Stimulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models

Tore Kleppe (), Jun Yu and Hans J. Skaug ()
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Hans J. Skaug: University of Bergen

No 20-2009, Working Papers from Singapore Management University, School of Economics

Abstract: In this paper we develop and implement a method for maximum simulated likelihood estimation of the continuous time stochastic volatility model with the constant elasticity of volatility. The approach do not require observations on option prices nor volatility. To integrate out latent volatility from the joint density of return and volatility, a modified efficient importance sampling technique is used after the continuous time model is approximated using the Euler-Maruyama scheme. The Monte Carlo studies show that the method works well and the empirical applications illustrate usefulness of the method. Empirical results provide strong evidence against the Heston model.

Keywords: Efficient importance sampler; Constant elasticity of volatility (search for similar items in EconPapers)
JEL-codes: C11 C15 G12 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2009-06
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Published in SMU Economics and Statistics Working Paper Series

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Related works:
Chapter: Simulated maximum likelihood estimation of continuous time stochastic volatility models (2010)
Working Paper: Simulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models (2009)
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