Bollinger bands

 


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Various studies of the effectiveness of the Bollinger Band strategy have been performed with mixed results.

In , Lento et al. The authors did, however, find that a simple reversal of the strategy "contrarian Bollinger Band" produced positive returns in a variety of markets.

Similar results were found in another study, which concluded that Bollinger Band trading strategies may be effective in the Chinese marketplace, stating: A recent study examined the application of Bollinger Band trading strategies combined with the ADX for Equity Market indices with similar results. A paper from uses Bollinger Bands to reduce variance in a Monte Carlo simulation used to forecast the Canadian treasury bill yield curve.

In , Butler et al. Their results indicated that by tuning the parameters to a particular asset for a particular market environment, the out-of-sample trading signals were improved compared to the default parameters. Companies like Forbes suggest that the use of Bollinger Bands is a simple and often an effective strategy but stop-loss orders should be used to mitigate losses from market pressure. Security price returns have no known statistical distribution , normal or otherwise; they are known to have fat tails , compared to a normal distribution.

Such techniques usually require the sample to be independent and identically distributed, which is not the case for a time series like security prices. Just the opposite is true; it is well recognized by practitioners that such price series are very commonly serially correlated [ citation needed ] —that is, each price will be closely related to its ancestor "most of the time".

Adjusting for serial correlation is the purpose of moving standard deviations , which use deviations from the moving average , but the possibility remains of high order price autocorrelation not accounted for by simple differencing from the moving average. For such reasons, it is incorrect to assume that the long-term percentage of the data that will be observed in the future outside the Bollinger Bands range will always be constrained to a certain amount.

Practitioners may also use related measures such as the Keltner channels , or the related Stoller average range channels, which base their band widths on different measures of price volatility, such as the difference between daily high and low prices, rather than on standard deviation.

Bollinger bands have been applied to manufacturing data to detect defects anomalies in patterned fabrics. The International Civil Aviation Organization is using Bollinger bands to measure the accident rate as a safety indicator to measure efficacy of global safety initiatives. From Wikipedia, the free encyclopedia.

Kirkpatrick and Julie R. Now, enough about tools already! When the market is quiet, the bands contract and when the market is LOUD, the bands expand. Notice on the chart below that when price is quiet, the bands are close together. When price moves up, the bands spread apart. One thing you should know about Bollinger Bands is that price tends to return to the middle of the bands.

If you said down, then you are correct! As you can see, the price settled back down towards the middle area of the bands. What you just saw was a classic Bollinger Bounce. To learn more about Bollinger Bands, please watch some of our videos.

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