Publication Type

Working Paper

Publication Date

7-2008

Abstract

This paper examines how volatility responds to return news in the context of stochastic volatility (SV) using a nonparametric method. The correlation structure in the classical leverage SV model is generalized based on a linear spline. In the new model the correlation between the return innovation and volatility innovation is dependent on the type of news arrived to the market. Theoretical properties of the proposed model are examined. A simulation-based maximum likelihood method is developed to estimate the new model. Simulations show that the estimation method provides reliable parameter estimates. The new model is fitted to daily and weekly data in the US and compared with the classical SV models in terms of their in-sample and out-of-sample performances. Empirical results suggest strong evidence in favor of the proposed model. In particular, the new model finds strong evidence of leverage effect when the classical model fails to identify it. Also, the new model provides better out-of-the-sample forecasts of volatility than the classical model.

Keywords

Leverage effect, Simulated maximum likelihood, Laplace approximation, Spline, Realized volatility

Discipline

Econometrics | Statistics and Probability

Research Areas

Econometrics

First Page

1

Last Page

27

Copyright Owner and License

Author

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Comments

Published in Journal of Econometrics https://doi.org/10.1016/j.jeconom.2011.09.029

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