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On the Distributional Characterization of Daily Log‐Returns of a World Stock Index

On the Distributional Characterization of Daily Log‐Returns of a World Stock Index In this paper distributions are identified which suitably fit log‐returns of the world stock index when these are expressed in units of different currencies. By searching for a best fit in the class of symmetric generalized hyperbolic distributions the maximum likelihood estimates appear to cluster in the neighbourhood of those of the Student t distribution. This is confirmed at a high significance level under the likelihood ratio test. Finally, the paper derives the minimal market model, which explains the empirical findings as a consequence of the optimal market dynamics. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Mathematical Finance Taylor & Francis

On the Distributional Characterization of Daily Log‐Returns of a World Stock Index

Applied Mathematical Finance , Volume 13 (1): 20 – Mar 1, 2006
20 pages

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References (37)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1466-4313
eISSN
1350-486X
DOI
10.1080/13504860500394052
Publisher site
See Article on Publisher Site

Abstract

In this paper distributions are identified which suitably fit log‐returns of the world stock index when these are expressed in units of different currencies. By searching for a best fit in the class of symmetric generalized hyperbolic distributions the maximum likelihood estimates appear to cluster in the neighbourhood of those of the Student t distribution. This is confirmed at a high significance level under the likelihood ratio test. Finally, the paper derives the minimal market model, which explains the empirical findings as a consequence of the optimal market dynamics.

Journal

Applied Mathematical FinanceTaylor & Francis

Published: Mar 1, 2006

Keywords: World stock index; log‐return distribution; Student t distribution; symmetric generalized hyperbolic distribution

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