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Reversal Trading Strategy Based on Stochastic RSI

This strategy is named "Reversal Trading Strategy Based on Stochastic RSI". It uses the Stochastic RSI indicator to identify overbought/oversold situations, entering reverse trades when extremes reverse. The…

Author
ChaoZhang
Complexity
Intermediate · 223 lines
Parameters
25
Backtest bar
5m · intraday
Tested on
BTC/USDT · futures

This strategy is named "Reversal Trading Strategy Based on Stochastic RSI". It uses the Stochastic RSI indicator to identify overbought/oversold situations, entering reverse trades when extremes reverse.

The Stochastic RSI calculates the Stochastic oscillator on RSI values, generating K and D line signals that reflect overbought/oversold conditions in the RSI itself.

The trading logic is:

  1. Calculate fast RSI to capture overbought/oversold.

  2. Apply a weighted moving average on RSI to derive Stochastic RSI K-line signal.

  3. When K-line crosses above its moving average, a buy signal is generated. When crossing below, a sell signal is generated.

  4. Reversal signals near overbought or oversold extremes hint at reversal trade opportunities.

The advantage of this strategy is using Stochastic RSI to identify reversal points. But parameter combinations need optimization, and overtrading should be prevented. Stop loss is also essential.

In conclusion, Stochastic RSI is a common and useful way to determine reversal timing. But traders still need overall trend judgment to avoid buying tops and selling bottoms in retracements.

Parameters

NameDefaultWhat it controls
v_input_1trueUse Heikin Ashi Candles in Algo Calculations
v_input_2trueFrom Month
v_input_3trueFrom Day
v_input_42021From Year
v_input_512Thru Month
v_input_630Thru Day
v_input_72021Thru Year
v_input_8trueShow Date Range
v_input_9_close0Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4
v_input_1080TopBand
v_input_1120LowBand
v_input_122RSI Length
v_input_1350MA Length
v_input_145RSI MA Length
v_input_150MA Type: LRC | EMA | DEMA | TEMA | SMA | WMA | MF | VAMA | TMA | HMA | JMA | Kijun v2 | EDSMA | McGinley
v_input_160RSI MA Type: TMA | EMA | DEMA | TEMA | LRC | WMA | MF | VAMA | SMA | HMA | JMA | Kijun v2 | EDSMA | McGinley
v_input_17trueKijun MOD Divider
v_input_183* Jurik (JMA) Only - Phase
v_input_19true* Jurik (JMA) Only - Power
v_input_2010* Volatility Adjusted (VAMA) Only - Volatility lookback length
v_input_210.8Modular Filter, General Filter Only - Beta
v_input_22falseModular Filter Only - Feedback
v_input_230.5Modular Filter Only - Feedback Weighting
v_input_2420EDSMA - Super Smoother Filter Length
v_input_250EDSMA - Super Smoother Filter Poles: 2 | 3

Source Pine Script

/*backtest
start: 2023-09-05 00:00:00
end: 2023-09-12 00:00:00
period: 5m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © MightyZinger
//@version=4
strategy(shorttitle="MZ SRSI",title="MightyZinger SRSI Strategy", overlay=false, pyramiding=1, calc_on_order_fills=true, calc_on_every_tick=true, default_qty_type=strategy.fixed, default_qty_value=5,commission_value=0.1)

//heiking ashi calculation
UseHAcandles    = input(true, title="Use Heikin Ashi Candles in Algo Calculations")
////
// === /INPUTS ===

// === BASE FUNCTIONS ===
haClose = UseHAcandles ? security(heikinashi(syminfo.tickerid), timeframe.period, close) : close
haOpen  = UseHAcandles ? security(heikinashi(syminfo.tickerid), timeframe.period, open) : open
haHigh  = UseHAcandles ? security(heikinashi(syminfo.tickerid), timeframe.period, high) : high
haLow   = UseHAcandles ? security(heikinashi(syminfo.tickerid), timeframe.period, low) : low


//Backtest dates
fromMonth = input(defval = 1,    title = "From Month",      type = input.integer, minval = 1, maxval = 12)
fromDay   = input(defval = 1,    title = "From Day",        type = input.integer, minval = 1, maxval = 31)
fromYear  = input(defval = 2021, title = "From Year",       type = input.integer, minval = 1970)
thruMonth = input(defval = 12,    title = "Thru Month",      type = input.integer, minval = 1, maxval = 12)
thruDay   = input(defval = 30,    title = "Thru Day",        type = input.integer, minval = 1, maxval = 31)
thruYear  = input(defval = 2021, title = "Thru Year",       type = input.integer, minval = 1970)

showDate  = input(defval = true, title = "Show Date Range", type = input.bool)

start     = timestamp(fromYear, fromMonth, fromDay, 00, 00)        // backtest start window
finish    = timestamp(thruYear, thruMonth, thruDay, 23, 59)        // backtest finish window
window()  => true       // create function "within window of time"

src = UseHAcandles ? haClose : input(close, title="Source")

TopBand = input(80, step=0.01)
LowBand = input(20, step=0.01)
lengthRSI = input(2, minval=1,title="RSI Length")
lengthMA = input(50, minval=1,title="MA Length")
lengthRSI_MA= input(5, minval=1,title="RSI MA Length")


//RSI Source
maType = input(title="MA Type", type=input.string, defval="LRC", options=["SMA","EMA","DEMA","TEMA","LRC","WMA","MF","VAMA","TMA","HMA", "JMA", "Kijun v2", "EDSMA","McGinley"])
rsiMaType = input(title="RSI MA Type", type=input.string, defval="TMA", options=["SMA","EMA","DEMA","TEMA","LRC","WMA","MF","VAMA","TMA","HMA", "JMA", "Kijun v2", "EDSMA","McGinley"])

//MA Function

//           Pre-reqs
//
tema(src, len) =>
    ema1 = ema(src, len)
    ema2 = ema(ema1, len)
    ema3 = ema(ema2, len)
    (3 * ema1) - (3 * ema2) + ema3
kidiv = input(defval=1,maxval=4,  title="Kijun MOD Divider")

jurik_phase = input(title="* Jurik (JMA) Only - Phase", type=input.integer, defval=3)
jurik_power = input(title="* Jurik (JMA) Only - Power", type=input.integer, defval=1)
volatility_lookback = input(10, title="* Volatility Adjusted (VAMA) Only - Volatility lookback length")
//                  MF
beta = input(0.8,minval=0,maxval=1,step=0.1,  title="Modular Filter, General Filter Only - Beta")
feedback = input(false, title="Modular Filter Only - Feedback")
z = input(0.5,title="Modular Filter Only - Feedback Weighting",step=0.1, minval=0, maxval=1)
//EDSMA
ssfLength = input(title="EDSMA - Super Smoother Filter Length", type=input.integer, minval=1, defval=20)
ssfPoles = input(title="EDSMA - Super Smoother Filter Poles", type=input.integer, defval=2, options=[2, 3])

//----
//                  EDSMA
get2PoleSSF(src, length) =>
    PI = 2 * asin(1)
    arg = sqrt(2) * PI / length
    a1 = exp(-arg)
    b1 = 2 * a1 * cos(arg)
    c2 = b1
    c3 = -pow(a1, 2)
    c1 = 1 - c2 - c3
    
    ssf = 0.0
    ssf := c1 * src + c2 * nz(ssf[1]) + c3 * nz(ssf[2])

get3PoleSSF(src, length) =>
    PI = 2 * asin(1)

    arg = PI / length
    a1 = exp(-arg)
    b1 = 2 * a1 * cos(1.738 * arg)
    c1 = pow(a1, 2)

    coef2 = b1 + c1
    coef3 = -(c1 + b1 * c1)
    coef4 = pow(c1, 2)
    coef1 = 1 - coef2 - coef3 - coef4

    ssf = 0.0
    ssf := coef1 * src + coef2 * nz(ssf[1]) + coef3 * nz(ssf[2]) + coef4 * nz(ssf[3])

//          MA Main function
ma(type, src, len) =>
    float result = 0
    if type=="TMA"
        result := sma(sma(src, ceil(len / 2)), floor(len / 2) + 1)
    if type=="MF"
        ts=0.,b=0.,c=0.,os=0.
        //----
        alpha = 2/(len+1)
        a = feedback ? z*src + (1-z)*nz(ts[1],src) : src
        //----
        b := a > alpha*a+(1-alpha)*nz(b[1],a) ? a : alpha*a+(1-alpha)*nz(b[1],a)
        c := a < alpha*a+(1-alpha)*nz(c[1],a) ? a : alpha*a+(1-alpha)*nz(c[1],a)
        os := a == b ? 1 : a == c ? 0 : os[1]
        //----
        upper = beta*b+(1-beta)*c
        lower = beta*c+(1-beta)*b 
        ts := os*upper+(1-os)*lower
        result := ts
    if type=="LRC"
        result := linreg(src, len, 0)
    if type=="SMA" // Simple
        result := sma(src, len)
    if type=="EMA" // Exponential
        result := ema(src, len)
    if type=="DEMA" // Double Exponential
        e = ema(src, len)
        result := 2 * e - ema(e, len)
    if type=="TEMA" // Triple Exponential
        e = ema(src, len)
        result := 3 * (e - ema(e, len)) + ema(ema(e, len), len)
    if type=="WMA" // Weighted
        result := wma(src, len)
    if type=="VAMA" // Volatility Adjusted
        /// Copyright © 2019 to present, Joris Duyck (JD)
        mid=ema(src,len)
        dev=src-mid
        vol_up=highest(dev,volatility_lookback)
        vol_down=lowest(dev,volatility_lookback)
        result := mid+avg(vol_up,vol_down)
    if type=="HMA" // Hull
        result := wma(2 * wma(src, len / 2) - wma(src, len), round(sqrt(len)))
    if type=="JMA" // Jurik
        /// Copyright © 2018 Alex Orekhov (everget)
        /// Copyright © 2017 Jurik Research and Consulting.
        phaseRatio = jurik_phase < -100 ? 0.5 : jurik_phase > 100 ? 2.5 : jurik_phase / 100 + 1.5
        beta = 0.45 * (len - 1) / (0.45 * (len - 1) + 2)
        alpha = pow(beta, jurik_power)
        jma = 0.0
        e0 = 0.0
        e0 := (1 - alpha) * src + alpha * nz(e0[1])
        e1 = 0.0
        e1 := (src - e0) * (1 - beta) + beta * nz(e1[1])
        e2 = 0.0
        e2 := (e0 + phaseRatio * e1 - nz(jma[1])) * pow(1 - alpha, 2) + pow(alpha, 2) * nz(e2[1])
        jma := e2 + nz(jma[1])
        result := jma
    if type=="Kijun v2"
        kijun = avg(lowest(len), highest(len))//, (open + close)/2)
        conversionLine = avg(lowest(len/kidiv), highest(len/kidiv))
        delta = (kijun + conversionLine)/2
        result :=delta
    if type=="McGinley"
        mg = 0.0
        mg := na(mg[1]) ? ema(src, len) : mg[1] + (src - mg[1]) / (len * pow(src/mg[1], 4))
        result :=mg
    if type=="EDSMA"
    
        zeros = src - nz(src[2])
        avgZeros = (zeros + zeros[1]) / 2
        
        // Ehlers Super Smoother Filter 
        ssf = ssfPoles == 2
             ? get2PoleSSF(avgZeros, ssfLength)
             : get3PoleSSF(avgZeros, ssfLength)
        
        // Rescale filter in terms of Standard Deviations
        stdev = stdev(ssf, len)
        scaledFilter = stdev != 0
             ? ssf / stdev
             : 0
        
        alpha = 5 * abs(scaledFilter) / len
        
        edsma = 0.0
        edsma := alpha * src + (1 - alpha) * nz(edsma[1])
        result :=  edsma
    result


//Indicator
hline(TopBand, color=color.red,linestyle=hline.style_dotted, linewidth=2)
hline(LowBand, color=color.green, linestyle=hline.style_dashed, linewidth=2)

// RSI Definition
rsiSource = ma(maType, src , lengthMA)
frsi = rsi(rsiSource, lengthRSI)
fsma = ma(rsiMaType, frsi , lengthRSI_MA)

plot(frsi,title='frsi', color= color.lime, linewidth=3)
fsmaColor=color.new(color.red, 80)
plot(fsma,title='fsma', color= fsmaColor , linewidth=3, style=plot.style_area)

//Background
bgcolor(frsi > fsma ? color.lime : color.orange, 80)

longcondition = crossover (frsi , fsma)
shortcondition = crossunder(frsi , fsma)


////////////////////////////////
//if (longcondition)
//    strategy.entry("BUY", strategy.long, when = window())
    
//if (shortcondition)
//    strategy.close("SELL", strategy.short, when = window())

strategy.entry(id="long", long = true, when = longcondition and window())
strategy.close("long", when = shortcondition and window())

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-13. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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