Stimulated Maximum Likelihood Estimation of Continuous Time Stochastic Volatility Models
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.
|Date of creation:||Jun 2009|
|Date of revision:|
|Publication status:||Published in SMU Economics and Statistics Working Paper Series|
|Contact details of provider:|| Postal: |
Phone: 65-6828 0832
Fax: 65-6828 0833
Web page: http://www.economics.smu.edu.sg/
More information through EDIRC
|Order Information:|| Email: |
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hull, John C & White, Alan D, 1987. " The Pricing of Options on Assets with Stochastic Volatilities," Journal of Finance, American Finance Association, vol. 42(2), pages 281-300, June.
- Jun Yu, 2004.
"On Leverage in a Stochastic Volatility Model,"
13-2004, Singapore Management University, School of Economics.
- BAUWENS, Luc & GALLI, Fausto, 2007.
"Efficient importance sampling for ML estimation of SCD models,"
CORE Discussion Papers
2007053, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Bauwens, L. & Galli, F., 2009. "Efficient importance sampling for ML estimation of SCD models," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1974-1992, April.
- BAUWENS, Luc & GALLI, Fausto, . "Efficient importance sampling for ML estimation of SCD models," CORE Discussion Papers RP 2088, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc, BAUWENS & Fausto Galli, 2007. "Efficient importance sampling for ML estimation of SCD models," Discussion Papers (ECON - Département des Sciences Economiques) 2007032, Université catholique de Louvain, Département des Sciences Economiques.
- Ai[diaeresis]t-Sahalia, Yacine & Kimmel, Robert, 2007. "Maximum likelihood estimation of stochastic volatility models," Journal of Financial Economics, Elsevier, vol. 83(2), pages 413-452, February.
- Kleppe, Tore Selland & Skaug, Hans Julius, 2012. "Fitting general stochastic volatility models using Laplace accelerated sequential importance sampling," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3105-3119.
- Nelson, Daniel B., 1990. "ARCH models as diffusion approximations," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 7-38.
- Yu, Jialin, 2007. "Closed-form likelihood approximation and estimation of jump-diffusions with an application to the realignment risk of the Chinese Yuan," Journal of Econometrics, Elsevier, vol. 141(2), pages 1245-1280, December.
- Jones, Christopher S., 2003. "The dynamics of stochastic volatility: evidence from underlying and options markets," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 181-224.
- Cox, John C & Ingersoll, Jonathan E, Jr & Ross, Stephen A, 1985. "A Theory of the Term Structure of Interest Rates," Econometrica, Econometric Society, vol. 53(2), pages 385-407, March.
- Jean-Francois Richard, 2007.
"Efficient High-Dimensional Importance Sampling,"
321, University of Pittsburgh, Department of Economics, revised Jan 2007.
- Durham, Garland B., 2006. "Monte Carlo methods for estimating, smoothing, and filtering one- and two-factor stochastic volatility models," Journal of Econometrics, Elsevier, vol. 133(1), pages 273-305, July.
- Hiroyuki Kawakatsu, 2007. "Numerical integration-based Gaussian mixture filters for maximum likelihood estimation of asymmetric stochastic volatility models," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 342-358, 07.
- Liesenfeld, Roman & Richard, Jean-Francois, 2003. "Univariate and multivariate stochastic volatility models: estimation and diagnostics," Journal of Empirical Finance, Elsevier, vol. 10(4), pages 505-531, September.
- Jean-Francois Richard & Roman Liesenfeld, 2007.
"Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models,"
322, University of Pittsburgh, Department of Economics, revised Jan 2004.
- Roman Liesenfeld & Jean-Francois Richard, 2006. "Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 335-360.
When requesting a correction, please mention this item's handle: RePEc:siu:wpaper:20-2009. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (QL THor)
If references are entirely missing, you can add them using this form.