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Qullamaggie Breakout V2 Strategy

Cryptocurrency
Created: 2023-10-24 16:30:32
Last modified: 3 years ago
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Overview

This strategy combines the advantages of breakout and trend-following trailing stop strategies to capture support/resistance breakout signals on longer timeframes while using moving averages for stop loss trailing in order to profit in the direction of the longer term trend while controlling risk.

Strategy Logic

  1. The strategy first calculates multiple moving averages with different parameters for trend determination, support/resistance and trailing stop loss.

  2. It then identifies the highest high and lowest low points within a specified period as the support/resistance breakout zones. Buy and sell signals are generated when price breaks these levels.

  3. The strategy buys when price breaks above the highest high and sells when price breaks below the lowest low.

  4. After entry, the lowest low is used as the initial stop loss for the position.

  5. Once the position becomes profitable, the stop loss switches to trailing the moving average. When price breaks below the moving average, the stop is set to the low of that candlestick.

  6. This allows the position to lock in profits while giving it enough room to follow the trend.

  7. The strategy also incorporates average true range for filtering to ensure only proper range breakouts are taken to avoid extended breakouts.

Advantage Analysis

  1. Combines the advantages of breakout and trailing stop strategies.

  2. Can buy breakouts according to longer term trends for higher probability.

  3. Trailing stop strategy protects position while allowing enough space to run.

  4. ATR filtering avoids unfavorable extended breakouts.

  5. Automated trading suitable for part time following.

  6. Customizable moving average parameters.

  7. Flexible trailing stop mechanisms.

Risk Analysis

  1. Breakout strategies prone to false breakout risks. Wider breakout confirmation may help.

  2. Sufficent volatility needed to generate signals, may fail in choppy markets.

  3. Some breakouts may be too short-lived to capture. Lower timeframes may uncover more opportunities.

  4. Trailing stops can be stopped out too frequently in ranging markets. Wider stops may help.

  5. ATR filtering may miss some potential trades. Lower filter settings can help.

Optimization Directions

  1. Test different moving average combinations for optimal parameters.

  2. Explore different breakout confirmations like channels, candlestick patterns etc.

  3. Try different trailing stop mechanisms to find best stop loss.

  4. Optimize money management strategies like position score.

  5. Add technical indicator filters to improve quality of signals.

  6. Test effectiveness across different products.

  7. Incorporate machine learning algorithms to boost strategy performance.

Conclusion

This strategy combines the philosophies of breakout and trend-following trailing stop strategies. With proper trend determination, it optimizes profit potential while maintaining controlled risk. The keys are finding the optimal parameter sets and incorporating prudent money management. Further enhancements may turn this into a robust trend following methodology.

Source
Pine
/*backtest
start: 2022-10-17 00:00:00
end: 2023-10-23 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © millerrh

// The intent of this strategy is to buy breakouts with a tight stop on smaller timeframes in the direction of the longer term trend.
Strategy parameters
Strategy parameters
backtest window and pivot history
Backtest Start Date
Backtest End Date
Show Historical Pivot Points?
moving averages
Timeframe of Moving Averages
Moving Average Type
1st Moving Average Length
2nd Moving Average Length
3rd Moving Average Length
Use 3rd Moving Average for Filtering?
stops
Trailing Stop
Trailing Stop Timeframe
Current Range S/R Colors:    Support
 Resistance
adr filtering
Use ADR for Filtering?
% of ADR Value
ADR Table Visibility
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