TFlab Trailing Stop StrategyThe trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward.
Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision.
SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading.
The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management.
A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making.
Indicators and strategies
15-Minute King (VWAP + Z-Score + CVD Oscillator)fridrich instituational secret . ( limited time only 4 free )
MULTI INDICATOR BY DEEPANINDIAThis TradingView strategy combines EMA, SuperTrend, and swing high/low to identify trend breakouts. A long trade is triggered when the previous candle closes above the EMA High and the current candle breaks the prior high. A short trade occurs (if not in Long Only mode) when the opposite happens with the EMA Low. The SuperTrend confirms trend direction, while swing points act as dynamic stop-loss levels. The script includes customizable inputs for EMA lengths, SuperTrend settings, and swing lookback. It helps traders capture strong trends with defined entries and exits using a rules-based, multi-indicator approach.
MULTI INDICATOR BY DEEPANINDIAThis TradingView strategy combines EMA, SuperTrend, and swing high/low to identify trend breakouts. A long trade is triggered when the previous candle closes above the EMA High and the current candle breaks the prior high. A short trade occurs (if not in Long Only mode) when the opposite happens with the EMA Low. The SuperTrend confirms trend direction, while swing points act as dynamic stop-loss levels. The script includes customizable inputs for EMA lengths, SuperTrend settings, and swing lookback. It helps traders capture strong trends with defined entries and exits using a rules-based, multi-indicator approach.
VWMA + ML RSI StrategyVWMA + ML RSI Strategy
This strategy combines the power of Volume-Weighted Moving Average (VWMA) with a Machine Learning-enhanced RSI to generate high-probability long entries.
✅ Buy Logic:
A buy signal is triggered when:
The candle closes above the VWMA
The ML RSI (smoothed using advanced moving averages) is above 60
If only one of the above conditions is met, the strategy waits for the second to confirm before entering.
❌ Sell Logic:
The position is closed when:
The candle closes below the VWMA, and
The ML RSI falls below 40
🎯 Risk Management:
Take Profit: 1.5% above entry
Stop Loss: 1.5% below entry
🤖 ML RSI Explanation:
The ML RSI is a refined version of the traditional RSI using smoothing techniques (like ALMA, EMA, etc.) to reduce noise and enhance responsiveness to price action. It helps filter out weak signals and improves trend confirmation.
🔧 Customization:
Adjustable VWMA length
Configurable ML RSI smoothing method, length, and ALMA sigma
Thresholds for entry/exit RSI levels
Williams Alligator Price vs Jaw StrategyWilliams Alligator using Price crossing over Jaw to go long and Price crossing under Jaw to close
Random Coin Toss Strategy📌 Overview
This strategy is a probability-based trading simulation that randomly decides trade direction using a coin-toss mechanism and executes trades with a customizable risk-reward ratio. It's designed primarily for testing entry frequency and risk dynamics, not predictive accuracy.
🎯 Core Concept
Every N bars (configurable), the strategy performs a pseudo-random coin toss.
Based on the result:
If heads → Buy
If tails → Sell
Once a position is opened, it sets a Stop-Loss (SL) and Take-Profit (TP) based on a multiple of the current ATR (Average True Range) value.
⚙️ Configurable Inputs
ATR Length Period for ATR calculation, determines volatility basis.
SL Multiplier SL distance = ATR × multiplier (e.g., 1.0 means 1x ATR) .
TP Multiplier TP distance = ATR × multiplier (e.g., 2.0 = 2x ATR) .
Entry Frequency Bars to wait between each new coin toss decision.
Show TP/SL Zones Toggle on/off for drawing visual TP and SL zones.
Box Size Number of bars used to define the width of the TP/SL boxes.
🔁 Entry & Exit Logic
Entry:
Happens only when no current position exists and it's the correct bar interval.
Entry direction is randomly decided.
Exit:
Positions exit at either:
Take-Profit (TP) level
Stop-Loss (SL) level
Both are calculated using the configured ATR-based distances.
🖼️ Visual Features
TP and SL zones:
Rendered as shaded rectangles (boxes) only once per trade.
Green box for TP zone, red box for SL zone.
Automatically deleted and redrawn for each new trade to avoid chart clutter.
ATR Display Table:
A minimal info table at the top-right shows the current ATR value.
Updates every few bars for performance.
🧪 Use Cases
Ideal for risk-reward modeling, strategy prototyping, and understanding how volatility-based SL/TP behavior affects results.
Great for backtesting frequency, RR tweaks (e.g., 2:5 or 3:1), and execution structure in random conditions.
⚠️ Disclaimer
Since the trade direction is random, this script is not meant for predictive trading but serves as a powerful experiment framework for studying how SL, TP, and volatility interact with random chance in a controlled, repeatable system.
Enhanced Ichimoku Cloud Strategy V1 [Quant Trading]Overview
This strategy combines the powerful Ichimoku Kinko Hyo system with a 171-period Exponential Moving Average (EMA) filter to create a robust trend-following approach. The strategy is designed for traders seeking to capitalize on strong momentum moves while using the Ichimoku cloud structure to identify optimal entry and exit points.
This is a patient, low-frequency trading system that prioritizes quality over quantity. In backtesting on Solana, the strategy achieved impressive results with approximately 3600% profit over just 29 trades, demonstrating its effectiveness at capturing major trend movements rather than attempting to profit from every market fluctuation. The extended parameters and strict entry criteria are specifically optimized for Solana's price action characteristics, making it well-suited for traders who prefer fewer, higher-conviction positions over high-frequency trading approaches.
What Makes This Strategy Original
This implementation enhances the traditional Ichimoku system by:
Custom Ichimoku Parameters: Uses non-standard periods (Conversion: 7, Base: 211, Lagging Span 2: 120, Displacement: 41) optimized for different market conditions
EMA Confirmation Filter: Incorporates a 171-period EMA as an additional trend confirmation layer
State Memory System: Implements a sophisticated memory system to track buy/sell states and prevent false signals
Dual Trade Modes: Offers both traditional Ichimoku signals ("Ichi") and cloud-based signals ("Cloud")
Breakout Confirmation: Requires price to break above the 25-period high for long entries
How It Works
Core Components
Ichimoku Elements:
-Conversion Line (Tenkan-sen): 7-period Donchian midpoint
-Base Line (Kijun-sen): 211-period Donchian midpoint
-Span A (Senkou Span A): Average of Conversion and Base lines, plotted 41 periods ahead
-Span B (Senkou Span B): 120-period Donchian midpoint, plotted 41 periods ahead
-Lagging Span (Chikou Span): Current close plotted 41 periods back
EMA Filter: 171-period EMA acts as a long-term trend filter
Entry Logic (Ichi Mode - Default)
A long position is triggered when ALL conditions are met:
Cloud Bullish: Span A > Span B (41 periods ago)
Breakout Confirmation: Current close > 25-period high
Ichimoku Bullish: Conversion Line > Base Line
Trend Alignment: Current close > 171-period EMA
State Memory: No previous buy signal is still active
Exit Logic
Positions are closed when:
Ichimoku Bearish: Conversion Line < Base Line
Alternative Cloud Mode
When "Cloud" mode is selected, the strategy uses:
Entry: Span A crosses above Span B with additional cloud and EMA confirmations
Exit: Span A crosses below Span B with cloud and EMA confirmations
Default Settings Explained
Strategy Properties
Initial Capital: $1,000 (realistic for average traders)
Position Size: 100% of equity (appropriate for backtesting single-asset strategies)
Commission: 0.1% (realistic for most brokers)
Slippage: 3 ticks (accounts for realistic execution costs)
Date Range: January 1, 2018 to December 31, 2069
Key Parameters
Conversion Periods: 7 (faster than traditional 9, more responsive to price changes)
Base Periods: 211 (much longer than traditional 26, provides stronger trend confirmation)
Lagging Span 2 Periods: 120 (custom period for stronger support/resistance levels)
Displacement: 41 (projects cloud further into future than standard 26)
EMA Period: 171 (long-term trend filter, approximately 8.5 months of daily data)
How to Use This Strategy
Best Market Conditions
Trending Markets: Works best in clearly trending markets where the cloud provides strong directional bias
Medium to Long-term Timeframes: Optimized for daily charts and higher timeframes
Volatile Assets: The breakout confirmation helps filter out weak signals in choppy markets
Risk Management
The strategy uses 100% equity allocation, suitable for backtesting single strategies
Consider reducing position size when implementing with real capital
Monitor the 25-period high breakout requirement as it may delay entries in fast-moving markets
Visual Elements
Green/Red Cloud: Shows bullish/bearish cloud conditions
Yellow Line: Conversion Line (Tenkan-sen)
Blue Line: Base Line (Kijun-sen)
Orange Line: 171-period EMA trend filter
Gray Line: Lagging Span (Chikou Span)
Important Considerations
Limitations
Lagging Nature: Like all Ichimoku strategies, signals may lag significant price moves
Whipsaw Risk: Extended periods of consolidation may generate false signals
Parameter Sensitivity: Custom parameters may not work equally well across all market conditions
Backtesting Notes
Results are based on historical data and past performance does not guarantee future results
The strategy includes realistic slippage and commission costs
Default settings are optimized for backtesting and may need adjustment for live trading
Risk Disclaimer
This strategy is for educational purposes only and should not be considered financial advice. Always conduct your own analysis and risk management before implementing any trading strategy. The unique parameter combinations used may not be suitable for all market conditions or trading styles.
Customization Options
Trade Mode: Switch between "Ichi" and "Cloud" signal generation
Short Trading: Option to enable short positions (disabled by default)
Date Range: Customize backtesting period
All Ichimoku Parameters: Fully customizable for different market conditions
This enhanced Ichimoku implementation provides a structured approach to trend following while maintaining the flexibility to adapt to different trading styles and market conditions.
ARSI – (VWAP & ATR) 3QKRAKThe ARSI Long & Short – Dynamic Risk Sizing (VWAP & ATR) indicator combines three core components—an adjusted RSI oscillator (ARSI), Volume‐Weighted Average Price (VWAP), and Average True Range (ATR)—so that entry/exit signals and position sizing are always tailored to current market conditions. ARSI, plotted from 0 to 100 with clearly marked overbought and oversold zones, is the primary signal driver: when ARSI falls below the lower threshold it indicates an excessive sell‐off and flags a long opportunity, whereas a break above the upper threshold signals overextended gains and foreshadows a short. A midpoint line at 50 can serve as an early exit or reduction signal when crossed against your position.
VWAP, showing the volume‐weighted average price over the chosen period, acts as a trend filter—long trades are only taken when price sits above VWAP, and shorts only when it’s below—ensuring each trade aligns with the prevailing market momentum. ATR measures current volatility and is used both to set safe stop‐loss levels and to dynamically size each position. In practice, this means positions automatically shrink in high‐volatility environments and grow in quieter markets, all while risking a fixed percentage of your capital.
Everything appears on a single chart: the ARSI pane below the price window with its reference levels; VWAP overlaid on the price; and the ATR‐based stop‐loss distances graphically displayed. Traders thus get a comprehensive, at-a-glance view of entries, exits, trend confirmation, and exactly how large a position they can safely take. The indicator runs in real time, removing the need for manual parameter calculations and letting you focus on strategic decision-making.
Holy GrailThis is a long-only educational strategy that simulates what happens if you keep adding to a position during pullbacks and only exit when the asset hits a new All-Time High (ATH). It is intended for learning purposes only — not for live trading.
🧠 How it works:
The strategy identifies pullbacks using a simple moving average (MA).
When price dips below the MA, it begins monitoring for the first green candle (close > open).
That green candle signals a potential bottom, so it adds to the position.
If price goes lower, it waits for the next green candle and adds again.
The exit happens after ATH — it sells on each red candle (close < open) once a new ATH is reached.
You can adjust:
MA length (defines what’s considered a pullback)
Initial buy % (how much to pre-fill before signals start)
Buy % per signal (after pullback green candle)
Exit % per red candle after ATH
📊 Intended assets & timeframes:
This strategy is designed for broad market indices and long-term appreciating assets, such as:
SPY, NASDAQ, DAX, FTSE
Use it only on 1D or higher timeframes — it’s not meant for scalping or short-term trading.
⚠️ Important Limitations:
Long-only: The script does not short. It assumes the asset will eventually recover to a new ATH.
Not for all assets: It won't work on assets that may never recover (e.g., single stocks or speculative tokens).
Slow capital deployment: Entries happen gradually and may take a long time to close.
Not optimized for returns: Buy & hold can outperform this strategy.
No slippage, fees, or funding costs included.
This is not a performance strategy. It’s a teaching tool to show that:
High win rate ≠ high profitability
Patience can be deceiving
Many signals = long capital lock-in
🎓 Why it exists:
The purpose of this strategy is to demonstrate market psychology and risk overconfidence. Traders often chase strategies with high win rates without considering holding time, drawdowns, or opportunity cost.
This script helps visualize that phenomenon.
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
Warrior Trading Momentum Strategy
# 🚀 Warrior Trading Momentum Strategy - Day Trading Excellence
## Strategy Overview
This comprehensive Pine Script strategy replicates the proven methodologies taught by Ross Cameron and the Warrior Trading community. Designed for active day traders, it identifies high-probability momentum setups with strict risk management protocols.
## 📈 Core Trading Setups
### 1. Gap and Go Trading
- **Primary Focus**: Stocks gapping up 2%+ with volume confirmation
- **Entry Logic**: Breakout above gap open with momentum validation
- **Volume Filter**: 2x average volume requirement for quality setups
### 2. ABCD Pattern Recognition
- **Pattern Detection**: Automated identification of classic ABCD reversal patterns
- **Validation**: A-B and C-D move relationship analysis
- **Entry Trigger**: D-point breakout with volume confirmation
### 3. VWAP Momentum Plays
- **Strategy**: Entries near VWAP with bounce confirmation
- **Distance Filter**: Configurable percentage distance for optimal entries
- **Direction Bias**: Above VWAP bullish momentum validation
### 4. Red to Green Reversals
- **Setup**: Reversal patterns after consecutive red candles
- **Confirmation**: Volume spike with bullish close required
- **Momentum**: Trend change validation with RSI support
### 5. Breakout Momentum
- **Logic**: Breakouts above recent highs with volume
- **Filters**: EMA20 and RSI confirmation for quality
- **Trend**: Established momentum direction validation
## ⚡ Key Features
### Smart Risk Management
- **Position Sizing**: Automatic calculation based on account risk percentage
- **Stop Loss**: 2 ATR-based stops for volatility adjustment
- **Take Profit**: Configurable risk-reward ratios (default 1:2)
- **Trailing Stops**: Profit protection with adjustable triggers
### Advanced Filtering System
- **Time Filters**: Market hours trading with lunch hour avoidance
- **Volume Confirmation**: Multi-timeframe volume analysis
- **Momentum Indicators**: RSI and moving average trend validation
- **Quality Control**: Multiple confirmation layers for signal accuracy
### PDT-Friendly Design
- **Trade Limiting**: Built-in daily trade counter for accounts under $25K
- **Selective Trading**: Priority scoring system for A+ setups only
- **Quality over Quantity**: Maximum 2-3 high-probability trades per day
## 🎯 Optimal Usage
### Best Timeframes
- **Primary**: 5-minute charts for entry timing
- **Secondary**: 1-minute for precise execution
- **Context**: Daily charts for gap analysis
### Ideal Market Conditions
- **Volatility**: High-volume, momentum-driven markets
- **Stocks**: Market cap $100M+, average volume 1M+ shares
- **Sectors**: Technology, biotech, growth stocks with news catalysts
### Account Requirements
- **Minimum**: $500+ for proper position sizing
- **Recommended**: $25K+ for unlimited day trading
- **Risk Tolerance**: Active day trading experience preferred
## 📊 Performance Optimization
### Entry Criteria (All Must Align)
1. ✅ Time filter (market hours, avoid lunch)
2. ✅ Volume spike (2x+ average volume)
3. ✅ Momentum confirmation (RSI 50-80)
4. ✅ Trend alignment (above EMA20)
5. ✅ Pattern completion (setup-specific)
### Risk Parameters
- **Maximum Risk**: 1-2% per trade
- **Position Size**: 25% of account maximum
- **Stop Loss**: 2 ATR below entry
- **Take Profit**: 2:1 risk-reward minimum
## 🔧 Customization Options
### Gap Trading Settings
- Minimum gap percentage threshold
- Volume multiplier requirements
- Gap validation criteria
### Pattern Recognition
- ABCD ratio parameters
- Swing point sensitivity
- Pattern completion filters
### Risk Management
- Risk-reward ratio adjustment
- Maximum daily trade limits
- Trailing stop trigger levels
### Time and Session Filters
- Trading session customization
- Lunch hour avoidance toggle
- Market condition filters
## ⚠️ Important Disclaimers
### Risk Warning
- **High Risk**: Day trading involves substantial risk of loss
- **Capital Requirements**: Only trade with risk capital
- **Experience**: Strategy requires active monitoring and experience
- **Market Conditions**: Performance varies with market volatility
### PDT Considerations
- **Day Trading Rules**: Accounts under $25K limited to 3 day trades per 5 days
- **Compliance**: Strategy includes trade counting for PDT compliance
- **Alternative**: Consider swing trading modifications for smaller accounts
### Backtesting vs Live Trading
- **Slippage**: Real trading involves execution delays and slippage
- **Commissions**: Factor in broker fees for accurate performance
- **Market Impact**: Large positions may affect fill prices
- **Psychological Factors**: Live trading involves emotional challenges
## 📚 Educational Value
This strategy serves as an excellent learning tool for understanding:
- Professional day trading methodologies
- Risk management principles
- Pattern recognition techniques
- Volume and momentum analysis
- Multi-timeframe analysis
## 🤝 Community and Support
Based on proven Warrior Trading methodologies with active community support. Strategy includes comprehensive plotting and information tables for educational purposes and trade analysis.
---
**Disclaimer**: This strategy is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose.
**Tags**: #DayTrading #Momentum #WarriorTrading #GapAndGo #ABCD #VWAP #PatternTrading #RiskManagement
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
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.
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.
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.
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.
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 |
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## 📊 **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
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## 🔬 **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
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## ⚠️ **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.
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## 🎯 **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
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**Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
