Open almost any stock trading app today and you’ll find something that looks a lot like a casino: flashing notifications, confetti animations after trades, and the constant promise of a quick win. That resemblance isn’t just aesthetic. Both gambling and active trading involve putting money at risk for a potential payoff, and research has long suggested that the same people are drawn to both.
A team of researchers decided to test something specific about this overlap. They wanted to know whether gamblers would trade stocks more often when the prices bounced around more wildly, mimicking the excitement of a game of chance. Their answer, published in the International Journal of Mental Health and Addiction, was yes. And the effect showed up most strongly among people considered to be at lower risk of gambling problems, not those at the highest risk.
The question behind the experiment
Led by Leonardo Weiss-Cohen of the University of Nottingham, along with colleagues at the University of Bristol, Northeastern University, Kingston University, and the University of Leeds, the researchers wanted to move past earlier studies that relied on self-reported trading habits or historical market data. Self-reports can be unreliable because gamblers, research suggests, tend to remember their wins more vividly than their losses. Historical data, meanwhile, makes it hard to tease apart what’s driving any given behavior.
Instead, the team built a controlled experiment. They focused on two concepts worth defining. The first is the Problem Gambling Severity Index (PGSI), a nine-question screening tool that sorts gamblers into four categories ranging from no-risk recreational players up to the highest-risk group, whose gambling causes significant harm. The second is price volatility, which is a measure of how much a stock’s price jumps around. Higher volatility means bigger swings in both directions, which finance researchers typically treat as a stand-in for risk.
Personal finance guides, for decades, have recommended a “buy-and-hold” approach: pick solid investments and leave them alone. Frequent trading tends to produce worse returns because of accumulating fees and bid-ask spreads. Yet people still trade frequently, and the researchers suspected that more volatile markets might tempt gamblers in particular to trade more than is good for them.
Building a stock market in miniature
The team recruited participants through the online platform Prolific, screening thousands of users in the United States to find people who had both gambled in the past year and made real financial investments. They oversampled higher-risk gamblers on purpose, since those individuals are relatively rare in the general population, ending up with 604 participants roughly split across the four PGSI categories.
Each participant was given a simulated trading platform with six fictional stocks. They started with a $103 balance, a mix of a simulated loan and a bonus they earned by completing a typing task designed to make the money feel more like their own. Over 30 simulated days, they could buy and sell shares. Any balance above $100 at the end became a real cash bonus, paid out in addition to a fixed participation fee.
Here’s where the experiment split in two. Half the participants saw stocks with low price volatility (a 0.5% daily standard deviation), while the other half saw high-volatility stocks (1.5% daily). Both groups were guaranteed the same underlying 3.1% return over the 30-day period. The only difference was how bumpy the ride was. Trading carried small costs in the form of bid-ask spreads, meaning frequent trading would erode returns on average.
What the numbers showed
Participants in the high-volatility group made about 17% more trades on average than those in the low-volatility group, about two extra trades per person. This effect held up even after the researchers accounted for individual differences in financial literacy, overconfidence (measured by how much participants expected to outperform the market), age, and gender.
The outcomes in the high-volatility condition also looked a lot like gambling outcomes. While the median final balance was nearly identical across both groups, the high-volatility group had much wider swings. Some participants walked away with as much as $116.99, while others ended below $100 and earned no bonus at all. In the low-volatility group, no one dropped below the starting threshold.
The researchers had also expected a direct link between higher PGSI scores and more trading. The data didn’t clearly support that prediction. However, a follow-up exploratory analysis produced a surprising wrinkle. When the team broke down the effect of volatility by PGSI category, the push toward more trading was strongest among gamblers at the lowest risk levels. Among the highest-risk gamblers, the effect was inconsistent and uncertain.
Why lower-risk gamblers might be the ones to watch
This pattern runs counter to how gambling-related harm is typically addressed. Prevention campaigns and treatment programs usually focus on people with severe gambling disorders. But the experiment suggests that casual or low-risk gamblers may be especially susceptible to the pull of volatile, gambling-like trading products, in part because no one is watching out for them.
For businesses and policymakers, the researchers point to a few practical takeaways. Financial literacy education, while valuable, may not be enough to curb excessive trading on its own, since the effect of volatility persisted even after accounting for how financially knowledgeable participants were. They suggest that regulatory approaches used in gambling, such as limits on the speed of play or restrictions on the most volatile products, could eventually be considered for trading platforms that mimic gambling features.
A few caveats are worth keeping in mind. The experiment used small sums of money in a simplified market, and real-life trading involves much larger stakes and emotional weight. The researchers also had difficulty recruiting enough participants at the very highest PGSI levels, which limits what can be said about that group. And because all participants were gamblers, the study can’t speak directly to how non-gamblers would respond to the same conditions. Still, the findings add to a growing body of work suggesting that the line between investing and gambling is thinner than many assume, and that product design choices may be doing more to shape trader behavior than anyone has fully accounted for.
