Niklaus

Beta

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https://en.wikipedia.org/wiki/Beta_(finance)
Beta is a measure of the risk arising from exposure to general market movements as opposed to idiosyncratic factors.
The market portfolio of all investable assets has a beta of exactly 1 (here the S&P500 ). A beta below 1 can indicate either an investment with lower volatility than the market, or a volatile investment whose price movements are not highly correlated with the market
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.

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study(title="Beta", shorttitle="Beta")

//by Niklaus
//SHOULD BE USED TOGETHER WITH "Alpha" INDICATOR
//beta (β or beta coefficient) of an investment indicates whether the investment is more or less volatile than the market. 
//In general, a beta less than 1 indicates that the investment is less volatile than the market,
//while a beta more than 1 indicates that the investment is more volatile than the market. Volatility is measured as the fluctuation of the price around the mean.

//Beta is a measure of the risk arising from exposure to general market movements as opposed to idiosyncratic factors. 
//The market portfolio of all investable assets has a beta of exactly 1 (here the S&P500). A beta below 1 can indicate either an investment with lower volatility than the market, 
//or a volatile investment whose price movements are not highly correlated with the market. 
//An example of the first is a treasury bill: the price does not go up or down a lot, so it has a low beta. 
//An example of the second is gold. The price of gold does go up and down a lot, but not in the same direction or at the same time as the market

//https://en.wikipedia.org/wiki/Beta_(finance)

sym = "SPX500", res=period, src = close, length = input(title = "Beta Window", defval=300, minval=1)
ovr = security(sym, res, src)

ret = ((close - close[1])/close)
retb = ((ovr - ovr[1])/ovr)
secd = stdev(ret, length), mktd = stdev(retb, length)
Beta = correlation(ret, retb, length) * secd / mktd

plot(Beta, color=blue, style=area, transp=40)

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