Behavioral finance is the study of human behavior and how that behavior leads to investment errors—including the mispricing of assets. I find it to be the most interesting area of financial research, as it provides us with important insights we can use to improve investor behavior and produce better investment results. If investors are made aware of their biases and the negative impact they are likely to have on their returns, they are more likely to change their behavior.
The field of behavioral finance has gained an increasing amount of attention in academia during the past 15 years or so as more and more pricing anomalies have been discovered. Pricing anomalies present a problem for those who believe in the efficient markets hypothesis. Among the many anomalies researchers have found is that individual investors have a preference (or taste) for gambling when buying individual stocks.
For example, research has found that individuals prefer stocks with low nominal prices, high volatility (and high beta) and high positive skewness (in which returns to the right of, or more than, the mean are fewer, but further from it, than returns to the left of, or less than, the mean, like a lottery ticket).
Research has also found that investors with gambling preferences trade actively, and that their trading activities are often correlated. As demonstrated by evidence presented in previous articles in this series (which you can find here, here, here and here), these preferences, combined with limits to arbitrage (which can prevent more sophisticated investors from correcting mispricings), have led to the overvaluation of “gambling” stocks and thus poor nominal returns, and even worse risk-adjusted returns.
Stocks & Lotteries
Alok Kumar, Jeremy Page and Oliver Spalt, contribute to the literature on investor behavior and its implication for stock prices with their study, “Gambling and Comovement,” which appears in the February 2016 issue of the Journal of Financial and Quantitative Analysis.
They constructed a lottery index (LIDX) by identifying lotterylike stocks, which are stocks that share certain features of attractive monetary gambles (low price, high volatility and high positive skewness). They also tested whether the degree of return co-movement among lotterylike stocks is stronger for lottery stocks that are disproportionately held by gambling-motivated investors.
The authors accomplished this by using a ratio of Catholics to Protestants in the local population (or CPRATIO), which research has shown to be an effective proxy for the gambling propensity of local investors. Religion-based differences in gambling norms have been shown to influence people’s actual gambling behavior.
Motivated by prior research, they conjectured that the “CPRATIO around a firm’s headquarters would reflect the gambling propensity of the firm’s investors. All else equal, a firm located in a high-CPRATIO region would have an investor clientele that is more likely to gamble.”
Their sample covered the period 1980 through 2005. Following is a summary of their findings:
- Large numbers of stocks, 14.3% of all stocks (12.0% by market capitalization) in the Center for Research in Security Prices universe, are significantly affected by gambling sentiment. This is an economically significant percentage of stocks that co-move significantly with a portfolio of high-LIDX stocks.
- Return co-movement among lotterylike stocks is strongest for lottery stocks located in regions where investors have stronger preferences for gambling, as proxied by the CPRATIO.
- Lotterylike stocks co-move strongly with one another, providing evidence that this return co-movement is generated by the correlated trading of gambling-motivated investors.
- High-LIDX stocks not only co-move significantly with one another, but are also less sensitive to other standard investment factors (beta, size, value and momentum).
- Retail as well as institutional investors in high-CPRATIO areas allocate larger portfolio weights to local as well as nonlocal high-LIDX stocks, and trade them more actively.
- Retail investor trades are more correlated, and comprise a larger fraction of trading volume, when CPRATIO and LIDX are high. Institutional investors exhibit a similar, but weaker, pattern.
- The relation between CPRATIO and lottery-stock co-movement is strongest when gambling enthusiasm, as proxied by state lottery sales, is high.
- The relation between CPRATIO and lottery-stock co-movement is stronger when the local economy performs well, which allows gambling-motivated investors to increase their demand for lotterylike stocks.
- Excess return co-movement is higher for stocks that are held more often by investors from higher-CPRATIO areas; younger investors; lower-income, nonprofessional, unmarried and male investors; and investors with lower education levels and more concentrated portfolios. These groups tend to exhibit a stronger preference for gambling (which negatively impacts returns).
Kumar, Page and Spalt noted that their findings were robust to explicit controls for local income, education and other geographic characteristics (such as local economic conditions) as well as to a variety of firm-level controls and year- and industry-fixed effects, and they weren’t exclusive to financial centers or any particular region in the United States.
They concluded: “We find robust evidence that lottery-like stocks that are disproportionately held by gambling-motivated investors co-move more strongly with other lottery stocks. This suggests that the excess return co-movement we observe among lottery-like stocks is driven by the trading behavior of investors with gambling preferences.”
Their findings have important implications for investors’ portfolio decisions. First, investors who are not aware of their biases, the riskiness of these “gambling stocks” and their poor returns are likely to overweight these stocks in their portfolios.
You no longer have that excuse. Unless you place value on the entertainment aspect of gambling when investing, you should avoid stocks with gambling characteristics, as they have very poor risk-adjusted returns.
This commentary originally appeared December 12 on ETF.com
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