Estimating Stochastic Volatility Models: A Comparison of Two Importance Samplers

Lee Kai Ming () and Siem Jan Koopman
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Lee Kai Ming: Free University Amsterdam and Tinbergen Institute

Studies in Nonlinear Dynamics & Econometrics, 2004, vol. 8, issue 2, 17

Abstract: In this paper, we describe and compare two simulated Maximum Likelihood estimation methods for a basic stochastic volatility model. For both methods, the likelihood function is estimated using importance sampling techniques. Based on a Monte Carlo study, we assess which method is more effective. Further, we validate the two methods using diagnostic importance sampling test procedures. Stochastic volatility models with Gaussian and Student-t distributed disturbances are considered.

Date: 2004
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DOI: 10.2202/1558-3708.1210

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