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Bekierman, Jeremias and Gribisch, Bastian (2016). Estimating stochastic volatility models using realized measures. Stud. Nonlinear Dyn. Econom., 20 (3). S. 279 - 301. BERLIN: WALTER DE GRUYTER GMBH. ISSN 1558-3708

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Abstract

This paper extends the basic stochastic volatility (SV) model in order to incorporate the realized variance (RV) as an additional measure for the latent daily volatility. The particular model we use explicitly accounts for the dependency between daily returns and measurement errors of the realized volatility estimate. Within a simulation study we investigate the form of the dependency. In order to capture the long memory property of asset volatility, we explore different autoregressive dynamics for the latent volatility process, including heterogeneous autoregressive (HAR) dynamics and a two-component approach. We estimate the model using simulated maximum likelihood based on efficient importance sampling (EIS), producing numerically accurate parameter estimates and filtered state sequences. The model is applied to daily asset returns and realized variances of New York Stock Exchange (NYSE) traded stocks. Estimation results indicate that accounting for the dependency of returns and realized measures significantly affects the estimation results and improves the model fit for all autoregressive dynamics.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Bekierman, Jeremias UNSPECIFIED UNSPECIFIED UNSPECIFIED Gribisch, Bastian UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-274120
DOI:	10.1515/snde-2014-0113
Journal or Publication Title:	Stud. Nonlinear Dyn. Econom.
Volume:	20
Number:	3
Page Range:	S. 279 - 301
Date:	2016
Publisher:	WALTER DE GRUYTER GMBH
Place of Publication:	BERLIN
ISSN:	1558-3708
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language LONG-MEMORY; LEVERAGE; HYPOTHESIS; VARIANCES; RETURNS; NOISE; JUMPS Multiple languages Economics; Social Sciences, Mathematical Methods Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/27412