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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Volume (Year): 16 (2006) Issue (Month): 6 (March) Pages: 479-490 Download reference. The following formats are available: HTML
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Ghysels, E. & Harvey, A. & Renault, E., 1995.
"Stochastic Volatility,"
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95.400, Toulouse - GREMAQ.
Other versions:
Ghysels, E. & Harvey, A. & Renault, E., 1996.
"Stochastic Volatility,"
Cahiers de recherche
9613, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
Ghysels, E. & Harvey, A. & Renault, E., 1996.
"Stochastic Volatility,"
Cahiers de recherche
9613, Universite de Montreal, Departement de sciences economiques.
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