Fractal properties, information theory, and market efficiency

Xavier Brouty and Matthieu Garcin

Chaos, Solitons & Fractals, 2024, vol. 180, issue C

Abstract: Considering that both the entropy-based market information and the Hurst exponent are useful tools for determining whether the efficient market hypothesis holds for a given asset, we study the link between the two approaches. We thus provide a theoretical expression for the market information when log-prices follow either a fractional Brownian motion or its stationary extension using the Lamperti transform. In the latter model, we show that a Hurst exponent close to 1/2 can lead to a very high informativeness of the time series, because of the stationarity mechanism induced by the Lamperti transform. This result contrasts with the zero information of the fractional Brownian motion for the same value of the Hurst exponent. In addition, we introduce a multiscale method to get a deeper interpretation of the entropy and of the market information, depending on the size of the information set. Applications to Bitcoin, CAC 40 index, Nikkei 225 index, and EUR/USD FX rate, using daily or intraday data, illustrate the methodological content.

Keywords: Fractional brownian motion; Hurst exponent; Market information; Multiscale entropy; Shannon entropy; Stationary process (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:180:y:2024:i:c:s0960077924000948

DOI: 10.1016/j.chaos.2024.114543

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