Forecasting international stock market correlations: does anything beat a CCC?

Hans Manner and Olga Reznikova

No 7/10, Discussion Papers in Econometrics and Statistics from University of Cologne, Institute of Econometrics and Statistics

Abstract: It is well known that the correlation between financial series varies over time. Here, the forecasting performance of different time-varying correlation models is compared for cross-country correlations of weekly G5 and daily European stock market indices. In contrast to previous studies only the correlation and not the entire covariance matrix is forecasted and multi-step forecasts are considered. The forecast comparison is done by considering statistical and economic criteria. The results suggest that under a statistical criterion time-varying correlation models perform quite well for weekly data, but cannot outperform the constant correlation model for daily data. Considering economic criteria it is hard to beat a constant correlation model.

Keywords: dynamic conditional correlation; regime switching; stochastic correlation; smooth correlations; indirect model comparison; portfolio construction (search for similar items in EconPapers)
JEL-codes: C53 G17 (search for similar items in EconPapers)
Date: 2010
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