Noise Traders Incarnate: Describing a Realistic Noise Trading Process

We estimate a realistic process for noise trading to help theorists calibrate their models. For this purpose we characterize the trades executed by individual investors, who are natural candidates for the role of noise traders because their trades are (on average) cross-correlated, loss making, and weakly correlated with stocks’ future fundamentals. We use transactions data from a retail brokerage house and small TAQ trades, obtaining consistent results. We find that noise trading can be treated as approximately i.i.d. normal at the monthly frequency, thus conforming well to standard modeling assumptions. Weekly trades follow an AR(1) process, but their residuals are not normal. Daily trades require multiple lags and have nonnormal residuals. We provide a complete description of these processes, including estimates of their standard deviation. In line with theory, these estimates are higher for more liquid and volatile stocks. ________________ * Joel Peress is at INSEAD, Boulevard de Constance, 77300 Fontainebleau, France. Email: [email protected]. Daniel Schmidt is at HEC Paris, 1 rue de la Libération, 78350 Jouy-en-Josas, France. Email: [email protected]. For helpful comments, we thank Bernard Dumas, Thierry Foucault and Bart Yueshen as well as seminar participants at INSEAD. We are grateful to Terry Odean for sharing the large discount brokerage data. Joel Peress thanks the AXA Research Fund and the Institut Europlace de Finance for their financial support; he also thanks the Marshall School of Business at the University of Southern California for its hospitality while some of this research was developed.