Bayesian Analysis of the Box-Cox Transformation in Stochastic Volatility Models

Journal Title: Dynamic Econometric Models - Year 2009, Vol 9, Issue 1

Abstract

In the paper, we consider the Box-Cox transformation of financial time series in Stochastic Volatility models. Bayesian approach is applied to make inference about the Box-Cox transformation parameter (). Using daily data (quotations of stock indices), we show that in the Stochastic Volatility models with fat tails and correlated errors (FCSV), the posterior distribution of parameter  strongly depends on the prior assumption about this parameter. In the majority of cases the values of  close to 0 are more probable a posteriori than the ones close to 1.

Authors and Affiliations

Anna Pajor

Keywords

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  • EP ID EP113921
  • DOI -
  • Views 103
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How To Cite

Anna Pajor (2009). Bayesian Analysis of the Box-Cox Transformation in Stochastic Volatility Models. Dynamic Econometric Models, 9(1), 81-90. https://europub.co.uk./articles/-A-113921