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Entropy-Based Financial Asset Pricing

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  • Mihály Ormos
  • Dávid Zibriczky

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 behavior of the beta along with entropy.

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  • Mihály Ormos & Dávid Zibriczky, 2014. "Entropy-Based Financial Asset Pricing," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-21, December.
    • Handle: RePEc:plo:pone00:0115742
    DOI: 10.1371/journal.pone.0115742
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    Cited by:

    1. Nathan Lassance & Frédéric Vrins, 2021. "Minimum Rényi entropy portfolios," Annals of Operations Research, Springer, vol. 299(1), pages 23-46, April.
    2. Daniel Chiew & Judy Qiu & Sirimon Treepongkaruna & Jiping Yang & Chenxiao Shi, 2019. "The predictive ability of the expected utility-entropy based fund rating approach: A comparison investigation with Morningstar ratings in US," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-22, April.
    3. Luckshay Batra & Harish Chander Taneja, 2022. "Comparison between Information Theoretic Measures to Assess Financial Markets," FinTech, MDPI, vol. 1(2), pages 1-18, May.
    4. L. Ponta & A. Carbone, 2019. "Quantifying horizon dependence of asset prices: a cluster entropy approach," Papers 1908.00257, arXiv.org, revised Apr 2020.
    5. Ponta, Linda & Carbone, Anna, 2018. "Information measure for financial time series: Quantifying short-term market heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 132-144.
    6. Pietro Murialdo & Linda Ponta & Anna Carbone, 2020. "Long-Range Dependence in Financial Markets: a Moving Average Cluster Entropy Approach," Papers 2004.14736, arXiv.org.
    7. Galina Deeva, 2017. "Comparing Entropy and Beta as Measures of Risk in Asset Pricing," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(6), pages 1889-1894.
    8. Noe Rodriguez-Rodriguez & Octavio Miramontes, 2022. "Shannon entropy: an econophysical approach to cryptocurrency portfolios," Papers 2210.02633, arXiv.org.
    9. Grilli, Luca & Santoro, Domenico, 2020. "Boltzmann Entropy in Cryptocurrencies: A Statistical Ensemble Based Approach," MPRA Paper 99591, University Library of Munich, Germany.
    10. László Nagy & Mihály Ormos, 2018. "Friendship of Stock Market Indices: A Cluster-Based Investigation of Stock Markets," JRFM, MDPI, vol. 11(4), pages 1-16, December.
    11. Seyma Caliskan Cavdar & Alev Dilek Aydin, 2015. "An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures," JRFM, MDPI, vol. 8(3), pages 1-18, August.
    12. Ormos Mihály & Timotity Dusán, 2017. "The Case of “Less is More”: Modelling Risk-Preference with Expected Downside Risk," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 17(2), pages 1-14, June.
    13. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa & de Oliveira, Wilson & Stosic, Tatijana, 2016. "Foreign exchange rate entropy evolution during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 233-239.
    14. Park, Sangjin & Jang, Kwahngsoo & Yang, Jae-Suk, 2021. "Information flow between bitcoin and other financial assets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    15. Harshit Mishra & Parama Barai, 2024. "Entropy Augmented Asset Pricing Model: Study on Indian Stock Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(1), pages 81-99, March.
    16. Ponta, Linda & Murialdo, Pietro & Carbone, Anna, 2021. "Information measure for long-range correlated time series: Quantifying horizon dependence in financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).

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