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</script>This paper is concerned with specification for modelling financial leverage effect in the context of stochastic volatility (SV) models. Two alternative specifications co-exist in the literature. One is the Euler approximation to the well known continuous time SV model with leverage effect and the other is the discrete time SV model of Jacquier, Polson and Rossi (2004, Journal of Econometrics, forthcoming). Using a Gaussian nonlinear state space form with uncorrelated measurement and transition errors, I show that it is easy to interpret the leverage effect in the conventional model whereas it is not clear how to obtain the leverage effect in the model of Jacquier et al. Empirical comparisons of these two models via Bayesian Markov chain Monte Carlo (MCMC) methods reveal that the specification of Jacquier et al is inferior. Simulation experiments are conducted to study the sampling properties of the Bayes MCMC for the conventional model.
Quasi maximum likelihood, Applied Statistics, Bayes factors; Leverage effect; Markov chain Monte Carlo; Nonlinear state space models; Quasi maximum likelihood., Markov chain Monte Carlo, Bayes factors, Particle filter, Nonlinear state space models, Econometrics, Leverage effect, jel: jel:C11, jel: jel:G12, jel: jel:C15
Quasi maximum likelihood, Applied Statistics, Bayes factors; Leverage effect; Markov chain Monte Carlo; Nonlinear state space models; Quasi maximum likelihood., Markov chain Monte Carlo, Bayes factors, Particle filter, Nonlinear state space models, Econometrics, Leverage effect, jel: jel:C11, jel: jel:G12, jel: jel:C15
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