Spectral Entropy as a Proposed Measure of Stock Volatility

Summary

The document raises the possibility of using spectral entropy to characterize stock volatility, partly because beta depends on selecting a benchmark. Its intuition is that a higher spectral entropy might indicate a more structured underlying signal and therefore lower volatility, while a lower value might reflect greater randomness and higher volatility.

This is presented only as a hypothesis. The text gives no definition or calculation procedure for spectral entropy, empirical comparison with realized volatility or beta, or evidence that the proposed direction of interpretation holds. It therefore introduces a possible research question rather than establishing a volatility estimator. Any use would require clarifying how the entropy is computed and testing whether it measures volatility reliably across stocks and conditions.

Key ideas

• The document proposes spectral entropy as a possible alternative lens on stock volatility.
• Its intuition associates higher entropy with a more structured signal and lower volatility.
• It associates lower entropy with greater randomness and higher volatility.
• No calculation method, empirical evidence, or validation against other measures is provided.

Tags

# spectral entropy as stock volatility


# spectral entropy as stock volatility












There are many way to capture to stock volatility and most common is `Beta`. But problem with `beta` this is difficult to select which benchmark to use. Can `spectral entropy` be used for stock volatility? The intuition is that higher the value of spectral entropy more knowledge about underlying function so less volatile is this and less value of spectral entropy more randomness so more volatile.

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