How to measure risk in asset pricing models: entropy or beta?

Authors

DEEVA Galina

Year of publication 2017
Type Article in Proceedings
Conference Enterprise and Competitive Environment Conference Proceedings
MU Faculty or unit

Faculty of Economics and Administration

Citation
Web https://ece.pefka.mendelu.cz/sites/default/files/imce/ECE2017_fin.pdf
Field Management and administrative
Keywords entropy; risk measure; beta; asset pricing
Description Financial theory borrows scientific methods from natural sciences. In this paper, we consider one of such methods called entropy, which in financial terms can be considered as a measure of risk in asset pricing models. We propose three different non-parametric estimation techniques to estimate financial entropy, the results of which we compare to the CAPM beta based on their explanatory power to describe the diversity in expected risk premiums. Kernel density estimated Shannon entropy provides the most efficient results not dependent on the choice of the market benchmark and without imposing any prior model restrictions. Kernel density estimated Rényi entropy and maximum likelihood estimated Shannon entropy also perform better in-sample than the CAPM beta.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.