Rashad

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.

开源脚本

本着真正的TradingView精神,该脚本的作者将其开源发布,以便交易者可以理解和验证它。为作者喝彩!您可以免费使用它,但在出版物中重复使用此代码受网站规则的约束。 您可以收藏它以在图表上使用。

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想在图表上使用此脚本?
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")