IQ and Stock Market Participation

Stock market participation is monotonically related to IQ, controlling for wealth, income, age, and other demographic and occupational information. The high correlation between IQ and participation exists even among the affluent. Supplemental data from siblings, studied with an instrumental variables approach and regressions that control for family effects, demonstrate that IQ's influence on participation extends to females and does not arise from omitted familial and nonfamilial variables. High‐IQ investors are more likely to hold mutual funds and larger numbers of stocks, experience lower risk, and earn higher Sharpe ratios. We discuss implications for policy and finance research.     

Reverse Survivorship Bias

Mutual funds often disappear following poor performance. When this poor performance is partly attributable to negative idiosyncratic shocks, funds' estimated alphas understate their true alphas. This paper estimates a structural model to correct for this bias. Although most funds still have negative alphas, they are not nearly as low as those suggested by the fund‐by‐fund regressions. Approximately 12% of funds have net four‐factor model alphas greater than 2% per year. All studies that run fund‐by‐fund regressions to draw inferences about the prevalence of skill among mutual fund managers are subject to reverse survivorship bias.     

Do Limit Orders Alter Inferences about Investor Performance and Behavior?

Individual investors lose money around earnings announcements, experience poor posttrade returns, exhibit the disposition effect, and make contrarian trades. Using simulations and trading records of all individual investors in Finland, I find that these trading patterns can be explained in large part by investors' use of limit orders. These patterns arise mechanically because limit orders are price‐contingent and suffer from adverse selection. Reverse causality from behavioral biases to order choices does not appear to explain my findings. I propose a simple method for measuring a data set's susceptibility to this limit order effect.     

Return Seasonalities

A strategy that selects stocks based on their historical same‐calendar‐month returns earns an average return of 13% per year. We document similar return seasonalities in anomalies, commodities, and international stock market indices, as well as at the daily frequency. The seasonalities overwhelm unconditional differences in expected returns. The correlations between different seasonality strategies are modest, suggesting that they emanate from different systematic factors. Our results suggest that seasonalities are not a distinct class of anomalies that requires an explanation of its own, but rather that they are intertwined with other return anomalies through shared systematic factors.     

Retail Financial Advice: Does One Size Fit All?

Using unique data on Canadian households, we show that financial advisors exert substantial influence over their clients' asset allocation, but provide limited customization. Advisor fixed effects explain considerably more variation in portfolio risk and home bias than a broad set of investor attributes that includes risk tolerance, age, investment horizon, and financial sophistication. Advisor effects remain important even when controlling flexibly for unobserved heterogeneity through investor fixed effects. An advisor's own asset allocation strongly predicts the allocations chosen on clients' behalf. This one‐size‐fits‐all advice does not come cheap: advised portfolios cost 2.5% per year, or 1.5% more than life cycle funds.