Fixing Bollinger bands · Although the volatility bands are original in design and execution, they...
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12/20/2014 Fixing Bollinger bands http://www.futuresmag.com/2010/05/01/fixingbollingerbands 1/4 Follow Futures From the May 01, 2010 issue of Futures Magazine • Subscribe! Fixing Bollinger bands Bollinger Bands are used widely in the trading community and are a key component of many trading strategies. By their nature, Bollinger bands offer a particular perspective of the market. But that perspective is not without its drawbacks. This article will present a revised approach to the trading band concept with the aim of sharpening the focus of this class of indicator significantly. Both are valid and share a common heritage, but they are quite different under evaluation and in application. The derivation here is termed a volatility band. This article will explain why this derivation is necessary and how it is constructed and provide high-level preliminary test results. Although the volatility bands are original in design and execution, they were inspired by Dennis McNicholl’s work to improve Bollinger bands in the late 1990s (“Better Bollinger Bands,” October 1998). Houston, we have a problem Popularized by John Bollinger, who gave them their name, Bollinger bands are simply a plot of a multiple of the standard deviation of price from its simple moving average (SMA), both above and below. By the use of standard deviation, we should reasonably expect that the distribution of price around the mean should conform to statistical normality, or get close to it. Unfortunately, this is not the case for Bollinger bands and has led to a search to fix the problem. Based on observations of Bollinger bands, here are some of the issues: • They are saddled with high lag, as virtually all SMA-based indicators are. Consequently, the user should be mindful of the delay in what the bands present. • They do not envelope price in a manner consistent with a Gaussian distribution. That is, 68.2% of prices should be found within one standard deviation of the sample mean, 95.4% of prices should be found within two standard deviations of the mean, etc. This Commodities more commodities >> Digital Currencies more digital currencies >> Commodities Equities Bonds Forex powered by tradingview.com Symbol Last Change (%) Emini 2067.00 +2.00 (+0.10%) Euro 1.22350 −0.00570 (−0.46%) Gold 1195.9 +1.2 (+0.10%) Oil 57.13 +3.02 (+5.58%) Gas 3.464 −0.178 (−4.89%) Corn 410'4 −0'4 (−0.12%) FEATURED TOPICS Crude stubbornly drills toward record Bitreserve raises nearly $10 million; Coinbase funding global expansion SEARCH SUBSCRIBE FOLLOW MAGAZINE FUTURES FAVORITES TRADERS FINalternatives HARD ASSETS THE ALPHA PAGES ALPHA TV JOBS ALL + ! By David Rooke May 1, 2010 • Reprints
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12/20/2014 Fixing Bollinger bands
http://www.futuresmag.com/2010/05/01/fixingbollingerbands 1/4
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From the May 01, 2010 issue of Futures Magazine • Subscribe!
Fixing Bollinger bands
Bollinger Bands are used widely in the trading community and are a key component ofmany trading strategies. By their nature, Bollinger bands offer a particular perspectiveof the market. But that perspective is not without its drawbacks.
This article will present a revised approach to the trading band concept with the aimof sharpening the focus of this class of indicator significantly. Both are valid and sharea common heritage, but they are quite different under evaluation and in application.The derivation here is termed a volatility band. This article will explain why thisderivation is necessary and how it is constructed and provide high-level preliminarytest results.
Although the volatility bands are original in design and execution, they were inspiredby Dennis McNicholl’s work to improve Bollinger bands in the late 1990s (“BetterBollinger Bands,” October 1998).
Houston, we have a problemPopularized by John Bollinger, who gave them their name, Bollinger bands are simplya plot of a multiple of the standard deviation of price from its simple moving average(SMA), both above and below. By the use of standard deviation, we should reasonablyexpect that the distribution of price around the mean should conform to statisticalnormality, or get close to it.
Unfortunately, this is not the case for Bollinger bands and has led to a search to fix theproblem. Based on observations of Bollinger bands, here are some of the issues:• They are saddled with high lag, as virtually all SMA-based indicators are.Consequently, the user should be mindful of the delay in what the bands present.
• They do not envelope price in a manner consistent with a Gaussian distribution. Thatis, 68.2% of prices should be found within one standard deviation of the sample mean,95.4% of prices should be found within two standard deviations of the mean, etc. This
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Emini 2067.00 +2.00 (+0.10%)
Euro 1.22350 −0.00570 (−0.46%)
Gold 1195.9 +1.2 (+0.10%)
Oil 57.13 +3.02 (+5.58%)
Gas 3.464 −0.178 (−4.89%)
Corn 410'4 −0'4 (−0.12%)
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By David Rooke
May 1, 2010 • Reprints
12/20/2014 Fixing Bollinger bands
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will be described as the price/band ratio. While it can be debated whether daily pricechanges are normally distributed, the Bollinger price/band ratio can be said to offerlittle or no information from a probabilistic perspective.
• The price/band ratio is not scale invariant. That is, the price/band ratio from a givenstandard deviation does not remain constant as timescales increase. For example, seethe following based on S&P 500 prices with 2xSD banding:
160-bar Bollinger bands:Price/band ratio = 83.7%
80-bar Bollinger bands:Price/band ratio = 86.2%
20-bar Bollinger bands:Price/band ratio = 88.5%
• The movement of the bands against the moving average does not correlate withhistorical volatility. Seeing as Bollinger bands are intended, in part, to reflect changesin volatility, this is an issue.
Thankfully, these issues can be resolved in a practical way. By systematicallyaddressing each of these issues in turn, we can construct an indicator thatcomplements rather than replaces Bollinger bands and provides a useful additionaltrading tool. The solution is also simpler than anticipated.
Volatility bandsLet us see how these so-called volatility bands address some of these issues beforeexplaining how the bands are constructed. Maybe the best way to demonstrate this iswith a chart (see “Volatile solution,” left).
In this chart of the S&P 500, it’s clear how tightly the volatility bands hug price changesrelative to the slow and sometimes wild and wide gyrations of the Bollinger bands.Volatility bands achieve this through the application of a low lag moving average and
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Firstwave • 4 years ago
Nothing here in the diosp;ayed gives a triggered buy or sell. Using Bands as noisefilters of shorter time frames and Bands with a tighter band as frequency filters willgivbe long and short signals on all time frames. ANd filter out the false up or downmoves.
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by calculating the standard deviation of price against that moving average. Note thatthe “standard” standard deviation function is an inappropriate tool for this.The result is trading bands with low lag. Let’s see how effectively these bandsencapsulate S&P 500 prices at 2xSD:
160-bar volatility bands:Price/band ratio = 94.6%
80-bar volatility bands:Price/band ratio = 95.3%
20-bar volatility bands:Price/band ratio = 95.7%
To validate this point let’s take a peek at the numbers for 1xSD:
160-bar volatility bands:Price/band ratio = 65.0%
80-bar volatility bands:Price/band ratio = 66.9%
20-bar volatility bands:Price/band ratio = 67.8%
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