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Title:Forecasting international stock market correlations: does anything beat a CCC? PDF Logo
Authors:Manner, Hans
Reznikova, Olga
Issue Date:2010
Series/Report no.:Discussion papers in statistics and econometrics 7/10
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.
Subjects:dynamic conditional correlation
regime switching
stochastic correlation
smooth correlations
indirect model comparison
portfolio construction
JEL:C53
G17
Document Type:Working Paper
Appears in Collections:Discussion Papers in Statistics and Econometrics, Seminar für Wirtschafts- und Sozialstatistik, Universität Köln

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