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A new variant of estimation approach to asymmetric stochastic volatilitymodel

1 Quantitative Research, JPMorgan Chase & Co., 277 Park Avenue, New York, USA
2 Department of Statistics and Actuarial Science, University of Waterloo, 200 University AvenueWest, Waterloo, Ontario, Canada
3 School of Accounting and Finance, University of Waterloo, 200 University Avenue West, Waterloo,Ontario, Canada

Special Issues: Volatility of Prices of Financial Assets

This paper proposes a novel simulation-based inference for an asymmetric stochastic volatility model. An acceptance-rejection Metropolis-Hastings algorithm is developed for the simulation of latent states of the model. A simple and e cient algorithm is also developed for estimation of a heavy-tailed stochastic volatility model. Simulation studies show that our proposed methods give rise to reasonable parameter estimates. Our proposed estimation methods are then used to analyze a benchmark data set of asset returns.
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