The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks

Liao, Yin (2013) The benefit of modeling jumps in realized volatility for risk prediction : evidence from Chinese mainland stocks. Pacific-Basin Finance Journal, 23, pp. 25-48.

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Abstract

Recent literature has focused on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.

Impact and interest:

8 citations in Scopus
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6 citations in Web of Science®

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ID Code: 61206
Item Type: Journal Article
Refereed: Yes
Keywords: Value at risk (VaR), Realized volatility, Jumps
DOI: 10.1016/j.pacfin.2013.01.002
ISSN: 0927-538X
Divisions: Current > QUT Faculties and Divisions > QUT Business School
Current > Schools > School of Economics & Finance
Copyright Owner: Copyright 2013 Elsevier B.V.
Copyright Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Pacific-Basin Finance Journal. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pacific-Basin Finance Journal, [Volume 23, (June 2013)] DOI: 10.1016/j.pacfin.2013.01.002
Deposited On: 10 Jul 2013 06:40
Last Modified: 10 Jun 2016 15:09

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