Estimation of SV Model with Leverage Effect Based on MCMC Technique

Xiao Cui Yin

doi:10.4028/www.scientific.net/AMM.530-531.605

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 530-531Estimation of SV Model with Leverage Effect Based...

Estimation of SV Model with Leverage Effect Based on MCMC Technique

Abstract:

This paper is to study the estimation of stochastic volatility model with leverage effect using Bayesian approach and Markov Chain Monte Carlo (MCMC) simulation technique. The data used is China's Shenzheng stock index. Estimations of model parameters are achieved by using MCMC technique in Openbugs Software, results show that there is leverage effect in Shenzheng stock series, convergence diagnostics suggest that parameters of the model are convergent.

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Periodical:

Applied Mechanics and Materials (Volumes 530-531)

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605-608

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.530-531.605

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Online since:

February 2014

Authors:

Xiao Cui Yin*

Keywords:

Leverage Effect, MCMC, Posterior Distribution, Stochastic Volatility Model

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References

[1] Sorensen, M: Prediction Based Estimating Equations. Econometrics 3, Forthcoming (2000).

Google Scholar

[2] Harvey, A. C., E. Ruiz, and N. Shephard: Multivariate Stochastic Variance Models, Review of Economic Studies, Vol. 61, 1994, p.247–64.

DOI: 10.2307/2297980

Google Scholar

[3] Kim, S., Shephard, N., Chib, S.: Stochastic Volatility: Likelihood Inference and Comparison with ARCH models. Review of Economic Studies, Vol. 65, 1998, pp.361-393.

DOI: 10.1111/1467-937x.00050

Google Scholar

[4] Andersen, T., H. Chung and B. Sorensen: Efficient Method of Moments Estimation of a Stochastic Volatility Model: A Monte Carlo Study. Journal of Econometrics, Vol. 91, 1999, p.61–87.

DOI: 10.1016/s0304-4076(98)00049-9

Google Scholar

[5] Jacquier, E., Nicholas G. P. and Rossi P. E.: Bayesian Analysis of Stochastic Volatility Models withFat-tails and Correlated Errors. Journal of Econometrics, Vol. 122, 2004, pp.185-212.

DOI: 10.1016/j.jeconom.2003.09.001

Google Scholar

[6] Hull, J. and White, A.: The Pricing of Options on Assets with Stochastic Volatilities. Journal of Finance, Vol. 42, 1987, p.281–300.

DOI: 10.1111/j.1540-6261.1987.tb02568.x

Google Scholar

[7] Omori, Y., Chib, S., Shephard, N., Nakajima, J.: Stochastic Volatility with Leverage: Fast Likelihood Inference. Journal of Econometrics Vol. 140, 2007, pp.425-449.

DOI: 10.1016/j.jeconom.2006.07.008

Google Scholar