Exponential Bollinger Bands

These Bollinger Bands are exponential because the variance is calculated using the exponential moving average , rather than just adding the normal standard deviation to the ema . This may be more useful because the exponential standard deviation should be more sensitive to near term increases or decreases in volatility .

Please do not forget that Bollinger Bands should always be combined with another method of analysis. Bollinger Bands just provide an easy way to gauge where the price could range in. At 2 standard deviations of a continuously random variable, more than 98% of data points are in this range. I am however going to test this in excel to get the average number of data points that stay in the range for Bitcoin . I will upload my findings when I complete that. Please monitor this description if your interested.


本著真正的TradingView精神,該腳本的作者將其開源發布,以便交易者可以理解和驗證它。為作者喝彩吧!您可以免費使用它,但在出版物中重複使用此代碼受網站規則的約束。 您可以收藏它以在圖表上使用。

study("Exponential Bollinger Bands", shorttitle = "EBB", overlay = true)
src = input(ohlc4, title = "source")
len = input(21, title = "timeframe / # of period's")
e = ema(src,len)
evar = (src - e)*(src - e)
evar2 = (sum(evar,len))/len
std = sqrt(evar2)
Multiplier = input(2, minval = 0.01, title = "# of STDEV's")
upband = e + (Multiplier * std)
dnband = e - (Multiplier * std)
//stdd = stdev(std)
//bsu = upband + std
//bsun = upband - std
//bsd = dnband + std
//bsdn = dnband - std
//plot(bsu, color = purple)
//plot(bsun, color = purple)
//plot(bsd, color = purple)
//plot(bsdn, color = purple)
plot(e, color = purple, linewidth = 2, title = "basis")
plot(upband, color = red, linewidth = 2, title = "up band")
plot(dnband, color = green, linewidth  = 2, title = "down band")