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Chauvenet Radius

The Chauvenet criterion is a well-known criterion of selection and rejection of the data used by the Physics. It establishes that in an experiment is well to discard the data whose distance from the average is greater than a certain number of the delta.
In the stock market if prices move away from the average with a volatility too high are suspect. This principle is embodied in the Chauvenet floor with the definition of two asymptotes and two data areas rejection.
The Chauvenet Radius is the quadratic sum of the delta (distance from average) and sigmoid ( volatility ) and is therefore an obvious market stability index. In fact the moments when price strongly moves away from the average with high volatility coincide with the moments of high instability of the market.

It can be considered an evolution of John Bollinger method introduced during the '80.

Source: http://www.performancetrading.it/Documen...

开源脚本

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想在图表上使用此脚本?
//@version=2
study("Chauvenet Radius",shorttitle="Chavrad",overlay=false)
len=input(defval=20,minval=1)
price=close
avg=sma(price,len)
x=price-avg
y=stdev(price,len)
rad=pow(x+y,2)
ema=ema(rad,10)
hist1=rad-ema
hist2=ema-rad
histpos=hist1<0?0:hist1
histneg=hist2<0?0:hist2
plot(rad,color=lime,transp=80)
plot(ema,color=red,transp=80)
plot(histpos,style=columns,color=green)
plot(histneg,style=columns,color=maroon)