This paper empirically examines the theoretically ambivalent relationship between socially responsible investing (SRI) and stock performance. It extends the existing literature by considering both the US and the entire European stock markets as well as by using consistent world-wide corporate...

We report results on the ex ante predictability of monthly excess stock returns in Germany using real-time and revised macroeconomic data. Our real-time macroeconomic data cover the period 1994-2005. We report three results. 1) Real-time macroeconomic data did not contribute much to ex ante...

Using monthly data for the period 1953-2003, we apply a real-time modeling approach to investigate the implications of U.S. political stock market anomalies for forecasting excess stock returns. Our empirical findings show that political variables, selected on the basis of widely used model...

We compared forecasts of stock market volatility based on real-time and revised macroeconomic data. To this end, we used a new dataset on monthly real-time macroeconomic variables for Germany. The dataset covers the period 1994-2005. We used a statistical, a utility-based, and an options-based...

An asymmetric multivariate generalization of the recently proposed class of normal mixture GARCH models is developed. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the fourth moment are derived, and expressions for the dynamic...

We develop a multivariate generalization of the Markov-switching GARCH model introduced by Haas, Mittnik, and Paolella (2004b) and derive its fourth-moment structure. An application to international stock markets illustrates the relevance of accounting for volatility regimes from both a...

Assessments of investors' risk appetite/aversion stance via indicators often yields results which seem unsatisfactory (see e.g. Illing and Aaron (2005)). Understanding how such indicators work therefore seems essential for further improvements. The present paper seeks to contribute to this...