methods vary between exchanges, and incorrect setup may lead to unintended trades. Users are responsible for ensuring proper configuration and monitoring of their automation.
Note on Lower Time Frame Usage
When using lower time frames (e.g., 1-minute charts) as the trading time frame, please be aware that available historical data may be limited depending on your subscription plan. This can affect the depth and reliability of backtesting, making it harder to establish a trustworthy probability model for a symbol’s behaviour over time.
Additionally, when pairing a high-level Main Baseline (MBL) time line (such as "1 Month") with low time frame resolutions (like 1-minute), you may encounter order execution limits or calculation overloads during backtesting. This is due to the large number of historical bars required, which can strain the system's capacity.
That said, if a user intentionally chooses to work with lower time frames, that decision is fully respected—but it should be done with awareness and at the user’s own risk.
Things to Be Aware Of (Web-hook Usage Only)
The following points apply if you're using web-hook automation to send signals from the system to an exchange:
Alert Signal Reliability
During extreme market volatility, some broker exchanges may fail to respond to web-hook signals due to traffic overload. While rare, this has occurred in the past and should be considered when relying on automation.
Alert Expiration (TradingView)
If you're on a Basic plan, TradingView alerts are only active for a limited time—typically around 1.5 months. Once expired, signals will no longer be sent out.
To keep your system active, reset the alert before expiration. For uninterrupted alerts, consider upgrading to a Premium plan, which supports permanent alert activation.
TradingView Alert Maintenance
TradingView may occasionally perform system maintenance, during which alerts may temporarily stop functioning. It’s recommended to monitor TradingView’s status if you’re relying on real-time automation.
Repainting
As of the current version, no repainting behaviour has been observed. Signal stability and consistency have been maintained across real-time and historical bars.
Order Execution Type and Fill Logic
All signals use Limit orders by default, except for MBL Exit and Fallback execution, which use Market orders.
Since Limit orders are not guaranteed to fill, the system includes logic to cancel unfilled orders and resend them. If necessary, a Fallback Market order is used to avoid conflict with new incoming trades.
This has only happened once, and is considered rare, but users should always monitor execution status to ensure accuracy and alignment with system behaviour.
Feedback
If you encounter any errors, bugs, or unexpected behaviour while using the system, please don’t hesitate to let me know. Your input is invaluable for helping improve the strategy in future updates.
Likewise, if you have any suggestions or ideas for enhancing the system—whether it’s a new feature, adjustment, or usability improvement—please feel free to share. Together, we can continue refining the tool to make it more robust and beneficial for everyone.
Disclaimer
All trading involves risk, particularly in the crypto market where conditions can be highly volatile. Past performance does not guarantee future outcomes, and market behaviour may evolve over time. This strategy is offered as a tool to support trading decisions and should not be considered financial or investment advice. Each user is responsible for their own actions and accepts full responsibility for any results that may arise from using this system.
LANZ Strategy 1.0 [Backtest]🔷 LANZ Strategy 1.0 — Time-Based Session Trading with Smart Reversal Logic and Risk-Controlled Limit Orders
This backtest version of LANZ Strategy 1.0 brings precision to session-based trading by using directional confirmation, pre-defined risk parameters, and limit orders that execute overnight. Designed for the 1-hour timeframe, it allows traders to evaluate the system with configurable SL, TP, and risk settings in a fully automated environment.
🧠 Core Strategy Logic:
1. Directional Confirmation at 18:00 NY:
At 18:00 NY, the system compares the 08:00 open vs the 18:00 close:
If the direction matches the previous day, the signal is reversed.
If the direction differs, the current day's trend is kept.
This logic is designed to avoid momentum exhaustion and capture corrective reversals.
2. Entry Level Definition:
Based on the confirmed direction:
For BUY, the Low of the day is used as Entry Point (EP).
For SELL, the High of the day becomes EP.
The system plots a Stop Loss and Take Profit based on user-defined pip inputs (default: SL = 18 pips, TP = 54 pips → RR 1:3).
3. Time-Limited Entry Execution (LIMIT Orders):
Orders are sent after 18:00 NY and can be triggered anytime between 18:00 and 08:00 NY.
If EP is not touched before 08:00, the order is automatically cancelled.
4. Manual Close Feature:
If the trade is still open at the configured hour (default 09:00 NY), the system closes all positions, simulating realistic intraday exit scenarios.
5. Lot Size Calculation Based on Risk:
Lot size is dynamically calculated using the account size, risk percentage, and SL distance.
This ensures consistent risk exposure regardless of market volatility.
⚙️ Step-by-Step Flow:
08:00 NY → Captures the open of the day.
18:00 NY → Confirms direction and defines EP, SL, and TP.
After 18:00 NY → If conditions are met, a LIMIT order is placed at EP.
Between 18:00–08:00 NY → If price touches EP, the trade is executed.
At 08:00 NY → If EP wasn’t touched, the order is cancelled.
At Configured Manual Close Time (default 09:00 NY) → All open positions are force-closed if still active.
🧪 Backtest Settings:
Timeframe: 1-hour only
Order Type: strategy.entry() with limit=
SL/TP Configurable: Yes, in pips
Risk Input: % of capital per trade
Manual Close Time: Fully adjustable (default 09:00 NY)
👨💻 Credits:
Developed by LANZ
Strategy logic and trading concept built with clarity and precision.
Code structure and documentation by Kairos, your AI trading assistant.
Designed for high-confidence execution and clean backtesting performance.
Aftershock Playbook: Stock Earnings Drift EngineStrategy type
Event-driven post-earnings momentum engine (long/short) built for single-stock charts or ADRs that publish quarterly results.
What it does
Detects the exact earnings bar (request.earnings, lookahead_off).
Scores the surprise and launches a position on that candle’s close.
Tracks PnL: if the first leg closes green, the engine automatically re-enters on the very next bar, milking residual drift.
Blocks mid-cycle trades after a loss until the next earnings release—keeping the risk contained to one cycle.
Think of it as a sniper that fires on the earnings pop, reloads once if the shot lands, then goes silent until the next report.
Core signal inputs
Component Default Purpose
EPS Surprise % +0 % / –5 % Minimum positive / negative shock to trigger longs/shorts.
Reverse signals? Off Quick flip for mean-reversion experiments.
Time Risk Mgt. Off Optional hard exit after 45 calendar days (auto-scaled to any TF).
Risk engine
ATR-based stop (ATR × 2 by default, editable).
Bar time stop (15-min → Daily: Have to select the bar value ).
No pyramiding beyond the built-in “double-tap”.
All positions sized as % of equity via Strategy Properties.
Visual aids
Yellow triangle marks the earnings bar.
Diagnostics table (top-right) shows last Actual, Estimate, and Surprise %.
Status-line tool-tips on every input.
Default inputs
Setting Value
Positive surprise ≥ 0 %
Negative surprise ≤ –5 %
ATR stop × 2
ATR length 50
Hold horizon 350 ( 1h timeframe chart bars)
Back-test properties
Initial capital 10 000
Order size 5 % of equity
Pyramiding 1 (internal re-entry only)
Commission 0.03 %
Slippage 5 ticks
Fills Bar magnifier ✔ · On bar close ✔ · Standard OHLC ✔
How to use
Add the script to any earnings-driven stock (AAPL, MSFT, TSLA…).
Turn on Time Risk Management if you want stricter risk management
Back-test different ATR multipliers to fit the stock’s volatility.
Sync commission & slippage with your broker before forward-testing.
Important notes
Works on every timeframe from 15 min to 1 D. Sweet spot around 30min/1h
All request.earnings() & request.security() calls use lookahead_off—zero repaint.
The “double-tap” re-entry occurs once per winning cycle to avoid drift-chasing loops.
Historical stats ≠ future performance. Size positions responsibly.
Out of the Noise Intraday Strategy with VWAP [YuL]This is my (naive) implementation of "Beat the Market An Effective Intraday Momentum Strategy for S&P500 ETF (SPY)" paper by Carlo Zarattini, Andrew Aziz, Andrea Barbon, so the credit goes to them.
It is supposed to run on SPY on 30-minute timeframe, there may be issues on other timeframes.
I've used settings that were used by the authors in the original paper to keep it close to the publication, but I understand that they are very aggressive and probably shouldn't be used like that.
Results are good, but not as good as they are stated in the paper (unsurprisingly?): returns are smaller and Sharpe is very low (which is actually weird given the returns and drawdown ratio), there are also margin calls if you enable margin check (and you should).
I have my own ideas of improvements which I will probably implement separately to keep this clean.
US30 Stealth StrategyOnly works on US30 (CAPITALCOM) 5 Minute chart
📈 Core Concept:
This is a trend-following strategy that captures strong market continuations by entering on:
The 3rd swing in the current trend,
Confirmed by a volume-verified engulfing candle,
With adaptive SL/TP and position sizing based on risk.
🧠 Entry Logic:
✅ Trend Filter
Uses a 50-period Simple Moving Average (SMA).
Buy only if price is above SMA → Uptrend
Sell only if price is below SMA → Downtrend
✅ Swing Count Logic
For buy: Wait for the 3rd higher low
For sell: Wait for the 3rd lower high
Uses a 5-bar lookback to detect highs/lows
This ensures you’re not buying early — but after trend is confirmed with structure.
✅ Engulfing Candle Confirmation
Bullish engulfing for buys
Bearish engulfing for sells
Candle must engulf previous bar completely (body logic)
✅ Volume Filter
Current candle volume must be greater than the 20-period volume average
Ensures trades only occur with institutional participation
✅ MA Slope Filter
Requires the slope of the 50 SMA over the last 3 candles to exceed 0.1
Avoids chop or flat trends
Adds momentum confirmation to the trade
✅ Session Filter (Time Filter)
Trades only executed between:
2:00 AM to 11:00 PM Oman Time (UTC+4)
Helps avoid overnight chop and illiquidity
📊 Position Sizing & Risk Management
✅ Smart SL (Adaptive Stop Loss)
SL is based on full size of the signal candle (including wick)
But if candle is larger than 25 points, SL is cut to half the size
This prevents oversized risk from long signals during volatile moves.
PMI Nifty (Intraday) 5 Mins V2This is a Special Strategy for Nifty Intraday to be used on 5 Minutes Chart.
We are not a SEBI-registered investment or financial advisor. Strategies should not be followed solely based on past performance. Profit and loss are part of the trading business and Back testing is a feature of Trading View and we show it only for informational and educational purposes.
Conducting paper trading for at least one month is highly recommended to understand strategy behavior.
Please note that trading strategies are not a shortcut to becoming wealthy, and a disciplined approach is essential for long-term results.
Quantum Reversal# 🧠 Quantum Reversal
## **Quantitative Mean Reversion Framework**
This algorithmic trading system employs **statistical mean reversion theory** combined with **adaptive volatility modeling** to capitalize on Bitcoin's inherent price oscillations around its statistical mean. The strategy integrates multiple technical indicators through a **multi-layered signal processing architecture**.
---
## ⚡ **Core Technical Architecture**
### 📊 **Statistical Foundation**
- **Bollinger Band Mean Reversion Model**: Utilizes 20-period moving average with 2.2 standard deviation bands for volatility-adjusted entry signals
- **Adaptive Volatility Threshold**: Dynamic standard deviation multiplier accounts for Bitcoin's heteroscedastic volatility patterns
- **Price Action Confluence**: Entry triggered when price breaches lower volatility band, indicating statistical oversold conditions
### 🔬 **Momentum Analysis Layer**
- **RSI Oscillator Integration**: 14-period Relative Strength Index with modified oversold threshold at 45
- **Signal Smoothing Algorithm**: 5-period simple moving average applied to RSI reduces noise and false signals
- **Momentum Divergence Detection**: Captures mean reversion opportunities when momentum indicators show oversold readings
### ⚙️ **Entry Logic Architecture**
```
Entry Condition = (Price ≤ Lower_BB) OR (Smoothed_RSI < 45)
```
- **Dual-Condition Framework**: Either statistical price deviation OR momentum oversold condition triggers entry
- **Boolean Logic Gate**: OR-based entry system increases signal frequency while maintaining statistical validity
- **Position Sizing**: Fixed 10% equity allocation per trade for consistent risk exposure
### 🎯 **Exit Strategy Optimization**
- **Profit-Lock Mechanism**: Positions only closed when showing positive unrealized P&L
- **Trend Continuation Logic**: Allows winning trades to run until momentum exhaustion
- **Dynamic Exit Timing**: No fixed profit targets - exits based on profitability state rather than arbitrary levels
---
## 📈 **Statistical Properties**
### **Risk Management Framework**
- **Long-Only Exposure**: Eliminates short-squeeze risk inherent in cryptocurrency markets
- **Mean Reversion Bias**: Exploits Bitcoin's tendency to revert to statistical mean after extreme moves
- **Position Management**: Single position limit prevents over-leveraging
### **Signal Processing Characteristics**
- **Noise Reduction**: SMA smoothing on RSI eliminates high-frequency oscillations
- **Volatility Adaptation**: Bollinger Bands automatically adjust to changing market volatility
- **Multi-Timeframe Coherence**: Indicators operate on consistent timeframe for signal alignment
---
## 🔧 **Parameter Configuration**
| Technical Parameter | Value | Statistical Significance |
|-------------------|-------|-------------------------|
| Bollinger Period | 20 | Standard statistical lookback for volatility calculation |
| Std Dev Multiplier | 2.2 | Optimized for Bitcoin's volatility distribution (95.4% confidence interval) |
| RSI Period | 14 | Traditional momentum oscillator period |
| RSI Threshold | 45 | Modified oversold level accounting for Bitcoin's momentum characteristics |
| Smoothing Period | 5 | Noise reduction filter for momentum signals |
---
## 📊 **Algorithmic Advantages**
✅ **Statistical Edge**: Exploits documented mean reversion tendency in Bitcoin markets
✅ **Volatility Adaptation**: Dynamic bands adjust to changing market conditions
✅ **Signal Confluence**: Multiple indicator confirmation reduces false positives
✅ **Momentum Integration**: RSI smoothing improves signal quality and timing
✅ **Risk-Controlled Exposure**: Systematic position sizing and long-only bias
---
## 🔬 **Mathematical Foundation**
The strategy leverages **Bollinger Band theory** (developed by John Bollinger) which assumes that prices tend to revert to the mean after extreme deviations. The RSI component adds **momentum confirmation** to the statistical price deviation signal.
**Statistical Basis:**
- Mean reversion follows the principle that extreme price deviations from the moving average are temporary
- The 2.2 standard deviation multiplier captures approximately 97.2% of price movements under normal distribution
- RSI momentum smoothing reduces noise inherent in oscillator calculations
---
## ⚠️ **Risk Considerations**
This algorithm is designed for traders with understanding of **quantitative finance principles** and **cryptocurrency market dynamics**. The strategy assumes mean-reverting behavior which may not persist during trending market phases. Proper risk management and position sizing are essential.
---
## 🎯 **Implementation Notes**
- **Market Regime Awareness**: Most effective in ranging/consolidating markets
- **Volatility Sensitivity**: Performance may vary during extreme volatility events
- **Backtesting Recommended**: Historical performance analysis advised before live implementation
- **Capital Allocation**: 10% per trade sizing assumes diversified portfolio approach
---
**Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
S4_IBS_Mean_Rev_3candleExitOverview:
This is a rules-based, mean reversion strategy designed to trade pullbacks using the Internal Bar Strength (IBS) indicator. The system looks for oversold conditions based on IBS, then enters long trades , holding for a maximum of 3 bars or until the trade becomes profitable.
The strategy includes:
✅ Strict entry rules based on IBS
✅ Hardcoded exit conditions for risk management
✅ A clean visual table summarizing key performance metrics
How It Works:
1. Internal Bar Strength (IBS) Setup:
The IBS is calculated using the previous bar’s price range:
IBS = (Previous Close - Previous Low) / (Previous High - Previous Low)
IBS values closer to 0 indicate price is near the bottom of the previous range, suggesting oversold conditions.
2. Entry Conditions:
IBS must be ≤ 0.25, signaling an oversold setup.
Trade entries are only allowed within a user-defined backtest window (default: 2024).
Only one trade at a time is permitted (long-only strategy).
3. Exit Conditions:
If the price closes higher than the entry price, the trade exits with a profit.
If the trade has been open for 3 bars without showing profit, the trade is forcefully exited.
All trades are closed automatically at the end of the backtest window if still open.
Additional Features:
📊 A real-time performance metrics table is displayed on the chart, showing:
- Total trades
- % of profitable trades
- Total P&L
- Profit Factor
- Max Drawdown
- Best/Worst trade performance
📈 Visual markers indicate trade entries (green triangle) and exits (red triangle) for easy chart interpretation.
Who Is This For?
This strategy is designed for:
✅ Traders exploring systematic mean reversion approaches
✅ Those who prefer strict, rules-based setups with no subjective decision-making
✅ Traders who want built-in performance tracking directly on the chart
Note: This strategy is provided for educational and research purposes. It is a backtested model and past performance does not guarantee future results. Users should paper trade and validate performance before considering real capital.
OBV ATR Strategy (OBV Breakout Channel) bas20230503ผมแก้ไขจาก OBV+SMA อันเดิม ของเดิม ดูที่เส้น SMA สองเส้นตัดกันมั่นห่วยแตกสำหรับที่ผมลองเทรดจริง และหลักการเบรค ได้แรงบันดาลใจ ATR จาก เทพคอย ที่ใช้กับราคา แต่นี้ใช้กับ OBV แทน
และผมใช้เจมินี้ เพื่อแก้ ให้ เป็น strategy เพื่อเช็คย้อนหลังได้ง่ายกว่าเดิม
หลักการง่ายคือถ้ามันขึ้น มันจะขึ้นเรื่อยๆ
เขียน แบบสุภาพ (น่าจะอ่านได้ง่ายกว่าผมเขียน)
สคริปต์นี้ได้รับการพัฒนาต่อยอดจากแนวคิด OBV+SMA Crossover แบบดั้งเดิม ซึ่งจากการทดสอบส่วนตัวพบว่าประสิทธิภาพยังไม่น่าพอใจ กลยุทธ์ใหม่นี้จึงเปลี่ยนมาใช้หลักการ "Breakout" ซึ่งได้รับแรงบันดาลใจมาจากการใช้ ATR สร้างกรอบของราคา แต่เราได้นำมาประยุกต์ใช้กับ On-Balance Volume (OBV) แทน นอกจากนี้ สคริปต์ได้ถูกแปลงเป็น Strategy เต็มรูปแบบ (โดยความช่วยเหลือจาก Gemini AI) เพื่อให้สามารถทดสอบย้อนหลัง (Backtest) และประเมินประสิทธิภาพได้อย่างแม่นยำ
หลักการของกลยุทธ์: กลยุทธ์นี้ทำงานบนแนวคิดโมเมนตัมที่ว่า "เมื่อแนวโน้มได้เกิดขึ้นแล้ว มีโอกาสที่มันจะดำเนินต่อไป" โดยจะมองหาการทะลุของพลังซื้อ-ขาย (OBV) ที่แข็งแกร่งเป็นพิเศษเป็นสัญญาณเข้าเทร
----
สคริปต์นี้เป็นกลยุทธ์ (Strategy) ที่ใช้ On-Balance Volume (OBV) ซึ่งเป็นอินดิเคเตอร์ที่วัดแรงซื้อและแรงขายสะสม แทนที่จะใช้การตัดกันของเส้นค่าเฉลี่ย (SMA Crossover) ที่เป็นแบบพื้นฐาน กลยุทธ์นี้จะมองหาการ "ทะลุ" (Breakout) ของพลัง OBV ออกจากกรอบสูงสุด-ต่ำสุดของตัวเองในรอบที่ผ่านมา
สัญญาณกระทิง (Bull Signal): เกิดขึ้นเมื่อพลังการซื้อ (OBV) แข็งแกร่งจนสามารถทะลุจุดสูงสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาขึ้น
สัญญาณหมี (Bear Signal): เกิดขึ้นเมื่อพลังการขาย (OBV) รุนแรงจนสามารถกดดันให้ OBV ทะลุจุดต่ำสุดของตัวเองในอดีตได้ บ่งบอกถึงโอกาสที่แนวโน้มจะเปลี่ยนเป็นขาลง
ส่วนประกอบบนกราฟ (Indicator Components)
เส้น OBV
เส้นหลัก ที่เปลี่ยนเขียวเป็นแดง เป็นทั้งแนวรับและแนวต้าน และ จุด stop loss
เส้นนี้คือหัวใจของอินดิเคเตอร์ ที่แสดงถึงพลังสะสมของ Volume
เมื่อเส้นเป็นสีเขียว (แนวรับ): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดกระทิง" เส้นนี้คือระดับต่ำสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวรับไดนามิก
เมื่อเส้นกลายเป็นสีแดงสีแดง (แนวต้าน): จะปรากฏขึ้นเมื่อกลยุทธ์เข้าสู่ "โหมดหมี" เส้นนี้คือระดับสูงสุดของ OBV ในอดีต และทำหน้าที่เป็นแนวต้านไดนามิก
สัญลักษณ์สัญญาณ (Signal Markers):
Bull 🔼 (สามเหลี่ยมขึ้นสีเขียว): คือสัญญาณ "เข้าซื้อ" (Long) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุขึ้นไปเหนือกรอบด้านบนเป็นครั้งแรก
Bear 🔽 (สามเหลี่ยมลงสีแดง): คือสัญญาณ "เข้าขาย" (Short) จะปรากฏขึ้น ณ จุดที่ OBV ทะลุลงไปต่ำกว่ากรอบด้านล่างเป็นครั้งแรก
วิธีการใช้งาน (How to Use)
เพิ่มสคริปต์นี้ลงบนกราฟราคาที่คุณสนใจ
ไปที่แท็บ "Strategy Tester" ด้านล่างของ TradingView เพื่อดูผลการทดสอบย้อนหลัง (Backtest) ของกลยุทธ์บนสินทรัพย์และไทม์เฟรมต่างๆ
ใช้สัญลักษณ์ "Bull" และ "Bear" เป็นตัวช่วยในการตัดสินใจเข้าเทรด
ข้อควรจำ: ไม่มีกลยุทธ์ใดที่สมบูรณ์แบบ 100% ควรใช้สคริปต์นี้ร่วมกับการวิเคราะห์ปัจจัยอื่นๆ เช่น โครงสร้างราคา, แนวรับ-แนวต้านของราคา และการบริหารความเสี่ยง (Risk Management) ของตัวคุณเองเสมอ
การตั้งค่า (Inputs)
SMA Length 1 / SMA Length 2: ใช้สำหรับพล็อตเส้นค่าเฉลี่ยของ OBV เพื่อดูเป็นภาพอ้างอิง ไม่มีผลต่อตรรกะการเข้า-ออกของ Strategy อันใหม่ แต่มันเป็นของเก่า ถ้าชอบ ก็ใช้ได้ เมื่อ SMA สองเส้นตัดกัน หรือตัดกับเส้น OBV
High/Low Lookback Length: (ค่าพื้นฐาน30/แก้ตรงนี้ให้เหมาะสมกับ coin หรือหุ้น ตามความผันผวน ) คือระยะเวลาที่ใช้ในการคำนวณกรอบสูงสุด-ต่ำสุดของ OBV
ค่าน้อย: ทำให้กรอบแคบลง สัญญาณจะเกิดไวและบ่อยขึ้น แต่อาจมีสัญญาณหลอก (False Signal) เยอะขึ้น
ค่ามาก: ทำให้กรอบกว้างขึ้น สัญญาณจะเกิดช้าลงและน้อยลง แต่มีแนวโน้มที่จะเป็นสัญญาณที่แข็งแกร่งกว่า
แน่นอนครับ นี่คือคำแปลฉบับภาษาอังกฤษที่สรุปใจความสำคัญ กระชับ และสุภาพ เหมาะสำหรับนำไปใช้ในคำอธิบายสคริปต์ (Description) ของ TradingView ครับ
---Translate to English---
OBV Breakout Channel Strategy
This script is an evolution of a traditional OBV+SMA Crossover concept. Through personal testing, the original crossover method was found to have unsatisfactory performance. This new strategy, therefore, uses a "Breakout" principle. The inspiration comes from using ATR to create price channels, but this concept has been adapted and applied to On-Balance Volume (OBV) instead.
Furthermore, the script has been converted into a full Strategy (with assistance from Gemini AI) to enable precise backtesting and performance evaluation.
The strategy's core principle is momentum-based: "once a trend is established, it is likely to continue." It seeks to enter trades on exceptionally strong breakouts of buying or selling pressure as measured by OBV.
Core Concept
This is a Strategy that uses On-Balance Volume (OBV), an indicator that measures cumulative buying and selling pressure. Instead of relying on a basic Simple Moving Average (SMA) Crossover, this strategy identifies a "Breakout" of the OBV from its own highest-high and lowest-low channel over a recent period.
Bull Signal: Occurs when the buying pressure (OBV) is strong enough to break above its own recent highest high, indicating a potential shift to an upward trend.
Bear Signal: Occurs when the selling pressure (OBV) is intense enough to push the OBV below its own recent lowest low, indicating a potential shift to a downward trend.
On-Screen Components
1. OBV Line
This is the main indicator line, representing the cumulative volume. Its color changes to green when OBV is rising and red when it is falling.
2. Dynamic Support & Resistance Line
This is the thick Green or Red line that appears based on the strategy's current "mode." This line serves as a dynamic support/resistance level and can be used as a reference for stop-loss placement.
Green Line (Support): Appears when the strategy enters "Bull Mode." This line represents the lowest low of the OBV in the recent past and acts as dynamic support.
Red Line (Resistance): Appears when the strategy enters "Bear Mode." This line represents the highest high of the OBV in the recent past and acts as dynamic resistance.
3. Signal Markers
Bull 🔼 (Green Up Triangle): This is the "Long Entry" signal. It appears at the moment the OBV first breaks out above its high-low channel.
Bear 🔽 (Red Down Triangle): This is the "Short Entry" signal. It appears at the moment the OBV first breaks down below its high-low channel.
How to Use
Add this script to the price chart of your choice.
Navigate to the "Strategy Tester" panel at the bottom of TradingView to view the backtesting results for the strategy on different assets and timeframes.
Use the "Bull" and "Bear" signals as aids in your trading decisions.
Disclaimer: No strategy is 100% perfect. This script should always be used in conjunction with other forms of analysis, such as price structure, key price-based support/resistance levels, and your own personal risk management rules.
Inputs
SMA Length 1 / SMA Length 2: These are used to plot moving averages on the OBV for visual reference. They are part of the legacy logic and do not affect the new breakout strategy. However, they are kept for traders who may wish to observe their crossovers for additional confirmation.
High/Low Lookback Length: (Most Important Setting) This determines the period used to calculate the highest-high and lowest-low OBV channel. (Default is 30; adjust this to suit the asset's volatility).
A smaller value: Creates a narrower channel, leading to more frequent and faster signals, but potentially more false signals.
A larger value: Creates a wider channel, leading to fewer and slower signals, which are likely to be more significant.
Canuck Trading Trader StrategyCanuck Trading Trader Strategy
Overview
The Canuck Trading Trader Strategy is a high-performance, trend-following trading system designed for NASDAQ:TSLA on a 15-minute timeframe. Optimized for precision and profitability, this strategy leverages short-term price trends to capture consistent gains while maintaining robust risk management. Ideal for traders seeking an automated, data-driven approach to trading Tesla’s volatile market, it delivers strong returns with controlled drawdowns.
Key Features
Trend-Based Entries: Identifies short-term trends using a 2-candle lookback period and a minimum trend strength of 0.2%, ensuring responsive trade signals.
Risk Management: Includes a configurable 3.0% stop-loss to cap losses and a 2.0% take-profit to lock in gains, balancing risk and reward.
High Precision: Utilizes bar magnification for accurate backtesting, reflecting realistic trade execution with 1-tick slippage and 0.1 commission.
Clean Interface: No on-chart indicators, providing a distraction-free trading experience focused on performance.
Flexible Sizing: Allocates 10% of equity per trade with support for up to 2 simultaneous positions (pyramiding).
Performance Highlights
Backtested from March 1, 2024, to June 20, 2025, on NASDAQ:TSLA (15-minute timeframe) with $1,000,000 initial capital:
Net Profit: $2,279,888.08 (227.99%)
Win Rate: 52.94% (3,039 winning trades out of 5,741)
Profit Factor: 3.495
Max Drawdown: 2.20%
Average Winning Trade: $1,050.91 (0.55%)
Average Losing Trade: $338.20 (0.18%)
Sharpe Ratio: 2.468
Note: Past performance is not indicative of future results. Always validate with your own backtesting and forward testing.
Usage Instructions
Setup:
Apply the strategy to a NASDAQ:TSLA 15-minute chart.
Ensure your TradingView account supports bar magnification for accurate results.
Configuration:
Lookback Candles: Default is 2 (recommended).
Min Trend Strength: Set to 0.2% for optimal trade frequency.
Stop Loss: Default 3.0% to cap losses.
Take Profit: Default 2.0% to secure gains.
Order Size: 10% of equity per trade.
Pyramiding: Allows up to 2 orders.
Commission: Set to 0.1.
Slippage: Set to 1 tick.
Enable "Recalculate After Order is Filled" and "Recalculate on Every Tick" in backtest settings.
Backtesting:
Run backtests over March 1, 2024, to June 20, 2025, to verify performance.
Adjust stop-loss (e.g., 2.5%) or take-profit (e.g., 1–3%) to suit your risk tolerance.
Live Trading:
Use with a compatible broker or TradingView alerts for automated execution.
Monitor execution for slippage or latency, especially given the high trade frequency (5,741 trades).
Validate in a demo account before deploying with real capital.
Risk Disclosure
Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
Long/Short/Exit/Risk management Strategy # LongShortExit Strategy Documentation
## Overview
The LongShortExit strategy is a versatile trading system for TradingView that provides complete control over entry, exit, and risk management parameters. It features a sophisticated framework for managing long and short positions with customizable profit targets, stop-loss mechanisms, partial profit-taking, and trailing stops. The strategy can be enhanced with continuous position signals for visual feedback on the current trading state.
## Key Features
### General Settings
- **Trading Direction**: Choose to trade long positions only, short positions only, or both.
- **Max Trades Per Day**: Limit the number of trades per day to prevent overtrading.
- **Bars Between Trades**: Enforce a minimum number of bars between consecutive trades.
### Session Management
- **Session Control**: Restrict trading to specific times of the day.
- **Time Zone**: Specify the time zone for session calculations.
- **Expiration**: Optionally set a date when the strategy should stop executing.
### Contract Settings
- **Contract Type**: Select from common futures contracts (MNQ, MES, NQ, ES) or custom values.
- **Point Value**: Define the dollar value per point movement.
- **Tick Size**: Set the minimum price movement for accurate calculations.
### Visual Signals
- **Continuous Position Signals**: Implement 0 to 1 visual signals to track position states.
- **Signal Plotting**: Customize color and appearance of position signals.
- **Clear Visual Feedback**: Instantly see when entry conditions are triggered.
### Risk Management
#### Stop Loss and Take Profit
- **Risk Type**: Choose between percentage-based, ATR-based, or points-based risk management.
- **Percentage Mode**: Set SL/TP as a percentage of entry price.
- **ATR Mode**: Set SL/TP as a multiple of the Average True Range.
- **Points Mode**: Set SL/TP as a fixed number of points from entry.
#### Advanced Exit Features
- **Break-Even**: Automatically move stop-loss to break-even after reaching specified profit threshold.
- **Trailing Stop**: Implement a trailing stop-loss that follows price movement at a defined distance.
- **Partial Profit Taking**: Take partial profits at predetermined price levels:
- Set first partial exit point and percentage of position to close
- Set second partial exit point and percentage of position to close
- **Time-Based Exit**: Automatically exit a position after a specified number of bars.
#### Win/Loss Streak Management
- **Streak Cutoff**: Automatically pause trading after a series of consecutive wins or losses.
- **Daily Reset**: Option to reset streak counters at the start of each day.
### Entry Conditions
- **Source and Value**: Define the exact price source and value that triggers entries.
- **Equals Condition**: Entry signals occur when the source exactly matches the specified value.
### Performance Analytics
- **Real-Time Stats**: Track important performance metrics like win rate, P&L, and largest wins/losses.
- **Visual Feedback**: On-chart markers for entries, exits, and important events.
### External Integration
- **Webhook Support**: Compatible with TradingView's webhook alerts for automated trading.
- **Cross-Platform**: Connect to external trading systems and notification platforms.
- **Custom Order Execution**: Implement advanced order flows through external services.
## How to Use
### Setup Instructions
1. Add the script to your TradingView chart.
2. Configure the general settings based on your trading preferences.
3. Set session trading hours if you only want to trade specific times.
4. Select your contract specifications or customize for your instrument.
5. Configure risk parameters:
- Choose your preferred risk management approach
- Set appropriate stop-loss and take-profit levels
- Enable advanced features like break-even, trailing stops, or partial profit taking as needed
6. Define entry conditions:
- Select the price source (such as close, open, high, or an indicator)
- Set the specific value that should trigger entries
### Entry Condition Examples
- **Example 1**: To enter when price closes exactly at a whole number:
- Long Source: close
- Long Value: 4200 (for instance, to enter when price closes exactly at 4200)
- **Example 2**: To enter when an indicator reaches a specific value:
- Long Source: ta.rsi(close, 14)
- Long Value: 30 (triggers when RSI equals exactly 30)
### Best Practices
1. **Always backtest thoroughly** before using in live trading.
2. **Start with conservative risk settings**:
- Small position sizes
- Reasonable stop-loss distances
- Limited trades per day
3. **Monitor and adjust**:
- Use the performance table to track results
- Adjust parameters based on how the strategy performs
4. **Consider market volatility**:
- Use ATR-based stops during volatile periods
- Use fixed points during stable markets
## Continuous Position Signals Implementation
The LongShortExit strategy can be enhanced with continuous position signals to provide visual feedback about the current position state. These signals can help you track when the strategy is in a long or short position.
### Adding Continuous Position Signals
Add the following code to implement continuous position signals (0 to 1):
```pine
// Continuous position signals (0 to 1)
var float longSignal = 0.0
var float shortSignal = 0.0
// Update position signals based on your indicator's conditions
longSignal := longCondition ? 1.0 : 0.0
shortSignal := shortCondition ? 1.0 : 0.0
// Plot continuous signals
plot(longSignal, title="Long Signal", color=#00FF00, linewidth=2, transp=0, style=plot.style_line)
plot(shortSignal, title="Short Signal", color=#FF0000, linewidth=2, transp=0, style=plot.style_line)
```
### Benefits of Continuous Position Signals
- Provides clear visual feedback of current position state (long/short)
- Signal values stay consistent (0 or 1) until condition changes
- Can be used for additional calculations or alert conditions
- Makes it easier to track when entry conditions are triggered
### Using with Custom Indicators
You can adapt the continuous position signals to work with any custom indicator by replacing the condition with your indicator's logic:
```pine
// Example with moving average crossover
longSignal := fastMA > slowMA ? 1.0 : 0.0
shortSignal := fastMA < slowMA ? 1.0 : 0.0
```
## Webhook Integration
The LongShortExit strategy is fully compatible with TradingView's webhook alerts, allowing you to connect your strategy to external trading platforms, brokers, or custom applications for automated trading execution.
### Setting Up Webhooks
1. Create an alert on your chart with the LongShortExit strategy
2. Enable the "Webhook URL" option in the alert dialog
3. Enter your webhook endpoint URL (from your broker or custom trading system)
4. Customize the alert message with relevant information using TradingView variables
### Webhook Message Format Example
```json
{
"strategy": "LongShortExit",
"action": "{{strategy.order.action}}",
"price": "{{strategy.order.price}}",
"quantity": "{{strategy.position_size}}",
"time": "{{time}}",
"ticker": "{{ticker}}",
"position_size": "{{strategy.position_size}}",
"position_value": "{{strategy.position_value}}",
"order_id": "{{strategy.order.id}}",
"order_comment": "{{strategy.order.comment}}"
}
```
### TradingView Alert Condition Examples
For effective webhook automation, set up these alert conditions:
#### Entry Alert
```
{{strategy.position_size}} != {{strategy.position_size}}
```
#### Exit Alert
```
{{strategy.position_size}} < {{strategy.position_size}} or {{strategy.position_size}} > {{strategy.position_size}}
```
#### Partial Take Profit Alert
```
strategy.order.comment contains "Partial TP"
```
### Benefits of Webhook Integration
- **Automated Trading**: Execute trades automatically through supported brokers
- **Cross-Platform**: Connect to custom trading bots and applications
- **Real-Time Notifications**: Receive trade signals on external platforms
- **Data Collection**: Log trade data for further analysis
- **Custom Order Management**: Implement advanced order types not available in TradingView
### Compatible External Applications
- Trading bots and algorithmic trading software
- Custom order execution systems
- Discord, Telegram, or Slack notification systems
- Trade journaling applications
- Risk management platforms
### Implementation Recommendations
- Test webhook delivery using a free service like webhook.site before connecting to your actual trading system
- Include authentication tokens or API keys in your webhook URL or payload when required by your external service
- Consider implementing confirmation mechanisms to verify trade execution
- Log all webhook activities for troubleshooting and performance tracking
## Strategy Customization Tips
### For Scalping
- Set smaller profit targets (1-3 points)
- Use tighter stop-losses
- Enable break-even feature after small profit
- Set higher max trades per day
### For Day Trading
- Use moderate profit targets
- Implement partial profit taking
- Enable trailing stops
- Set reasonable session trading hours
### For Swing Trading
- Use longer-term charts
- Set wider stops (ATR-based often works well)
- Use higher profit targets
- Disable daily streak reset
## Common Troubleshooting
### Low Win Rate
- Consider widening stop-losses
- Verify that entry conditions aren't triggering too frequently
- Check if the equals condition is too restrictive; consider small tolerances
### Missing Obvious Trades
- The equals condition is extremely precise. Price must exactly match the specified value.
- Consider using floating-point precision for more reliable triggers
### Frequent Stop-Outs
- Try ATR-based stops instead of fixed points
- Increase the stop-loss distance
- Enable break-even feature to protect profits
## Important Notes
- The exact equals condition is strict and may result in fewer trade signals compared to other conditions.
- For instruments with decimal prices, exact equality might be rare. Consider the precision of your value.
- Break-even and trailing stop calculations are based on points, not percentage.
- Partial take-profit levels are defined in points distance from entry.
- The continuous position signals (0 to 1) provide valuable visual feedback but don't affect the strategy's trading logic directly.
- When implementing continuous signals, ensure they're aligned with the actual entry conditions used by the strategy.
---
*This strategy is for educational and informational purposes only. Always test thoroughly before using with real funds.*
Timeshifter Triple Timeframe Strategy w/ SessionsOverview
The "Enhanced Timeshifter Triple Timeframe Strategy with Session Filtering" is a sophisticated trading strategy designed for the TradingView platform. It integrates multiple technical indicators across three different timeframes and allows traders to customize their trading Sessions. This strategy is ideal for traders who wish to leverage multi-timeframe analysis and session-based trading to enhance their trading decisions.
Features
Multi-Timeframe Analysis and direction:
Higher Timeframe: Set to a daily timeframe by default, providing a broader view of market trends.
Trading Timeframe: Automatically set to the current chart timeframe, ensuring alignment with the trader's primary analysis period.
Lower Timeframe: Set to a 15-minute timeframe by default, offering a granular view for precise entry and exit points.
Indicator Selection:
RMI (Relative Momentum Index): Combines RSI and MFI to gauge market momentum.
TWAP (Time Weighted Average Price): Provides an average price over a specified period, useful for identifying trends.
TEMA (Triple Exponential Moving Average): Reduces lag and smooths price data for trend identification.
DEMA (Double Exponential Moving Average): Similar to TEMA, it reduces lag and provides a smoother trend line.
MA (Moving Average): A simple moving average for basic trend analysis.
MFI (Money Flow Index): Measures the flow of money into and out of a security, useful for identifying overbought or oversold conditions.
VWMA (Volume Weighted Moving Average): Incorporates volume data into the moving average calculation.
PSAR (Parabolic SAR): Identifies potential reversals in price movement.
Session Filtering:
London Session: Trade during the London market hours (0800-1700 GMT+1).
New York Session: Trade during the New York market hours (0800-1700 GMT-5).
Tokyo Session: Trade during the Tokyo market hours (0900-1800 GMT+9).
Users can select one or multiple sessions to align trading with specific market hours.
Trade Direction:
Long: Only long trades are permitted.
Short: Only short trades are permitted.
Both: Both long and short trades are permitted, providing flexibility based on market conditions.
ADX Confirmation:
ADX (Average Directional Index): An optional filter to confirm the strength of a trend before entering a trade.
How to Use the Script
Setup:
Add the script to your TradingView chart.
Customize the input parameters according to your trading preferences and strategy requirements.
Indicator Selection:
Choose the primary indicator you wish to use for generating trading signals from the dropdown menu.
Enable or disable the ADX confirmation based on your preference for trend strength analysis.
Session Filtering:
Select the trading sessions you wish to trade in. You can choose one or multiple Sessions based on your trading strategy and market focus.
Trade Direction:
Set your preferred trade direction (Long, Short, or Both) to align with your market outlook and risk tolerance. You can use this feature to gauge the market and understand the possible directions.
Tips for Profitable and Safe Trading:
Recommended Timeframes Combination:
LT: 1m , CT: 5m, HT: 1H
LT: 1-5m , CT: 15m, HT: 4H
LT: 5-15m , CT: 4H, HT: 1W
Backtesting:
Always backtest the strategy on historical data to understand its performance under various market conditions.
Adjust the parameters based on backtesting results to optimize the strategy for your specific trading style.
Risk Management:
Use appropriate risk management techniques, such as setting stop-loss and take-profit levels, to protect your capital.
Avoid over-leveraging and ensure that you are trading within your risk tolerance.
Market Analysis:
Combine the script with other forms of market analysis, such as fundamental analysis or market sentiment, to make well-rounded trading decisions.
Stay informed about major economic events and news that could impact market volatility and trading sessions.
Continuous Monitoring:
Regularly monitor the strategy's performance and make adjustments as necessary.
Keep an eye on the results and settings for real-time statistics and ensure that the strategy aligns with current market conditions.
Education and Practice:
Continuously educate yourself on trading strategies and market dynamics.
Practice using the strategy in a demo account before applying it to live trading to gain confidence and understanding.
[Mustang Algo] Channel Strategy# Mustang Algo Channel Strategy - Universal Market Sentiment Oscillator
## 🎯 ORIGINAL CONCEPT
This strategy employs a unique market sentiment oscillator that works on ALL financial assets. It uses Bitcoin supply dynamics combined with stablecoin market capitalization as a macro sentiment indicator to generate universal timing signals across stocks, forex, commodities, indices, and cryptocurrencies.
## 🌐 UNIVERSAL APPLICATION
- **Any Asset Class:** Stocks, Forex, Commodities, Indices, Crypto, Bonds
- **Market-Wide Timing:** BTC/Stablecoin ratio serves as a global risk sentiment gauge
- **Cross-Market Signals:** Trade any instrument using macro liquidity conditions
- **Ecosystem Approach:** One oscillator for all financial markets
## 🧮 METHODOLOGY
**Core Calculation:** BTC Supply / (Combined Stablecoin Market Cap / BTC Price)
- **Data Sources:** DAI + USDT + USDC market capitalizations
- **Signal Generation:** RSI(14) applied to the ratio, double-smoothed with WMA
- **Timing Logic:** Crossover signals filtered by overbought/oversold zones
- **Multi-Timeframe:** Configurable timeframe analysis (default: Daily)
## 📈 TRADING STRATEGY
**LONG Entries:** Bullish crossover when market sentiment is oversold (<48)
**SHORT Entries:** Bearish crossover when market sentiment is overbought (>55)
**Universal Timing:** These macro signals apply to trading any financial instrument
## ⚙️ FLEXIBLE RISK MANAGEMENT
**Three SL/TP Calculation Modes:**
- **Percentage Mode:** Traditional % based (4% SL, 12% TP default)
- **Ticks Mode:** Precise tick-based calculation (50/150 ticks default)
- **Pips Mode:** Forex-style pip calculation (50/150 pips default)
**Realistic Parameters:**
- Commission: 0.1% (adjustable for different asset classes)
- Slippage: 2 ticks
- Position sizing: 10% of equity (conservative)
- No pyramiding (single position management)
## 📊 KEY ADVANTAGES
✅ **Universal Application:** One strategy for all asset classes
✅ **Macro Foundation:** Based on global liquidity and risk sentiment
✅ **False Signal Filtering:** Overbought/oversold zones reduce noise
✅ **Flexible Risk Management:** Multiple SL/TP calculation methods
✅ **No Lookahead Bias:** Clean backtesting with realistic results
✅ **Cross-Market Correlation:** Captures broad market risk cycles
## 🎛️ CONFIGURATION GUIDE
1. **Asset Selection:** Apply to stocks, forex, commodities, indices, crypto
2. **Timeframe Setup:** Daily recommended for swing trading
3. **Sentiment Bounds:** Adjust 48/55 levels based on market volatility
4. **Risk Management:** Choose appropriate SL/TP mode for your asset class
5. **Direction Filter:** Select Long Only, Short Only, or Both
## 📋 BACKTESTING STANDARDS
**Compliant with TradingView Guidelines:**
- ✅ Realistic commission structure (0.1% default)
- ✅ Appropriate slippage modeling (2 ticks)
- ✅ Conservative position sizing (10% equity)
- ✅ Sustainable risk ratios (1:3 SL/TP)
- ✅ No lookahead bias (proper historical simulation)
- ✅ Sufficient sample size potential (100+ trades possible)
## 🔬 ORIGINAL RESEARCH
This strategy introduces a revolutionary approach to financial markets by treating the BTC/Stablecoin ratio as a global risk sentiment gauge. Unlike traditional indicators that analyze individual asset price action, this oscillator captures macro liquidity flows that affect ALL financial markets - from stocks to forex to commodities.
## 🎯 MARKET APPLICATIONS
**Stocks & Indices:** Risk-on/risk-off sentiment timing
**Forex:** Global liquidity flow analysis for major pairs
**Commodities:** Risk appetite for inflation hedges
**Bonds:** Flight-to-safety vs. risk-seeking behavior
**Crypto:** Native application with direct correlation
## ⚠️ RISK DISCLOSURE
- Designed for intermediate to long-term trading across all timeframes
- Market sentiment can remain extreme longer than expected
- Always use appropriate position sizing for your specific asset class
- Adjust commission and slippage settings for different markets
- Past performance does not guarantee future results
## 🚀 INNOVATION SUMMARY
**What makes this strategy unique:**
- First to use BTC/Stablecoin ratio as universal market sentiment indicator
- Applies macro-economic principles to technical analysis across all assets
- Single oscillator provides timing signals for entire financial ecosystem
- Bridges traditional finance with digital asset insights
- Combines fundamental liquidity analysis with technical precision
Bollinger Band Breakout With Volatility StoplossDetailed Explanation of the Bollinger Band Breakout With Volatility Stoploss System
Introduction
The "Bollinger Band Breakout With Volatility Stoploss" system is a trading strategy designed to exploit price volatility in financial markets using the Bollinger Bands indicator, a widely recognized tool developed by John Bollinger. This system adapts the traditional Bollinger Bands framework into a Volatility Breakout strategy, focusing on capturing significant price movements by leveraging customized parameters and precise trading rules. The system operates exclusively on long positions, employs a daily timeframe, and incorporates dynamic risk management techniques to optimize trade outcomes while preserving capital.
System Parameters
The system modifies the standard Bollinger Bands configuration to suit its breakout methodology:
Standard Deviation (SD): Set to 1x, determining the width of the bands relative to the central moving average. This tighter setting enhances sensitivity to price movements, making the system responsive to smaller volatility shifts compared to the conventional 2x SD.
Period: A 30-day (1-month) lookback period is used to calculate the bands, providing a balance between capturing medium-term price trends and avoiding excessive noise from shorter timeframes.
Moving Average Type: The system uses an Exponential Moving Average (EMA) instead of the Simple Moving Average (SMA). The EMA places greater weight on recent price data, making it more responsive to current market conditions and better suited for detecting breakout opportunities in dynamic markets.
Core Concept
The Bollinger Band Breakout system is built on the principle of Volatility Breakout, which seeks to capitalize on significant price movements when the price breaks out of a defined volatility range. The Bollinger Bands, consisting of an EMA as the central line and two bands (Upper and Lower) calculated as the EMA plus or minus 1x SD, define this range. The system operates on a Daily Chart (D) timeframe, making it suitable for traders who prefer analyzing and executing trades based on daily price action. By focusing solely on Long Positions (buying low and selling high), the system avoids short-selling, aligning with strategies that capitalize on upward price momentum.
The core idea is to use the 1x SD multiplier over a 30-day period to establish a dynamic price range that reflects recent market volatility. Breakouts above the Upper Band signal potential buying opportunities, while penetrations below the Lower Band indicate exits, ensuring trades are aligned with significant price movements.
Trading Signals
The system generates clear entry and exit signals based on price interactions with the Bollinger Bands:
Buy Signal: A buy signal is triggered when the closing price of a daily candle exceeds the Upper Bollinger Band (EMA + 1x SD over 30 days). The trade is entered at the opening price of the subsequent candle, ensuring the breakout is confirmed by the close of the prior day. This approach minimizes false signals by waiting for a definitive breach of the volatility threshold.
Sell Signal: A sell signal occurs when the closing price falls below the Lower Bollinger Band (EMA - 1x SD over 30 days). The position is exited at the opening price of the next candle, allowing the trader to lock in profits or limit losses when the price reverses or loses momentum.
Risk Management
Risk management is a cornerstone of the system, ensuring capital preservation and disciplined trade execution:
Initial Stoploss: The stoploss is set at the Lower Bollinger Band of the candle that triggered the buy signal. This level acts as a volatility-based threshold, below which the trade is deemed invalid, prompting an immediate exit to protect capital. Traders have two options for implementing the stoploss:
Pending Stoploss: A predefined stoploss order placed at the Lower Band level.
Conditional Exit: Using the sell signal condition (price closing below the Lower Band) as the exit trigger, effectively aligning the stoploss with the system’s exit rules.
Position Sizing: The system employs Fixed Fractional Position Sizing with a risk per trade capped at 3% of the account balance. The position size is calculated based on the distance between the entry price and the Initial Stoploss, incorporating Volatility Position Sizing. This method adjusts the trade size according to the market’s volatility, ensuring that risk remains consistent across varying market conditions. Two options are available for managing capital:
Gear Up Option: Profits from previous trades are reinvested into the account’s capital, increasing the base for calculating the next position size. This compounding approach can amplify returns but also increases risk exposure.
Fixed Equity Option: Profits from previous trades are withdrawn, and only the remaining capital is used for calculating the next position size. This conservative approach prioritizes capital preservation by not compounding gains.
Trailing Stop: The system uses the Lower Bollinger Band as a dynamic trailing stop, which adjusts with price movements and volatility. This ensures that profits are protected during favorable trends while allowing the trade to remain open as long as the price stays above the Lower Band. The trailing stop aligns with the sell signal condition, maintaining consistency in the system’s exit strategy.
Supporting Indicators
The system incorporates two additional indicators to enhance market analysis and decision-making:
Bollinger Band Width (BBW): BBW measures the distance between the Upper and Lower Bollinger Bands relative to the EMA, serving as a proxy for market volatility.
A high BBW indicates significant price volatility, often associated with strong trends or large price movements, which may confirm the strength of a breakout.
A low BBW suggests low volatility, potentially signaling a period of consolidation or "squeeze" that could precede a breakout. This can help traders anticipate potential trade setups.
The BBW calculation uses the EMA to maintain consistency with the system’s core parameters.
Bollinger Band Ratio (BBR) or %B: BBR measures the price’s position relative to the Bollinger Bands, providing insight into market conditions.
BBR > 1: The price is above the Upper Band, indicating potential overbought conditions or strong upward momentum, which aligns with the system’s buy signal.
BBR < 0: The price is below the Lower Band, suggesting oversold conditions or downward momentum, corresponding to the sell signal or stoploss trigger.
BBR between 0 and 1: The price is within the bands, indicating a neutral state where no immediate action is required.
Like BBW, BBR is calculated using the EMA for consistency.
Backtesting and Implementation
To evaluate the system’s performance, traders can utilize the Backtest Parameter function, which allows for testing the strategy across user-defined time periods. This feature enables traders to assess the system’s effectiveness under various market conditions, optimize parameters, and refine their approach based on historical data.
Conclusion
The Bollinger Band Breakout With Volatility Stoploss system is a robust, volatility-driven trading strategy that combines the predictive power of Bollinger Bands with disciplined risk management. By focusing on long positions, using a 1x SD multiplier, and incorporating EMA-based calculations, the system is designed to capture significant price breakouts while minimizing risk through dynamic stoplosses and volatility-adjusted position sizing. The inclusion of BBW and BBR indicators provides additional context for assessing market conditions, enhancing the trader’s ability to make informed decisions. With its structured approach and backtesting capabilities, this system is well-suited for traders seeking a systematic, data-driven method to trade in volatile markets.
Daily Bias on 5 minutes Reversal StrategyThis strategy combines higher-timeframe bias (daily and 1-hour) with 5-minute reversal signals to identify intraday trades. It aims to capitalize on false breakouts of the previous day's high/low, with strict risk management (Strict position sizing, max risk cap, and R:R enforcement), Avoids Over-Trading (1 trade/day rule prevents chasing), SL buffer adapts to volatility.
#1. This strategy does not utilize indicators. We will use the daily (D) price range and look for breakout attempts and rejections at the extreme points on the lower time frame (1h). If rejection occurs, it establishes our bias (bullish or bearish). For final confirmation, we move to the 5-minute timeframe to observe attempts to retest that daily price range. If significant rejection occurs again, that becomes our entry point.
#2. When rejection occurs, the 1-hour candle may form a new extreme point (low/high). Therefore, we will no longer use the daily price range as our trade exit point but instead the new extreme level established after the breakout attempt and price rejection.
To prevent premature trade exits, we also add an SL buffer using ATR while still capping the maximum acceptable risk per trade (as a percentage). Take profit is calculated using a risk-to-reward ratio, with a default setting of 1.5x.
#3. Key Input Parameters
a. Timeframes :
1. Daily TF ((Anchor for daily high/low (default: D).)
2. 1H Bias TF (Bias confirmation timeframe (default: 60))
3. Execution TF (Entry signal timeframe (default: 5, should match chart).
b. Trade Management
1. SL Buffer ATR Multiplier (Buffer beyond swing low/high (default: 6.0))
2. Min ATR Threshold (Minimum buffer size (default: 1.0))
3. Risk Reward Ratio (TP distance multiplier (default: 1.5))
4. Max Risk Allowed (Max risk % of entry (default: 3.0%))
Lookback Bars for SL Bars for swing low/high (default: 60))
c. Break Thresholds
1. 1H Candle Break Threshold (ATR multiplier for 1H break (default: 0.75))
2. 5M Candle Break Threshold (ATR multiplier for 5M break (default: 0.5))
