Research article Special Issues

A new variant of estimation approach to asymmetric stochastic volatilitymodel

  • Received: 31 August 2017 Accepted: 23 April 2018 Published: 09 May 2018
  • JEL Codes: C10, C11, C13, C15, C22, C58, C53

  • 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.

    Citation: Zhongxian Men, Tony S. Wirjanto. A new variant of estimation approach to asymmetric stochastic volatilitymodel[J]. Quantitative Finance and Economics, 2018, 2(2): 325-347. doi: 10.3934/QFE.2018.2.325

    Related Papers:

  • 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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