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SSRN Electronic Journal
Article . 2006 . Peer-reviewed
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Empirical Optimization of Bollinger Bands for Profitability

Authors: Oliver Douglas Williams;

Empirical Optimization of Bollinger Bands for Profitability

Abstract

This paper endeavours to evaluate the profitability of Bollinger Bands through an empirical study. Bollinger Bands are able to capture sudden fluctuations in price level, which may be useful when tweaking its inputs to derive a trading rule. For the purpose of projecting prices, technical analysts have chosen a moving average of 20 days for short term analysis and 200 days for long term analyst. Moving averages in relation to profitability is the focus of this study. What follows is a discussion on the development of Bollinger Bands from trading bands, and moving averages. After testing a simple trading rule on the components of the DOW 30 index there is a revelation that a single moving average window cannot be used to derive an all (security) encompassing trading rule.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
bronze