A semiparametric stochastic volatility model

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 a...

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Main Author: YU, Jun
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2008
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Online Access:https://ink.library.smu.edu.sg/soe_research/1268
https://ink.library.smu.edu.sg/context/soe_research/article/2267/viewcontent/Semiparametric_Stochastic_Volatility_Model_2008.pdf
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spelling sg-smu-ink.soe_research-22672020-03-31T06:13:38Z A semiparametric stochastic volatility model YU, Jun 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. 2008-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1268 https://ink.library.smu.edu.sg/context/soe_research/article/2267/viewcontent/Semiparametric_Stochastic_Volatility_Model_2008.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Leverage effect Simulated maximum likelihood Laplace approximation Spline Realized volatility Econometrics Statistics and Probability
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Leverage effect
Simulated maximum likelihood
Laplace approximation
Spline
Realized volatility
Econometrics
Statistics and Probability
spellingShingle Leverage effect
Simulated maximum likelihood
Laplace approximation
Spline
Realized volatility
Econometrics
Statistics and Probability
YU, Jun
A semiparametric stochastic volatility model
description 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.
format text
author YU, Jun
author_facet YU, Jun
author_sort YU, Jun
title A semiparametric stochastic volatility model
title_short A semiparametric stochastic volatility model
title_full A semiparametric stochastic volatility model
title_fullStr A semiparametric stochastic volatility model
title_full_unstemmed A semiparametric stochastic volatility model
title_sort semiparametric stochastic volatility model
publisher Institutional Knowledge at Singapore Management University
publishDate 2008
url https://ink.library.smu.edu.sg/soe_research/1268
https://ink.library.smu.edu.sg/context/soe_research/article/2267/viewcontent/Semiparametric_Stochastic_Volatility_Model_2008.pdf
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