Measuring Mutual Fund Herding - A Structural Approach

36 Pages Posted: 5 Mar 2008 Last revised: 8 Jan 2015

See all articles by Stefan Frey

Stefan Frey

Leibniz Universität Hannover; Centre for Financial Research (CFR)

Patrick Herbst

University of Stirling - Department of Accounting and Finance

Andreas Walter

University of Giessen - Department of Financial Services

Date Written: June 27, 2012

Abstract

This paper proposes a methodological improvement to empirical studies of herd behavior based on investor transactions. By developing a simple model of trading behavior, we show that the traditionally used herding measure produces biased results. As this bias depends on characteristics of the data, it also affects the robustness of previous findings. We derive a new measure that is unbiased and shows superior statistical properties for data sets commonly used. In an analysis of the German mutual fund market, our measure provides new insights into fund manager herding that would have been undetected under the traditional statistic.

Keywords: Herding, LSV measure, mutual funds, trading behavior

JEL Classification: G11, G14, G23

Suggested Citation

Frey, Stefan and Herbst, Patrick and Walter, Andreas, Measuring Mutual Fund Herding - A Structural Approach (June 27, 2012). Journal of International Financial Markets, Institutions and Money, Volume 32, September 2014, Pages 219–239. Available at SSRN: https://ssrn.com/abstract=984828 or http://dx.doi.org/10.2139/ssrn.984828

Stefan Frey

Leibniz Universität Hannover

Koenigsworther Platz 1
30167 Hannover, DE 30167
Germany

Centre for Financial Research (CFR) ( email )

Albertus-Magnus Platz
Cologne, 50923
Germany

Patrick Herbst (Contact Author)

University of Stirling - Department of Accounting and Finance ( email )

Stirling, Scotland FK9 4LA
United Kingdom

Andreas Walter

University of Giessen - Department of Financial Services ( email )

Betriebswirtschaftslehre V
Giessen, 35394
Germany

HOME PAGE: http://wiwi.uni-giessen.de/ma/dat/walter/Andreas_Walter/

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
797
Abstract Views
4,680
rank
31,737
PlumX Metrics