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Implementing likelihood-based inference for fat-tailed distributions

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  • Rekkas, M.
  • Wong, A.

Abstract

The theoretical advancements in higher-order likelihood-based inference methods have been tremendous over the past two decades. The application of these methods in the applied literature however has been far from widespread. A critical barrier to adoption has likely been the computational difficulties associated with the implementation of these methods. This paper provides the applied researcher with a systematic exposition of the calculations and computer code required to implement the higher-order conditional inference methodology of Fraser and Reid [1995. Utilitas Mathematica 47, 33-53] for problems involving heavy- or fat-tailed distributions.

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Bibliographic Info

Article provided by Elsevier in its journal Finance Research Letters.

Volume (Year): 5 (2008)
Issue (Month): 1 (March)
Pages: 32-46

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Handle: RePEc:eee:finlet:v:5:y:2008:i:1:p:32-46

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Web page: http://www.elsevier.com/locate/frl

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