Dual EMA Indicator Smart Crossing Trading System with Dynamic Stop Loss and Take Profit Strategy

Pine ScriptTrend following Volatility Tools & templates EMA ATR ADX / DMI

Author: ChaoZhang
Complexity: Starter · 59 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 an intelligent trading system based on dual moving average crossovers, utilizing 9-period and 21-period Exponential Moving Averages (EMA) as core indicators. The strategy incorporates a dynamic stop-loss and take-profit mechanism, automatically executing trading orders by monitoring EMA crossover signals in real-time. The system employs percentage-based trailing stops and fixed-ratio take-profit levels, ensuring both trading safety and profit potential.

Strategy Principles

The core logic operates on the crossover relationship between the fast EMA (9-period) and slow EMA (21-period). When the fast line crosses above the slow line, the system recognizes a bullish signal, automatically closes any short positions and opens long positions. When the fast line crosses below the slow line, the system identifies a bearish signal, closes any long positions and opens short positions. Additionally, the system implements dynamic stop-loss and take-profit mechanisms: for long positions, the stop-loss is set 5% below the entry price and take-profit 10% above; for short positions, the stop-loss is set 5% above the entry price and take-profit 10% below.

Strategy Advantages

Scientific indicator selection: EMA responds more sensitively to market changes, effectively capturing market trends
Comprehensive stop-loss and take-profit mechanism: Percentage-based settings allow flexible adjustment to different market conditions
High degree of automation: Fully automated from signal detection to trade execution, minimizing human intervention
Effective risk control: Clear stop-loss and take-profit levels for each trade
Clear code structure: Standardized variable naming and logical hierarchy, facilitating maintenance and optimization

Strategy Risks

Sideways market risk: Frequent crossover signals may occur in ranging markets, leading to excessive trading
Slippage risk: Potential discrepancies between theoretical and actual execution prices during high volatility
Money management risk: Fixed-ratio position sizing may lack flexibility in certain market conditions
Systemic risk: Stop-loss or take-profit orders may not execute timely in extreme market conditions

Optimization Directions

Implement trend filters: Add ADX or ATR indicators to assess trend strength and avoid frequent trading in ranging markets
Optimize stop-loss and take-profit mechanisms: Consider using ATR for dynamic adjustment of stop-loss and take-profit distances
Add time filters: Implement specific trading time restrictions to avoid highly volatile periods
Improve position sizing: Dynamically adjust position sizes based on market volatility
Add market sentiment indicators: Incorporate RSI or MACD for trade confirmation

Summary

This strategy represents a complete and logically sound automated trading system. Through EMA crossover signals combined with dynamic stop-loss and take-profit mechanisms, it can perform well in trending markets. However, users need to monitor market conditions, adjust parameters accordingly, and maintain proper risk control. Through continuous optimization and refinement, this strategy has the potential to become a stable and reliable trading tool.

Source Pine Script

/*backtest
start: 2019-12-23 08:00:00
end: 2024-11-28 00:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("EMA Cross Strategy", overlay=true, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=100)

// Add strategy parameter settings
var showLabels = input.bool(true, "Show Labels")
var stopLossPercent = input.float(5.0, "Stop Loss Percentage", minval=0.1, maxval=20.0, step=0.1)
var takeProfitPercent = input.float(10.0, "Take profit percentage", minval=0.1, maxval=50.0, step=0.1)

// CalculationEMA
ema9 = ta.ema(close, 9)
ema21 = ta.ema(close, 21)

// DrawEMALine
plot(ema9, "EMA9", color=color.blue, linewidth=2)
plot(ema21, "EMA21", color=color.red, linewidth=2)

// Detect Cross
crossOver = ta.crossover(ema9, ema21)  
crossUnder = ta.crossunder(ema9, ema21)

// Format time display (UTC+8)
utc8Time = time + 8 * 60 * 60 * 1000
timeStr = str.format("{0,date,MM-dd HH:mm}", utc8Time)

// Calculate stop loss and take profit prices
longStopLoss = strategy.position_avg_price * (1 - stopLossPercent / 100)
longTakeProfit = strategy.position_avg_price * (1 + takeProfitPercent / 100)
shortStopLoss = strategy.position_avg_price * (1 + stopLossPercent / 100)
shortTakeProfit = strategy.position_avg_price * (1 - takeProfitPercent / 100)

// Transaction logic
if crossOver
    if strategy.position_size < 0  // If holding a short position
        strategy.close("go short")     // Close Short Position First
    strategy.entry("go long", strategy.long)  // Open long position
    if showLabels
        label.new(bar_index, high, text="Long Entry\n" + timeStr, color=color.green, textcolor=color.white, style=label.style_label_down, yloc=yloc.abovebar)

if crossUnder
    if strategy.position_size > 0  // If holding a long position
        strategy.close("go long")     // Close Long Position First
    strategy.entry("go short", strategy.short)  // Open short position
    if showLabels
        label.new(bar_index, low, text="Short Entry\n" + timeStr, color=color.red, textcolor=color.white, style=label.style_label_up, yloc=yloc.belowbar)

// Set stop loss and take profit
if strategy.position_size > 0  // Stop loss and take profit for long position
    strategy.exit("Stop loss and take profit for long position", "go long", stop=longStopLoss, limit=longTakeProfit)
    
if strategy.position_size < 0  // Stop loss and take profit for a short position
    strategy.exit("Stop loss and take profit for a short position", "go short", stop=shortStopLoss, limit=shortTakeProfit)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-11-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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