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Investigating asymmetry in US stock market indexes: evidence from a stochastic volatility model

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  • Nunzio Cappuccio
  • Diego Lubian
  • Davide Raggi

Abstract

This study provides empirical evidence on asymmetry in financial returns using a simple stochastic volatility model which allows a parsimonious yet flexible treatment of both skewness and heavy tails in the conditional distribution of returns. In particular, it is assumed that returns have a Skew-GED conditional distribution. Inference is conducted under a Bayesian framework using Markov Chain Monte Carlo methods for estimating the properties of the posterior distributions of the parameters. One is also able to perform some specification testing via Bayes factors. The data set consists of daily and weekly returns on the DJ30, S&P500 and Nasdaq US stock market indexes. The estimation results are consistent with the presence of substantial asymmetry and heavy tails in the distribution of US stock market indexes.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

Volume (Year): 16 (2006)
Issue (Month): 6 ()
Pages: 479-490

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Handle: RePEc:taf:apfiec:v:16:y:2006:i:6:p:479-490

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Cited by:
  1. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
  2. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods and Applications, Springer, vol. 20(4), pages 487-506, November.

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