Simulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models

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

Working Papers from Singapore Management University, Sim Kee Boon Institute for Financial 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 modi ed ecient 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: 19 Pages
Date: 2009-06
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Citations: View citations in EconPapers (1)

Published in SMU-SKBI CoFie Working Paper

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http://www.smu.edu.sg/institutes/skbife/downloads/ ... atility%20Models.pdf

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