Momentum Indicator RSI Reversal Trading Strategy

This strategy first calculates ADX and SMA on higher timeframes to identify trend direction and changes. Then RSI is calculated on lower timeframes to identify overbought and oversold conditions to generate trading…

Pine ScriptMean reversion Momentum Trend following RSI SMA ADX / DMI

Author: ChaoZhang
Complexity: Intermediate · 63 lines
Parameters: 8
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

ADX on higher timeframes judges the strength of the trend. Rising ADX represents strengthening trend.
SMA on higher timeframes judges the direction of the trend. Rising SMA represents rising prices, falling SMA represents falling prices.
RSI on lower timeframes judges overbought and oversold conditions. RSI above threshold means overbought, RSI below threshold means oversold.
When ADX rises, SMA rises, and RSI overbought on lower timeframe, it's considered the uptrend is strengthening, go short here.
When ADX rises, SMA falls, and RSI oversold on lower timeframe, it's considered the downtrend is strengthening, go long here.

Advantage Analysis

Combines trend judgment and reversal trading, can capture reversal opportunities in major trends.
Utilizes indicators across timeframes, improves reliability of signals.
RSI strategy is simple to understand and implement.

Risk Analysis

Potential for false RSI signals, causing losing trades. Can optimize parameters to reduce false signals.
Major cycle trend judgment can be wrong, making strategy not suitable for market condition. Can consider more indicators for trend judgment.
Potentially high trading frequency, impacting profitability due to transaction costs. Can adjust RSI parameters to reduce number of trades.

Optimization Directions

Test more parameter combinations to find optimal match between RSI and ADX, SMA parameters.
Add stop loss mechanism to control single trade loss.
Consider volatility indicator to reduce position size when volatility is low.
Optimize specific entry and exit prices, like entering short upon breaking previous bar's high.

Conclusion

This strategy combines trend judgment and reversal signals to find local reversals within major trends. Compared to solely using RSI, it is more reliable and avoids being trapped. Overall a relatively conservative strategy suitable for investors looking to reduce false signals. Further parameter testing and mechanism optimization can improve strategy performance.

Parameters

Name	Default	What it controls
v_input_1	true	Custom Resolution / TF ?
v_input_2	180	Custom Resolution / TF
v_input_3	14	ADX Smoothing
v_input_4	14	DI Length
v_input_5	7	RSI length
v_input_6	28	RSI oversold
v_input_7	68	RSI overbought
v_input_8	20	SMA HTF Length

Source Pine Script

/*backtest
start: 2022-12-27 00:00:00
end: 2024-01-02 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy("RSI scalping", overlay=true)

CustSession 	= input(defval=true,title= "Custom Resolution / TF ? ",type=bool)
SessionTF0	= input(title="Custom Resolution / TF", defval="180")
adxlen = input(14, title="ADX Smoothing")
dilen = input(14, title="DI Length")
length = input(7, title= "RSI length")
overSold = input( 28, title= "RSI oversold" )
overBought = input( 68, title= "RSI overbought" )

RSI = rsi(close, 7)

res		=	CustSession ? SessionTF0 : period

o = request.security(syminfo.tickerid, res, open)
c = request.security(syminfo.tickerid, res, close)
l = request.security(syminfo.tickerid, res, low)
h = request.security(syminfo.tickerid, res, high)

 // ADX higher time frame
dirmov(len) =>
	up = change(h)
	down = -change(l)
	plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
    minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
    truer = request.security(syminfo.tickerid, res, tr)
	truerange = rma(truer, len)
	plus = fixnan(100 * rma(plusDM, len) / truerange)
	minus = fixnan(100 * rma(minusDM, len) / truerange)
	[plus, minus]

adx(dilen, adxlen) =>
	[plus, minus] = dirmov(dilen)
	sum = plus + minus
	adx = 100 * rma(abs(plus - minus) / (sum == 0 ? 1 : sum), adxlen)

sig = adx(dilen, adxlen)

// SMA higher time frame
len = input(20, minval=1, title="SMA HTF Length")
smma = 0.0
smma := na(smma[1]) ? sma(c, len) : (smma[1] * (len - 1) + c) / len

ADXrising = (sig > sig[1]) and (sig[1] > sig[2]) and (sig[2]  > sig[3]) and (sig > 15)
SMAdrop= (smma < smma[1]) and (smma[1] < smma[2]) and (smma[2] < smma[3])
SMArising = (smma > smma[1]) and (smma[1] > smma[2]) and (smma[2] > smma[3])
longCondition = crossover(RSI, overBought) and ADXrising and SMArising
shortCondition = crossunder(RSI, overSold) and SMAdrop and ADXrising 

if (longCondition)
    strategy.entry("Long entry", strategy.long)

if (shortCondition)
    strategy.entry("Short Entry", strategy.short)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-03. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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