Strategy vault / Trend following
Swing Hull rsi EMA Strategy
A Swing trading strategy that use a combination of indicators, Hull average to get the trend direction, ema and rsi do the rest, use it are your own risk expecially at the end of any hull trend Past Performance Does…
A Swing trading strategy that use a combination of indicators, Hull average to get the trend direction, ema and rsi do the rest, use it are your own risk expecially at the end of any hull trend Past Performance Does Not Guarantee Future Results
backtest

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: 2022-04-24 00:00:00
end: 2022-05-23 23:59:00
period: 30m
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 2022-05-25. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.
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