Dual EMA Golden Cross Trend Tracking Strategy

Pine ScriptTrend following Mean reversion EMA ATR

Author: ChaoZhang
Complexity: Intermediate · 111 lines
Parameters: 18
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy calculates fast EMA line and slow EMA line and compares the size relationship between the two EMAs to determine the trend direction of the market. It belongs to a simple trend tracking strategy. When the fast EMA crosses above the slow EMA, go long. When the fast EMA crosses below the slow EMA, go short. It is a typical dual EMA golden cross strategy.

Strategy Logic

The core indicators of this strategy are fast EMA and slow EMA. The fast EMA length is set to 21 periods and the slow EMA length is set to 55 periods. The fast EMA can respond to price changes faster, reflecting the recent short-term trend; the slow EMA responds more slowly to price changes, filtering out some noise and reflecting the medium-to-long term trend.

When the fast EMA crosses above the slow EMA, it indicates that the short-term trend has turned upward and the medium-to-long term trend may have reversed, which is a signal to go long. When the fast EMA crosses below the slow EMA, it indicates that the short-term trend has turned downward and the medium-to-long term trend may have reversed, which is a signal to go short.

By comparing fast and slow EMAs, it captures trend reversal points on two timescales, short-term and medium-to-long term, which is a typical trend tracking strategy.

Advantages

Simple and clear logic, easy to understand and implement
Flexible parameter tuning, fast and slow EMA periods can be customized
Configurable ATR stop loss and take profit for controllable risks

Risks

Inappropriate timing of EMA crossovers, risk of missing best entry point
Frequent invalid signals during market consolidation, causing losses
Improper ATR parameter setting, leading to too loose or too aggressive stops

Risk Management:

Optimize EMA fast and slow line parameters to find optimal combinations
Add filtering mechanisms to avoid invalid signals from market consolidation
Test and optimize ATR parameters to ensure reasonable stop loss and take profit

Enhancement Areas

Test stability of different EMA period parameters based on statistical methods
Add filtering conditions combined with other indicators to avoid invalid signals
Optimize ATR parameters to get best stop loss/take profit ratio

Summary

This strategy judges trend based on EMA crossovers, which is simple and clear to implement. With ATR-based stops, risks are controllable. Further improvements on stability and profitability can be made through parameter optimization and filtering conditions.

Parameters

Name	Default	What it controls
v_input_1	2017	Backtest Start Year
v_input_2	true	Backtest Start Month
v_input_3	true	Backtest Start Day
v_input_4	2025	Backtest End Year
v_input_5	true	Backtest End Month
v_input_6	true	Backtest End Day
v_input_7	false	Fixed Perc stop
v_input_8	0.1	Percentage for fixed stop
v_input_9	true	ATR Based stop
v_input_10	14	ATR Length for stop
v_input_11	1.5	ATR Multiplier for stoploss
v_input_12	true	ATR Multiplier for profit
v_input_13	true	Trade the Asian Session
v_input_14	true	Trade the European Session
v_input_15	true	Trade the US session
v_input_16	true	End of Session Close Out?
v_input_17	21	fastInput
v_input_18	55	slowInput

Source Pine Script

/*backtest
start: 2023-10-21 00:00:00
end: 2023-11-20 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy(title = "VP Backtester", overlay=false)


// Create General Strategy Inputs
st_yr_inp = input(defval=2017, title='Backtest Start Year')
st_mn_inp = input(defval=01, title='Backtest Start Month')
st_dy_inp = input(defval=01, title='Backtest Start Day')
en_yr_inp = input(defval=2025, title='Backtest End Year')
en_mn_inp = input(defval=01, title='Backtest End Month')
en_dy_inp = input(defval=01, title='Backtest End Day')
 
// Default Stop Types
fstp = input(defval=false, title="Fixed Perc stop")
fper = input(defval=0.1, title='Percentage for fixed stop', type=float)
atsp = input(defval=true, title="ATR Based stop")
atrl = input(defval=14, title='ATR Length for stop')
atrmsl = input(defval=1.5, title='ATR Multiplier for stoploss')
atrtpm = input(defval=1, title='ATR Multiplier for profit')
 
// Sessions
asa_inp = input(defval=true, title="Trade the Asian Session")
eur_inp = input(defval=true, title="Trade the European Session")
usa_inp = input(defval=true, title="Trade the US session")
ses_cls = input(defval=true, title="End of Session Close Out?")
 
// Session Start / End times (In exchange TZ = UTC-5)    
asa_ses = "1700-0300" 
eur_ses = "0200-1200" 
usa_ses = "0800-1700"  
 
in_asa = time(timeframe.period, asa_ses)
in_eur = time(timeframe.period, eur_ses)
in_usa = time(timeframe.period, usa_ses)
 
strategy.risk.allow_entry_in(strategy.direction.all)
 
// Set start and end dates for backtest
start = timestamp(st_yr_inp, st_mn_inp, st_dy_inp,00,00)
end = timestamp(en_yr_inp, en_mn_inp, en_dy_inp,00,00)
window()  => time >= start and time <= end ? true : false // create function "within window of time"

 
// Check if we are in a sessions we want to trade
can_trade = asa_inp and not na(in_asa) ? true :
  eur_inp and not na(in_eur) ? true :
  usa_inp and not na(in_usa) ? true :
  false
  
// atr calc for stop and profit
atr = atr(atrl)
atr_stp_dst_sl = atr * atrmsl
atr_stp_dst_tp = atr * atrtpm



//*************************************************************************************
// Put your strategy/indicator code below
// and make sure to set long_condition=1 for opening a buy trade
// and short_condition for opening a sell trade
//*************************************************************************************
fastInput = input(21)
slowInput = input(55)

fast = ema(close, fastInput)
slow = ema(close, slowInput)

plot(fast, color = red)
plot(slow, color = blue)

long_condition = crossover(fast, slow)
short_condition = crossunder(fast, slow)


//*************************************************************************************
// Trade management with ATR based stop & profit
//*************************************************************************************
if (long_condition and window() )
    strategy.entry("Long Entry",  strategy.long)
    if strategy.position_size <= 0 // Less than as in both direction strat - Could be long before switching
        if atsp
            atr_stop = open  - atr_stp_dst_sl
            atr_profit = open + atr_stp_dst_tp
            strategy.exit('ATR Long Exit', "Long Entry", stop=atr_stop, limit = atr_profit)
        if fstp
            stop = open - (open * fper)
            strategy.exit('Perc Fixed Long Stop Exit', "Long Entry", stop=stop)
 
if (short_condition and window() )
    strategy.entry("Short Entry",strategy.short)
    if strategy.position_size >= 0 // Greater than as in both direction strat - Could be long before switching
        if atsp
            atr_stop = open  + atr_stp_dst_sl
            atr_profit = open - atr_stp_dst_tp
            strategy.exit('ATR Short Exit', "Short Entry", stop=atr_stop, limit = atr_profit)
        if fstp
            stop = open + (open * fper)
            strategy.exit('Perc Fixed Short Stop Exit', "Short Entry", stop=stop)
 
 
strategy.close_all(when=not can_trade and ses_cls)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-21. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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