In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...

This paper aims at decomposing the forecast error variance of excess returns in five major European stock markets into the variance of news about future excess returns, dividends and real interest rates. Special emphasis is given on the issue of stationarity and structural breaks in the...