Implementing likelihood-based inference for fat-tailed distributions

Marie Rekkas and A. Wong

Finance Research Letters, 2008, vol. 5, issue 1, 32-46

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.

Date: 2008
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