Swing Dual Moving Average and RSI Crossover Strategy

This strategy integrates dual moving average and RSI indicator to construct a crossover trading strategy between long and short positions. It can capture mid-to-long term trends while avoiding unnecessary noise…

Pine ScriptTrend following Breakout Mean reversion RSI EMA ATR

Author: ChaoZhang
Complexity: Intermediate · 96 lines
Parameters: 9
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Strategy Logic

This strategy adopts two sets of moving averages, consisting of fast moving average (EMA 59 and EMA 82) and slow moving average (EMA 96 and EMA 95). It goes long when price crosses above fast EMA, and goes short when price crosses below fast EMA. Meanwhile, the overbought and oversold area of RSI indicator is used to confirm trading signals and stop-loss.

Specifically, when fast EMA breaks above slow EMA, a long signal is generated. If RSI is below 30 (oversold area) at this time, go long. When fast EMA breaks below slow EMA, a short signal is produced. If RSI surpasses 70 (overbought area) at this point, go short.

The advantage of using dual moving average is to better recognize changes in mid-to-long term trends. RSI filters out some noise trading from false breakouts.

Advantages

Capture mid-to-long term trends with dual moving averages
Filter noise trading with RSI indicator
Combine trend following and mean reversion trading
Simple and clear logic

Risk Analysis

In largely range-bound markets, moving average signals may be subject to whipsaws
RSI indicator also fails in certain market conditions
Stop loss placement needs prudence to avoid too loose or too tight

Enhancement Areas

Test longer cycle moving average combinations
Try different parameter tuning e.g. thresholds of RSI overbought/oversold areas
Add additional filters like trading volume
Optimize stop loss strategies, incorporate dynamic stop loss with ATR etc.

Summary

This strategy integrates the trend following of dual moving averages and mean reversion trading of RSI indicator. The dual EMAs track mid-to-long term trend directions, while RSI confirms validity of trading signals and stop loss. This is a simple and practical crossover strategy between long and short. It can be adapted to different market environments through parameter tuning and optimization.

Parameters

Name	Default	What it controls
v_input_1	500	period
v_input_2	14	length
v_input_3	70	overSold
v_input_4	30	overBought
v_input_5	59	fastLength
v_input_6	82	fastLengthL
v_input_7	96	slowLength
v_input_8	95	slowLengthL
v_input_9	75	sl

Source Pine Script

/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2
strategy("Swing Hull/rsi/EMA Strategy", overlay=true,default_qty_type=strategy.cash,default_qty_value=10000,scale=true,initial_capital=10000,currency=currency.USD)

//A Swing trading strategy that use a combination of indicators, rsi for target, hull for overall direction enad ema for entering the martket.
// hull ma copied from syrowof HullMA who copied from mohamed982 :) thanks both
// Performance 

n=input(title="period",defval=500)

n2ma=2*wma(close,round(n/2))
nma=wma(close,n)
diff=n2ma-nma
sqn=round(sqrt(n))

n2ma1=2*wma(close[1],round(n/2))
nma1=wma(close[1],n)
diff1=n2ma1-nma1
sqn1=round(sqrt(n))

n1=wma(diff,sqn)
n2=wma(diff1,sqn)
c=n1>n2?green:red
ma=plot(n1,color=c)



// RSi and Moving averages

length = input( 14 )
overSold = input( 70)
overBought = input( 30)
point = 0.0001
dev= 2

fastLength = input(59)
fastLengthL = input(82)
slowLength = input(96)
slowLengthL = input(95)
price = close

mafast = ema(price, fastLength)
mafastL= ema(price, fastLengthL)
maslow = ema(price, slowLength)
maslowL = ema(price, slowLengthL)
vrsi = rsi(price, length)
cShort =  (crossunder(vrsi, overBought))

condDown = n2 >= n1
condUp = condDown != true
closeLong =  (crossover(vrsi, overSold))
closeShort = cShort 


// Strategy Logic
longCondition = n1> n2
shortCondition = longCondition != true

col =condUp ? lime : condDown ? red : yellow
plot(n1,color=col,linewidth=3)


if (not na(vrsi))
    if shortCondition    
        if (price[0] < maslow[0] and price[1] > mafast[1]) //cross entry
            strategy.entry("SYS-SHORT", strategy.short, comment="short")
strategy.close("SYS-SHORT", when=closeShort) //output logic

if (not na(vrsi))
    if longCondition // swing condition          
        if (price[0] < mafast[0] and price[1] > mafast[1]) //cross entry
            strategy.entry("SYS-LONG", strategy.long, comment="long")
strategy.close("SYS-LONG", when=closeLong) //output logic


// Stop Loss 


sl = input(75)
Stop = sl * 10
Q = 100


strategy.exit("Out Long", "SYS-LONG", qty_percent=Q, loss=Stop)
strategy.exit("Out Short", "SYS-SHORT", qty_percent=Q, loss=Stop)



//plot(strategy.equity, title="equity", color=red, linewidth=2, style=areabr)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-01. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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