TAILIEUCHUNG - The Cross-section of Conditional Mutual Fund Performance in European Stock Markets 

We also add, to the four-factor model above, country-specic market indexes in some of our analysis to performance models for country-focused funds. For instance, when we turn to such models, a UK fund will have, in addition to the Pan-European factors, a UK market index in a ve- factor model. 11 These augmented models help to control for persistent fund loadings on unpriced factors, as described by Pastor and Stambaugh (2002a). Adding such factors can help tighten the predictive distribution for fund alphas, which can be benecial for the construction of portfolios. . | CFR-working Paper NO. 09-03 The cross-section of conditional Mutual Fund Performance in European Stock Markets A. Banegas B. Gillen A. Tlmmermann R. wermers The Cross-section of Conditional Mutual Fund Performance in European Stock Markets Ayelen Banegasy Ben Gillenz Federal Reserve Board California Institute of Technology Allan Timmermannx Russ Wermers University of California San Diego University of Maryland at College Park 12 June 2012 Abstract This paper implements strategies that use macroeconomic variables to select European equity mutual funds including Pan-European country and sector funds. We find that several macro-variables are useful in locating funds with future outperformance and that countryspecific mutual funds provide the best opportunities for fund rotation strategies using macroeconomic information. Specifically our baseline long-only strategies that exploit time-varying predictability provide four-factor alphas of 12-13 year over the 1993-2008 period. Our study provides new evidence on the skills of local versus Pan-European asset managers as well as how macroeconomic information can be used to locate and time these local fund manager skills. Key words European equity markets mutual fund performance time-varying investment opportunities. JEL codes G11 G15 G23. We thank an anonymous referee for extensive comments that greatly improved the paper. We are also grateful to Otto Kober Global Head of Methodology at Lipper and Matthew Lemieux Research Analyst at Lipper for generously providing the mutual fund data used in this study. We thank Bernard Delbecque of the European Fund and Asset Management Association EFAMA for providing statistics on the number of funds domiciled in Europe with European investment objectives and Alberto Jurij Plazzi for help with the Datastream European stock data. Finally we thank seminar participants at the Fifth Erasmus Conference on Professional Asset Management in Rotterdam Fifth Biennial McGill Global Asset Management

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