Shannon Entropy for Price and Volume Signals

Summary

This indicator applies Shannon entropy to price and volume data as a measure of how information changes over a rolling window. It can calculate the two streams separately or display their difference, with optional bands and percentile-rank markers. The author interprets unusually high information as a sign of substantial change and unusually low information as possible complacency, prompting further review rather than a prescribed trade.

The document describes an example that uses percentile-rank extremes to enter long or short positions, but it does not provide performance results or explain how those entries were validated. It cautions that short lookback lengths can amplify noise and recommends using a window at least about twice the noisy frequency. The method is presented as an exploratory indicator: trading decisions remain discretionary, and the examples do not establish that entropy extremes reliably predict reversals or profitable trades.

Key ideas

• Shannon entropy is used to represent information or surprise in price and volume data.
• The indicator can compare price entropy with volume entropy or plot either input alone.
• Bands and percentile-rank markers help flag unusual readings for investigation.
• The example associates percentile-rank extremes with long and short entries, without reporting their performance.
• Short windows may emphasize noise, so the author recommends choosing a length above the noisy frequency.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.