Simulated maximum likelihood estimation of continuous time stochastic volatility models

Abstract

In this chapter 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 does 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.

Citation

Selland Kleppe, T., Yu, J. and Skaug, H.J. (2010), "Simulated maximum likelihood estimation of continuous time stochastic volatility models", Greene, W. and Carter Hill, R. (Ed.) Maximum Simulated Likelihood Methods and Applications (Advances in Econometrics, Vol. 26), Emerald Group Publishing Limited, Leeds, pp. 137-161. https://doi.org/10.1108/S0731-9053(2010)0000026009