This study is an optimized version of Bollinger Bands based on volume weighted data points: more volume on a bar gives those prices a higher impact. FHX bands base on the assumptions of auction market theory (e.g., as does volume profiling). Bollinger Bands implicitly assume a uniform probability mass function for data points and consider only the - somewhat arbitrary - close price. In contrast to this, FHX bands take all four available data points into account (OHLC) and use the volume at each candle* to define a probability mass function in order to compute mean and standard deviation.
As an indicator, FHX bands could be used in the same way as BB to facilitate or confirm Break-Out trades and identify strong momentum moves. Settings for the standard deviation multiplier should be interpreted as follows (following the 68–95–99.7 rule):
x standard deviation set to 1: ~32% chance that a move outside the bands is by chance
x standard deviation set to 2: ~5% chance that a move outside the bands is by chance
x standard deviation set to 3: ~0.3% chance that a move outside the bands is by chance
This however assumes a fairly solid period of consolidation beforehand (visible through notable contraction of the bands) and a normal distribution of values within that consolidation period. Therefore users need to experiment within their time frame in order to identify a Length setting that suits their needs. Personally, I set Length to 21 or lower, depending on my targeted time frame. Note that the indicator does not test for normality in any way; you can, however, use a quick visual test using the fixed range volume profile indicator to increase its reliability.
Good luck and mind your risk -fhx
* of course tick data would be the real deal, but we work with what we have
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