Why are people betting thousands of dollars on how hot it will be in Singapore?

An analysis by The New York Times found that just hours before the US and Israel launched an attack on Iran in March, bets totalling US$855,000 were made on Polymarket correctly predicting the strike.

These bets were anomalous and suggestive of insider knowledge because they broke with the majority of Polymarket users at the time who predicted that a strike would not happen on that day.

In March, Kalshi was sued by users over failing to pay out more than US$54 million to those who had bet that Iran’s then supreme leader, Ayatollah Ali Khamenei, would leave office before March 1.

After he was killed in an air strike, Kalshi reimbursed the fees paid by all users in the market instead of paying out winnings.

Rife criticism that followed can partly explain why users are now turning towards betting on arguably lower-stakes items such as daily temperature.

Dr Jia believes markets have formed around daily temperature because the event is publicly verifiable by the pre-specified settlement date and the event itself is not easy to manipulate.

Wisdom of the crowds?

“Our markets reflect accurate, unbiased and real-time probabilities for the events that matter most to you,” writes Polymarket’s website. “Markets seek truth.”

However, the turn towards markets such as daily temperature, how often billionaire Elon Musk tweets over a period of time, and whether there will soon be proof that aliens exist, show the inherent contradictions of platforms like Polymarket.

For many users, prediction markets are often less about truth-seeking and more about speculation and thrill.

Polymarket currently predicts a 22 per cent likelihood that the US will confirm aliens exist by Dec 31.

Dr Feng notes that while there is a conceptual distinction between prediction markets and gambling, this becomes more blurry in practice.

Prediction markets can be different from gambling when they genuinely aggregate information and produce useful forecasts, which represent informational value that goes beyond mere betting, says Dr Feng.

“That said, when the topic is mainly recreational, or the main attraction is speculative excitement rather than forecasting itself, the gap becomes narrower,” he adds.

In his view, this is ultimately why regulation and market design matter.

For instance, some of the earliest examples of prediction markets existed in academic institutions.

Dr Jia points to the Iowa Electronic Markets (IEM), not-for-profit prediction markets operated by the University of Iowa that allow academics to stake real money against their predictions for election outcomes or economic indicators. Established in 1988, the IEM frequently outperformed many leading polls when it came to predicting electoral outcomes.

The IEM is an early predecessor to modern prediction markets, which have opened the door to retail investors – something that Dr Jia believes would ideally improve accuracy and efficiency.

However, as these retail investors can have vastly different motivations than academic traders, one should interpret their predictions with a grain of salt.

Dr Feng says: “With the right guard rails, prediction markets can serve a genuine informational role. Without them, they can start to look less like forecasting tools and more like another form of speculative betting.”

FOMO a feature, not a bug

Researchers are increasingly calling attention to the addictive design of prediction markets, which use gamified features such as leaderboards, streak-based bonuses and countdown timers to exploit the same psychological mechanisms that encourage problem gambling behaviours.

Trivial markets are often surfaced to users through push notifications as they are about to resolve, creating a continuous stream of action, said US-based Baruch College researchers as part of a commentary for the academic journal Science in April.

Seemingly frivolous markets (such as those predicting the weather) serve a function for prediction market platforms, says Dr Chen Yi-Chun, professor of economics at the National University of Singapore and director of the Risk Management Institute.

“They are short-horizon, easy-to-settle contracts that can generate user activity and liquidity,” he adds.

All of this manifests in the subculture that has formed around prediction markets, where there is an undeniable sense of “fear of missing out” (FOMO) in the air.

Polymarket and Kalshi turn high-stakes political events – from election results to the outcome of court cases – into spectacle through a never-ending stream of social media posts that is not unlike the play-by-play coverage of sports commentators.

Social media platform X, where most discussion of prediction markets is concentrated, is flooded with content by users claiming that betting on the weather can be a get-rich-quick scheme, often by following the behaviour of popular traders – whose betting histories are public on Polymarket.

These hype-filled posts are out of touch with the reality experienced by most users.

One analysis of Polymarket user data from 2022 to 2025, by researchers from ESSEC Business School, HEC Montreal and University of Toronto, reveals a striking feature of the platform: Out of 70 million trades (totalling more than US$20 billion in volume), the top 1 per cent of users captured 84 per cent of all trading gains.

About 70 per cent of users recorded a loss, with most losing trivial amounts. The median amount lost was US$1.

For the majority of users, all of the hype appears to serve primarily as a means to get more on board to increase the amount at stake in prediction markets. In other words, increasing the potential winnings of the minority who already earn the most.

Source: The Straits Times © SPH Media Limited. Permission required for reproduction

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