We explore behavioral explanations for sub-optimal corporate investment decisions. Focusing on the sensitivity of investment to cash flow, we argue that personal characteristics of chief executive officers, in particular overconfidence, can account for this widespread and persistent investment distortion. Overconfident CEOs overestimate the quality of their investment projects and view external finance as unduly costly. As a result, they invest more when they have internal funds at their disposal. We test the overconfidence hypothesis, using data on personal portfolio and corporate investment decisions of CEOs in Forbes 500 companies. We classify CEOs as overconfident if they repeatedly fail to exercise options that are highly in the money, or if they habitually acquire stock of their own company. The main result is that investment is significantly more responsive to cash flow if the CEO displays overconfidence. In addition, we identify personal characteristics other than overconfidence (education, employment background, cohort, military service, and status in the company) that strongly affect the correlation between investment and cash flow. We are indebted to Brian Hall and David Yermack for providing us with the data. We are very grateful to Jeremy Stein for his invaluable support and comments. We also would like to thank Philippe Aghion, George

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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

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