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

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14560%2F17%3A00108735" target="_blank" >RIV/00216224:14560/17:00108735 - isvavai.cz</a>
Result on the web
<a href="https://ece.pefka.mendelu.cz/sites/default/files/imce/ECE2017_fin.pdf" target="_blank" >https://ece.pefka.mendelu.cz/sites/default/files/imce/ECE2017_fin.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
How to measure risk in asset pricing models: entropy or beta?
Original language 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.
Czech name
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Czech description
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Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Enterprise and Competitive Environment Conference Proceedings
ISBN
9788075094995
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
224-230
Publisher name
Mendel University in Brno
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000427306200024

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