More Than Money: Experienced Positive Affect Reduces Risk-Taking Behavior on a Real-World Gambling Task.

Previous research indicates that when people participate in multi-trial games of chance, the results of previous trials impact subsequent wager size. For example, the "house money" and "break even" effects suggest that an individual's risk-taking propensity increases when financially winning or losing during a gambling session. Additionally, the "mood maintenance hypothesis" and affect regulation hypothesis suggest that people in positive and negative affective states are less and more likely to gamble than when in neutral affective states, respectively. In the present study, participants completed a series of trials on three computerized slot machines with varying expected values (EV; -10, 0, +10%) of return on investment, and they were paid a percentage of their final bankrolls in real money. Although results did not support the "house money" or "break even" effects, the "mood maintenance hypothesis" was robustly supported in all EV conditions. This is some of the first evidence supporting this theory using an ecologically valid, real-money gambling task.

A fallacious "Gambler's Fallacy"? Commentary on Xu and Harvey (2014).

In their recent article in Cognition, Xu and Harvey (2014) suggested that people who placed wagers on an online gambling site demonstrated very different wagering preferences depending on whether they were on winning or losing streaks. Specifically, they reported that people on winning streaks were more likely to win their subsequent wagers because they chose increasingly "safer," higher-probability bets as the win streak continued. People on losing streaks were more likely to lose their subsequent wagers because they chose "riskier," lower-probability wagers as the losing streak progressed. The authors suggested that individuals on winning and losing streaks both fell prey to the Gambler's Fallacy. Specifically, individuals on winning streaks combatted their expectancy to lose soon by choosing higher-probability wagers (with lower payoffs). Conversely, people on losing streaks expected to win soon and thus preferred lower-probability wagers with higher payoffs. Though their paper is fascinating and contains a remarkable data set, we note that the statistical methods employed by Xu and Harvey are prone to a serious selection bias, such that participants on winning or losing streaks may have already been choosing safer and riskier wagers, respectively, prior to the beginning of their streaks. We suggest easy, intuitive analyses to determine whether the effects reported in Xu and Harvey (2014) are real.