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Self-affinity in financial asset returns

Goddard, J. and Onali, E. (2012) Self-affinity in financial asset returns. International Review of Financial Analysis, 24. pp. 1-11. DOI: 10.1016/j.irfa.2012.06.004

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Abstract

We test for departures from normal and independent and identically distributed (NIID) log returns, for log returns under the alternative hypothesis that are self-affine and either long-range dependent, or drawn randomly from an L-stable distribution with infinite higher-order moments. The finite sample performance of estimators of the two forms of self-affinity is explored in a simulation study. In contrast to rescaled range analysis and other conventional estimation methods, the variant of fluctuation analysis that considers finite sample moments only is able to identify both forms of self-affinity. When log returns are self-affine and long-range dependent under the alternative hypothesis, however, rescaled range analysis has higher power than fluctuation analysis. The techniques are illustrated by means of an analysis of the daily log returns for the indices of 11 stock markets of developed countries. Several of the smaller stock markets by capitalization exhibit evidence of long-range dependence in log returns.

Item Type: Article
Subjects: Research Publications
Departments: College of Business, Law, Education and Social Sciences > Bangor Business School
Date Deposited: 09 Dec 2014 16:50
Last Modified: 23 Sep 2015 03:12
ISSN: 1057-5219
URI: http://e.bangor.ac.uk/id/eprint/1212
Identification Number: DOI: 10.1016/j.irfa.2012.06.004
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