Correlated Trading and Returns

A German broker’s clients place similar speculative trades and therefore tend to be on the same side of the market in a given stock during a given day, week, month, and quarter. Aggregate liquidity effects, short sale constraints, the systematic execution of limit orders (coordinated through price movements) or the correlated trading of other investors who pick off retail limit orders do not fully explain why retail investors trade similarly. Correlated market orders lead returns, presumably due to persistent speculative price pressure. Correlated limit orders also predict subsequent returns, consistent with executed limit orders being compensated for accommodating liquidity demands. ACROSS ALL MARKET PARTICIPANTS, trades net to zero in each stock: There is a buyer for every seller. However, subgroups of investors may be net buyers or sellers in a given stock during a given period. The subgroup studied in this paper is a sample of more than 37,000 retail clients at one of the three largest German (and European) discount brokers—brokers that do not give investment advice. The clients’ complete daily transaction records, available from February 1998 to May 2000, allow us to address three related questions. First, do retail investors trade more similarly than we would expect them to merely by chance? Second, what coordinates retail trades? Third, what role does correlated retail trading play in price formation? We are not the first to consider these questions. Barber, Odean, and Zhu (2003) report that trades of clients at a U.S. discount broker are correlated at a monthly frequency and that past returns and trading volume help coordinate retail trades. Using the same data, Kumar and Lee (2006) report that retail trading imbalances help explain monthly stock return variation in addition to what can be explained with commonly used empirical asset pricing factors. Both studies, as well as contemporaneous work on the relation between retail trading and price formation (Kaniel, Saar, and Titman (2008), Andrade, Chang, ∗Dorn is with the LeBow College of Business, Drexel University; Huberman is with Columbia Business School and CEPR. Sengmueller is with CentER—Tilburg University and University of Amsterdam. We thank Martin Bohl, Maurice Bun, Larry Glosten, Will Goetzmann, Charlie Himmelberg, Frank de Jong, Anne Dorn, Alexander Ljungqvist, Mark Seasholes, Rob Stambaugh (the editor), Suresh Sundaresan, Russ Wermers, an anonymous referee, seminar participants at the Helsinki School of Economics, and conference participants at the 2006 workshop on “The Architecture of Financial System Stability” in Capri (Italy), the 12th Mitsui Life Symposium on Financial Markets at the University of Michigan, and the 2006 WFA meetings in Keystone for their comments. We also thank Inessa Love for sharing her panel VAR code with us. Daniel Dorn acknowledges financial support from a Dean’s research grant.