Strategi Dagangan Pembalikan Berdasarkan RSI Stochastic

Penulis:ChaoZhang, Tarikh: 2023-09-13 18:00:13
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Strategi ini dinamakan Reversal Trading Strategy Based on Stochastic RSI. Ia menggunakan penunjuk Stochastic RSI untuk mengenal pasti situasi overbought/oversold, memasuki perdagangan terbalik apabila ekstrem berbalik.

Stochastic RSI mengira osilator Stochastic pada nilai RSI, menghasilkan isyarat garis K dan D yang mencerminkan keadaan overbought / oversold dalam RSI itu sendiri.

Logik perdagangan adalah:

  1. Mengira RSI pantas untuk menangkap overbought/oversold.

  2. Menggunakan purata bergerak bertingkat pada RSI untuk mendapatkan isyarat K-line RSI Stochastic.

  3. Apabila garis K melintasi di atas purata bergerak, isyarat beli dihasilkan. Apabila melintasi di bawah, isyarat jual dihasilkan.

  4. Isyarat pembalikan berhampiran kelebihan beli atau kelebihan jual menunjukkan peluang perdagangan pembalikan.

Kelebihan strategi ini adalah menggunakan RSI Stochastic untuk mengenal pasti titik pembalikan. Tetapi kombinasi parameter memerlukan pengoptimuman, dan overtrading harus dicegah. Hentikan kerugian juga penting.

Kesimpulannya, Stochastic RSI adalah cara yang biasa dan berguna untuk menentukan masa pembalikan. Tetapi peniaga masih memerlukan penilaian trend keseluruhan untuk mengelakkan membeli puncak dan menjual bawah dalam retracements.


/*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())

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