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Franck, A., Walter, A. Portfolio Complexity and Herd Behavior: Evidence from the German Mutual Fund Market. Credit and Capital Markets – Kredit und Kapital, 45(3), 343-371. https://doi.org/10.3790/kuk.45.3.343
Franck, Alexander and Walter, Andreas "Portfolio Complexity and Herd Behavior: Evidence from the German Mutual Fund Market" Credit and Capital Markets – Kredit und Kapital 45.3, 2012, 343-371. https://doi.org/10.3790/kuk.45.3.343
Franck, Alexander/Walter, Andreas (2012): Portfolio Complexity and Herd Behavior: Evidence from the German Mutual Fund Market, in: Credit and Capital Markets – Kredit und Kapital, vol. 45, iss. 3, 343-371, [online] https://doi.org/10.3790/kuk.45.3.343

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Portfolio Complexity and Herd Behavior: Evidence from the German Mutual Fund Market

Franck, Alexander | Walter, Andreas

Credit and Capital Markets – Kredit und Kapital, Vol. 45 (2012), Iss. 3 : pp. 343–371

7 Citations (CrossRef)

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Author Details

Alexander Franck, Justus Liebig University Giessen, Department of Financial Services, Licher Straße 74, D-35394 Giessen

Prof. Dr. Andreas Walter, Justus Liebig University Giessen, Department of Financial Services, Licher Straße 74, D-35394 Giessen

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Abstract

Portfolio Complexity and Herd Behavior: Evidence from the German Mutual Fund Market

We examine the herd behavior among equity funds in Germany based on a large sample of funds from 2000 to 2009. We show that a large portion of the detected herding can be explained by identical trading among funds of the same investment company. However, we also find statistically significant stock herding among funds belonging to different fund families. In contrast to existing herding studies which analyze herd behavior within a purely national stock environment, we investigate mutual fund herding in international stocks. We contribute to the literature by analyzing the impact of portfolio complexity on herd behavior. We find the most pronounced levels of herding for funds choosing their portfolio stocks from a broad, international and therefore complex investment universe. Further, we approximate a fund's portfolio complexity by its size and find high levels of herding among the biggest funds. To analyze the herd behavior of individual funds, we introduce a new and intuitive way to assign levels of herding to funds according to their trading activity within a given period. We show that managers differentiate between buy-herding and sell-herding and that individual funds exhibit similar herding intensities within a given and a succeeding period. (JEL D82, G11, G23)