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Cross-sectional Tests of Conditional Asset Pricing Models: Evidence from the German Stock Market


  • We thank Theofanis Archontakis, Erik Lüders, Emanuel Mönch, Waldemar Rotfuss and seminar participants at Humboldt University Berlin, the joint finance seminar of the Universities of Cologne and Tübingen 2006, the annual meetings of the European Financial Management Association (EFMA, Madrid) 2006, the German Finance Association (DGF, Östrich-Winkel) 2006 and the Swiss Society for Financial Market Research (SGF, Zürich) 2007 for helpful comments and discussions. We are also grateful to an anonymous referee and the editor, John Doukas, for their valuable comments. In particular, we want to thank Anja Schulz for substantial assistance with data construction and Stefan Frey and Joachim Grammig for helpful advice and providing us with their GMM library for Gauss. Access to the German bond database of Wolfgang Bühler, University of Mannheim, is gratefully acknowledged. Zohal Hessami provided excellent research assistance. This research benefited from financial support of Fritz Thyssen Foundation. Earlier versions of the paper were circulated under the title ‘Evaluating conditional asset pricing models for the German stock’ market. The usual disclaimer applies.


We study the performance of conditional asset pricing models and multifactor models in explaining the German cross-section of stock returns. We focus on several variables, which (according to previous research) are associated with market expectations on future market excess returns or business cycle conditions. Our results suggest that the empirical performance of the Capital Asset Pricing Model (CAPM) can be improved when allowing for time-varying parameters of the stochastic discount factor. A conditional CAPM using the term spread explains the returns on our size and book-to-market sorted portfolios about as well as the Fama-French three-factor model and performs best in terms of the Hansen-Jagannathan distance. Structural break tests do not necessarily indicate parameter instability of conditional model specifications. Another major finding of the paper is that the Fama-French model – despite its generally good cross-sectional performance – is subject to model instability. Unconditional models, however, do a better job than conditional ones at capturing time-series predictability of the test portfolio returns.

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