EconPapers    
Economics at your fingertips  
 

Comparison of Volatility Measures: a Risk Management Perspective

Christian Brownlees () and Giampiero Gallo ()

Journal of Financial Econometrics, 2010, vol. 8, issue 1, 29-56

Abstract: In this paper we address the issue of forecasting Value--at--Risk (VaR) using different volatility measures: realized volatility, bipower realized volatility, two-scales realized volatility, realized kernel, as well as the daily range. We propose a dynamic model with a flexible trend specification bonded with a penalized maximum likelihood estimation strategy: the P-spline multiplicative error model. Exploiting ultra-high-frequency data (UHFD) volatility measures, VaR predictive ability is considerably improved upon relative to a baseline GARCH but not so relative to the range; there are gains from modeling volatility trends and from using realized kernels that are robust to dependent microstructure noise. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oupjournals.org, Oxford University Press.

Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (69) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1093/jjfinec/nbp009 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Comparison of Volatility Measures: a Risk Management Perspective (2008) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:jfinec:v:8:y:2010:i:1:p:29-56

Ordering information: This journal article can be ordered from
http://www.oup.co.uk/journals

Access Statistics for this article

Journal of Financial Econometrics is currently edited by RenÈ Garcia and Eric Renault

More articles in Journal of Financial Econometrics from Society for Financial Econometrics Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. Contact information at EDIRC.
Bibliographic data for series maintained by Oxford University Press ().

 
Page updated 2019-08-05
Handle: RePEc:oup:jfinec:v:8:y:2010:i:1:p:29-56