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Comparison between Information Theoretic Measures to Assess Financial Markets

Author

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  • Luckshay Batra

    (Department of Applied Mathematics, Delhi Technological University, Delhi 110042, India)

  • Harish Chander Taneja

    (Department of Applied Mathematics, Delhi Technological University, Delhi 110042, India)

Abstract

Information theoretic measures were applied to the study of the randomness associations of different financial time series. We studied the level of similarities between information theoretic measures and the various tools of regression analysis, i.e., between Shannon entropy and the total sum of squares of the dependent variable, relative mutual information and coefficients of correlation, conditional entropy and residual sum of squares, etc. We observed that mutual information and its dynamical extensions provide an alternative approach with some advantages to study the association between several international stock indices. Furthermore, mutual information and conditional entropy are relatively efficient compared to the measures of statistical dependence.

Suggested Citation

  • Luckshay Batra & Harish Chander Taneja, 2022. "Comparison between Information Theoretic Measures to Assess Financial Markets," FinTech, MDPI, vol. 1(2), pages 1-18, May.
    • Handle: RePEc:gam:jfinte:v:1:y:2022:i:2:p:11-154:d:819564
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    References listed on IDEAS

    as
    1. Andreia Dionisio & Rui Menezes & Diana A. Mendes, 2007. "Entropy and Uncertainty Analysis in Financial Markets," Papers 0709.0668, arXiv.org.
    2. Batra, Luckshay & Taneja, H.C., 2020. "Evaluating volatile stock markets using information theoretic measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    3. M. Tumminello & T. Di Matteo & T. Aste & R. N. Mantegna, 2007. "Correlation based networks of equity returns sampled at different time horizons," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 209-217, January.
    4. Batra, Luckshay & Taneja, H.C., 2021. "Approximate-Analytical solution to the information measure’s based quanto option pricing model," Chaos, Solitons & Fractals, Elsevier, vol. 153(P1).
    5. Les Gulko, 1999. "The Entropy Theory Of Stock Option Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 331-355.
    6. Darbellay, Georges A & Wuertz, Diethelm, 2000. "The entropy as a tool for analysing statistical dependences in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 429-439.
    7. Xue Guo & Hu Zhang & Tianhai Tian, 2018. "Development of stock correlation networks using mutual information and financial big data," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-16, April.
    8. Mihály Ormos & Dávid Zibriczky, 2014. "Entropy-Based Financial Asset Pricing," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-21, December.
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    Cited by:

    1. Emanuele Citera & Francesco De Pretis, 2023. "An Information Theory Approach to the Stock and Cryptocurrency Market: A Statistical Equilibrium Perspective," Papers 2310.04907, arXiv.org.

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