This study shows that the propensity to gamble and investment decisions are correlated. At the aggregate level, individual investors prefer stocks with lottery features, and like lottery demand, the demand for lottery-type stocks increases during economic downturns. In the cross-section, socioeconomic factors that induce greater expenditure in lotteries are associated with greater investment in lottery-type stocks. Further, lottery investment levels are higher in regions with favorable lottery environments. Because lottery-type stocks underperform, gambling-related underperformance is greater among low-income investors who excessively overweight lottery-type stocks. These results indicate that state lotteries and lottery-type stocks attract very similar socioeconomic clienteles.

This study shows that the propensity to gamble and investment decisions are correlated. At the aggregate level, individual investors prefer stocks with lottery features, and like lottery demand, the demand for lottery‐type stocks increases during economic downturns. In the cross‐section, socioeconomic factors that induce greater expenditure in lotteries are associated with greater investment in lottery‐type stocks. Further, lottery investment levels are higher in regions with favorable lottery environments. Because lottery‐type stocks underperform, gambling‐related underperformance is greater among low‐income investors who excessively overweight lottery‐type stocks. These results indicate that state lotteries and lottery‐type stocks attract very similar socioeconomic clienteles.

Alfred Cowles' test of the Dow Theory apparently provides strong evidence against the ability of Wall Street's most famous chartist to forecast the stock market. Cowles (1934) analyzes editorials published by the chief exponent of the Dow Theory, William Peter Hamilton. We review Cowles' evidence and find that it supports the contrary conclusion. Hamilton's timing strategies actually yield high Sharpe ratios and positive alphas for the period 1902 to 1929. Neural net modeling to replicate Hamilton's market calls provides interesting insight into the Dow Theory and allows us to examine the properties of the theory itself out of sample.

We study stock holdings and trading behavior of more than 60,000 households and find evidence consistent with dividend clienteles. Retail investor stock holdings indicate a preference for dividend yield that increases with age and decreases with income, consistent with age and tax clienteles, respectively. Trading patterns reinforce this evidence: Older, low‐income investors disproportionally purchase stocks before the ex‐dividend day. Furthermore, among small stocks, the ex‐day price drop decreases with age and increases with income, consistent with clientele effects. Finally, consistent with the behavioral “attention” hypothesis, we document that older and low‐income investors purchase stocks following dividend announcements.

This study examines whether local stock returns vary with local business cycles in a predictable manner. We find that U.S. state portfolios earn higher future returns when state‐level unemployment rates are higher and housing collateral ratios are lower. During the 1978 to 2009 period, geography‐based trading strategies earn annualized risk‐adjusted returns of 5%. This abnormal performance reflects time‐varying systematic risks and local‐trading induced mispricing. Consistent with the mispricing explanation, the evidence of predictability is stronger among firms with low visibility and high local ownership. Nonlocal domestic and foreign investors arbitrage away the predictable patterns in local returns in 1 year.

Using a database of more than 1.85 million retail investor transactions over 1991–1996, we show that these trades are systematically correlated—that is, individuals buy (or sell) stocks in concert. Moreover, consistent with noise trader models, we find that systematic retail trading explains return comovements for stocks with high retail concentration (i.e., small‐cap, value, lower institutional ownership, and lower‐priced stocks), especially if these stocks are also costly to arbitrage. Macroeconomic news and analyst earnings forecast revisions do not explain these results. Collectively, our findings support a role for investor sentiment in the formation of returns.

Alfred Cowles' test of the Dow Theory apparently provides strong evidence against the ability of Wall Street's most famous chartist to forecast the stock market. Cowles (1934) analyzes editorials published by the chief exponent of the Dow Theory, William Peter Hamilton. We review Cowles' evidence and find that it supports the contrary conclusion. Hamilton's timing strategies actually yield high Sharpe ratios and positive alphas for the period 1902 to 1929. Neural net modeling to replicate Hamilton's market calls provides interesting insight into the Dow Theory and allows us to examine the properties of the theory itself out of sample.

We propose a theoretical measure of income hedging demand and show that it affects asset prices. We focus on the value factor and first demonstrate that our demand estimates are correlated with the actual demands of retail and mutual fund investors. We then show that the aggregate high‐minus‐low (HML) demand predicts HML returns. Exploiting the state‐level variation in income risk, we demonstrate that state‐level hedging demands predict state‐level HML returns. A long‐short portfolio that exploits this hedging‐induced predictability earns an annualized risk‐adjusted return of 6%.