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A Bayesian Estimation of Stable Distributions

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  • Ece Oral
  • Cenap Erdemir

Abstract

Stable distributions are a rich class of probability distributions that are widely used to model leptokurtic data. Since the probability density and distribution functions are not known in closed form, stable distributions are often specified by their characteristic functions. This paper reviews both the techniques used to compute the density functions and the methods used to estimate parameters of the stable distributions. A new Bayesian approach using Metropolis random walk chain and direct numerical integration is proposed. The performance of the method is examined by a simulation study.

Suggested Citation

  • Ece Oral & Cenap Erdemir, 2012. "A Bayesian Estimation of Stable Distributions," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 1(3), pages 1-4.
  • Handle: RePEc:spt:stecon:v:1:y:2012:i:3:f:1_3_4
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    Cited by:

    1. Kimera Naradh & Retius Chifurira & Knowledge Chinhamu, 2022. "Analysis of stock exchange risk and currency in South African Financial Markets using stable parameter estimation," International Journal of Finance & Banking Studies, Center for the Strategic Studies in Business and Finance, vol. 11(1), pages 120-131, January.

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