Causality and forecasting in temporally aggregated multivariate GARCH processes
Christian Hafner ()
Econometrics Journal, 2009, vol. 12, issue 1, 127-146
This paper discusses the effects of temporal aggregation on causality and forecasting in multivariate GARCH processes. It is shown that spurious instantaneous causality in variance will only appear in degenerated cases, but that spurious Granger causality will be more common. For forecasting volatility, it is generally advisable to aggregate forecasts of the disaggregate series rather than forecasting the aggregated series directly, and unlike for vector autoregressive moving average (VARMA) processes, the advantage does not diminish for large forecast horizons. Results are derived for the distribution of multivariate realized volatility if the high-frequency process follows multivariate GARCH. A numerical example illustrates some of the results. Copyright The Author(s). Journal compilation Royal Economic Society 2009
References: Add references at CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed
Downloads: (external link)
http://www.blackwell-synergy.com/doi/abs/10.1111/j.1368-423X.2008.00276.x link to full text (text/html)
Access to full text is restricted to subscribers.
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:ect:emjrnl:v:12:y:2009:i:1:p:127-146
Ordering information: This journal article can be ordered from
Access Statistics for this article
Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms
More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing ().