Up: 2:2

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

Oren J. Tapiero

Algorithmic Finance (2013), 2:2, 141-150
DOI: 10.3233/AF-13022

Published: Abstract, PDF.
Archived: SSRN.

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.

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AT&T Labs Research

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Massachusetts Institute of Technology

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Wolfram Research

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California Institute of Technology

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Columbia University

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Lawrence Berkeley National Laboratory

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Georgia Tech

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Yale University

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University of Virginia

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University of Lugano

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University of California, San Diego

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