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Simulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models

Author

Listed:
  • Tore Selland Kleppe

    (University of Bergen)

  • Hans J. Skaug

    (University of Bergen)

  • Jun Yu

    (Sim Kee Boon Institute for Financial Economics, Singapore Management University)

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.

Suggested Citation

  • Tore Selland Kleppe & Hans J. Skaug & Jun Yu, 2009. "Simulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models," Working Papers CoFie-09-2009, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    • Handle: RePEc:skb:wpaper:cofie-09-2009
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    File URL: http://www.smu.edu.sg/institutes/skbife/downloads/CoFiE/Working%20Papers/Simulated%20Maximum%20Likelihood%20Estimation%20of%20Continuous%20Time%20Stochastic%20Volatility%20Models.pdf
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    Cited by:

    1. Niu Wei-Fang, 2013. "Maximum likelihood estimation of continuous time stochastic volatility models with partially observed GARCH," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 421-438, September.

    More about this item

    Keywords

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    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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