Enhanced Range Filter Strategy with ATR TP/SLBuilt by Omotola
## **Enhanced Range Filter Strategy: A Comprehensive Overview**
### **1. Introduction**
The **Enhanced Range Filter Strategy** is a powerful technical trading system designed to identify high-probability trading opportunities while filtering out market noise. It utilizes **range-based trend filtering**, **momentum confirmation**, and **volatility-based risk management** to generate precise entry and exit signals. This strategy is particularly useful for traders who aim to capitalize on trend-following setups while avoiding choppy, ranging market conditions.
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### **2. Key Components of the Strategy**
#### **A. Range Filter (Trend Determination)**
- The **Range Filter** smooths price fluctuations and helps identify clear trends.
- It calculates an **adjusted price range** based on a **sampling period** and a **multiplier**, ensuring a dynamic trend-following approach.
- **Uptrends:** When the current price is above the range filter and the trend is strengthening.
- **Downtrends:** When the price falls below the range filter and momentum confirms the move.
#### **B. RSI (Relative Strength Index) as Momentum Confirmation**
- RSI is used to **filter out weak trades** and prevent entries during overbought/oversold conditions.
- **Buy Signals:** RSI is above a certain threshold (e.g., 50) in an uptrend.
- **Sell Signals:** RSI is below a certain threshold (e.g., 50) in a downtrend.
#### **C. ADX (Average Directional Index) for Trend Strength Confirmation**
- ADX ensures that trades are only taken when the trend has **sufficient strength**.
- Avoids trading in low-volatility, ranging markets.
- **Threshold (e.g., 25):** Only trade when ADX is above this value, indicating a strong trend.
#### **D. ATR (Average True Range) for Risk Management**
- **Stop Loss (SL):** Placed **one ATR below** (for long trades) or **one ATR above** (for short trades).
- **Take Profit (TP):** Set at a **3:1 reward-to-risk ratio**, using ATR to determine realistic price targets.
- Ensures volatility-adjusted risk management.
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### **3. Entry and Exit Conditions**
#### **📈 Buy (Long) Entry Conditions:**
1. **Price is above the Range Filter** → Indicates an uptrend.
2. **Upward trend strength is positive** (confirmed via trend counter).
3. **RSI is above the buy threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **📉 Sell (Short) Entry Conditions:**
1. **Price is below the Range Filter** → Indicates a downtrend.
2. **Downward trend strength is positive** (confirmed via trend counter).
3. **RSI is below the sell threshold** (e.g., 50, to confirm momentum).
4. **ADX confirms trend strength** (e.g., above 25).
5. **Volatility is supportive** (using ATR analysis).
#### **🚪 Exit Conditions:**
- **Stop Loss (SL):**
- **Long Trades:** 1 ATR below entry price.
- **Short Trades:** 1 ATR above entry price.
- **Take Profit (TP):**
- Set at **3x the risk distance** to achieve a favorable risk-reward ratio.
- **Ranging Market Exit:**
- If ADX falls below the threshold, indicating a weakening trend.
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### **4. Visualization & Alerts**
- **Colored range filter line** changes based on trend direction.
- **Buy and Sell signals** appear as labels on the chart.
- **Stop Loss and Take Profit levels** are plotted as dashed lines.
- **Gray background highlights ranging markets** where trading is avoided.
- **Alerts trigger on Buy, Sell, and Ranging Market conditions** for automation.
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### **5. Advantages of the Enhanced Range Filter Strategy**
✅ **Trend-Following with Noise Reduction** → Helps avoid false signals by filtering out weak trends.
✅ **Momentum Confirmation with RSI & ADX** → Ensures that only strong, valid trades are executed.
✅ **Volatility-Based Risk Management** → ATR ensures adaptive stop loss and take profit placements.
✅ **Works on Multiple Timeframes** → Effective for day trading, swing trading, and scalping.
✅ **Visually Intuitive** → Clearly displays trade signals, SL/TP levels, and trend conditions.
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### **6. Who Should Use This Strategy?**
✔ **Trend Traders** who want to enter trades with momentum confirmation.
✔ **Swing Traders** looking for medium-term opportunities with a solid risk-reward ratio.
✔ **Scalpers** who need precise entries and exits to minimize false signals.
✔ **Algorithmic Traders** using alerts for automated execution.
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### **7. Conclusion**
The **Enhanced Range Filter Strategy** is a powerful trading tool that combines **trend-following techniques, momentum indicators, and risk management** into a structured, rule-based system. By leveraging **Range Filters, RSI, ADX, and ATR**, traders can improve trade accuracy, manage risk effectively, and filter out unfavorable market conditions.
This strategy is **ideal for traders looking for a systematic, disciplined approach** to capturing trends while **avoiding market noise and false breakouts**. 🚀
Cerca negli script per "algo"
RSI Pro+ (Bear market, financial crisis and so on EditionIn markets defined by volatility, fear, and uncertainty – the battlegrounds of bear markets and financial crises – you need tools forged in resilience. Introducing RSI Pro+, a strategy built upon a legendary indicator born in 1978, yet engineered with modern visual clarity to remain devastatingly effective even in the chaotic financial landscapes of 3078.
This isn't about complex algorithms predicting the unpredictable. It's about harnessing the raw, time-tested power of the Relative Strength Index (RSI) to identify potential exhaustion points and capitalize on oversold conditions. RSI Pro+ cuts through the noise, providing clear, actionable signals when markets might be poised for a relief bounce or reversal.
Core Technology (The 1978 Engine):
RSI Crossover Entry: The strategy initiates a LONG position when the RSI (default period 11) crosses above a user-defined low threshold (default 30). This classic technique aims to enter when selling pressure may be waning, offering potential entry points during sharp downturns or periods of consolidation after a fall.
Modern Enhancements (The 3078 Cockpit):
RSI Pro+ isn't just about the signal; it's about providing a professional-grade visual experience directly on your chart:
Entry Bar Highlight: A subtle background flash on the chart signals the exact bar where the RSI crossover condition is met, alerting you to potential entry opportunities.
Trade Bar Coloring: Once a trade is active, the price bars are subtly colored, giving you immediate visual confirmation that the strategy is live in the market.
Entry Price Line: A clear, persistent line marks your exact average entry price for the duration of the trade, serving as a crucial visual anchor.
Take Profit Line: Your calculated Take Profit target is plotted as a distinct line, keeping your objective clearly in sight.
Custom Entry Marker: A precise shape (▲) appears below the bar where the trade entry was actually executed, pinpointing the start of the position.
On-Chart Info Table (HUD): A clean, customizable Heads-Up Display appears when a trade is active, showing vital information at a glance:
Entry Price: Your position's average cost basis.
TP Target: The calculated price level for your Take Profit exit.
Current PnL%: Real-time Profit/Loss percentage for the open trade.
Full Customization: Nearly every aspect is configurable via the settings menu:
RSI Period & Crossover Level
Take Profit Percentage
Toggle ALL visual enhancements on/off individually
Position the Info Table wherever you prefer on the chart.
How to Use RSI Pro+:
Add to Chart: Apply the "RSI Pro+ (Bear market...)" strategy to your TradingView chart. Ensure any previous versions are removed.
Access Settings: Click the cogwheel icon (⚙️) next to the strategy name on your chart.
Configure Inputs (Crucial Step):
RSI Crossover Level: This is key. The default (30) targets standard oversold conditions. In severe downturns, you might experiment with lower levels (e.g., 25, 20) or higher ones (e.g., 40) depending on the asset and timeframe. Observe where RSI(11) typically bottoms out on your chart.
Take Profit Percentage (%): Define your desired profit target per trade (e.g., enter 0.5 for 0.5%, 1.0 for 1%). The default is a very small 0.11%.
RSI Period: While default is 11, you can adjust this (e.g., the standard 14).
Visual Enhancements: Enable or disable the visual features (background highlights, bar coloring, lines, markers, table) according to your preference using the checkboxes. Adjust table position.
Observe & Backtest: Watch how the strategy behaves on your chosen asset and timeframe. Use TradingView's Strategy Tester to analyze historical performance based on your settings. No strategy works perfectly everywhere; testing is essential.
Important Considerations:
Risk Management: This specific script version focuses on a Take Profit exit. It does not include an explicit Stop Loss. You MUST manage risk through appropriate position sizing, potentially adding a Stop Loss manually, or by modifying the script.
Oversold ≠ Reversal: An RSI crossover is an indicator of potential exhaustion, not a guarantee of a price reversal.
Fixed TP: A fixed percentage TP ensures small wins but may exit before larger potential moves.
Backtesting Limitations: Past performance does not guarantee future results.
RSI Pro+ strips away complexity to focus on a robust, time-honored principle, enhanced with modern visuals for the discerning trader navigating today's (and tomorrow's) challenging markets
Buy on 5% dip strategy with time adjustment
This script is a strategy called "Buy on 5% Dip Strategy with Time Adjustment 📉💡," which detects a 5% drop in price and triggers a buy signal 🔔. It also automatically closes the position once the set profit target is reached 💰, and it has additional logic to close the position if the loss exceeds 14% after holding for 230 days ⏳.
Strategy Explanation
Buy Condition: A buy signal is triggered when the price drops 5% from the highest price reached 🔻.
Take Profit: The position is closed when the price hits a 1.22x target from the average entry price 📈.
Forced Sell Condition: If the position is held for more than 230 days and the loss exceeds 14%, the position is automatically closed 🚫.
Leverage & Capital Allocation: Leverage is adjustable ⚖️, and you can set the percentage of capital allocated to each trade 💸.
Time Limits: The strategy allows you to set a start and end time ⏰ for trading, making the strategy active only within that specific period.
Code Credits and References
Credits: This script utilizes ideas and code from @QuantNomad and jangdokang for the profit table and algorithm concepts 🔧.
Sources:
Monthly Performance Table Script by QuantNomad:
ZenAndTheArtOfTrading's Script:
Strategy Performance
This strategy provides risk management through take profit and forced sell conditions and includes a performance table 📊 to track monthly and yearly results. You can compare backtest results with real-time performance to evaluate the strategy's effectiveness.
The performance numbers shown in the backtest reflect what would have happened if you had used this strategy since the launch date of the SOXL (the Direxion Daily Semiconductor Bull 3x Shares ETF) 📅. These results are not hypothetical but based on actual performance from the day of the ETF’s launch 📈.
Caution ⚠️
No Guarantee of Future Results: The results are based on historical performance from the launch of the SOXL ETF, but past performance does not guarantee future results. It’s important to approach with caution when applying it to live trading 🔍.
Risk Management: Leverage and capital allocation settings are crucial for managing risk ⚠️. Make sure to adjust these according to your risk tolerance ⚖️.
Premarket Gap MomoTrader(SC)🚀 Pre-Market Momentum Trader | Dynamic Position Sizing 🔥
📈 Trade explosive pre-market breakouts with confidence! This algorithmic strategy automatically detects high-momentum setups, dynamically adjusts position size, and ensures risk control with a one-trade-per-day rule.
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🎯 Key Features
✅ Pre-Market Trading (4:00 - 9:30 AM EST) – Only trades during the most volatile session for early breakouts.
✅ Dynamic Position Sizing – Adapts trade size based on candle strength:
• ≥90% body → 100% position
• ≥85% body → 50% position
• ≥75% body → 25% position
✅ 1 Trade Per Day – Avoids overtrading by allowing only one high-quality trade daily.
✅ Momentum Protection – Stays in the trade as long as:
• Every candle remains green (no red candles).
• Each new candle has increasing volume (confirming strong buying).
✅ Automated Exit – Closes position if:
• A red candle appears.
• Volume fails to increase on a green candle.
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🔍 How It Works
📌 Entry Conditions:
✔️ Candle gains ≥5% from previous close.
✔️ Candle is green & body size ≥75% of total range.
✔️ Volume >15K (confirming liquidity).
✔️ Occurs within pre-market session (4:00 - 9:30 AM EST).
✔️ Only the first valid trade of the day is taken.
📌 Exit Conditions:
❌ First red candle after entry → Exit trade.
❌ First green candle with lower volume → Exit trade.
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🏆 Why Use This?
🔹 Eliminates Fake Breakouts – No trade unless volume & momentum confirm.
🔹 Prevents Overtrading – Restricts to one quality trade per day.
🔹 Adaptable to Any Market – Works on stocks, crypto, or forex.
🔹 Hands-Free Execution – No manual chart watching required!
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🚨 Important Notes
📢 Not financial advice. Trading involves risk—always backtest & practice on paper trading before using real money.
📢 Enable pre-market data in your TradingView settings for accurate results.
📢 Optimized for 1-minute & 5-minute timeframes.
🔔 Like this strategy? Leave a comment, share your results, and don’t forget to hit Follow for more strategies! 🚀🔥
ScalpZilla Strategy Claude 0.53====== ScalpZilla Strategy Description ======
ScalpZilla is an advanced algorithmic trading strategy designed for the TradingView platform.
This is a fully reversible system that automatically closes opposing positions and manages multiple trade targets with configurable take-profit and stop-loss levels.
=== STRATEGY ARCHITECTURE ===
The strategy operates with two independent signal sections that can work together or separately:
1. CROSS SECTION: Generates signals based on price crossing a user-defined source indicator
2. SEPARATE SECTION: Uses independent sources for LONG and SHORT signals
=== REVERSIBLE SYSTEM FUNCTIONALITY ===
- The strategy automatically closes all opposing positions when a new signal is triggered
- For example, if a SHORT signal is received while in a LONG position, the system will:
* Close all current LONG positions
* Open a new SHORT position
- This reversible mechanism ensures the strategy always follows the current market direction
=== CONFIRMATION MECHANISM ===
Both sections can be configured to require confirmation from each other:
- When "Use As Confirmation" is enabled for a section, its signals act as confirmation triggers
- Two confirmation modes available:
* DELAYED: Waits for confirmation, opens position either when signal arrives and confirmation exists, or when confirmation arrives for an existing signal
* IMMEDIATE: Opens position only if confirmation already exists when signal arrives, otherwise skips
This allows creating complex conditions like: "Enter LONG only when both Cross and Separate sections agree on the direction"
=== TAKE PROFIT AND STOP LOSS MANAGEMENT ===
- Multiple take-profit levels (TP1-TP5) with individual activation and percentage settings
- Position size is automatically split equally between active TP levels
- Stop-loss protection with customizable percentage-based distance from entry
- All orders are managed separately for each section to avoid conflicts
=== ALERT SYSTEM ===
The strategy includes a comprehensive alert system with formatted messages that include:
- Trading pair/symbol
- Position direction (LONG/SHORT)
- Entry price
- All take-profit target levels (TP1-TP5)
- Stop-loss level
- Recommended leverage (25x)
Three alert configuration options are available:
1. "alert() function calls only" - For entry signals only
2. "Order fills and alert() function calls" - For all events
3. "Order fills only" - For order executions only
Alerts are formatted for compatibility with Cornix automation platform.
Sniper Trade Pro (ES 15-Min) - Topstep Optimized🔹 Overview
Sniper Trade Pro is an advanced algorithmic trading strategy designed specifically for E-mini S&P 500 (ES) Futures on the 15-minute timeframe. This strategy is optimized for Topstep 50K evaluations, incorporating strict risk management to comply with their max $1,000 daily loss limit while maintaining a high probability of success.
It uses a multi-confirmation approach, integrating:
✅ Money Flow Divergence (MFD) → To track liquidity imbalances and institutional accumulation/distribution.
✅ Trend Confirmation (EMA + VWAP) → To identify strong trend direction and avoid choppy markets.
✅ ADX Strength Filter → To ensure entries only occur in trending conditions, avoiding weak setups.
✅ Break-Even & Dynamic Stop-Losses → To reduce drawdowns and protect profits dynamically.
This script automatically generates Buy and Sell signals and provides built-in risk management for automated trading execution through TradingView Webhooks.
🔹 How Does This Strategy Work?
📌 1. Trend Confirmation (EMA + VWAP)
The strategy uses:
✔ 9-EMA & 21-EMA: Fast-moving averages to detect short-term momentum.
✔ VWAP (Volume-Weighted Average Price): Ensures trades align with institutional volume flow.
How it works:
Bullish Condition: 9-EMA above 21-EMA AND price above VWAP → Confirms buy trend.
Bearish Condition: 9-EMA below 21-EMA AND price below VWAP → Confirms sell trend.
📌 2. Liquidity & Money Flow Divergence (MFD)
This indicator measures liquidity shifts by tracking momentum changes in price and volume.
✔ MFD Calculation:
Uses Exponential Moving Average (EMA) of Momentum (MOM) to detect changes in buying/selling pressure.
If MFD is above its moving average, it signals liquidity inflows → bullish strength.
If MFD is below its moving average, it signals liquidity outflows → bearish weakness.
Why is this important?
Detects when Smart Money is accumulating or distributing before major moves.
Filters out false breakouts by confirming momentum strength before entry.
📌 3. Trade Entry Triggers (Candlestick Patterns & ADX Filter)
To avoid random entries, the strategy waits for specific candlestick confirmations with ADX trend strength:
✔ Bullish Entry (Buy Signal) → Requires:
Bullish Engulfing Candle (Reversal confirmation)
ADX > 20 (Ensures strong trending conditions)
MFD above its moving average (Liquidity inflows)
9-EMA > 21-EMA & price above VWAP (Trend confirmation)
✔ Bearish Entry (Sell Signal) → Requires:
Bearish Engulfing Candle (Reversal confirmation)
ADX > 20 (Ensures strong trending conditions)
MFD below its moving average (Liquidity outflows)
9-EMA < 21-EMA & price below VWAP (Trend confirmation)
📌 4. Risk Management & Profit Protection
This strategy is built with strict risk management to maintain low drawdowns and maximize profits:
✔ Dynamic Position Sizing → Automatically adjusts trade size to risk a fixed $400 per trade.
✔ Adaptive Stop-Losses → Uses ATR-based stop-loss (0.8x ATR) to adapt to market volatility.
✔ Take-Profit Targets → Fixed at 2x ATR for a Risk:Reward ratio of 2:1.
✔ Break-Even Protection → Moves stop-loss to entry once price moves 1x ATR in profit, locking in gains.
✔ Max Daily Loss Limit (-$1,000) → Stops trading if total losses exceed $1,000, complying with Topstep rules.
Dynamic Breakout Master by tradingbauhaus 🌟 Code Description:
This Pine Script implements a trading strategy called "Dynamic Breakout Master" 💥. The core idea of the strategy is to identify breakouts (price movements) at key support 💙 and resistance 🔴 levels, through a dynamic channel that adapts to the market’s conditions. Here's how it works:
🔧 Customizable Input Parameters:
🧭 Pivot Period: This defines the number of bars (candles) to the left and right used to detect pivots (highs and lows) that mark the support and resistance zones.
📊 Data Source: You can choose whether to use highs and lows or closes and opens of the candles to identify the pivots.
📏 Max Channel Width: Specifies the maximum width allowed for the support/resistance channel, expressed as a percentage over the last 300 bars.
💪 Minimum Pivot Strength: This defines the minimum number of pivots needed for a support or resistance level to be considered valid.
🏔 Max Support/Resistance Zones: Limits the number of key zones displayed on the chart.
📅 Lookback Period: Adjusts how many bars back the system should check to find and validate support and resistance levels.
🎨 Custom Colors: You can choose colors for the support, resistance, and in-channel zones.
📉 Moving Averages (MA): The strategy allows adding up to two moving averages (SMA or EMA) to assist in making trading decisions.
📊 Calculating Support/Resistance Levels:
The system uses an algorithm to identify pivots from prices and calculates dynamic support and resistance zones 🔒🔓.
The closer the pivots are and the stronger their influence, the more relevant the zone becomes for the strategy.
The dynamic channel is drawn on the chart, with a maximum width limit for these zones defined by the input parameter.
📈 Trading Logic:
🚀 Identifying Breakouts:
The strategy looks for when the price breaks (breakouts) a resistance or support level.
If the price breaks upward through the resistance level, a buy order 📈 is triggered.
If the price breaks downward through the support level, a sell order 📉 is triggered.
🔔 Alerts:
Resistance Break (ResBreak) and Support Break (SupBreak) alerts are configured to notify users when a significant breakout occurs.
💰 Commissions:
The strategy includes a commission (0.1%) to simulate transaction costs for each trade.
📊 Chart Visualization:
The support and resistance zones are displayed as colored rectangles:
🔴 Resistance (red) and
🔵 Support (blue).
Pivots of support and resistance can be labeled as P (for resistance) and V (for support).
Breakouts of support or resistance levels are marked with triangles that appear on the chart 🔺🔻.
📈 Trading Strategy:
If the price breaks upward through the resistance level, a long position (buy) 📈 is opened.
If the price breaks downward through the support level, a short position (sell) 📉 is opened.
🏆 Conclusion:
This script is a dynamic breakout strategy 💥 that allows traders to capture significant price movements when support or resistance channels break. The customizable parameters let users fine-tune the strategy according to their preferences, while the visual alerts on the chart make it easier to follow trading opportunities. The inclusion of moving averages and key price zones adds an extra layer of analysis to improve decision-making 💡.
Supertrend pro+ (Adaptive ATR) Supertrend Pro+ (Adaptive ATR) - Param Approach
By SKP
Overview
This advanced Supertrend Pro+ strategy improves on the classic Supertrend indicator by integrating an Adaptive ATR, ensuring dynamic volatility adjustments for more accurate trend detection. This strategy filters out false signals using ADX trend strength validation and volume confirmation, making it a powerful tool for trend-following traders.
Key Features
✔ Adaptive ATR Calculation - Dynamically adjusts to market volatility for more reliable Supertrend signals.
✔ ADX Trend Filter - Ensures trades occur only in strong trending markets, avoiding false breakouts.
✔ Volume Confirmation - Prevents trading in low-liquidity conditions by verifying volume strength.
✔ Multi-Timeframe Analysis - Displays Supertrend trends from different timeframes for enhanced trade confidence.
✔ Trailing Stop & Take Profit Options - Allows flexible risk management with stop-loss and profit-targeting mechanisms.
✔ Custom Alerts for Trade Signals - Alerts trigger on confirmed Supertrend buy/sell signals and potential trend shifts.
✔ Max Drawdown Protection - Automatically closes trades if equity drops beyond a set percentage, preventing excessive losses.
How It Works
Adaptive ATR Calculation
Instead of using a fixed ATR, this strategy calculates an adaptive ATR based on a longer-term ATR baseline.
If volatility increases, the ATR expands dynamically, ensuring stop-losses and Supertrend calculations adjust accordingly.
Supertrend Confirmation
Uses an enhanced Supertrend algorithm with adaptive ATR to determine trend direction.
If price crosses above the trendline, it signals a bullish reversal (Buy Signal).
If price crosses below the trendline, it signals a bearish reversal (Sell Signal).
ADX Trend Strength Filter
Trades are only taken when ADX is above the threshold, ensuring entry in strong trending markets.
Volume Confirmation
Uses a relative volume filter to ensure sufficient liquidity before entering trades.
Helps avoid false breakouts in low-volume conditions.
Risk Management
Trailing Stop Loss - Automatically moves the stop as price moves in favor of the trade.
Manual Stop Loss & Take Profit - Allows precise percentage-based exit points.
Max Drawdown Protection - Closes all trades if equity falls below a set threshold, reducing risk.
Multi-Timeframe Supertrend Table
Displays Supertrend signals across different timeframes (1 min, 5 min, 15 min, 1 hour, Daily)
Helps traders align their entries with higher timeframe trends for better accuracy.
Custom Alerts
Alerts notify when a new buy/sell signal appears.
Extra early warning alerts indicate potential trade setups before confirmation.
How to Use
📌 For trend-following traders:
Focus on entries in the direction of the higher timeframes.
Only enter when ADX is trending and volume confirms liquidity.
📌 For scalpers:
Use shorter timeframes (1m, 5m, 15m) for quick trades.
Adjust the ATR multiplier and Adaptive ATR sensitivity for tighter stops.
📌 For swing traders:
Use longer timeframes (1H, Daily) for more stable trends.
Enable trailing stop loss to lock in profits as the trend progresses.
Inputs & Customization
ATR Period & Adaptive ATR Sensitivity
Supertrend Multiplier
ADX Filter & Threshold
Volume Confirmation Settings
Stop Loss & Take Profit Options
Multi-Timeframe Supertrend Display
Custom Alerts
Universal Strategy | QuantEdgeBIntroducing the Universal Strategy by QuantEdgeB
The Universal Strategy | QuantEdgeB is a dynamic, multi-indicator strategy designed to operate across various asset classes with precision and adaptability. This cutting-edge system utilizes four sophisticated methodologies, each integrating advanced trend-following, volatility filtering, and normalization techniques to provide robust signals. Its modular architecture and customizable features ensure suitability for diverse market conditions, empowering traders with data-driven decision-making tools. Its adaptability to different price behaviors and volatility levels makes it a robust and versatile tool, equipping traders with data-driven confidence in their market decisions.
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1. Core Methodologies and Features
1️⃣ DEMA ATR
Strength : Fast responsiveness to trend shifts.
The double exponential moving average is inherently aggressive, designed to reduce lag and quickly identify early signs of trend reversals or breakout opportunities. ATR bands add a volatility-sensitive layer, dynamically adjusting the breakout thresholds to match current market conditions, ensuring it remains responsive while filtering out noise
How It Fits :
This indicator is the first responder, providing early signals of potential trend shifts. While its aggressiveness can result in quick entries, it may occasionally overreact in noisy markets. This is where the smoother indicators step in to confirm signals.
2️⃣ Gaussian - VIDYA ATR (Variable Index Dynamic Average)
Strength : Smooth, adaptive trend identification.
Unlike DEMA, VIDYA adapts to market volatility through its standard deviation-based formula, making it smoother and less reactive to short-term fluctuations. ATR filtering ensures the indicator remains effective in volatile markets by dynamically adjusting its sensitivity.
How It Fits :
The smoother complement to DEMA ATR, VIDYA ATR filters out false signals from minor price movements. It provides confirmation for the trends identified by DEMA ATR, ensuring entries are based on robust, sustained price movements.
3️⃣ VIDYA Loop Trend Scoring
Strength : Historical trend scoring for consistent momentum detection.
This module evaluates the relative strength of trends by comparing the current VIDYA value to its historical values over a defined range. The loop mechanism provides a trend confidence score, quantifying the momentum behind price movements.
How It Fits :
VIDYA For-Loop adds a quantitative measure of trend strength, ensuring that trades are backed by sustained momentum. It balances the early signals from DEMA ATR and the smoothness of VIDYA ATR by providing a statistical check on the underlying trend.
4️⃣ Median SD with Normalization
Strength : Precision in breakout detection and market normalization.
The Median price serves as a robust baseline for detecting breakouts and reversals.
SD bands expand dynamically during periods of high volatility, making the indicator particularly effective for spotting strong trends or breakout opportunities. Normalization ensures the indicator adapts seamlessly across different assets and timeframes, providing consistent performance.
How It Fits :
The Median SD module provides final confirmation by focusing on price breakouts and market normalization. While the other indicators focus on momentum and trend strength, Median SD emphasizes precision, ensuring entries align with significant price movements rather than random fluctuations.
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2. How The Single Components Work Together
1️⃣ Balance of Speed and Smoothness :
The strategy blends quick responsiveness (DEMA ATR) with smooth and adaptive confirmation (VIDYA ATR & For-Loop), ensuring timely reactions without overreacting to market fluctuations. Median SD with Normalization refines breakout detection and stabilizes performance across assets using statistical anchors like price median and standard deviation.
Adaptability to Market Dynamics:
2️⃣ Adaptability to Market Dynamics :
The indicators complement each other seamlessly in trending markets, with the DEMA ATR and Median SD with Normalization quickly identifying shifts and confirming sustained momentum. In volatile or choppy markets, normalization and SD bands work together to filter out noise and reduce false signals, ensuring precise entries and exits. Meanwhile, the For-Loop scoring and Gaussian-Filtered VIDYA ATR focus on providing smoother, more reliable trend detection, offering consistent performance regardless of market conditions.
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3. Scoring and Signal Confirmation
The Universal Strategy consolidates signals from all four methodologies, calculating a Trend Probability Index (TPI). The four core indicators operate independently but contribute to a unified TPI, enabling highly adaptive behavior across asset classes.
- Each methodology generates a trend score: 1 for bullish trends, -1 for bearish trends.
- The TPI averages the scores, creating a unified signal.
- Long Position: Triggered when the TPI exceeds the long threshold (default: 0).
- Short Position: Triggered when the TPI falls below the short threshold (default: 0).
The strategy’s customizable settings allow traders to tailor its behavior to different market conditions—whether smoother trends in low-volatility assets or quick reaction to high-volatility breakouts. The long and short thresholds can be fine-tuned to match a trader’s risk tolerance and preferences.
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4. Use Cases:
The Universal Strategy | QuantEdgeB is designed to excel across a wide range of trading scenarios, thanks to its modular architecture and adaptability. Whether you're navigating trending, volatile, or range-bound markets, this strategy offers robust tools to enhance your decision-making. Below are the key use cases for its application:
1️⃣ Trend Trading
The strategy’s Gaussian-Filtered DEMA ATR and VIDYA ATR modules are perfect for identifying and riding sustained trends.
Ideal For: Traders looking to capture long-term momentum or position trades.
2️⃣ Breakout and Volatility-Based Strategies
With its Median SD with Normalization, the strategy excels in detecting volatility breakouts and significant price movements.
Ideal For: Traders aiming to capitalize on sudden market movements, especially in assets like cryptocurrencies and commodities.
3️⃣ Momentum and Strength Assessment
By generating a trend confidence score, the VIDYA For-Loop quantifies momentum strength—helping traders distinguish temporary spikes from sustainable trends.
Ideal For: Swing traders and those focusing on momentum-driven setups.
4️⃣ Adaptability Across Multiple Assets
The strategy’s robust framework ensures it performs consistently across different assets and timeframes.
Ideal For: Traders managing diverse portfolios or shifting between asset classes.
5️⃣ Backtesting and Optimization
Built-in backtesting and equity visualization tools make this strategy ideal for testing and refining parameters in real-world conditions.
• How It Helps: The strategy equity curve and metrics table offer a clear picture of performance, helping traders identify optimal settings for their chosen market and timeframe.
• Ideal For: Traders focused on rigorous testing and long-term optimization.
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5. Signal Composition Table:
This table presents a real-time breakdown of each indicator’s trend score (+1 bullish, -1 bearish) alongside the final aggregated signal. By visualizing the contribution of each methodology, traders gain greater transparency, confidence, and clarity in identifying long or short opportunities.
6. Customized Settings:
1️⃣ General Inputs
• Strategy Long Threshold (Lu): 0
• Strategy Short Threshold (Su): 0
2️⃣ Gaussian Filter
• Gaussian Length (len_FG): 4
• Gaussian Source (src_FG): close
• Gaussian Sigma (sigma_FG): 2.0
3️⃣ DEMA ATR
• DEMA Length (len_D): 30
• DEMA Source (src_D): close
• ATR Length (atr_D): 14
• ATR Multiplier (mult_D): 1.0
4️⃣ VIDYA ATR
• VIDYA Length (len_V1): 9
• SD Length (len_VHist1): 30
• ATR Length (atr_V): 14
• ATR Multiplier (mult_V): 1.7
5️⃣ VIDYA For-Loop
• VIDYA Length (len_V2): 2
• SD Length (len_VHist2): 5
• VIDYA Source (src_V2): close
• Start Loop (strat_loop): 1
• End Loop (end_loop): 60
• Long Threshold (long_t): 40
• Short Threshold (short_t): 8
6️⃣ Median SD
• Median Length (len_m): 24
• Normalized Median Length (len_msd): 50
• SD Length (SD_len): 32
• Long SD Weight (w1): 0.98
• Short SD Weight (w2): 1.02
• Long Normalized Smooth (smooth_long): 1
• Short Normalized Smooth (smooth_short): 1
Conclusion
The Universal Strategy | QuantEdgeB is a meticulously crafted, multi-dimensional trading system designed to thrive across diverse market conditions and asset classes. By combining Gaussian-Filtered DEMA ATR, VIDYA ATR, VIDYA For-Loop, and Median SD with Normalization, this strategy provides a seamless balance between speed, smoothness, and adaptability. Each component complements the others, ensuring traders benefit from early responsiveness, trend confirmation, momentum scoring, and breakout precision.
Its modular structure ensures versatility across trending, volatile, and consolidating markets. Whether applied to equities, forex, commodities, or crypto, it delivers data-driven precision while minimizing reliance on randomness, reinforcing confidence in decision-making.
With built-in backtesting tools, traders can rigorously evaluate performance under real-world conditions, while customization options allow fine-tuning for specific market dynamics and individual trading styles.
Why It Stands Out
The Universal Strategy | QuantEdgeB isn’t just a trading algorithm—it’s a comprehensive framework that empowers traders to make confident, informed decisions in the face of ever-changing market conditions. Its emphasis on precision, reliability, and transparency makes it a powerful tool for both professional and retail traders seeking consistent performance and enhanced risk management.
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🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Forex Hammer and Hanging Man StrategyThe strategy is based on two key candlestick chart patterns: Hammer and Hanging Man. These chart patterns are widely used in technical analysis to identify potential reversal points in the market. Their relevance in the Forex market, known for its high liquidity and volatile price movements, is particularly pronounced. Both patterns provide insights into market sentiment and trader psychology, which are critical in currency trading, where short-term volatility plays a significant role.
1. Hammer:
• Typically occurs after a downtrend.
• Signals a potential trend reversal to the upside.
• A Hammer has:
• A small body (close and open are close to each other).
• A long lower shadow, at least twice as long as the body.
• No or a very short upper shadow.
2. Hanging Man:
• Typically occurs after an uptrend.
• Signals a potential reversal to the downside.
• A Hanging Man has:
• A small body, similar to the Hammer.
• A long lower shadow, at least twice as long as the body.
• A small or no upper shadow.
These patterns are a manifestation of market psychology, specifically the tug-of-war between buyers and sellers. The Hammer reflects a situation where sellers tried to push the price down but were overpowered by buyers, while the Hanging Man shows that buyers failed to maintain the upward movement, and sellers could take control.
Relevance of Chart Patterns in Forex
In the Forex market, chart patterns are vital tools because they offer insights into price action and market sentiment. Since Forex trading often involves large volumes of trades, chart patterns like the Hammer and Hanging Man are important for recognizing potential shifts in market momentum. These patterns are a part of technical analysis, which aims to forecast future price movements based on historical data, relying on the psychology of market participants.
Scientific Literature on the Relevance of Candlestick Patterns
1. Behavioral Finance and Candlestick Patterns:
Research on behavioral finance supports the idea that candlestick patterns, such as the Hammer and Hanging Man, are relevant because they reflect shifts in trader psychology and sentiment. According to Lo, Mamaysky, and Wang (2000), patterns like these could be seen as representations of collective investor behavior, influenced by overreaction, optimism, or pessimism, and can often signal reversals in market trends.
2. Statistical Validation of Chart Patterns:
Studies by Brock, Lakonishok, and LeBaron (1992) explored the profitability of technical analysis strategies, including candlestick patterns, and found evidence that certain patterns, such as the Hammer, can have predictive value in financial markets. While their study primarily focused on stock markets, their findings are generally applicable to the Forex market as well.
3. Market Efficiency and Candlestick Patterns:
The efficient market hypothesis (EMH) posits that all available information is reflected in asset prices, but some studies suggest that markets may not always be perfectly efficient, allowing for profitable exploitation of certain chart patterns. For instance, Jegadeesh and Titman (1993) found that momentum strategies, which often rely on price patterns and trends, could generate significant returns, suggesting that patterns like the Hammer or Hanging Man may provide a slight edge, particularly in short-term Forex trading.
Testing the Strategy in Forex Using the Provided Script
The provided script allows traders to test and evaluate the Hammer and Hanging Man patterns in Forex trading by entering positions when these patterns appear and holding the position for a specified number of periods. This strategy can be tested to assess its performance across different currency pairs and timeframes.
1. Testing on Different Timeframes:
• The effectiveness of candlestick patterns can vary across different timeframes, as market dynamics change with the level of detail in each timeframe. Shorter timeframes may provide more frequent signals, but with higher noise, while longer timeframes may produce more reliable signals, but with fewer opportunities. This multi-timeframe analysis could be an area to explore to enhance the strategy’s robustness.
2. Exit Strategies:
• The script incorporates an exit strategy where positions are closed after holding them for a specified number of periods. This is useful for testing how long the reversal patterns typically take to play out and when the optimal exit occurs for maximum profitability. It can also help to adjust the exit logic based on real-time market behavior.
Conclusion
The Hammer and Hanging Man patterns are widely recognized in technical analysis as potential reversal signals, and their application in Forex trading is valuable due to the market’s high volatility and liquidity. This strategy leverages these candlestick patterns to enter and exit trades based on shifts in market sentiment and psychology. Testing and optimization, as offered by the script, can help refine the strategy and improve its effectiveness.
For further refinement, it could be valuable to consider combining candlestick patterns with other technical indicators or using multi-timeframe analysis to confirm patterns and increase the probability of successful trades.
References:
• Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705-1770.
• Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731-1764.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
This provides a theoretical basis for the use of candlestick patterns in trading, supported by academic literature and research on market psychology and efficiency.
Adaptive Trend Flow Strategy with Filters for SPXThe Adaptive Trend Flow Strategy with Filters for SPX is a complete trading algorithm designed to identify traits and offer actionable alerts for the SPX index. This Pine Script approach leverages superior technical signs and user-described parameters to evolve to marketplace conditions and optimize performance.
Key Features and Functionality
Dynamic Trend Detection: Utilizes a dual EMA-based totally adaptive method for fashion calculation.
The script smooths volatility the usage of an EMA filter and adjusts sensitivity through the sensitivity enter. This allows for real-time adaptability to market fluctuations.
Trend Filters for Precision:
SMA Filter: A Simple Moving Average (SMA) guarantees that trades are achieved best while the rate aligns with the shifting average trend, minimizing false indicators.
MACD Filter: The Moving Average Convergence Divergence (MACD) adds some other layer of confirmation with the aid of requiring alignment among the MACD line and its sign line.
Signal Generation:
Long Signals: Triggered when the fashion transitions from bearish to bullish, with all filters confirming the pass.
Short Signals: Triggered while the trend shifts from bullish to bearish, imparting opportunities for final positions.
User Customization:
Adjustable parameters for EMAs, smoothing duration, and sensitivity make certain the strategy can adapt to numerous buying and selling patterns.
Enable or disable filters (SMA or MACD) based totally on particular market conditions or consumer possibilities.
Leverage and Position Sizing: Incorporates a leverage aspect for dynamic position sizing.
Automatically calculates the exchange length based on account fairness and the leverage element, making sure hazard control is in area.
Visual Enhancements: Plots adaptive fashion ranges (foundation, top, decrease) for actual-time insights into marketplace conditions.
Color-coded bars and heritage to visually represent bullish or bearish developments.
Custom labels indicating crossover and crossunder occasions for clean sign visualization.
Alerts and Automation: Configurable alerts for each lengthy and quick indicators, well matched with automated buying and selling structures like plugpine.Com.
JSON-based alert messages consist of account credentials, motion type, and calculated position length for seamless integration.
Backtesting and Realistic Assumptions: Includes practical slippage, commissions, and preliminary capital settings for backtesting accuracy.
Leverages excessive-frequency trade sampling to make certain strong strategy assessment.
How It Works
Trend Calculation: The method derives a principal trend basis with the aid of combining fast and gradual EMAs. It then uses marketplace volatility to calculate adaptive upper and decrease obstacles, creating a dynamic channel.
Filter Integration: SMA and MACD filters work in tandem with the fashion calculation to ensure that handiest excessive-probability signals are accomplished.
Signal Execution: Signals are generated whilst the charge breaches those dynamic tiers and aligns with the fashion and filters, ensuring sturdy change access situations.
How to Use
Setup: Apply the approach to SPX or other well suited indices.
Adjust person inputs, together with ATR length, EMA smoothing, and sensitivity, to align together with your buying and selling possibilities.
Enable or disable the SMA and MACD filters to test unique setups.
Alerts: Configure signals for computerized notifications or direct buying and selling execution through third-celebration systems.
Use the supplied JSON payload to integrate with broking APIs or automation tools.
Optimization:
Experiment with leverage, filter out settings, and sensitivity to find most effective configurations to your hazard tolerance and marketplace situations.
Considerations and Best Practices
Risk Management: Always backtest the method with realistic parameters, together with conservative leverage and commissions.
Market Suitability: While designed for SPX, this method can adapt to other gadgets by means of adjusting key parameters.
Limitations: The method is trend-following and can underperform in enormously risky or ranging markets. Regularly evaluate and modify parameters primarily based on recent market conduct.
If you have any questions please let me know - I'm here to help!
DCA Alpha 1.0 Trading Tool for Dollar-Cost Averaging
Description:
DCA Alpha 1.0 is a precision-engineered trading tool designed to assist traders and investors in accumulating assets during market downturns. Using proprietary algorithms that combine momentum decay, extreme price deviation metrics, trend dynamics, divergence analysis, and mean regression, it identifies potential bottom extreme zones in various asset classes such as indices, stocks, crypto, and commodities.
This indicator highlights market conditions where assets are oversold, undervalued, or experiencing capitulation—providing disciplined, unleveraged dollar-cost averaging (DCA) opportunities. Ideal for long-term growth strategies, DCA Alpha 1.0 helps cut through market noise, pinpointing moments of peak fear and maximum reward potential.
Whether navigating volatile crypto markets, timing corrections in indices, or accumulating commodities, DCA Alpha 1.0 serves as a vital tool for mastering the art of buying low and building your assets up strategically.
Instructions:
Getting Started:
Add the Indicator:
Install DCA Alpha 1.0 on your TradingView chart.
Select your preferred asset class: stocks, indices, crypto, or commodities.
Choose an appropriate timeframe (e.g., daily or weekly for long-term DCA strategies).
Customize Inputs: Adjust the following settings to align with your strategy:
Percentage of Equity to Trade: Define the portion of your portfolio to allocate per signal (default: 1% equity).
Profit Target Percentages: Set thresholds for locking in gains (default: 50% on lower timeframes, 500% on higher timeframes).
Zones and Signals:
Extreme Negative Zones:
What It Represents:
These zones highlight conditions where prices are deeply oversold, indicating extreme bearish sentiment. The market is likely nearing a bottom, offering high-probability buying opportunities.
Entry Signals:
When the price enters these extreme negative zones, visual markers (e.g., green triangles or other indicators) will signal a potential buying opportunity. These moments are indicative of market exhaustion, signaling that a reversal could be imminent.
Momentum Decay & Divergence:
Momentum decay occurs when price movement slows over time. In extreme negative zones, if prices continue to fall but at a diminishing rate (e.g., decreased volume or a fading oscillator), it suggests weakening bearish momentum. This, coupled with bullish divergence (oscillator forming higher lows while price makes lower lows), signifies a reversal, making it an ideal point to consider dollar-cost averaging into the asset.
Neutral Zones:
What It Represents:
The neutral zone is a state of market equilibrium, where prices are neither overbought nor oversold. The market is in a balanced state, with no strong trend emerging.
Mean Regression:
In a neutral zone, the market is reverting to its mean or average price after overreacting in either direction. A price transition from extreme zones (overbought/oversold) to the neutral zone suggests a reversion to the market's long-term average, making this a period of reduced volatility and uncertainty.
Entering or Exiting Neutral Zones:
Traders should avoid entering or exiting positions during neutral zone conditions unless transitioning from an extreme zone (negative or positive). Transitioning from an extreme negative zone to neutral may suggest an opportunity to accumulate assets gradually, while a shift from neutral to an extreme negative zone may indicate a deeper correction and warrant caution.
Momentum Decay & Divergence (Exiting Neutral Zone):
If prices are rising but the oscillator shows lower highs (bearish divergence), and momentum is fading, this could signal a pullback. A transition out of the neutral zone in this context may prompt traders to hold off on new positions or consider profit-taking.
Extreme Positive Zones:
What It Represents:
Markets can also become overbought or overvalued. When price enters extreme positive zones, the asset may be overvalued, suggesting potential selling or a waiting period.
Exit Signals:
Red triangle indicators signal potential exit points when prices reach overbought conditions, signaling a time to lock in profits and reduce exposure.
Momentum Decay & Divergence (Exiting Positive Zone):
When prices are making new highs but momentum is weakening (momentum decay) and the oscillator is showing lower highs (bearish divergence), this could indicate a faltering rally. Such conditions represent an ideal time to reduce exposure or exit positions.
Key Inputs for Customization:
Percentage of Equity to Trade:
This setting allows you to allocate a portion of your total portfolio per buy signal. By default, 1% of equity is used per signal, but this can be adjusted based on your risk tolerance and strategy.
Profit Target Percentages:
These thresholds help lock in gains once the price moves a set percentage in your favor.
Lower Timeframes: Default profit target of 50%.
Higher Timeframes: Default profit target of 500%.
These settings can be customized for specific risk/reward preferences.
Warning!!! : Aggressive Mode
Aggressive Mode is an advanced feature designed for traders who want to increase the frequency of signals during periods of market volatility. This mode will trigger more frequent entries, even into slightly less extreme zones, capturing short-term reversals.
What Aggressive Mode Does:
It amplifies signals by allowing the tool to identify more frequent price reversals, including brief market corrections, increasing trade frequency. While this can offer more trading opportunities, it also exposes you to higher risk.
Warning:
Aggressive Mode should be used only by experienced traders familiar with short-term volatility. The increased frequency of signals could lead to higher risk exposure. Ensure robust risk management practices, such as stop-loss orders and profit-taking strategies, are in place before activating this mode.
Default Setting:
Aggressive Mode is disabled by default. It can be activated at your discretion based on your experience level and risk appetite.
Best Practices:
Focus on High-Quality Assets: Prioritize assets with strong recovery potential (e.g., major indices, blue-chip cryptocurrencies).
Use Longer Timeframes: Minimize market noise and optimize your DCA strategy by focusing on higher timeframes (e.g., daily or weekly charts).
Review Trading Inputs: Regularly adjust your inputs to ensure they align with your financial goals and risk tolerance.
Implement Risk Management: Use stop-loss orders and profit targets to manage risk, especially when using Aggressive Mode.
Disclaimer:
DCA Alpha 1.0 is designed specifically for unleveraged, long-term dollar-cost averaging strategies. It is not intended for day trading or leveraged positions. The tool excels at identifying market dips but cannot guarantee success. Users are fully responsible for their own risk management, including the use of stop-losses, profit targets, and position sizing.
Aggressive Mode increases trade frequency and may lead to higher exposure and potential losses. Only experienced traders should consider using this mode. Always understand the risks involved before incorporating this tool into your trading strategy.
DemaRSI StrategyThis is a repost to a old script that cant be updated anymore, the request was made on Feb, 27, 2016.
Here's a engaging description for the tradingview script:
**DemaRSI Strategy: A Proven Trading System**
Join thousands of traders who have already experienced the power of this highly effective strategy. The DemaRSI system combines two powerful indicators - DEMA (Double Exponential Moving Average) and RSI (Relative Strength Index) - to generate profitable trades with minimal risk.
**Key Features:**
* **Trend-Following**: Our algorithm identifies strong trends using a combination of DEMA and RSI, allowing you to ride the waves of market momentum.
* **Risk Management**: The system includes built-in stop-loss and take-profit levels, ensuring that your gains are protected and losses are minimized.
* **Session-Based Trading**: Trade during specific sessions only (e.g., London or New York) for even more targeted results.
* **Customizable Settings**: Adjust the length of moving averages, RSI periods, and other parameters to suit your trading style.
**What You'll Get:**
* A comprehensive strategy that can be used with any broker or platform
* Easy-to-use interface with customizable settings
* Real-time performance metrics and backtesting capabilities
**Start Trading Like a Pro Today!**
This script is designed for intermediate to advanced traders who want to take their trading game to the next level. With its robust risk management features, this strategy can help you achieve consistent profits in various market conditions.
**Disclaimer:** This script is not intended as investment advice and should be used at your own discretion. Trading carries inherent risks, and losses are possible.
~Llama3
FXC NQ Opening Range Breakout Strategy V2.4Mechanical Strategy that trades breakouts on NQ futures on the 15min timeframe during the NYSE session. It's designed to manage Apex and Top Step accounts with the lowest risk possible.
Risk Disclaimer:
Past results as well as strategy tester reports do not indicate future performance. Guarantees do not exist in trading. By using this strategy you risk losing all your money.
Important:
It only trades on Monday, Wednesday and Friday and takes usually only 1 trade per trading day.
It works on the 15min timeframe only.
The settings are optimised already for NQ but feel free to change them.
How it works:
Every selected trading day it measures the range of the first 15min candle after the NYSE open. As soon as price closes above on the 15min timeframe, it will trade the breakout targeting a set risk to reward ratio. SL on the opposite side of the range. It will trail the SL after a set amount of points and uses a buffer of the set amount of points to trail it.
Settings:
Opening Range Time : This is the time of the day in hours and minutes when the strategy starts looking for trades. It's in the EST/ NY Timezone and set to 9:30-09:45 by default
because that's the NYSE open.
Session Time : This is the time of the day in hours and minutes until the strategy trades. It's in the EST/ NY Timezone and set to 09:45-14:45 by default.
because that's what gave the best results in backtesting. Open trades will get closed automatically once the end of the session is reached. No matter if win or loss. This is just to prevent holding positions over night.
Session Border This setting is to select the border color in which the session box will be plotted.
Opening Range Box This setting is to select the fill color of the opening range box.
Opening Range Border This setting is to select the border color of the session box.
Trade Timeframe This setting determines on which timeframe candle has to close outside the opening range box in order to take a trade. It's set to 15min by default because this is what worked by far the best in backtests and live trading.
Stop Loss Buffer in Points: This is simply the buffer in points that is added to the SL for safety reasons. If you have it on 0, the SL will be at the exact price of the opposite side of the range. By default it's set to 0 pips because this is what delivered the best results in backtests.
Profit Target Factor: This is simply the total SL size in points multiplied by x.
Example: If you put 2, you get a 1:2 Risk to Reward Ratio. By Default it's set to 4 because this gave the best results in backtests, because trades always get closed either by trailing SL or because the end of the session is reached.
Use Trailing Stop Loss: This setting is to enable/ disable the trailing stop loss. It's enabled by default because this is a fundamental part of the strategy.
Trailing Stop Buffer: This setting determines after how many points in profit the trailing SL will be activated.
Risk Type: You can chose either between Fixed USD Amount, Risk per Trade in % or Fixed Contract Size. By default it's set to fixed contract size.
Risk Amount (USD or Contracts): This setting is to set how many USD or how many contracts you want to risk per trade. Make sure to check which risk type you have selected before you chose the risk amount.
Use Limit Orders If enabled, the strategy will place a pending order x points from the current price, instead of a market order. Limit orders are enabled by default for a better performance. Important: It doesn't actually place a limit order. The strategy will just wait for a pullback and then enter with a market order. It's more like a hidden limit order.
Limit Order Distance (points): If you have limit orders enabled, this setting determines how many points from the current price the limit order will be placed.
Trading Days: These checkboxes are to select on which week days the strategy has to trade. Thursday is disabled by default because backtests have shown that Thursday is the least profitable day
Backtest Settings:
For the backtest the commissions ere set to 0.35 USD per mini contract which is the highest amount Tradeovate charges. Margin was not accounted for because typically on Apex accounts you can use way more contracts than you need for the extremely low max drawdown. Margin would be important on personal accounts but even there typically it's not an issue at all especially because this strategy runs on the 15min timeframe so it won't use a lot of contracts anyways.
What makes it unique:
This script is unique because it's designed to be used on Apex and Top Step accounts with extremely strict drawdown rules.
The strategy is optimised to be traded with a fixed contract size instead of using % risk. The reason for that is that the drawdown rules of these Futures Prop Accounts are very strict and the fact that the smallest trade-able contract size is 1.
Why the source code is hidden:
The source code is hidden because I invested a lot of time and money into developing this strategy and optimising it with paid 3rd party software. Also since I use it myself on my Apex accounts and prop firms don't allow copy trading I don't want it to be used by too many traders.
MultiLayer Awesome Oscillator Saucer Strategy [Skyrexio]Overview
MultiLayer Awesome Oscillator Saucer Strategy leverages the combination of Awesome Oscillator (AO), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Awesome Oscillator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Awesome Oscillator shall create the "Saucer" long signal (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created "Saucer signal".
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one "Saucer" signal another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's go through all concepts used in this strategy to understand how they works together. Let's start from the easies one, the EMA. Let's briefly explain what is EMA. The Exponential Moving Average (EMA) is a type of moving average that gives more weight to recent prices, making it more responsive to current price changes compared to the Simple Moving Average (SMA). It is commonly used in technical analysis to identify trends and generate buy or sell signals. It can be calculated with the following steps:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy uses EMA an initial long term trend filter. It allows to open long trades only if price close above EMA (by default 50 period). It increases the probability of taking long trades only in the direction of the trend.
Let's go to the next, short-term trend filter which consists of Alligator and Fractals. Let's briefly explain what do these indicators means. The Williams Alligator, developed by Bill Williams, is a technical indicator designed to spot trends and potential market reversals. It uses three smoothed moving averages, referred to as the jaw, teeth, and lips:
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 these lines diverge and are properly aligned, the "alligator" is considered "awake," signaling a strong trend. Conversely, when the lines overlap or intertwine, the "alligator" is "asleep," indicating a range-bound or sideways market. This indicator assists traders in identifying when to act on or avoid trades.
The Williams Fractals, another tool introduced by Bill Williams, are used to pinpoint potential reversal points on a price chart. A fractal forms when there are at least five consecutive bars, with the middle bar displaying the highest high (for an up fractal) or the lowest low (for a down fractal), relative to the two bars on either side.
Key Points:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often combine fractals with other indicators to confirm trends or reversals, improving the accuracy of trading decisions.
How we use their combination in this strategy? Let’s consider an uptrend example. A breakout above an up fractal can be interpreted as a bullish signal, indicating a high likelihood that an uptrend is beginning. Here's the reasoning: an up fractal represents a potential shift in market behavior. When the fractal forms, it reflects a pullback caused by traders selling, creating a temporary high. However, if the price manages to return to that fractal’s high and break through it, it suggests the market has "changed its mind" and a bullish trend is likely emerging.
The moment of the breakout marks the potential transition to an uptrend. It’s crucial to note that this breakout must occur above the Alligator's teeth line. If it happens below, the breakout isn’t valid, and the downtrend may still persist. The same logic applies inversely for down fractals in a downtrend scenario.
So, if last up fractal breakout was higher, than Alligator's teeth and it happened after last down fractal breakdown below teeth, algorithm considered current trend as an uptrend. During this uptrend long trades can be opened if signal was flashed. If during the uptrend price breaks down the down fractal below teeth line, strategy considered that uptrend is finished with the high probability and strategy closes all current long trades. This combination is used as a short term trend filter increasing the probability of opening profitable long trades in addition to EMA filter, described above.
Now let's talk about Awesome Oscillator's "Sauser" signals. Briefly explain what is the Awesome Oscillator. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
Now we know what is AO, but what is the "Saucer" signal? This concept was introduced by Bill Williams, let's briefly explain it and how it's used by this strategy. Initially, this type of signal is a combination of the following AO bars: we need 3 bars in a row, the first one shall be higher than the second, the third bar also shall be higher, than second. All three bars shall be above the zero line of AO. The price bar, which corresponds to third "saucer's" bar is our signal bar. Strategy places buy stop order one tick above the price bar which corresponds to signal bar.
After that we can have the following scenarios.
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower low. If current AO bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AO bar become decreasing. In the second case buy order cancelled and strategy wait for the next "Saucer" signal.
If long trades has been opened strategy use all the next signals until number of trades doesn't exceed 5. All trades are closed when the trend changes to downtrend according to combination of Alligator and Fractals described above.
Why we use "Saucer" signals? If AO above the zero line there is a high probability that price now is in uptrend if we take into account our two trend filters. When we see the decreasing bars on AO and it's above zero it's likely can be considered as a pullback on the uptrend. When we see the stop of AO decreasing and the first increasing bar has been printed there is a high probability that this local pull back is finished and strategy open long trade in the likely direction of a main trend.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next saucer signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.25. 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: 10%
Maximum Single Position Loss: -5.10%
Maximum Single Profit: +22.80%
Net Profit: +2838.58 USDT (+28.39%)
Total Trades: 107 (42.99% win rate)
Profit Factor: 3.364
Maximum Accumulated Loss: 373.43 USDT (-2.98%)
Average Profit per Trade: 26.53 USDT (+2.40%)
Average Trade Duration: 78 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 3h 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 Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
Adaptive Squeeze Momentum StrategyThe Adaptive Squeeze Momentum Strategy is a versatile trading algorithm designed to capitalize on periods of low volatility that often precede significant price movements. By integrating multiple technical indicators and customizable settings, this strategy aims to identify optimal entry and exit points for both long and short positions.
Key Features:
Long/Short Trade Control:
Toggle Options: Easily enable or disable long and short trades according to your trading preferences or market conditions.
Flexible Application: Adapt the strategy for bullish, bearish, or neutral market outlooks.
Squeeze Detection Mechanism:
Bollinger Bands and Keltner Channels: Utilizes the convergence of Bollinger Bands inside Keltner Channels to detect "squeeze" conditions, indicating a potential breakout.
Dynamic Squeeze Length: Calculates the average squeeze duration to adapt to changing market volatility.
Momentum Analysis:
Linear Regression: Applies linear regression to price changes over a specified momentum length to gauge the strength and direction of momentum.
Dynamic Thresholds: Sets momentum thresholds based on standard deviations, allowing for adaptive sensitivity to market movements.
Momentum Multiplier: Adjustable setting to fine-tune the aggressiveness of momentum detection.
Trend Filtering:
Exponential Moving Average (EMA): Implements a trend filter using an EMA to align trades with the prevailing market direction.
Customizable Length: Adjust the EMA length to suit different trading timeframes and assets.
Relative Strength Index (RSI) Filtering:
Overbought/Oversold Signals: Incorporates RSI to avoid entering trades during overextended market conditions.
Adjustable Levels: Set your own RSI oversold and overbought thresholds for personalized signal generation.
Advanced Risk Management:
ATR-Based Stop Loss and Take Profit:
Adaptive Levels: Uses the Average True Range (ATR) to set stop loss and take profit points that adjust to market volatility.
Custom Multipliers: Modify ATR multipliers for both stop loss and take profit to control risk and reward ratios.
Minimum Volatility Filter: Ensures trades are only taken when market volatility exceeds a user-defined minimum, avoiding periods of low activity.
Time-Based Exit:
Holding Period Multiplier: Defines a maximum holding period based on the momentum length to reduce exposure to adverse movements.
Automatic Position Closure: Closes positions after the specified holding period is reached.
Session Filtering:
Trading Session Control: Limits trading to predefined market hours, helping to avoid illiquid periods.
Custom Session Times: Set your preferred trading session to match market openings, closings, or specific timeframes.
Visualization Tools:
Indicator Plots: Displays Bollinger Bands, Keltner Channels, and trend EMA on the chart for visual analysis.
Squeeze Signals: Marks squeeze conditions on the chart, providing clear visual cues for potential trade setups.
Customization Options:
Indicator Parameters: Fine-tune lengths and multipliers for Bollinger Bands, Keltner Channels, momentum calculation, and ATR.
Entry Filters: Choose to use trend and RSI filters to refine trade entries based on your strategy.
Risk Management Settings: Adjust stop loss, take profit, and holding periods to match your risk tolerance.
Trade Direction Control: Enable or disable long and short trades independently to align with your market strategy or compliance requirements.
Time Settings: Modify the trading session times and enable or disable the time filter as needed.
Use Cases:
Trend Traders: Benefit from aligning entries with the broader market trend while capturing breakout movements.
Swing Traders: Exploit periods of low volatility leading to significant price swings.
Risk-Averse Traders: Utilize advanced risk management features to protect capital and manage exposure.
Disclaimer:
This strategy is a tool to assist in trading decisions and should be used in conjunction with other analyses and risk management practices. Past performance is not indicative of future results. Always test the strategy thoroughly and adjust settings to suit your specific trading style and market conditions.
Candle Range Theory [Advanced] - AlgoVisionUnderstanding Candle Range Theory (CRT) in the AlgoVision Indicator
Candle Range Theory (CRT) is a structured approach to analyzing market movements within the price ranges of candlesticks. CRT is founded on the idea that each candlestick on a chart, regardless of timeframe, represents a distinct range of price action, marked by the candle's open, high, low, and close. This range gives insights into market dynamics, and when analyzed in lower timeframes, reveals patterns that indicate underlying market sentiment and institutional behaviors.
Key Concepts of Candle Range Theory
Candlestick Range: The range of a candlestick is simply the distance between its high and low. Across timeframes, this range highlights significant price behavior, with each candlestick representing a snapshot of price movement. The body (distance between open and close) shows the primary price action, while wicks (shadows) reflect price fluctuations or "noise" around this movement.
Multi-Timeframe Analysis: A higher-timeframe (HTF) candlestick can be dissected into smaller, structured price movements in lower timeframes (LTFs). By analyzing these smaller movements, traders gain a detailed view of the market’s progression within the HTF candlestick’s range. Each HTF candlestick’s high and low provide support and resistance levels on the LTF, where the price can "sweep," break out, or retest these levels.
Market Behavior within the Range: Price action within a range doesn’t move randomly; it follows structured behavior, often revealing patterns. By analyzing these patterns, CRT provides insights into the market’s intention to accumulate, manipulate, or distribute assets within these ranges. This behavior can indicate future market direction and increase the probability of accurate trading signals.
CRT and ICT Power of 3: Accumulation, Manipulation, and Distribution (AMD)
A foundational element of our CRT indicator is its combination with ICT’s Power of 3 (Accumulation, Manipulation, and Distribution or AMD). This approach identifies three stages of market movement:
Accumulation: During this phase, institutions accumulate positions within a tight price range, often leading to sideways movement. Here, price consolidates as institutions carefully enter or exit positions, erasing traces of their intent from public view.
Manipulation: Institutions often use manipulation to create false breakouts, targeting retail traders who enter the market on perceived breakouts or reversals. Manipulation is characterized by liquidity grabs, false breakouts, or stop hunts, as price momentarily moves outside the established range before quickly returning.
Distribution: Following accumulation and manipulation, the distribution phase aligns with the true market direction. Institutions now allow the market to move with the trend, initiating a stronger and more sustained price movement that aligns with their intended position.
This AMD cycle is often observed across multiple timeframes, allowing traders to refine entries and exits by identifying accumulation, manipulation, and distribution phases on smaller timeframes within the range of a higher-timeframe candle. CRT views this cycle as the "heartbeat" of the market—a continuous loop of price movements. With our indicator, you can identify this cycle on your current timeframe, with the signal candle acting as the "manipulation" candle.
How to Use the Premium AlgoVision CRT Indicator
1. Indicator Display Options
Bullish/Bearish Plot Indication: Toggles the display of bullish or bearish CRT signals. Turn this on to display signals on your chart or off to reduce screen clutter.
Order Block Indication: Highlights the order block entry price, which is the preferred entry point for CRT trades.
Purge Time Indication: Shows when the low or high of Candle 1 is purged by Candle 2, helping to identify potential manipulation points.
2. Filter Options
Match Indicator Candle with Signal: Ensures that only bullish Candle 2s (for longs) or bearish Candle 2s (for shorts) are signaled. This filter helps eliminate signals where the candlestick’s direction does not align with the CRT model.
Take Profit Already Reached: When enabled, this filter removes CRT signals if take profit levels are reached within Candle 2. This helps focus on setups where there’s still room for price movement.
Midnight Price Filter: Filters signals based on midnight price levels:
Longs: Only signals if the order block entry price is below the midnight price.
Shorts: Only signals if the order block entry price is above the midnight price.
3. Entry and Exit Settings
Wick out prevention: Allows positions to stay open and prevent getting wicked out. Positions will still be able to close if determined by the algorithm.
Buy/Sell: This allows you to set you daily bias. You can select to only see buys or sells.
Custom Stop Loss: Sets a custom stop loss distance from the entry price (e.g., $100 or $200 away) if the predefined stop loss based on Candle 2’s low/high doesn’t suit your preference.
Take Profit Levels: Choose from three take profit levels:
Optimized Take Profit: Uses an optimized take profit level based on CRT’s recommended exit point.
Take Profit 1: Sets an initial take profit level.
Take Profit 2: Sets a secondary take profit level for a more extended exit target.
Timeframe of Order Block: Select the timeframe of the order block entry, which can be tailored based on the timeframe of the CRT signal.
Risk-to-Reward Filter: Filters trades based on a specified risk-to-reward ratio, using the indicator’s stop loss as the base. This helps to ensure trades meet minimum reward criteria.
4. Risk Management
Fixed Entry QTY: This will allow you to open all positions with a fixed QTY
Risk to Reward Ratio: This allows you to set a minimum risk to reward ratio, the strategy will only take trades if this risk to reward is met.
Risk Type:
Fixed Amount: Allows you to risk a fixed $ amount.
% of account: Allows you to risk % of account equity.
5. Day and Time Filters
Filter by Days: Specify the days of the week for CRT signals to appear. For instance, you could enable signals only on Thursdays. This setting can be adjusted to any day or combination of days.
Purge Time Filter: Filters CRT signals based on specific purge times when Candle 1’s low/high is breached by Candle 2, as CRT setups are observed to work best during certain times.
Hour Filters for CRT Signals:
1-Hour CRT Times: Allows filtering CRT signals based on specific 1-hour time intervals.
4-Hour CRT Times: Filter 4-hour CRT signals based on specified times.
Forex and Futures Conversion: Adjusts times based on standard sessions for Forex (e.g., 9:00 AM 4-hour candle) and Futures (e.g., 10 PM candle for Futures or 8 AM for Crypto).
6. Currency and Asset-Specific Filters
Crypto vs. Forex Mode: This setting adjusts the indicator’s timing to match market sessions specific to either crypto or Forex/Futures, ensuring the CRT model aligns with the asset type.
Additional Notes
Backtesting Options: Adjust these to test risk management, such as risking a fixed amount or a percentage of the account, for historical performance insights.
Optimized Settings: This version includes all features and optimized settings, with the most refined data analysis.
Conclusion By combining CRT with ICT Power of 3, the AlgoVision Indicator allows traders to leverage the CRT candlestick as a versatile tool for identifying potential market moves. This method provides beginners and seasoned traders alike with a robust framework to understand market dynamics and refine trade strategies across timeframes. Setting alerts on the higher timeframe to catch bullish or bearish CRT signals allows you to plan and execute trades on the lower timeframe, aligning your strategy with the broader market flow.
Keltner Channel Strategy by Kevin DaveyKeltner Channel Strategy Description
The Keltner Channel Strategy is a volatility-based trading approach that uses the Keltner Channel, a technical indicator derived from the Exponential Moving Average (EMA) and Average True Range (ATR). The strategy helps identify potential breakout or mean-reversion opportunities in the market by plotting upper and lower bands around a central EMA, with the channel width determined by a multiplier of the ATR.
Components:
1. Exponential Moving Average (EMA):
The EMA smooths price data by placing greater weight on recent prices, allowing traders to track the market’s underlying trend more effectively than a simple moving average (SMA). In this strategy, a 20-period EMA is used as the midline of the Keltner Channel.
2. Average True Range (ATR):
The ATR measures market volatility over a 14-period lookback. By calculating the average of the true ranges (the greatest of the current high minus the current low, the absolute value of the current high minus the previous close, or the absolute value of the current low minus the previous close), the ATR captures how much an asset typically moves over a given period.
3. Keltner Channel:
The upper and lower boundaries are set by adding or subtracting 1.5 times the ATR from the EMA. These boundaries create a dynamic range that adjusts with market volatility.
Trading Logic:
• Long Entry Condition: The strategy enters a long position when the closing price falls below the lower Keltner Channel, indicating a potential buying opportunity at a support level.
• Short Entry Condition: The strategy enters a short position when the closing price exceeds the upper Keltner Channel, signaling a potential selling opportunity at a resistance level.
The strategy plots the upper and lower Keltner Channels and the EMA on the chart, providing a visual representation of support and resistance levels based on market volatility.
Scientific Support for Volatility-Based Strategies:
The use of volatility-based indicators like the Keltner Channel is supported by numerous studies on price momentum and volatility trading. Research has shown that breakout strategies, particularly those leveraging volatility bands such as the Keltner Channel or Bollinger Bands, can be effective in capturing trends and reversals in both trending and mean-reverting markets  .
Who is Kevin Davey?
Kevin Davey is a highly respected algorithmic trader, author, and educator, known for his systematic approach to building and optimizing trading strategies. With over 25 years of experience in the markets, Davey has earned a reputation as an expert in quantitative and rule-based trading. He is particularly well-known for winning several World Cup Trading Championships, where he consistently demonstrated high returns with low risk.
Universal Trend Following Strategy | QuantumRsearchUniversal All Assets Strategy by Rocheur
The Universal All Assets Strategy is a cutting-edge, trend-following algorithm designed to operate seamlessly across multiple asset classes, including equities, commodities, forex, and cryptocurrencies. This strategy leverages the power of eight unique indicators, offering traders robust, adaptive signals. Its dynamic logic, combined with a comprehensive risk management framework, allows for precision trading in a variety of market conditions.
Core Methodologies and Features
1. Eight Integrated Trend Indicators
At the heart of the Universal All Assets Strategy are eight sophisticated trend-following indicators, each designed to capture different facets of market behavior. These indicators work together to provide a multi-dimensional analysis of price trends, filtering out noise and reacting only to significant movements:
Directional Moving Averages : Tracks the primary market trend, offering a clear indication of long-term price direction, ideal for identifying sustained upward or downward movements.
Smoothed Moving Averages : Reduces short-term volatility and noise to reveal the underlying trend, enhancing signal clarity and helping traders avoid reacting to temporary price spikes.
RSI Loops : Utilizes the Relative Strength Index (RSI) to assess market momentum, using a unique for loop mechanism to smooth out data and enhance precision.
Supertrend Filters : This indicator dynamically adjusts to market volatility, closely following price action to detect significant breakouts or reversals. The Supertrend is a core component for identifying shifts in trend direction with minimal lag.
RVI for Loop : The Relative Volatility Index (RVI) measures the strength of market volatility. It is optimized with a for loop mechanism, which smooths out the data and improves directional cues, especially in choppy or sideways markets.
Hull for Loop : The Hull Moving Average is designed to minimize lag while offering a smooth, responsive trend line. The for loop mechanism further enhances this by making the Hull even more sensitive to trend shifts, ensuring faster reaction to market movements without generating excessive noise.
These indicators evaluate market conditions independently, assigning a score of 1 for bullish trends and -1 for bearish trends. The average score across all eight indicators is calculated for each time frame (or bar), and this score determines whether the strategy should enter, exit, or remain neutral in a trade.
2. Scoring and Signal Confirmation
The strategy’s confirmation system ensures that trades are initiated only when there is strong alignment across multiple indicators:
A Long Position (Buy) is initiated when the majority of indicators generate a bullish signal, i.e., the average score exceeds a predefined upper threshold.
A Short Position or Exit is triggered when the average score falls below a lower threshold, signaling a bearish trend or neutral market.
By using a majority-rule confirmation system, the strategy filters out weak signals, reducing the chances of reacting to market noise or false positives. This ensures that only robust trends—those supported by multiple indicators—trigger trades.
Adaptive Logic for All Asset Classes
The Universal All Assets Strategy stands out for its ability to adapt dynamically across different asset classes. Whether it’s applied to highly volatile assets like cryptocurrencies or more stable instruments like equities, the strategy fine-tunes its behavior to match the asset’s volatility profile and price behavior.
Volatility Filters : The system incorporates volatility-sensitive filters, such as the Average True Range (ATR) and standard deviation metrics, which dynamically adjust its sensitivity based on market conditions. This ensures the strategy remains responsive to significant price movements while filtering out inconsequential fluctuations.
This adaptability makes the Universal All Assets Strategy effective across diverse markets, providing consistent performance whether the market is trending, range-bound, or experiencing high volatility.
Customization and Flexibility
1. Directional Bias
The strategy offers traders the flexibility to set a customizable directional bias, allowing it to focus on:
Long-only trades during bullish markets.
Short-only trades during bear markets.
Bi-directional trades for those looking to capitalize on both uptrends and downtrends.
This bias can be fine-tuned based on market conditions, trader preference, or risk tolerance, without compromising the integrity of the overall signal-generation process.
2. Volatility Sensitivity
Traders can adjust the strategy’s volatility sensitivity through customizable settings. By modifying how the system reacts to volatility, traders can make the strategy more aggressive in high-volatility environments or more conservative in quieter markets, depending on their individual trading style.
Visual Representation of Component Behavior
One of the unique features of the strategy is its real-time visual representation of the eight indicators through a component table displayed on the chart. This table provides a clear overview of the current status of each indicator:
A score of 1 indicates a bullish signal.
A score of -1 indicates a bearish signal.
The table is updated at each time frame (bar), showing how each indicator is contributing to the overall trend decision. This real-time feedback allows traders to monitor the exact composition of the strategy’s signal, helping them better understand market dynamics.
Oscillator Visualization for Trend Detection
To complement the component table, the strategy includes a trend oscillator displayed beneath the price chart, offering a visual summary of the overall market direction:
Green bars represent bullish trends when the majority of indicators signal an uptrend.
Red bars represent bearish trends or a neutral (cash) position when the majority of indicators detect a downtrend.
This oscillator allows traders to quickly assess the market’s overall direction at a glance, without needing to analyze each individual indicator, providing a clear and immediate visual of the market trend.
Backtested and Forward-Tested for Real-World Conditions
The Universal All Assets Strategy has been thoroughly tested under real-world trading conditions, incorporating key factors like:
Slippage : Set at 20 ticks to represent real market fluctuations.
Order Size : Calculated as 10% of equity, ensuring appropriate risk exposure for realistic capital management.
Commission : A fee of 0.05% has been factored in to account for trading costs.
These settings ensure that the strategy’s performance metrics—such as the Sortino Ratio , Sharpe Ratio , Omega Ratio , and Profit Factor —are reflective of actual trading environments. The rigorous backtesting and forward-testing processes ensure that the strategy produces realistic results, making it compatible with the markets it is written for and demonstrating how the system would behave in live conditions. It also includes robust risk management tools to minimize drawdowns and preserve capital, making it suitable for both professional and retail traders.
Anti-Fragile Design and Realistic Expectations
The Universal All Assets Strategy is engineered to be anti-fragile, thriving in volatile markets by adjusting to turbulence rather than being damaged by it. This is a crucial feature that ensures the strategy remains effective even during times of significant market instability.
Moreover, the strategy is transparent about realistic expectations, acknowledging that no system can guarantee a 100% win rate and that past performance is not indicative of future results. This transparency fosters trust and provides traders with a realistic framework for long-term success, making it an ideal choice for traders looking to navigate complex market conditions with confidence.
Acknowledgment of External Code
Special credit goes to bii_vg, whose invite-only code was used with permission in the development of the Universal All Assets Strategy. Their contributions have been instrumental in refining certain aspects of this strategy, ensuring its robustness and adaptability across various markets.
Conclusion
The Universal All Assets Strategy by Rocheur offers traders a powerful, adaptable tool for capturing trends across a wide range of asset classes. Its eight-indicator confirmation system, combined with customizable settings and real-time visual representations, provides a comprehensive solution for traders seeking precision, flexibility, and consistency. Whether used in high-volatility markets or more stable environments, the strategy’s dynamic adaptability, transparent logic, and robust testing make it an excellent choice for traders aiming to maximize performance while managing risk effectively.
Advanced Multi-Seasonality StrategyThe Multi-Seasonality Strategy is a trading system based on seasonal market patterns. Seasonality refers to recurring market trends driven by predictable calendar-based events. These patterns emerge due to economic cycles, corporate activities (e.g., earnings reports), and investor behavior around specific times of the year. Studies have shown that such effects can influence asset prices over defined periods, leading to opportunities for traders who exploit these patterns (Hirshleifer, 2001; Bouman & Jacobsen, 2002).
How the Strategy Works:
The strategy allows the user to define four distinct periods within a calendar year. For each period, the trader selects:
Entry Date (Month and Day): The date to enter the trade.
Holding Period: The number of trading days to remain in the trade after the entry.
Trade Direction: Whether to take a long or short position during that period.
The system is designed with flexibility, enabling the user to activate or deactivate each of the four periods. The idea is to take advantage of seasonal patterns, such as buying during historically strong periods and selling during weaker ones. A well-known example is the "Sell in May and Go Away" phenomenon, which suggests that stock returns are higher from November to April and weaker from May to October (Bouman & Jacobsen, 2002).
Seasonality in Financial Markets:
Seasonal effects have been documented across different asset classes and markets:
Equities: Stock markets tend to exhibit higher returns during certain months, such as the "January effect," where prices rise after year-end tax-loss selling (Haugen & Lakonishok, 1987).
Commodities: Agricultural commodities often follow seasonal planting and harvesting cycles, which impact supply and demand patterns (Fama & French, 1987).
Forex: Currency pairs may show strength or weakness during specific quarters based on macroeconomic factors, such as fiscal year-end flows or central bank policy decisions.
Scientific Basis:
Research shows that market anomalies like seasonality are linked to behavioral biases and institutional practices. For example, investors may respond to tax incentives at the end of the year, and companies may engage in window dressing (Haugen & Lakonishok, 1987). Additionally, macroeconomic factors, such as monetary policy shifts and holiday trading volumes, can also contribute to predictable seasonal trends (Bouman & Jacobsen, 2002).
Risks of Seasonal Trading:
While the strategy seeks to exploit predictable patterns, there are inherent risks:
Market Changes: Seasonal effects observed in the past may weaken or disappear as market conditions evolve. Increased algorithmic trading, globalization, and policy changes can reduce the reliability of historical patterns (Lo, 2004).
Overfitting: One of the risks in seasonal trading is overfitting the strategy to historical data. A pattern that worked in the past may not necessarily work in the future, especially if it was based on random chance or external factors that no longer apply (Sullivan, Timmermann, & White, 1999).
Liquidity and Volatility: Trading during specific periods may expose the trader to low liquidity, especially around holidays or earnings seasons, leading to slippage and larger-than-expected price swings.
Economic and Geopolitical Shocks: External events such as pandemics, wars, or political instability can disrupt seasonal patterns, leading to unexpected market behavior.
Conclusion:
The Multi-Seasonality Strategy capitalizes on the predictable nature of certain calendar-based patterns in financial markets. By entering and exiting trades based on well-established seasonal effects, traders can potentially capture short-term profits. However, caution is necessary, as market dynamics can change, and seasonal patterns are not guaranteed to persist. Rigorous backtesting, combined with risk management practices, is essential to successfully implementing this strategy.
References:
Bouman, S., & Jacobsen, B. (2002). The Halloween Indicator, "Sell in May and Go Away": Another Puzzle. American Economic Review, 92(5), 1618-1635.
Fama, E. F., & French, K. R. (1987). Commodity Futures Prices: Some Evidence on Forecast Power, Premiums, and the Theory of Storage. Journal of Business, 60(1), 55-73.
Haugen, R. A., & Lakonishok, J. (1987). The Incredible January Effect: The Stock Market's Unsolved Mystery. Dow Jones-Irwin.
Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. Journal of Finance, 56(4), 1533-1597.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Sullivan, R., Timmermann, A., & White, H. (1999). Data-Snooping, Technical Trading Rule Performance, and the Bootstrap. Journal of Finance, 54(5), 1647-1691.
This strategy harnesses the power of seasonality but requires careful consideration of the risks and potential changes in market behavior over time.
Neural Momentum StrategyThis strategy combines Exponential Moving Average (EMA) analysis with a multi-timeframe approach. It uses a neural scoring system to evaluate market momentum and generate precise trading signals. The strategy is implemented in Pine Script v5 and is designed for use on TradingView.
Key Components
The strategy utilizes short-term (10-period) and long-term (25-period) EMAs. It calculates the difference between these EMAs to assess trend direction and strength. A neural scoring system evaluates EMA crossovers (weight: 12 points), trend strength (weight: 10 points), and price acceleration (weight: 4 points). The system implements a score smoothing algorithm using a 10-period EMA.
Multi-timeframe Analysis
The strategy automatically selects a higher timeframe based on the current chart timeframe. It calculates scores for both the current and higher timeframes, then combines these scores using a weighted average. The higher timeframe factor ranges from 3 to 6, depending on the current timeframe.
Trading Logic
Entry occurs when the final combined score turns positive after a change. Exit happens when the final combined score turns negative after a change. The strategy recalculates scores on each bar, ensuring responsive trading decisions.
Risk Management
An optional adaptive stop-loss system based on Average True Range (ATR) is available. The default ATR period is 10, and the stop factor is 1.2. Stop levels are dynamically adjusted on the higher timeframe.
Customization Options
Users can adjust EMA periods, signal line period, scoring weights, and enable/disable multi-timeframe analysis. The strategy allows setting specific date ranges for backtesting and deployment.
Position Sizing
The strategy uses a percentage-of-equity position sizing method, with a default of 30% of account equity per trade.
Code Structure
The strategy is built using TradingView's strategy framework. It employs efficient use of the request.security() function for multi-timeframe analysis. The main calculation function, calculate_score(), computes the neural score based on EMA differences and acceleration.
Performance Considerations
The strategy adapts to various market conditions through its multi-faceted scoring system. Multi-timeframe analysis helps filter out noise and identify stronger trends. The neural scoring approach aims to capture subtle market dynamics often missed by traditional indicators.
Limitations
Performance may vary across different markets and timeframes. The strategy's effectiveness relies on proper calibration of its numerous parameters. Users should thoroughly backtest and forward test before live implementation.
To summarize, the Neural Momentum Strategy represents a sophisticated approach to market analysis. It combines traditional technical indicators with advanced scoring techniques and multi-timeframe analysis. This strategy is designed for traders seeking a data-driven and adaptive method. It aims to identify high-probability trading opportunities across various market conditions.
This Neural Momentum Strategy is for informational and educational purposes only. It should not be considered financial advice. The strategy may exhibit slight repainting behavior due to the nature of multi-timeframe analysis and the use of the request.security() function. Historical values might change as new data becomes available.
Trading carries a high level of risk, and may not be suitable for all investors. Before deciding to trade, you should carefully consider your investment objectives, level of experience, and risk appetite. The possibility exists that you could sustain a loss of some or all of your initial investment. Therefore, you should not invest money that you cannot afford to lose.
Past performance is not indicative of future results. The author and TradingView are not responsible for any losses incurred as a result of using this strategy. Always exercise caution when using this or any trading strategy, and thoroughly test it before implementing in live trading scenarios.
Users are solely responsible for any trading decisions they make based on this strategy. It is strongly recommended that you seek advice from an independent financial advisor if you have any doubts.
Larry Connors RSI 3 StrategyThe Larry Connors RSI 3 Strategy is a short-term mean-reversion trading strategy. It combines a moving average filter and a modified version of the Relative Strength Index (RSI) to identify potential buying opportunities in an uptrend. The strategy assumes that a short-term pullback within a long-term uptrend is an opportunity to buy at a discount before the trend resumes.
Components of the Strategy:
200-Day Simple Moving Average (SMA): The price must be above the 200-day SMA, indicating a long-term uptrend.
2-Period RSI: This is a very short-term RSI, used to measure the speed and magnitude of recent price changes. The standard RSI is typically calculated over 14 periods, but Connors uses just 2 periods to capture extreme overbought and oversold conditions.
Three-Day RSI Drop: The RSI must decline for three consecutive days, with the first drop occurring from an RSI reading above 60.
RSI Below 10: After the three-day drop, the RSI must reach a level below 10, indicating a highly oversold condition.
Buy Condition: All the above conditions must be satisfied to trigger a buy order.
Sell Condition: The strategy closes the position when the RSI rises above 70, signaling that the asset is overbought.
Who Was Larry Connors?
Larry Connors is a trader, author, and founder of Connors Research, a firm specializing in quantitative trading research. He is best known for developing strategies that focus on short-term market movements. Connors co-authored several popular books, including "Street Smarts: High Probability Short-Term Trading Strategies" with Linda Raschke, which has become a staple among traders seeking reliable, rule-based strategies. His research often emphasizes simplicity and robust testing, which appeals to both retail and institutional traders.
Scientific Foundations
The Relative Strength Index (RSI), originally developed by J. Welles Wilder in 1978, is a momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100 and is typically used to identify overbought or oversold conditions in an asset. However, the use of a 2-period RSI in Connors' strategy is unconventional, as most traders rely on longer periods, such as 14. Connors' research showed that using a shorter period like 2 can better capture short-term reversals, particularly when combined with a longer-term trend filter such as the 200-day SMA.
Connors' strategies, including this one, are built on empirical research using historical data. For example, in a study of over 1,000 signals generated by this strategy, Connors found that it performed consistently well across various markets, especially when trading ETFs and large-cap stocks (Connors & Alvarez, 2009).
Risks and Considerations
While the Larry Connors RSI 3 Strategy is backed by empirical research, it is not without risks:
Mean-Reversion Assumption: The strategy is based on the premise that markets revert to the mean. However, in strong trending markets, the strategy may underperform as prices can remain oversold or overbought for extended periods.
Short-Term Nature: The strategy focuses on very short-term movements, which can result in frequent trading. High trading frequency can lead to increased transaction costs, which may erode profits.
Market Conditions: The strategy performs best in certain market environments, particularly in stable uptrends. In highly volatile or strongly trending markets, the strategy's performance can deteriorate.
Data and Backtesting Limitations: While backtests may show positive results, they rely on historical data and do not account for future market conditions, slippage, or liquidity issues.
Scientific literature suggests that while technical analysis strategies like this can be effective in certain market conditions, they are not foolproof. According to Lo et al. (2000), technical strategies may show patterns that are statistically significant, but these patterns often diminish once they are widely adopted by traders.
References
Connors, L., & Alvarez, C. (2009). Short-Term Trading Strategies That Work. TradingMarkets Publishing Group.
Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705-1770.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research
Vix Trading System (VTS)Introduction
The Vix Trading System (VTS) is an algorithm designed specifically for trading the VIX index CFD. The system combines price action and trend analysis to identify optimal entry and exit points for trades. The system is designed to maintain a single position at any given time, ensuring focused and controlled trading activity.
The VIX
The VIX, also known as the "Fear Index," is a popular measure of market volatility. It reflects the market's expectations for volatility over the coming 30 days and is often used as a gauge of investor sentiment. The VIX index is not directly tradable, but there are various financial vehicles, such as VIX futures, options, and CFDs, that allow traders to capitalise on its movements. This strategy is designed to trade the VIX index CFD, a derivative product available through brokers like Capital (used in this backtest). CFDs allow traders to speculate on the price movements of the VIX without owning the underlying asset, offering the potential for profit in both rising and falling markets. The VTS is tailored to leverage the unique characteristics of the VIX, providing traders with a structured approach to navigating the often volatile and unpredictable nature of this index.
Design
The Vix Trading System employs a balanced approach with six long strategies and one short strategy. The long strategies are designed to capitalise on price action patterns that indicate potential price increases, while the short strategy focuses on patterns where the VIX is likely to decline.
While I cannot give you the exact patterns I used to protect my IP, I can give you an example of a price pattern.
Long Entry: close > close and high < low and close >= sma200
These price patterns occur regularly to be traded but not too often to prevent overtrading. By using the price patterns to gauge price action, while using the moving averages to gauge the trend, the system is able to find entry and exit conditions for trading. This blend of price action and trend analysis ensures that the system is robust and adaptable, capable of responding to both short-term fluctuations and longer-term trends in the VIX.
How to Use It
The Vix Trading System is designed with notifications coded into all orders. Traders should set up alerts to notify them of long and short entries, as well as for take profit and stop loss orders for risk management and control. Since the strategy only holds one position at a time, traders can enter trades as soon as an alert is received. This system allows for efficient and timely execution, reducing the need for constant market monitoring.
Backtest
The backtest results for the Vix Trading System provide a valuable guide but should not be taken as a guarantee of future performance. To ensure realistic expectations, a starting capital of $200 was used, which produced a net profit of $18,000 over twelve years. The backtest included a commission of 1.05% of the order size and slippage of 3 ticks to model transaction costs. While these results are encouraging, traders should be aware that real-world trading conditions may differ, and ongoing risk management is essential.
