Synchronizing Multivariate Financial Time Series

Francesco Audrino and Peter Bühlmann

May 2001

Abstract

Prices or returns of financial assets are most often collected in local times of the trading markets. The need to synchronize multivariate time series of financial prices or returns is motivated by the fact that information continues to flow for closed markets while others are still open. We propose here a synchronization technique which takes this into account.

Besides the nice interpretation of synchronization, the method potentially increases the predictive performance of any reasonable model. We found empirically that this was the case for the CCC-GARCH(1,1) model for a 7-dimensional time series of daily exchange rate returns. Since multivariate analysis is generally important for analyzing time-changing portfolios and for better portfolio predictions (even when portfolio weights are time-constant), synchronization is a valuable technique for a variety of problems with multivariate financial data.

Download:

Compressed Postscript (227 Kb)
PDF(309 Kb)

Go back to the Research Reports from Seminar für Statistik.