A Multivariate Random Walk Model with Slowly Changing Drift and Cross-correlation Applied to Finance

Yuanhua Feng (), David Hand () and Keming Yu ()
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Yuanhua Feng: University of Paderborn
David Hand: Imperial College
Keming Yu: Brunel University
Authors registered in the RePEc Author Service: Yuanhua Feng

No 50, Working Papers CIE from Paderborn University, CIE Center for International Economics

Abstract: A new multivariate random walk model with slowly changing drift and cross-correlations for multivariate processes is introduced and investigated in detail. In the model, not only the drifts and the cross-covariances but also the cross-correlations between single series are allowed to change slowly over time. The model can accompany any number of components such as many number of assets. The model is particularly useful for modelling and forecasting the value of financial portfolios under very complex market conditions. Kernel estimation of local covariance matrix is used. The integrated effect of the estimation errors involved in estimating the integrated processes is derived. Practical relevance of the model and estimation is illustrated by application to several foreign exchange rates.

Keywords: Forecasting; Kernel estimation; Multivariate time series analysis; Portfolio return; Slowly changing multivariate random walk (search for similar items in EconPapers)
Pages: 26 pages
Date: 2012-05
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