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The relationship between risk and incomplete states uncertainty: a Tsallis entropy perspective

Author

Listed:
  • Tapiero, Oren J.

    (Université Paris 1 Panthéon-Sorbonne)

Abstract

This paper provides a “non-extensive” information theoretic perspective on the relationship between risk and incomplete states uncertainty. Theoretically and empirically, we demonstrate that a substitution effect between the latter two may take place. Theoretically, the “non-extensive” volatility measure is concave with respect to the standard (based on normal distribution) volatility measure. With the degree of concavity depending on an incomplete states uncertainty parameter-the Tsallis-q. Empirically, the latter negatively causes the normal measure of volatility, positively affecting the tails of the distribution of realised log-returns.

Suggested Citation

  • Tapiero, Oren J., 2013. "The relationship between risk and incomplete states uncertainty: a Tsallis entropy perspective," Algorithmic Finance, IOS Press, vol. 2(2), pages 141-150.
    • Handle: RePEc:ris:iosalg:0020
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    Cited by:

    1. Muhammad Sheraz & Imran Nasir, 2021. "Information-Theoretic Measures and Modeling Stock Market Volatility: A Comparative Approach," Risks, MDPI, vol. 9(5), pages 1-20, May.

    More about this item

    Keywords

    Tsallis Entropy; Incomplete Statistics; Volatility; Uncertainty;
    All these keywords.

    JEL classification:

    • D00 - Microeconomics - - General - - - General
    • E00 - Macroeconomics and Monetary Economics - - General - - - General

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