trading.kay27

Kay_StochasticRSI

This is a different version of Stochastic RSI. the only difference is the use of variable moving average by Lazybear instead of regular sma for K smoothing.

Its purely an experiment. I am not a professional trader but an enthusiastic programmer trying different indicator combination to see different results.

Criticizing and negative comments will be gracefully accepted. :)
Appreciation will be even more. :)

Open-source script

In true TradingView spirit, the author of this script has published it open-source, so traders can understand and verify it. Cheers to the author! You may use it for free, but reuse of this code in a publication is governed by House Rules. You can favorite it to use it on a chart.

Disclaimer

The information and publications are not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by TradingView. Read more in the Terms of Use.

Want to use this script on a chart?
//@version=2
//vma function is originally written by @LazyBear
//Stochastic RSI code taken from stochcharts.com
//Merging both is my brain child. (Unless someone have already thought that) :)

study(title="Kay_StochasticRSI", shorttitle="Kay_StochRSI", precision=5)
smoothK = input(3, title="Smooth K", minval=1)
smoothD = input(3, title="Smooth D", minval=1)
lengthRSI = input(14, title="RSI", minval=1)
ls = input(14, title="Stoch", minval=1)
src = input(close, title="Source")

vma(src, l) => 
    k = 2.0/(l+1)
    pdm = max((src - src[1]), 0)
    mdm = max((src[1] - src), 0)
    pdmS = ((1 - k)*nz(pdmS[1]) + k*pdm)
    mdmS = ((1 - k)*nz(mdmS[1]) + k*mdm)
    s = pdmS + mdmS
    pdi = pdmS/s
    mdi = mdmS/s
    pdiS = ((1 - k)*nz(pdiS[1]) + k*pdi)
    mdiS = ((1 - k)*nz(mdiS[1]) + k*mdi)
    d = abs(pdiS - mdiS)
    s1 = pdiS + mdiS
    iS = ((1 - k)*nz(iS[1]) + k*d/s1)
    hhv = highest(iS, l) 
    llv = lowest(iS, l) 
    d1 = hhv - llv
    vI = (iS - llv)/d1
    vma=(1 - k*vI)*nz(vma[1]) + k*vI*src
    vma

//First calculate RSI
rsi = rsi(src, lengthRSI)

//Calculate stocastic using rsi as series instead of close
st = ((rsi - lowest(rsi, ls))/(highest(rsi, ls) - lowest(rsi, ls))) * 100
//smooth out Stoch using variable moving average instead of simple moving average (no idea why I did it)
k = vma(st, smoothK)
//Smooth out K using again vma to get D
d = vma(k, smoothD)

//Color calculation.
kC=(k > k[1]) ? green : (k<k[1]) ? red : (k==k[1]) ? blue : black
plot(k, color=kC, transp=0)
plot(d, color=orange)
h0 = hline(80)
h1 = hline(20)
fill(h0, h1, color=purple, transp=80)