Hi, everyone. I'm Liz Ann Sonders, and this is the May Market Snapshot. Thanks for tuning in.
I'm going to do something a little bit different this time. I'm going to stay on the theme of last month's video, but expand a bit. And that theme was differentiating gambling and investing, and how we're really seeing a blurring of the lines between those two.
[High/low charts for "Parabolic growth in prediction markets" for Prediction market monthly notional volume, number of transactions and number of users is displayed]
As I highlighted last month, prediction markets have grown exponentially. It's not just monthly volume growth. That has risen to nearly $30 billion since 2024. It's also total transactions, which have skyrocketed from about 240,000 to now just under 200 million, while monthly active users have grown from about 4,000 to nearly 775,000.
[High/low chart for "Geopolitics drove latest spike" for Notional volume for Polymarket and Kalshi is displayed]
Our friends at Arbor Data Science put out a recent report in which they showed the notional volume on both Polymarket and Kalshi. Those are the two dominant prediction market platforms. In the case of Polymarket, it is crypto native, it's offshore, has higher volume, but kind of in the legal gray area for U.S. users. Kalshi, on the other hand, is regulated, U.S. legal, and fiat currency based.
Now, in terms of notional volume on both platforms, Polymarket had a slight lead over Kalshi until September of last year. But since then, Kalshi has been recording higher volume. Now, the large month-over-month increases that you see in January and March of this year were likely driven by major geopolitical events, such as the US invasion of Venezuela and the onset of the war with Iran.
[High/low chart for "Majority of transactions not even humans" for Number of wallets and trading volume for Polymarket bots and regular wallets is displayed]
A majority of transactions conducted on prediction markets are not even humans. While bots made up only 5% of all wallets on Polymarket, they comprised about 75% of all trading volume.
[People chart for "Miniscule profit takers" for Polymarket breakdown of accounts by profitability and bar chart for Polymarket share of profitable traders is displayed]
There's also a recent Wall Street Journal article. It was titled, 'Why Almost Everyone Loses, Except a Few Sharks on Prediction Markets.' And the article highlighted that a minuscule number of accounts on Polymarket and Kalshi take home most of the winnings, and they are often pros using data-driven algorithmic trading.
So the Journal analyzed 1.6 million Polymarket accounts that have traded since November of 2022, and they found that 67% of profits go to just 0.1% of accounts. That means less than 2,000 accounts netted a total of nearly half-a-billion dollars. On Kalshi as well, losers vastly outnumber winners. According to a company spokeswoman there, she noted that there are 2.9 unprofitable users for each profitable one based on data from the prior month.
[Bar chart for "Pronounced information asymmetry within military/defense" for Longshot win rate by political topic is displayed]
Shown here are what's called long shot bets, which are defined as any instance where a single wallet purchases at least $2,500 worth of a contract at an average price of 35 cents or lower within a one-hour window. Those bets are expected to win about 35% of the time or less, and the contract price is directly tied to theoretical probabilities.
Now, most political topics fall in line with those expected odds, but the exception is the military and defense category, where long shot bets actually won about 52% of the time. That unusually high win percentage could indicate pronounced information asymmetry within the military and defense markets that is absent in other categories.
[High/low chart for "Societally bad" for Are prediction markets good for society? is displayed]
So what about the societal psychology associated with these markets? According to a poll conducted by the American Institute for Boys and Men, which is AIBM for short, 38% of respondents said that prediction markets were bad for society. Some respondents were neutral, with 34% saying prediction markets were neither good nor bad. But get this, only 4% thought they were actually good for society.
[High/low chart for "Rolling the dice" for How do Americans view prediction markets? is displayed]
Now, one reason people may view prediction markets adversely is because of its close association with gambling. Findings from that same AIBM poll indicate that 61% of respondents thought that prediction markets were closer to gambling, while only 8% thought it was closer to investing.
[List of "Takeaways" is displayed]
Let's bring this to a close. As the Wall Street Journal article highlighted, proponents of the betting markets say it doesn't count as gambling, and that they harness the wisdom of crowds to accurately predict future events. Even the Federal Reserve has research showing Kalshi is an effective tool for forecasting economic trends.
That said, the prediction market landscape has shifted meaningfully. Professional operations, some employing dozens of people, spending millions on proprietary data and deploying algorithmic trading strategies now compete directly against casual users, recreational betters, and low-volume participants. Those participants still make up the bulk of the user base.
The structural difference from traditional gambling is worth noting, though. Conventional bookmakers in the world of gambling, they function as the house. They set the lines, accept wagers, payout winners. Prediction markets have no equivalent intermediary. Participants are trading against each other, not against a centralized operator. The platforms themselves generate revenue through transactions fees, which can vary depending on contract pricing, market type, and other variables.
It's important for us to continue to distinguish between gambling and investing. The gambler hopes. The investor owns. Both involve uncertain outcomes, and both require accepting the possibility of loss, but the underlying architecture of each is fundamentally different.
Here it is in a nutshell. Owning beats hoping. Discipline beats speculation. And we continue to be unflinching as it relates to that distinction. So thanks as always for tuning in, and I'll be back next month.
[Disclosures and Definitions are displayed]