Dynamic Moving Average Crossover Trend Following Strategy with Adaptive Risk Management

Pine ScriptTrend following Mean reversion Volatility SMA

Author: ChaoZhang
Complexity: Intermediate · 105 lines
Parameters: 0
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is a trend-following system based on dual moving average crossover signals, incorporating a dynamic take-profit and stop-loss mechanism. It utilizes 5-period and 12-period Simple Moving Averages (SMA) to generate trading signals, optimizing risk-reward ratio through dynamic adjustment of take-profit and stop-loss levels. Initial take-profit is set at 10% and stop-loss at 5%, with levels adjusting to 20% and 2.5% respectively when price moves favorably.

Strategy Principles

The core logic relies on the crossover relationship between fast (5-period) and slow (12-period) moving averages. A buy signal is generated when the fast MA crosses above the slow MA, while positions are closed when the fast MA crosses below the slow MA. The strategy's uniqueness lies in its dynamic risk management mechanism: after position entry, the system continuously monitors price movement and dynamically adjusts take-profit and stop-loss levels to maximize profits while controlling risk.

Strategy Advantages

Employs classic dual MA crossover strategy with clear signals, easy to understand and execute
Dynamic take-profit/stop-loss mechanism effectively protects realized profits and prevents drawdowns
Strategy parameters can be flexibly adjusted for different market characteristics
Comprehensive risk management mechanism effectively controls single-trade risk
Clear code structure facilitates maintenance and optimization

Strategy Risks

May generate false signals in ranging markets, leading to frequent trading
Potential significant drawdowns in quick reversal scenarios
Improper parameter settings may affect strategy performance
Market liquidity issues may impact stop-loss execution Risk management recommendations:

Add trend filters
Optimize parameter selection
Monitor market liquidity in real-time
Establish comprehensive money management system

Optimization Directions

Introduce trend strength indicators to filter ranging market signals
Consider incorporating volume factors to improve signal reliability
Optimize take-profit/stop-loss parameters to enhance risk-reward ratio
Add market volatility adaptation mechanism
Improve position sizing system

Summary

This strategy effectively captures trends and dynamically controls risk by combining classic moving average crossover signals with innovative dynamic risk management. The strategy design is clear, implementation is efficient, and it demonstrates good practicality and scalability. Through continuous optimization and improvement, this strategy shows promise for achieving stable returns in actual trading.

Source Pine Script

/*backtest
start: 2019-12-23 08:00:00
end: 2024-12-25 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=6
strategy("My Moving Average Crossover Strategy with Take Profit and Stop Loss", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100)
//risk_free_rate = float(request.security("IRUS", "D", close)/request.security("IRUS", "D", close[1]) - 1  ))




// MA periods
fastLength = input.int(5, title="Fast MA Length")
slowLength = input.int(12, title="Slow MA Length")




// Take Profit and Stop Loss
takeProfitLevel = input(10, title="Take Profit (пункты)") // Take profit % from the last price
stopLossLevel = input(5, title="Stop Loss (пункты)") // Stop loss  % from the last price
takeProfitLevel_dyn = input(20, title="Dynamic Take Profit (пункты)") // Move TP if current_price higher buy_px
stopLossLevel_dyn =  input(2.5, title="Dynamic Stop Loss (пункты)") // S Move SL if current_price higher buy_px


// Вычисление скользящих средних
fastMA = ta.sma(close, fastLength)
slowMA= ta.sma(close, slowLength)


// Conditions for Sell and Buy
longCondition = ta.crossover (fastMA, slowMA) // покупаем, если короткая MA персекает длинную снизу-вверх
shortCondition = ta.crossunder(fastMA, slowMA) // продаем, если короткая MA персекает длинную сверху-вниз




// Buy position condition
if (longCondition)
    strategy.entry("Buy", strategy.long)






// Dynamic TP SL leveles
takeProfitPrice = strategy.position_avg_price * (1+ takeProfitLevel / 100)
stopLossPrice = strategy.position_avg_price * (1-stopLossLevel / 100)


entryPrice = strategy.position_avg_price




if (strategy.position_size > 0) // если есть открытая позиция




    // takeProfitPrice := entryPrice * (1+ takeProfitLevel / 100)
    // stopLossPrice := entryPrice * (1-stopLossLevel / 100)


    // // Перемещение Stop Loss и Take Profit
    if (close > entryPrice)
   
        takeProfitPrice := close * (1+ takeProfitLevel_dyn / 100)
        stopLossPrice := close * (1- stopLossLevel_dyn/ 100)






if (shortCondition)
    strategy.close("Buy")




strategy.exit("Take Profit/Stop loss", "Buy", limit=takeProfitPrice, stop=stopLossPrice)


// Drawing MA lines
plot(fastMA, color=color.blue, title="Fast Moving Average")
plot(slowMA, color=color.orange, title="Slow Moving Average")




// Визуализация
plot(longCondition ? na : takeProfitPrice, title="Take Profit Level", color=color.green, linewidth=1, style=plot.style_line)
plot(longCondition ? na: stopLossPrice, title="Stop Loss Level", color=color.red, linewidth=1, style=plot.style_line)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-12-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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