Entropy-Based Financial Asset Pricing

TL;DR

This paper introduces entropy as a novel risk measure in financial asset pricing, demonstrating its superior explanatory power over traditional beta and its dynamic behavior over time.

Contribution

It proposes entropy as an alternative risk measure, showing its effectiveness in explaining asset returns better than CAPM beta and analyzing its properties in portfolio contexts.

Findings

Entropy explains equity premiums more simply and effectively than beta.

Efficient portfolios lie on a hyperbola in the return-entropy space.

Entropy exhibits higher explanatory power and time variation compared to beta.

Abstract

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return - entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behaviour of the beta along with entropy.