Dallas, and the First Annual Texas Finance Festival for discussions and comments helpful to the evolution of the paper. Pattarake Sarajoti provided valuable assistance. Mann acknowledges the support of the Charles Tandy American Enterprise Center. A good portion of this work was completed while Locke was on the staff of the U.S. Commodity Futures Trading Commission. However, the views expressed are the authors ’ only and do not purport to represent the views of the Commodity Futures Trading Commission or its staff. Do Professional Traders Exhibit Loss Realization Aversion? Recent evidence (e.g. Odean, 1998a) describes investor behavior that is at odds with traditional economic theory. These alternative behaviors, such as those consistent with the disposition effect or overconfidence, form the basis for recent "behavioral " explanations for asset returns (e.g. Daniel, Hirshleifer and Subrahmanyam 1998a and 1998b, Odean 1998b, and Shumway, 1998). Notably, the evidence of alternative investor behavior is based largely on retail customer accounts- those of amateur traders. In this paper we examine trades by populations of professional futures traders for evidence of activity best described by the “behavioral finance ” literature. The data provide

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Theoretical models predict that overconfident investors will trade more than rational investors. We directly test this hypothesis by correlating individual overconfidence scores with several measures of trading volume of individual investors (number of trades, turnover). Approximately 3000 online broker investors were asked to answer an internet questionnaire which was designed to measure various facets of overconfidence (miscalibration, the better than average effect, illusion of control, unrealistic optimism). The measures of trading volume were calculated by the trades of 215 individual investors who answered the questionnaire. We find that investors who think that they are above average in terms of investment skills or past performance trade more. Measures of miscalibration are, contrary to theory, unrelated to measures of trading volume. This result is striking as theoretical models that incorporate overconfident investors mainly motivate this assumption by the calibration literature and model overconfidence as underestimation of the variance of signals. The results hold even when we control for several other determinants of trading volume in a cross-sectional regression analysis. In connection with other recent findings, we conclude that the usual way of motivating and modelling overconfidence which is mainly based on the calibration literature has to be treated with caution. We