ANALYTICAL EVALUATION OF VOLATILITY FORECASTS
Torben Andersen (),
Tim Bollerslev () and
International Economic Review, 2004, vol. 45, issue 4, 1079-1110
Estimation and forecasting for realistic continuous-time stochastic volatility models is hampered by the lack of closed-form expressions for the likelihood. In response, Andersen, Bollerslev, Diebold, and Labys ("Econometrica", 71 (2003), 579-625) advocate forecasting integrated volatility via reduced-form models for the realized volatility, constructed by summing high-frequency squared returns. Building on the eigenfunction stochastic volatility models, we present analytical expressions for the forecast efficiency associated with this reduced-form approach as a function of sampling frequency. For popular models like GARCH, multifactor affine, and lognormal diffusions, the reduced form procedures perform remarkably well relative to the optimal (infeasible) forecasts. Copyright 2004 by the Economics Department Of The University Of Pennsylvania And Osaka University Institute Of Social And Economic Research Association.
References: Add references at CitEc
Citations: View citations in EconPapers (111) Track citations by RSS feed
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Working Paper: Analytic Evaluation of Volatility Forecasts (2002)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:ier:iecrev:v:45:y:2004:i:4:p:1079-1110
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0020-6598
Access Statistics for this article
International Economic Review is currently edited by Harold L. Cole
More articles in International Economic Review from Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association 160 McNeil Building, 3718 Locust Walk, Philadelphia, PA 19104-6297. Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and ().