MACD Moving Average Crossover Trend Following Strategy with Trailing Stop Loss

Pine ScriptTrend following Momentum Volatility MACD EMA SMA ATR

Author: ChaoZhang
Complexity: Intermediate · 116 lines
Parameters: 19
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy uses MACD to determine the trend direction, combined with EMA and SMA crossover as confirmation. The entry signal is when MACD histogram crosses above signal line and the trend is up. The stop loss is set at the price level below the floating ATR trailing stop. The strategy also exits partially to take profit, exits more on larger price surge, and holds some position with trailing stop until stop loss is hit.

Logic

Entry Signal

When faster EMA crosses above slower EMA, it indicates the short term trend is better than long term trend, signaling a buy. Meanwhile, faster SMA crossing above slower SMA also suggests stronger upside momentum in short term. So the combination of MACD line crossing above signal and uptrend based on EMA&SMA crossover helps identify stronger entry signals.

Stop Loss

ATR is used to calculate the stop loss level. ATR can effectively measure the price fluctuation range. When price breaks below this range, the stop loss is triggered. The ATR period can be adjusted - smaller period allows more precise stop but easier to get stopped out, while larger period gives wider stop but more robust. The stop level also trails the price upside, achieving trend following effect.

Exit Signals

Exits partially on small price surge to take profit. Exits more on large price spike to lock in profit. Keeps some position with trailing stop until stop loss is hit. This helps lock in profit, while still be able to hold position for some period.

Advantages

MACD judging trend combined with EMA/SMA crossover confirms entry timing
ATR trailing stop allows effective stop loss while following trend
Partial exits help take profit, lock in profit and hold for duration

Risks & Solutions

Risk of wrong signal from MACD and trend indicators. Fine tune parameters or add other indicators.
Risk of ATR stop loss being hit. Can increase ATR period or stop loss multiplier.
Risk of trailing position being trapped. Reduce trailing position size and cut loss in time.

Enhancement Opportunities

Optimize MACD parameters for better trend judgment
Optimize ATR period for better stop loss level
Optimize exit ratios and position sizing to reduce trapped risk
Consider adding moving take profit or volatility index to improve stop loss

Summary

The strategy combines MACD, EMA/SMA and other indicators to determine trend and entry timing accurately. The floating ATR stop loss helps lock in profit while following the trend. Exits are staggered to take profit, ensure gain and hold position for duration. Overall it is stable with decent result. But parameters and exits can be further optimized for better return.

Parameters

Name	Default	What it controls
v_input_1	34	Period
v_input_2	3	Fast Length
v_input_3	5	Slow Length
v_input_4_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_5	2	Signal Smoothing
v_input_6	false	Simple MA(Oscillator)
v_input_7	true	Simple MA(Signal Line)
v_input_8	true	Long Take Profit 1 %
v_input_9	10	Long Take Profit 1 Qty
v_input_10	5	Long Take Profit 2%
v_input_11	50	Long Take Profit 2 Qty
v_input_12	2.2	SL Mutiplier
v_input_13	17	ATR period
v_input_14	2018	Backtest Start Year
v_input_15	true	Backtest Start Month
v_input_16	true	Backtest Start Day
v_input_17	2020	Backtest Stop Year
v_input_18	12	Backtest Stop Month
v_input_19	31	Backtest Stop Day

Source Pine Script

/*backtest
start: 2022-10-30 00:00:00
end: 2023-11-05 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/
// © Deobald

//@version=4
strategy("MACD Strategy", overlay=true)

// FUNCTIONS

Ema(src,p) =>
    ema = 0.
    sf = 2/(p+1)
    ema := nz(ema[1] + sf*(src - ema[1]),src)

Sma(src,p) => a = cum(src), (a - a[max(p,0)])/max(p,0)

Atr(p) =>
    atr = 0.
    Tr = max(high - low, max(abs(high - close[1]), abs(low - close[1])))
    atr := nz(atr[1] + (Tr - atr[1])/p,Tr)

/// TREND
ribbon_period = input(34, "Period", step=1)

leadLine1 = ema(close, ribbon_period)
leadLine2 = sma(close, ribbon_period)

p3 = plot(leadLine1, color= #53b987, title="EMA", transp = 50, linewidth = 1)
p4 = plot(leadLine2, color= #eb4d5c, title="SMA", transp = 50, linewidth = 1)
fill(p3, p4, transp = 60, color = leadLine1 > leadLine2 ? #53b987 : #eb4d5c)


// MACD
fast_length = input(title="Fast Length", type=input.integer, defval=3)
slow_length = input(title="Slow Length", type=input.integer, defval=5)
src = input(title="Source", type=input.source, defval=close)
signal_length = input(title="Signal Smoothing", type=input.integer, minval = 1, maxval = 50, defval = 2)
sma_source = input(title="Simple MA(Oscillator)", type=input.bool, defval=false)
sma_signal = input(title="Simple MA(Signal Line)", type=input.bool, defval=true)

// Plot colors
col_grow_above = #26A69A
col_grow_below = #FFCDD2
col_fall_above = #B2DFDB
col_fall_below = #EF5350
col_macd = #0094ff
col_signal = #ff6a00

// Calculating
fast_ma = sma_source ? Sma(src, fast_length) : Ema(src, fast_length)
slow_ma = sma_source ? Sma(src, slow_length) : Ema(src, slow_length)
macd = fast_ma - slow_ma
signal = sma_signal ? Sma(macd, signal_length) : Ema(macd, signal_length)
hist = macd - signal

//plot(hist, title="Histogram", style=plot.style_columns, color=(hist>=0 ? (hist[1] < hist ? col_grow_above : col_fall_above) : (hist[1] < hist ? col_grow_below : col_fall_below) ), transp=0 )
// plot(macd, title="MACD", color=col_macd, transp=0)
// plot(signal, title="Signal", color=col_signal, transp=0)



// TAKE PROFIT AND STOP LOSS
long_tp1_inp = input(1, title='Long Take Profit 1 %', step=0.1)/100
long_tp1_qty = input(10, title="Long Take Profit 1 Qty", step=1)

long_tp2_inp = input(5, title='Long Take Profit 2%', step=0.1)/100
long_tp2_qty = input(50, title="Long Take Profit 2 Qty", step=1)

long_take_level_1 = strategy.position_avg_price * (1 + long_tp1_inp)
long_take_level_2 = strategy.position_avg_price * (1 + long_tp2_inp)




// Stop Loss
multiplier = input(2.2, "SL Mutiplier", minval=1, step=0.1)
ATR_period=input(17,"ATR period", minval=1, step=1)

// Strategy
entry_long=crossover(macd,signal) and leadLine2 < leadLine1
entry_price_long=valuewhen(entry_long,close,0)
SL_floating_long = entry_price_long - multiplier*Atr(ATR_period)
exit_long= close < SL_floating_long 

///// BACKTEST PERIOD ///////
testStartYear = input(2018, "Backtest Start Year")
testStartMonth = input(1, "Backtest Start Month")
testStartDay = input(1, "Backtest Start Day")
testPeriodStart = timestamp(testStartYear, testStartMonth, testStartDay, 0, 0)

testStopYear = input(2020, "Backtest Stop Year")
testStopMonth = input(12, "Backtest Stop Month")
testStopDay = input(31, "Backtest Stop Day")
testPeriodStop = timestamp(testStopYear, testStopMonth, testStopDay, 0, 0)

testPeriod() => true

if testPeriod()
    strategy.entry("long", strategy.long, comment="Long", when=entry_long)
    strategy.exit("TP1","long", qty_percent=long_tp1_qty, limit=long_take_level_1)//, trail_points=entry_price_long * long_trailing / syminfo.mintick, trail_offset=entry_price_long * long_trailing / syminfo.mintick)
    strategy.exit("TP2", qty_percent=long_tp2_qty, limit=long_take_level_2) //, trail_points=entry_price_long * long_trailing / syminfo.mintick, trail_offset=entry_price_long * long_trailing / syminfo.mintick)
    strategy.close_all("long", when=exit_long, comment="exit long" )


// LONG POSITION
plot(strategy.position_size > 0 ? long_take_level_1 : na, style=plot.style_linebr, color=color.green, linewidth=1, title="1st Long Take Profit")
plot(strategy.position_size > 0 ? long_take_level_2 : na, style=plot.style_linebr, color=color.green, linewidth=1, title="2nd Long Take Profit")
plot(strategy.position_size > 0 ? SL_floating_long : na, style=plot.style_linebr, color=color.red, linewidth=1, title="Long Stop Loss")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-06. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/MACD-Moving-Average-Crossover-Trend-Following-Strategy-with-Trailing-Stop-Loss.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.