HPotter

Historical Volatility Strategy

Strategy buy when HVol above BuyBand and close position when HVol below CloseBand.
Markets oscillate from periods of low volatility to high volatility
and back. The author`s research indicates that after periods of
extremely low volatility, volatility tends to increase and price
may move sharply. This increase in volatility tends to correlate
with the beginning of short- to intermediate-term moves in price.
They have found that we can identify which markets are about to make
such a move by measuring the historical volatility and the application
of pattern recognition.
The indicator is calculating as the standard deviation of day-to-day
logarithmic closing price changes expressed as an annualized percentage.

Skrip sumber terbuka

Dalam semangat TradingView yang sebenar, penulis skrip ini telah menerbitkannya dengan menggunakan sumber terbuka supaya pedagang-pedagang dapat memahami dan mengesahkannya. Sorakan kepada penulis! Anda dapat menggunakannya secara percuma tetapi penggunaan semula kod ini dalam penerbitan adalah dikawalselia oleh Peraturan Dalaman. Anda boleh menyukainya untuk menggunakannya pada carta.

Penafian

Maklumat dan penerbitan adalah tidak dimaksudkan untuk menjadi, dan tidak membentuk, nasihat untuk kewangan, pelaburan, perdagangan dan jenis-jenis lain atau cadangan yang dibekalkan atau disahkan oleh TradingView. Baca dengan lebih lanjut di Terma Penggunaan.

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////////////////////////////////////////////////////////////
//  Copyright by HPotter v1.0 16/07/2014
// Strategy buy when HVol above BuyBand and close position when HVol below CloseBand.
// Markets oscillate from periods of low volatility to high volatility 
// and back. The author`s research indicates that after periods of 
// extremely low volatility, volatility tends to increase and price 
// may move sharply. This increase in volatility tends to correlate 
// with the beginning of short- to intermediate-term moves in price. 
// They have found that we can identify which markets are about to make 
// such a move by measuring the historical volatility and the application 
// of pattern recognition.
// The indicator is calculating as the standard deviation of day-to-day 
// logarithmic closing price changes expressed as an annualized percentage.
////////////////////////////////////////////////////////////
study(title="Historical Volatility")
LookBack = input(20, minval=1)
Annual = input(365, minval=1)
BuyBand = input(20, minval=1)
CloseBand = input(10, minval=1)
hline(0, color=purple, linestyle=dashed)
hline(BuyBand, color=green, linestyle=line)
hline(CloseBand, color=red, linestyle=line)
xPrice = log(close / close[1])
nPer = iff(isintraday or isdaily, 1, 7)
xPriceAvg = sma(xPrice, LookBack)
xStdDev = stdev(xPrice, LookBack)
HVol = (xStdDev * sqrt(Annual / nPer)) * 100
pos =	iff(HVol > BuyBand, 1, 
            iff(HVol < CloseBand, -1, nz(pos[1], 0))) 
barcolor(pos == 1 ? yellow : na)
plot(HVol, color=blue, title="Historical Volatility")