Overconfidence and trading volume

Abstract

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. Approximately 3,000 online broker investors were asked to answer an internet questionnaire which was designed to measure various facets of overconfidence (miscalibration, volatility estimates, better than average effect). 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 (but who did not have above average performance in the past) 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. In connection with other recent findings, we conclude that the usual way of motivating and modeling overconfidence which is mainly based on the calibration literature has to be treated with caution. Moreover, our way of empirically evaluating behavioral finance models-the correlation of economic and psychological variables and the combination of psychometric measures of judgment biases (such as overconfidence scores) and field data-seems to be a promising way to better understand which psychological phenomena actually drive economic behavior.

Testing overconfidence bias in Pakistani stock market

“…In second study, bets were produced to make position of value which is independent of overconfidence by taking 384 participants consisting of 105 females and 279 males and they concluded that problem gamblers showed greater overconfidence and bet taking. Glaser and Weber (2007) revealed that more than half of investors believe that their abilities are above average which convinced them to go for excessive trading. Odean (1998) concluded that overconfidence is quality of people, not of markets and studied that how different characteristics of people affect the market.…”

Do we measure overconfidence? A closer look at the interval production task

“…Similarly, exclusion instructions that induce people to think about the values that lie outside of their provided intervals in the IP yield smaller levels of overconfidence than inclusion questions (Soll and Klayman, 2004;Teigen and Jorgensen, 2005;Yaniv and Schul, 1997). Interestingly, other forms of overconfidence such as better-than-average beliefs (Svenson, 1981) or the illusion of control (Langer, 1975) were found to be inconsistent with the IP measure (Deaves et al, 2008;Glaser and Weber, 2007;Hilton et al, 2011;Menkhoff et al, 2006;Moore and Healy, 2008). Moreover, the level of overconfidence has been found to vary with the difficulty (Lichtenstein et al, 1982) and domain (Klayman et al, 1999) of the question set.…”

An Experimental Analysis of Over-Confidence

“…There is a causality bond between return and trading volume. The affirmation that overconfidence induces investors to exchange more aggressively, was also confirmed by many experimental studies [12,13].…”