This study shows that individual investors systematically shift their preferences across extreme style portfolios (small vs. large, value vs. growth). These preference shifts are influenced by past style returns and earnings differentials, and advice from investment newsletters, but are unaffected by innovations in macroeconomic variables or shifts in expectations about future cash flows. Furthermore, investors’ dynamic style preferences influence returns along multiple dimensions: i) the contemporaneous relation between style returns and style-level preference shifts is strong, ii) there is weak evidence of style return predictability, and iii) the correlations among stocks within a style increase when investors move into or out of the style with greater intensity. Overall, the results indicate that stock categorization influences investors’ portfolio decisions and stock returns.

This paper uses investor-level data to provide direct evidence for an intuitive but surprisingly untested proposition that investors make larger investment mistakes when valuation uncertainty is higher and stocks are more difficult to value. Using multiple measures of valuation uncertainty and multiple behavioral bias proxies, I show that individual investors exhibit stronger behavioral biases when stocks are harder to value and when market-level uncertainty is higher. I also find that informed trading intensity is higher among stocks where individual investors exhibit stronger behavioral biases. Collectively, these results indicate that uncertainty at both stock and market levels amplifies individual investors’ behavioral biases and that relatively better informed investors attempt to exploit those biases.

This paper examines the characteristics and pricing of stocks that are actively traded by speculative retail investors. We find that stocks with high retail trading proportion (RTP) have strong lottery features and they attract retail investors with strong gambling propensity. Furthermore, these stocks tend to be overpriced and earn significantly negative alpha. The average monthly return differential between the extreme RTP quintiles is −0.60%. This negative RTP premium is stronger among stocks that have lottery features or arelocated in regions where people exhibit stronger gambling propensity. Collectively, these results indicate that speculative retail trading affects stock prices.

Investment managers are subject to personal and institutional norms that can constrain their investment choices. We conjecture that norm-constrained investors deviate from such norms only when they have compelling information, and we predict that deviating investments earn relatively high abnormal returns ex post. Consistent with our conjecture, we find that institutions averse to holding lottery-like stocks or sin stocks earn relatively high abnormal returns when they choose to hold such stocks. We find similar but weaker results for deviations from broader style categories. Overall, our evidence indicates that deviations from established institutional or social norms signal informed investing.

Using a demographics-based proxy for smartness, we show that the portfolio distortions of “smart” investors reflect an informational advantage, while the distortions of “dumb” investors reflect psychological biases. Specifically, smart investors outperform dumb investors by about 3% annually on a risk-adjusted basis. Furthermore, among investors with high portfolio distortions, smart investors outperform passive benchmarks by 2%, and the smart-dumb performance differential is 5%. At the stock level, a portfolio of stocks with smart investor clientele outperforms the dumb clientele portfolio by 3.50% annually. These findings suggest that behavioral and information-based explanations for portfolio distortions apply to distinct subsets of investors.

Using Internet search volume for lottery to capture gambling sentiment shifts, we show that when the overall gambling sentiment is strong, investor demand for lottery stocks increases, these stocks earn positive short-run abnormal returns, managers are more likely to split stocks to cater to the increased demand for low-priced lottery stocks, and initial public offerings (IPOs) earn higher first day returns. Further, the sentiment-return relation is stronger among low institutional ownership firms, headquartered in regions where gambling is more acceptable and local bias is stronger. These results suggest that gambling sentiment has a spillover effect on the stock market.

We demonstrate that personal political preferences of corporate managers influence corporate policies. Specifically, Republican managers who are likely to have conservative personal ideologies adopt and maintain more conservative corporate policies. Those firms have lower levels of corporate debt, lower capital and research and development (R&D) expenditures, less risky investments, but higher profitability. Using the 9/11 terrorist attacks and Sept. 2008 Lehman Brothers bankruptcy as natural experiments, we demonstrate that investment policies of Republican managers became more conservative following these exogenous uncertainty-increasing events. Furthermore, around chief executive officer (CEO) turnovers, including CEO deaths, firm leverage policy becomes more conservative when managerial conservatism increases.

We study the aggregate impact of information spillovers emerging from industry star firms. Changes in stars’ relative earnings growth predict future earnings growth, consensus earnings surprises, and job postings of same-industry nonstar firms. Star-firm performance also predicts industry-level GDP and employment growth. Price markup and innovation spillovers are potential channels underlying these patterns. Our results further show that this performance predictability is not fully incorporated into nonstars’ stock prices. A long–short portfolio based on star firms’ earnings growth earns an annualized 6-factor alpha of 8.7%. Together, our findings provide consistent evidence of the economic importance of star firms.

This study shows that correlated trading by gambling-motivated investors generates excess return comovement among stocks with lottery features. Lottery-like stocks comove strongly with one another, and this return comovement is strongest among lottery stocks located in regions where investors exhibit stronger gambling propensity. Looking directly at investor trades, we find that investors with a greater propensity to gamble trade lottery-like stocks more actively and that those trades are more strongly correlated. Finally, we demonstrate that time variation in general gambling enthusiasm and income shocks from fluctuating economic conditions induce a systematic component in investors’ demand for lottery-like stocks.

This study examines whether state-level economic conditions affect the liquidity of local firms. We find that liquidity levels of local stocks are higher (lower) when the local economy has performed well (poorly). This relation is stronger when local financing constraints are more binding, the local information environment is more opaque, and local institutional ownership levels and trading intensity are higher. Overall the evidence supports the notion that the geographical segmentation of U.S. capital markets generates predictable patterns in local liquidity.