Dual EMA Crossover Trend Strategy

This strategy uses the golden cross and death cross of dual EMA indicators to determine the current trend direction, and combines the RSI indicator to avoid missing buy and sell opportunities. It is a typical trend…

Pine ScriptTrend following Breakout Mean reversion RSI EMA

Author: ChaoZhang
Complexity: Intermediate · 72 lines
Parameters: 9
Backtest bar: 2h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

Calculate the 10-period and 20-period EMA lines, named ma00 and ma01 respectively
A buy signal is generated when ma00 crosses above ma01
A sell signal is generated when ma00 crosses below ma01
At the same time, when price crosses above ma00, if ma00 is above ma01, a buy signal will also be generated
Similarly, when price crosses below ma00, if ma00 is below ma01, a sell signal will also be generated
Through such dual validation, some buy and sell points can be avoided missing
Set stop loss and take profit prices to control risks

Advantage Analysis

Using dual EMA to determine can effectively filter false breakouts
Dual condition validation avoids missing orders
Stop loss and take profit settings are beneficial for risk management

Risk Analysis

The dual EMA strategy belongs to the trend tracking strategy. Frequent buys and sells in sideways markets can easily hit stop loss
It cannot accurately determine trend reversal points, which may lead to losses
Improper stop loss point settings may amplify losses

Optimization Directions

EMA cycles can be properly optimized to find the best parameter combination
Other indicators can be added to improve strategy stability
Dynamic stops can be set to adjust stop loss points in real time based on market fluctuations

Parameters

Name	Default	What it controls
v_input_1	true	Use Trading Session?
v_input_2	true	Use Trailing Stop?
v_input_3	0400-1500	Trade Session:
v_input_4	true	Trade Size:
v_input_5	55	Take profit in pips:
v_input_6	11	Stop loss in pips:
v_input_7	10	EMA length:
v_input_8	20	DEMA length:
v_input_9_open	0	Price source:: open \| high \| low \| close \| hl2 \| hlc3 \| hlcc4 \| ohlc4

Source Pine Script

/*backtest
start: 2023-12-21 00:00:00
end: 2023-12-28 00:00:00
period: 2h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4

strategy(title='[STRATEGY][RS]MicuRobert EMA cross V1', shorttitle='S', overlay=true, pyramiding=0, initial_capital=100000)
USE_TRADESESSION = input(title='Use Trading Session?', type=bool, defval=true)
USE_TRAILINGSTOP = input(title='Use Trailing Stop?', type=bool, defval=true)
trade_session = input(title='Trade Session:',  defval='0400-1500', confirm=false)
istradingsession = not USE_TRADESESSION ? false : not na(time('1', trade_session))
bgcolor(istradingsession?color.gray:na)
trade_size = input(title='Trade Size:', type=float, defval=1)
tp = input(title='Take profit in pips:', type=float, defval=55.0) * (syminfo.mintick*10)
sl = input(title='Stop loss in pips:', type=float, defval=11.0) * (syminfo.mintick*10)
ma_length00 = input(title='EMA length:',  defval=10)
ma_length01 = input(title='DEMA length:',  defval=20)
price = input(title='Price source:', defval=open)

//  ||--- NO LAG EMA, Credit LazyBear:  ---||
f_LB_zlema(_src, _length)=>
    _ema1=ema(_src, _length)
    _ema2=ema(_ema1, _length)
    _d=_ema1-_ema2
    _zlema=_ema1+_d
//  ||-------------------------------------||

ma00 = f_LB_zlema(price, ma_length00)
ma01 = f_LB_zlema(price, ma_length01)
plot(title='M0', series=ma00, color=black)
plot(title='M1', series=ma01, color=black)

isnewbuy = change(strategy.position_size)>0 and change(strategy.opentrades)>0
isnewsel = change(strategy.position_size)<0 and change(strategy.opentrades)>0

buy_entry_price = isnewbuy ? price : buy_entry_price[1]
sel_entry_price = isnewsel ? price : sel_entry_price[1]
plot(title='BE', series=buy_entry_price, style=circles, color=strategy.position_size <= 0 ? na : aqua)
plot(title='SE', series=sel_entry_price, style=circles, color=strategy.position_size >= 0 ? na : aqua)
buy_appex = na(buy_appex[1]) ? price : isnewbuy ? high : high >= buy_appex[1] ? high : buy_appex[1]
sel_appex = na(sel_appex[1]) ? price : isnewsel ? low : low <= sel_appex[1] ? low : sel_appex[1]
plot(title='BA', series=buy_appex, style=circles, color=strategy.position_size <= 0 ? na : teal)
plot(title='SA', series=sel_appex, style=circles, color=strategy.position_size >= 0 ? na : teal)
buy_ts = buy_appex - sl
sel_ts = sel_appex + sl
plot(title='Bts', series=buy_ts, style=circles, color=strategy.position_size <= 0 ? na : red)
plot(title='Sts', series=sel_ts, style=circles, color=strategy.position_size >= 0 ? na : red)

buy_cond1 = crossover(ma00, ma01) and (USE_TRADESESSION ? istradingsession : true)
buy_cond0 = crossover(price, ma00) and ma00 > ma01 and (USE_TRADESESSION ? istradingsession : true)
buy_entry = buy_cond1 or buy_cond0
buy_close = (not USE_TRAILINGSTOP ? false : low <= buy_ts) or high>=buy_entry_price+tp//high>=last_traded_price + tp or low<=last_traded_price - sl //high >= hh or 
sel_cond1 = crossunder(ma00, ma01) and (USE_TRADESESSION ? istradingsession : true)
sel_cond0 = crossunder(price, ma00) and ma00 < ma01 and (USE_TRADESESSION ? istradingsession : true)
sel_entry = sel_cond1 or sel_cond0
sel_close = (not USE_TRAILINGSTOP ? false : high >= sel_ts) or low<=sel_entry_price-tp//low<=last_traded_price - tp or high>=last_traded_price + sl //low <= ll or 

strategy.entry('buy', long=strategy.long, qty=trade_size, comment='buy', when=buy_entry)
strategy.close('buy', when=buy_close)
strategy.entry('sell', long=strategy.short, qty=trade_size, comment='sell', when=sel_entry)
strategy.close('sell', when=sel_close)

//What i add .!
pos = iff(ma01 < ma00 , 1,
	    iff(ma01 > ma00 , -1, nz(pos[1], 0))) 
barcolor(pos == -1 ? red: pos == 1 ? green : blue)
plot(ma00, color=red, title="MA")
plot(ma01, color=blue, title="EMA")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-29. 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/Dual-EMA-Crossover-Trend-Strategy.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.