687. Are Prediction Markets the Best Forecasting Tool Ever — or Just Another Casino?
Freakonomics Radio
This episode explores the rise and potential of prediction markets as tools for forecasting global events, from elections to climate patterns.
Key takeaways
- Prediction markets can outperform experts by aggregating diverse information from the crowd.
- Kalshi prioritizes regulation and market integrity over rapid growth, setting it apart from other platforms.
Main topics
- Prediction markets as information aggregators
- Regulatory challenges and compliance
Notable quotes
"If you believe in the crowd wisdom and people kind of putting skin in the game on something, it tends to be more accurate than other places." – Tarek Mansour
Conclusion
Prediction markets like Kalshi represent a powerful but controversial tool for
Transcript preview
Speaker 5 (0:05) Hey there, it's Stephen Dubner. Before we start today's episode, I want to ask for your help with a future episode about psychotherapy. The episode includes what is called a misery index, and we want to hear some of your stories. I realize this isn't for everyone, but if you are interested, use your phone to record a voice memo and send it to us at radio at Freakonomics.com. I'd like you to identify your most intense and persistent form of misery. and include some specifics. What exactly was the emotion you were feeling? What's the worst it ever got? How did it affect you? And how did you deal with it? If you only want to include your first name, that's fine. Again, the address is radio at Freakonomics.com. Many thanks. And here now is today's episode. Speaker 5 (1:00) Most of us are not very comfortable with uncertainty. And that's a problem, since so many things are uncertain, like the future. Since the beginning of time, we've been trying to predict the future. The ancient Greeks were famous for their oracles. They would also cut open a sheep and read its liver for signs about whether it was a good time to start a war, for instance. For centuries, potato farmers in the Andes have looked skyward to the Pleiades to help determine when to plant their potatoes. 25 years ago, scientists were finally able to explain why this actually worked. Pleiades' visibility is related to the climate pattern known as El Niño. Today, there are prediction markets on El Nino, and the markets indicate this year's El Nino may be the most extreme on record. So are prediction markets an upgrade or maybe a disaster waiting to happen? Will they improve our collective decision making or are they just another casino in an economy full of casinos? And aren't prediction markets susceptible to insider trading? The biggest prediction market in the U.S., Calche, recently imposed its first-ever lifetime ban against an individual trading on their site. This was over bets on whether George Santos, the disgraced New York congressman, would attend President Trump's State of the Union address. Santos had posted on social media that he was going to attend, but in the end, he didn't. On Calche, someone made a profit of $17,000 by first betting that Santos would attend and then betting that he wouldn't. Who was that someone? You guessed it. George Santos. So how much credit should Kalshi get for figuring that out and banning Santos? Today on Freakonomics Radio, we will hear from Speaker 3 (2:47) the CEO of Kalshi. Kalshi is really the most accurate way to predict the future. As well as their chief contract writer. Speaker 1 (2:54) These are legal contracts that people are signing on to when they're trading those markets. Speaker 5 (2:58) We'll also hear from an intellectual godfather of prediction Speaker 4 (3:02) markets. The hope is that we could use betting markets as a general information institution all across society. Speaker 5 (3:10) And next week in part two of this series, we will hear from a regulator. What I think is the cost, and a very real serious cost, is trust in the markets. Our two-part series, The Price of Prediction, starts now. Speaker 2 (3:35) This is Freakonomics Radio, the podcast that explores the hidden side of everything, with your host, Stephen Dubner. Speaker 5 (3:52) Kalshi and Polymarket, the two big prediction markets at the moment, are together worth over $40 billion. Shane Copeland, who founded Polymarket in his early 20s, was for a time the world's youngest self-made billionaire. One Kalshi founder, Luana Lopez Lara, is the youngest self-made female billionaire. The other founder and current CEO, Tarek Mansour, joined the billionaire list at age 29. Speaker 3 (4:19) But that is not what Mansour wants to talk about. This valuation of the company or my net worth or others, I just don't think that's that important. It's kind of paper money. Okay, so what is important to talk about when it comes to Kalshi and other prediction markets? If you believe in markets and their ability to aggregate information and price something, in the case of prediction markets, they're essentially aggregating information about a question about the future. If you believe in the crowd wisdom and people kind of putting skin in the game on something. It tends to be more accurate than other places. For someone who doesn't know Kalshi, just describe what the firm is. The easiest, most compelling way to describe Kalshi, it's essentially a financial market, but that captures a much broader universe of things. Historically, financial markets have been sort of limited to an elite audience. Whether it's the stock market or commodities or interest rates, what we got excited about was broadening that universe to yes, no questions about whether an event is going to happen or not. It's about things that people care about or relate to or they understand, whether it's in politics, the economy, climate, weather, culture, you name it. Mansour was Speaker 5 (5:24) born in Bakersfield, California, to Lebanese parents, but they moved back to Lebanon Speaker 3 (5:29) when he was young, and they divorced when he was six. I grew up outside the system a bit. I mean, I was a math nerd, single mom. My dad is alive, but he was never really present. And then there was a lot of turbulence in Lebanon, a lot. Growing up, there's a mix of two things. There was one, my mom really had high expectations of us. It's like, you should do something big in life, make it count, make it worth it. And then the second thing is we had a deep level of frustration with just the way that Lebanon worked, like the corruption. This is like a bad country. What drives me is I just want to have some sort of legacy. Like I want to build something that people point to and respect and have sort of validation. Speaker 5 (6:05) You were born in a good generation. One generation earlier would have been okay, but like nerds won the Speaker 3 (6:09) war in a way. It's kind of amazing, honestly. The nerds are cool right now. It wasn't the case when we were growing up. It's like a 10, 15 year phenomenon now. But 20 years ago, I don't think that was consensus yet. In 2014, Mansour left Lebanon to attend Speaker 5 (6:25) MIT. He studied math and computer science, and he soon landed internships and jobs with elite. firms, Goldman Speaker 3 (6:32) Sachs, Palantir, and Citadel. When I got the idea, you probably know the story, but, you know, when I was in 2016 at Goldman, a lot of the trades was like, hey, do we want to go long Trump or hedge against Trump winning the election? But they're very sloppy trades, yeah? They was very sloppy. We said, like, short the S &P, that's the Trump trade. Bad trade. They were right about Trump winning, but then they lost money because the S &P actually rallied. So the use case is very clear. I just think it's opening up access for people with significantly... broader or more diverse set of interests to have a shot that they don't have in traditional financial markets. Speaker 5 (7:04) It wasn't long before Mansour and his MIT classmate, Lopez Lara, started Kalshi. Speaker 3 (7:10) Where does the name come from? Kalshi means everything in Arabic. Back when we first started the company towards the end of 2018, we got into the startup accelerator, Y Combinator, and they needed like a name for the application. We were looking for like a cheap domain name, and I kind of like names with K. It was like, what if we call it Kalshi? And then we're like, we'll change it later because it's like a bad name. It's hard to pronounce. But now it's a big brand, so it's harder to change. Speaker 5 (7:35) Many tech startups embrace the Facebook mantra, moving fast and breaking things. Let's not Kalshi. Speaker 3 (7:42) What we did is the exact opposite. What Luan and I decided is we're going to abide by a core principle in the company, which is regulatory first. And we spent four years getting regulated before we launched a single market. We went to the federal government and said, hey, how do we regulate this? And what does that mean? Two pillars. How do you build a market that has market integrity, where fraud is policed, there's no insider trading, or you police it? Number two is you enable the right set of customer protections. Speaker 5 (8:06) Kalshi opened to the public in 2021. Some of their first contracts were on mainstream current events. For instance, in a given week, how many Americans would get the COVID vaccine? Would the Tokyo Olympics be canceled? The hard part came when Kalshi wanted to offer election contracts. The CFTC, the Commodity Futures Trading Commission, said they couldn't. Kalshi sued, and the case was decided by a federal appeals court in favor of Kalshi in the fall of 2024, just in time for the presidential election. Speaker 3 (8:38) It had taken Kalshi a while to get there. Imagine the first four years of my career. I mean, it came at a great personal sacrifice. It really was very tough because regulation is not fun. It's not sexy. It's super boring. It's like exhausting sometimes. Did you come close to quitting a few times? I mean, daily, pretty much. But the thing that I just really wanted to see exist in the world, I just felt like the cost of regret would be too great. There's a little bit of sunk cost fallacy when you're like two years deep. You're like, I'll try another few months and then it keeps going. What were your advisors saying? People always trusted our approach because we were pretty dogmatic, but it's an anti-pattern. The pattern in Silicon Valley is you build and you move fast and you build a product that customers love. Did you have potential funders tell you like, Speaker 5 (9:17) Tariq, that's a really nice idea, but there are 50 people who are capable of doing something like this and they're not going to go the slow, Speaker 3 (9:24) legit route? Yeah. I mean, Polymarket was launched at the time. That's why people know about the brand of Poly first. That's not because they started the company first. We started first. They started after us, but they took the idea and they were like, hey, we'll launch it offshore. Why do we wait? That distinction is... Really a large part for why we're at 90 % market share today, like why we've grown so much is because we stayed committed to that approach. And I think regulation has given us a huge edge because people trust it more. And I think we can go mainstream. Institutions are onboarding at a higher rate because it's harder to do it from outside the system. You have to really change the system, which is harder. I do feel like many of us, even in the Speaker 5 (9:59) political realm, or maybe especially in the political realm, but even in the financial realm, a lot of decisions are made with some insight and some information, but an awful lot of guesswork that we then convince ourselves is empirical somehow. I'm Speaker 4 (10:12) just curious whether you think Speaker 5 (10:14) that Kalshi ultimately, or even now, serves a bigger purpose of Speaker 3 (10:20) improving decision-making. It's not like we're making... bad judgment calls based on the information we have. It's just that we have a very limited set of information. That's the key thing. During World War II, an economist, Frederick Hayek, talked about the knowledge problem. It was this very basic idea, which is that a lot of decisions is centralized. It's centralized authority figures, whether it's governments or heads of households or leaders and companies and so on and so forth. But the information that is relevant to that decision is actually pretty distributed. If you think about this as a tree, a lot of decisions are made at the root of the tree. But the information is lying in the nodes of the tree. Speaker 5 (10:57) Distributed makes it sound to me like distributed among many people. The word I would think of is more like siloed or hidden. Are we talking about the same thing or no? Speaker 3 (11:05) It's all of them. It's actually distributed. It's siloed. It's hidden. It's fragmented even. So sometimes you may have a piece of information that standalone doesn't make much sense. So you have to combine it with someone else's piece of information and all of a sudden it could click. And then it's also dynamic. These nodes. In the network or the tree, the information is updating in real time. You could probe it. You could ask the node, you know, yesterday, but today it might have a different answer. At the time, Hayek didn't call them prediction markets, but he's like, well, the best way to solve that problem is probably some version of market prices. Because that's what they do. Market prices in traditional financial markets, they sort of aggregate information that could be distributed. This was the idea of this information market. Use market prices to disseminate and propagate information. What form did that take for Hayek? Did he try to do something like this? It was very theoretical. In my opinion, the first test of that theory was in the 80s with the University of Iowa. Are you familiar with that experiment? Yes, these are the Iowa electronic markets. Exactly. And they ran a small-scale prediction market. A few hundred people doing very limited sums. Real money? Real money, yes, yes. Real money is absolutely key. There needs to be skin in the game. You have to be punished if you lose, and you have to be rewarded if you win. There's no better reward. than making money. And no better punishment than losing money. Speaker 3 (12:26) The Iowa Speaker 5 (12:27) electronic markets, originally called the Iowa political stock market, was focused on elections. The CFTC had allowed it on the condition that it remained