Publication Type
Working Paper
Version
publishedVersion
Publication Date
11-2009
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
Discipline
Econometrics
Research Areas
Econometrics
First Page
1
Last Page
19
Publisher
SMU Economics and Statistics Working Paper Series, No. 20-2009
City or Country
Singapore
Citation
KLEPPE, Tore Selland; YU, Jun; and SKAUG, Hans J..
Stimulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models. (2009). 1-19.
Available at: https://ink.library.smu.edu.sg/soe_research/1156
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.