This paper derives results for the temporal aggregation of multivariate GARCH processes in the general vector specification. It is shown that the class of weak multivariate GARCH processes is closed under temporal aggregation. Fourth moment characteristics turn out to be crucial for the low frequency dynamics for both stock and flow variables. It is shown that spurious instantaneous causality in variance will only appear in degenerated cases, but that spurious Granger causality will be more common. Forecasting volatility, it is generally advisable to aggregate forecasts of the disaggregate series rather than forecasting the aggregated series directly, and unlike for 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. Finally, the estimation problem is discussed. A numerical example illustrates some of the results.

causality in variance, multivariate GARCH, realized volatility, temporal aggregation, volatility forecasts
Time-Series Models; Dynamic Quantile Regressions (jel C22)
Econometric Institute Research Papers
Erasmus School of Economics

Hafner, C.M. (2004). Temporal aggregation of multivariate GARCH processes (No. EI 2004-29). Econometric Institute Research Papers. Retrieved from