Shannon entropy: an econophysical approach to cryptocurrency portfolios

TL;DR

This paper applies an econophysical approach to cryptocurrency portfolios, demonstrating that their returns are heavy-tailed and that entropy measures support diversification to reduce risk.

Contribution

It introduces an econophysical framework analyzing cryptocurrency returns and entropy, highlighting non-Gaussian behavior and the benefits of diversification.

Findings

Cryptocurrency returns are heavy-tailed, not Gaussian.

Entropy measures indicate diversification reduces return uncertainty.

Portfolio diversification is effective for risk management.

Abstract

Cryptocurrency markets have attracted many interest for global investors because of their novelty, wide online availability, increasing capitalization and potential profits. In the econophysics tradition we show that many of the most available cryptocurrencies have return statistics that do not follow Gaussian distributions but heavy--tailed distributions instead. Entropy measures are also applied showing that portfolio diversification is a reasonable practice for decreasing return uncertainty.