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This paper focuses on egocentric biases in financial decisions. Subjects first design a portfolio, whereby each combination of assets yields the same expected return and variance of returns. They are then confronted with two alternative portfolios; the average portfolio and the portfolio of one's selected expert. Illusion of expertise prevails if one prefers nevertheless the own portfolio. Using the random price mechanism reveals that most subjects prefer their own portfolio to the average or the expert's portfolio. Illusion of expertise is shown to be stable individually, over alternatives, and for both elicitation methods, willingness to pay and to accept.

Dynamics of compliance, depending on audit probability, sanctions, and the time lag between audits, are investigated in a tax experiment. Compliance varied significantly over time: it decreased immediately after an audit and increased afterwards, especially if audits were frequent and sanctions high.

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

This paper presents an online-experiment on overconfidence in the context of financial markets. Our subject pool consists of institutional investors, investment advisors and individual investors, all of them being registered users of a large online platform for market sentiment data. Due to their registration, several socioeconomic characteristics of participants can be controlled for in our analysis. It turns out that there are stable differences in overconfidence between the three investor groups. Moreover, investment experience and age have a significant impact on the degree of overconfidence which goes surprisingly in opposite direction. We argue that these results have important implications for studies analyzing the impact of experience on behavior in (financial) markets.

We perform an asset market experiment in order to test the central result coming from the new overconfidence models, namely that high levels of overconfidence lead to enhanced trading activity. We find that overconfidence does engender additional trade. Unlike previous experimental or survey-based evidence, ours is the first study to find this to be so when overconfidence is measured using a calibration-based approach that is most akin to the theoretical literature. Further, we investigate the contention that gender influences trading activity through overconfidence. There is no evidence of this, as women have about the same level of both overconfidence and trading activity as do men, and gender is not a useful explanatory variable of trading in a multivariate regression. 2