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We use unique data from financial advisers’ professional exam scores and combine it with other variables to create an index of financial sophistication. Using this index to explain long-term stock return expectations, we find that more sophisticated financial advisers tend to have lower return expectations. A one standard deviation increase in the sophistication index reduces expected returns by 1.1 percentage points. The effect is stronger for emerging market stocks (2.3 percentage points). The sophistication effect contributes 60% to the model fit, while employer fixed effects combined contribute less than 30%. These results help understand the formation of potentially excessively optimistic expectations.
This paper investigates whether preference interactions can explain why risk preferences change over time and across contexts. We conduct an experiment in which subjects accept or reject gambles involving real money gains and losses. We introduce within-subject variation by alternating subjectively liked music and disliked music in the background. We find that favourite music increases risk-taking, and disliked music suppresses risk-taking, compared to a baseline of no music. Several theories in psychology propose mechanisms by which mood affects risktaking, but none of them fully explain our results. The results are, however, consistent with preference complementarities that extend to risk preference.
A natural experiment in which customer-owned mutual companies converted to publicly listed firms created a plausibly exogenous shock to the stock market participation status of tens of thousands of people. We find the shock changed the way people vote in the affected areas, with a 10% increase in share-ownership rate being followed by a 1.3%–3.1% increase in right-of-center vote share. The institutional details and additional tests suggest that wealth, liquidity, and tax-related incentives cannot fully explain the results. A plausible explanation is that the associated increase in the salience of stock ownership causes a shift in voters’ attention.
We test whether investor mood affects trading with data on all stock market transactions in Finland, utilizing variation in daylight and local weather. We find some evidence that environmental mood variables (local weather, length of day, daylight saving and lunar phase) affect investors’ direction of trade and volume. The effect magnitudes are roughly comparable to those of classical seasonals, such as the Monday effect. The statistical significance of the mood variables is weak in many cases, however. Only very little of the day-to-day variation in trading is collectively explained by all mood variables and calendar effects, but lower frequency variation seems connected to holiday seasons.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
