Trend Following Strategy Based on Dynamic Stop Loss of Dual EMA Crossover

This strategy utilizes the golden cross and dead cross of EMA lines for dual-directional trend following, and sets up dynamic stop loss lines for long and short positions to capture trending moves in the market.

Pine ScriptTrend following Machine learning Tools & templates MACD EMA ATR VWAP

Author: ChaoZhang
Complexity: Starter · 77 lines
Parameters: 5
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

Calculate fast EMA line (5-day) and slow EMA line (20-day)
Go long when fast line crosses above slow line from below; Go short when fast line crosses below slow line from above
After long entry, set dynamic stop loss at entry price * (1 - long stop loss percentage); After short entry, set dynamic stop loss at entry price * (1 + short stop loss percentage)
Exit position with stop loss once price hits the stop loss level

Advantage Analysis

EMA lines have stronger capabilities in tracking trends. Dual-crossover works as a timing tool to effectively catch trend opportunities
Dynamic stop loss moves along with profit, maximizing trend catching profit
Additional filter with vwap avoids being trapped in whipsaws and improves signal quality

Risk Analysis

As a pure trend following strategy, it's vulnerable to ranging markets with whipsaws
Overly loose stop loss may lead to magnified losses
Lagging nature of EMA crossover signals may miss best entry points

Enhancements like ATR-based risk management, optimizing stop loss rules, adding filter indicators etc. can help improve the strategy.

Enhancement Directions

Incorporate dynamic stop loss indicators like ATR or DONCH to set better adaptive stops
Add more filter indicators like MACD, KDJ to avoid bad trades
Optimize parameters to find best EMA lengths combination
Utilize machine learning methods to discover optimal parameters

Conclusion

In conclusion, this is a very typical trend following strategy. Dual EMA crossover with dynamic stop loss can effectively lock in trend profits. Meanwhile the risks like lagging signals and overwide stops still exist. Through parameter tuning, risk management, filter additions etc., further refinement can lead to better results.

Parameters

Name	Default	What it controls
v_input_1	5	Short EMA Length
v_input_2	20	Long EMA Length
v_input_3	true	Price EMA Length
v_input_float_1	0.05	Long Stop Loss (%)
v_input_float_2	0.05	Short Stop Loss (%)

Source Pine Script

/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5

strategy("EMA Crossover Strategy", shorttitle="EMAC", overlay=true,calc_on_every_tick=true)

// Input parameters
shortEmaLength = input(5, title="Short EMA Length")
longEmaLength = input(20, title="Long EMA Length")
priceEmaLength = input(1, title="Price EMA Length")

// Set stop loss level with input options (optional)
longLossPerc = input.float(0.05, title="Long Stop Loss (%)",
     minval=0.0, step=0.1) * 0.01

shortLossPerc = input.float(0.05, title="Short Stop Loss (%)",
     minval=0.0, step=0.1) * 0.01

// Calculating indicators
shortEma = ta.ema(close, shortEmaLength)
longEma = ta.ema(close, longEmaLength)
//priceEma = ta.ema(close, priceEmaLength)
vwap = ta.vwap(close)

// Long entry conditions
longCondition = ta.crossover(shortEma, longEma) and close > vwap
// Short entry conditions
shortCondition = ta.crossunder(shortEma, longEma) and close > vwap

// STEP 2:
// Determine stop loss price
longStopPrice  = strategy.position_avg_price * (1 - longLossPerc)
shortStopPrice = strategy.position_avg_price * (1 + shortLossPerc)


if (longCondition)
    strategy.entry("Enter Long", strategy.long)
    strategy.exit("Exit Long",from_entry = "Enter Long",stop= longStopPrice)
plotshape(series=longCondition, title="Long Signal", color=color.green, style=shape.triangleup, location=location.belowbar)


if (shortCondition)
    strategy.entry("Enter Short", strategy.short)
    strategy.exit("Exit Short", from_entry = "Enter Short",stop = shortStopPrice)
plotshape(series=shortCondition, title="Short Signal", color=color.red, style=shape.triangledown, location=location.abovebar)

// Stop loss levels
//longStopLoss = (1 - stopLossPercent) * close
//shortStopLoss = (1 + stopLossPercent) * close

// Exit conditions
//strategy.exit("Long", from_entry="Long", loss=longStopLoss)
//strategy.exit("Short", from_entry="Short", loss=shortStopLoss)

// Plotting indicators on the chart
plot(shortEma, color=color.yellow, title="Short EMA")
plot(longEma, color=color.green, title="Long EMA")
plot(close, color=color.black, title="Close")
plot(vwap, color=color.purple, title="VWAP")

// Plot stop loss values for confirmation
plot(strategy.position_size > 0 ? longStopPrice : na,
     color=color.red, style=plot.style_line,
     linewidth=2, title="Long Stop Loss")

plot(strategy.position_size < 0 ? shortStopPrice : na,
     color=color.blue, style=plot.style_line,
     linewidth=2, title="Short Stop Loss")
// Plotting stop loss lines
//plot(longStopLoss, color=color.red, title="Long Stop Loss", linewidth=2, style=plot.style_line)
//plot(shortStopLoss, color=color.aqua, title="Short Stop Loss", linewidth=2, style=plot.style_line)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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