Moving Average Crossover Gold Strategy

This strategy is a simple moving average crossover strategy. It goes long when the fast EMA crosses above the slow EMA and goes short when the fast EMA crosses below the slow EMA. The strategy incorporates stop loss…

Pine ScriptTrend following Machine learning Mean reversion EMA SMA

Author: ChaoZhang
Complexity: Starter · 53 lines
Parameters: 5
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy is based on fast and slow moving averages. The fast line is 9-day EMA and the slow line is 21-day EMA. It goes long when the fast line crosses above the slow line from below. It goes short when the fast line crosses below the slow line from above. Exits are triggered by reverse crosses.

Stop loss is set based on a percentage of close. Take profit is set based on a percentage of close. Break-even stop loss moves to entry price when price reaches break-even level.

Advantage Analysis

The advantages of this strategy are:

Simple and clear logic, easy to understand and implement
Utilizes trend following ability of moving averages, catching trends effectively
Incorporates stop loss, take profit and break-even to control risks
Flexible parameter adjustment, optimizable for different markets

Risk Analysis

There are some risks:

Lagging issue of moving averages, potentially missing reversal signals
Improper stop loss or take profit setting may cause unnecessary loss or profit loss
Improper parameter setting may lead to over-trading or missing trades

Solutions:

Optimize parameters and set moving averages properly
Adjust stop loss/take profit percentage, ensure reasonable setting
Adjust parameters for different markets to avoid over-trading

Optimization Directions

The strategy can be optimized by:

Testing different length combinations of moving averages
Adjusting percentages of stop loss, take profit and break-even for different market volatility
Adding other technical indicators for filtering entry signals
Dynamically optimizing parameters with statistical techniques or machine learning

Summary

Overall, this moving average crossover gold strategy has clear logic and is easy to implement. With stop loss, take profit and break-even, it controls risks. With proper parameter tuning and optimization for different markets, it can achieve good performance. But the risks of whipsaws and difficulty of parameter optimization need to be noted.

Parameters

Name	Default	What it controls
v_input_1	9	Fast EMA Length
v_input_2	21	Slow EMA Length
v_input_3	true	Stop Loss (%)
v_input_4	2	Take Profit (%)
v_input_5	true	Break Even (%)

Source Pine Script

/*backtest
start: 2022-12-20 00:00:00
end: 2023-12-26 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("XAUUSD Strategy with SL, TP, and BE", shorttitle="EA", overlay=true)

// Define strategy parameters
fastLength = input(9, title="Fast EMA Length")
slowLength = input(21, title="Slow EMA Length")
stopLossPercent = input(1, title="Stop Loss (%)", minval=0, maxval=5) / 100
takeProfitPercent = input(2, title="Take Profit (%)", minval=0, maxval=5) / 100
breakEvenPercent = input(1, title="Break Even (%)", minval=0, maxval=5) / 100

// Calculate EMAs
fastEMA = ema(close, fastLength)
slowEMA = ema(close, slowLength)

// Plot EMAs on the chart
plot(fastEMA, color=color.blue, title="Fast EMA")
plot(slowEMA, color=color.red, title="Slow EMA")

// Strategy logic
enterLong = crossover(fastEMA, slowEMA)
exitLong = crossunder(fastEMA, slowEMA)

enterShort = crossunder(fastEMA, slowEMA)
exitShort = crossover(fastEMA, slowEMA)

// Calculate stop loss, take profit, and break-even levels
longStopLoss = close * (1 - stopLossPercent)
longTakeProfit = close * (1 + takeProfitPercent)
shortStopLoss = close * (1 + stopLossPercent)
shortTakeProfit = close * (1 - takeProfitPercent)

longBreakEven = close * (1 + breakEvenPercent)
shortBreakEven = close * (1 - breakEvenPercent)

// Execute strategy with stop loss, take profit, and break-even
strategy.entry("Long", strategy.long, when = enterLong)
strategy.exit("Take Profit/Stop Loss Long", from_entry="Long", profit = longTakeProfit, loss = longStopLoss)

strategy.entry("Short", strategy.short, when = enterShort)
strategy.exit("Take Profit/Stop Loss Short", from_entry="Short", profit = shortTakeProfit, loss = shortStopLoss)

// Move stop loss to break even when price reaches break-even level
strategy.exit("Break Even Long", from_entry="Long", loss = longBreakEven)
strategy.exit("Break Even Short", from_entry="Short", loss = shortBreakEven)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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