I mean, this year we have people that are making over $100 million this year, but just on Kalshi, and they're like not even 30 years old.
Yeah. And no one knows who these people are.
They're pretty secretive.
One of the fastest growing companies in the world, but also one of the most controversial. Kalshi calls itself a prediction market, but a lot of people consider it gambling.
You find the card counter and what do you do with them? You kick them out of the casino. And so, if anyone is doing smart research, you incentivize them not to. You push them out. We have an open market where winners can win. Actually, that incentivizes people to do research and get better at the thing. Those guys are banned from the casino anyways.
So then why do they hate you?
I'm building the modern-day financial market. That's what I'm building. Instead of giving the microphone to a select few, we're giving the megaphone to millions of people that are battling it out in the open in a completely transparent way, putting money where their mouth is. Imagine millions of people are doing that, competing on the open market all the time. You get truth out of that.
But what if some of these guys try to manipulate this because they see how much of an impact it has? What would that do to the market?
Complete waste of money. Where should they have put it? Giving it to the campaign, put a bunch of ads on TV, attack ads on the other candidates, or they should have commissioned their own polls that will say whatever they want them to say, which by the way, you know, now we're in the last stretch of the election. What is going to happen?
So, it's great to have you on.
Thanks for having me. I'm excited.
Kalshi, you're everywhere. I can't turn on TV without seeing Kalshi, right? Tarek Mansour, co-founder of Kalshi, went from what, zero to now they're saying it's 22 billion, soon to be 40 billion, depending on who's reading what article. But for the audience that doesn't know, maybe walk me through how the whole story of Kalshi came about, your background before starting Kalshi.
You know, I was born in California, and then at a young age I moved back to Lebanon because my parents are Lebanese. You know, I grew up with a single mom, and you know, Lebanon is — you read some like — it's a crazy country. It's very volatile.
And it's kind of a shit show, honestly. Like, but there's a lot of positive about it. It's beautiful, and you know, you probably hear some from friends like we have a great nightlife, great restaurants, etc. But it's just the most defining thing is that everything's unpredictable. Like, you don't know what you're going to wake up to the next day. And, you know, especially with a single mom, that makes you an anxious kid. And I was very anxious. I still am. That led me to love math. I always liked math. And I would play around with — I would read like papers, and because math, you know, what's nice about it is like you have an answer. There's no debate. There's no my opinion versus your opinion.
Yeah. There's an answer. Like either the proof works or it doesn't work, right? That led me to, okay, I want to go where the math people go. And at the time I was thinking like MIT. This is the place. I went to MIT. And then where are the math people going? Finance, because finance is a very good application of math. And you know, it's funny, like there's this saying in — because I also did the master's during MIT and in academia circles and in Wall Street there's always this joke which is like, you know, doing data science and research in academia is the same as Wall Street because people do data science and research on both. The only difference in Wall Street is you have to be right, you know, because you put a paper out and — but in Wall Street you have to make money.
And you know, that's why I always liked markets, because markets are a good application of incentives. Because what do markets incentivize? If you're right, if you get a piece of admission, if you're knowledgeable about the world, you make money. And if you're wrong, you lose money. Went to work at Goldman as an intern in 2016. And you know, all these complicated products, the everyday layman doesn't understand any of this stuff. You know, swaps and swaptions and credit default and like all these weird crazy terms. I think Wall Street, what they do over time is they complexify everything. They add more and more layers so that the average person doesn't understand what's going on. That kind of frustrated me a little bit. And the second thing is people were coming and asking us simple questions about the future. They're like, 'Hey, I think Trump is going to win. How do I bet on it? How do I?' And these are, by the way, hedge funds, large corporations, like institutional investors. How do I trade on Trump winning the election?
So, who are you working under at Goldman? Are you working on Charmaine or are you —
Equity derivatives on the trading side. So I was in the trading business, and you know, they would say, 'Okay, I think Trump is going to win. How do I play it out in the markets?' And we would say, you know, at the time, I remember the Trump trade was you short the S&P. Trump is a popular candidate. If he wins, he's obviously going to tank the market. So you should, you know, if you think he's going to win, you should short the S&P. So that's what a lot of people did. Come November, he won. People were right about the prediction, when the S&P went up, they all lost money. Bad trade. Really bad way to express that opinion. So I started thinking, okay —
And that was Goldman's position at the time?
No, we sold to a lot of customers, you know, but that's what happens like the banks at the end of the day. You're not taking the position necessarily. You're selling it to — but the key thing to me is like, what is a market? The market is a place that aggregates a large number of the large diversity of participants, people from all walks of life, to trade on their difference of opinions on, you know, to predict the price of a stock, Apple, or price of grain or oil. What if you build the same mechanic where buyers and sellers — we match buyers and sellers like the New York Stock Exchange, exactly the same thing, but the underlying thing is something that people care about or relate to. Whether it's politics like Trump is going to win or not, Brexit happens, whether tomorrow if it's going to rain, if OKC is going to win the next game, if inflation is going to go up or down — just simple questions about the future that can bring in a much larger number of people. And the more I read about it, you know, the idea wasn't new. A lot of economists love the idea of information markets dating back to World War II. Why? Because at a time, you know, when they would talk about the idea that market prices are the only form of truth. Why? Because markets, what they do is they aggregate information from everybody. Like, you know, you have a piece of information in Hawaii and California and Texas, and markets are like a magnet. They incentivize you. If you have valuable information, what do you do? You go trade on it, and you think something is underpriced, you move it up a little bit. And if you think something is overpriced, you move it down a little bit. Imagine millions of people are doing that, competing on the open market all the time. You get truth out of that.
And that's what an information market does. And I love that idea. It's like the application of free markets to the pursuit of truth. Right? Like if you and I want to figure out what the price of Apple is, we're not going to go and like debate what the price of Apple is. We're going to look at the New York Stock Exchange. We have — there's a big — why? Because there's rigor in it. The incentive is to get it right. But now in politics, what do we do? We debate. But now we've built markets with the same level of financial rigor where people are — there's quants and hedge funds and people are doing research, and if they have good information, they're going to come trade on it and make money. And if they have bad information, if they're having stupid opinions, they're going to trade on those opinions and lose money. And that's what the beauty of a market is. It filters out bad information from good information and then aggregates it beautifully across the wisdom of the crowds, millions of people. So I had to start a company. I was like, I got to do this. I was going to go work at Citadel, which I love, by the way. Citadel, great place. But I was like, I got to do this. This is like, I think, too important to not do.
Was anybody doing that at the time?
You know, there was a lot of trials, you know. So there was University of Iowa that tried an election market in the '90s, way back in the '90s, and it was super accurate, small scale, not for profit. Yeah. And I was like, this is interesting. And then —
How did you find out about it?
I just started reading online, and because economists really loved the idea forever. They really wanted this to exist. And then, you know, then there was a book, Superforecasters, written by an MIT professor, which was Philip Tetlock, and it's about this idea like about super forecasting and like the art of — who are the people that are good at forecasting the future? Who are the people that are good at doing this? And you know, he did this very interesting analysis where he put a bunch of geopolitical experts, like elites from DC, Wall Street, the big guys, the big talking heads, and he pit them against a bunch of random dudes to predict — you know, random dudes and random women to predict geopolitics, the thing that the experts are experts in. Guess who did better?
Because this is what's beautiful about it, is like what he realized, like actually information doesn't sit with the elites. We are always making decisions based on what the elite tell us. Top down, you know.
Wow. So, it sits with the people instead of the elite.
It sits with people. A lot of decisions are made by a handful of people, but the information that's important sits with millions of people on the nodes, on the extreme, everywhere. It's decentralized, distributed. And so markets surface that. They are a magnet for all that information, for all the people to kind of bring it up and then predict the future. And I love that. And like to me right now as you look at it, why is Kalshi more accurate than all these other places, you know? And we — the Federal Reserve put out a paper in February. They compared our forecast to Kalshi, which is Main Street, average people, to Wall Street on the economy, like inflation, Fed interest rates, GDP, unemployment, which are the things that Wall Street, Bloomberg, and all these guys are very good at. Guess who did better? Kalshi. And then people come to me like, who are these traders? Like, who are these people doing it? And like, you know, and there's actually some research, I don't know if you can pull it up, about who the traders are. I think it's one of these. Yeah, this one. If you go down a little bit on the chart, and I love this, I mean, a little bit higher. That chart that's right here, right? Like 80% of our customers went to public school. If you look at our customers, our top customers are twice as likely to have worked in retail than have worked on Wall Street. You know, our best inflation forecaster is a random dude in Kansas, never traded financial markets, just loves reading about the economy and asks people about what do you think about prices, and imagine millions of these people. But that's the beauty. We're giving people the opportunity.
How did you find a guy in Kansas?
I mean, now we build a — you know, the people know —
Because on the back end, you keep asking, why does this guy keep getting it right?
Yeah. And I talk, you know, I talk to him, he's very anonymous. And like there's others that are like that, but the people that know good —
But do you look at people that are the best at picking? Like is there like a leaderboard on the back end?
Yeah. Some public, some of them don't opt into like showing it because they want to be very private. So they don't want people to know. It's like Wall Street. A lot of people don't want to know how.
Do you have the ability to find out who are the people, percentage, and what pattern would I give names? What pattern? Because last week I had Frances Haugen on from the Facebook whistleblower who was here. That's right. That's right. The movie that they just did, The Social Reckoning, whatever it was called. She told me about a program Facebook had, well, it was called Crosscheck. And under that division they developed a group where they looked at how many people who high score of reasonability — meaning say this person's a conservative but they get the most people from the left that like their post, or say this person's a liberal, how many people on the right listen to them, and they say this is a reasonable human being, give them a bigger wide audience because they're reasonable, they're fair, even though we know which side they lean on. What patterns did you notice with who gets the most things?
You just described it, because the people — and so this is what's important. It's not the elites.
I mean, this is the key thing about — and that's why, by the way, prediction markets, you look at the news and the elites, they don't like them because it's like at the core it's moving power from — information from being centered with a few gatekeepers and a few people that tell us here's what to believe and what not to believe, and it's giving it to millions of people. Nobody controls a free market. So I don't — it's all the trading activity is public and you can see who's trading and what they're doing, but it's millions of people saying here's the percentage of something happening or not happening, and that shift of balance of power, it's this what free markets do so well. It's they're giving — instead of giving the microphone to a select few, we're giving the megaphone to millions of people that are battling it out in the open, a completely transparent way, and competing on their opinions. And if you look at who they really are, it's not like the same people that predict sports are good at predicting politics, economics, financial markets. You notice a pattern like — if you're able to be specific, not age, not gender, not who they are, what their background is. It's more a skill, which is a skill of self-calibration, which is you go out, they're always reading below the headline. They look for information like opposing views. They look for information that comes from opposing views that they send them to understand what the other side has.
Covered their own blind spots.
Yes. Where am I wrong? They're always thinking. They're not thinking — they're trying to self-calibrate because you know humans, we have this thing called the affect heuristic. Have you heard of it?
The affect heuristic is this thing where humans, when you put something in front of them, in the first five seconds we have this thing where emotionally we decide whether we like it or not immediately. And that's why, you know, social media has really fueled that. That's why we're becoming so polarized because you see a 10-second reel about a person. If it's positive the first time, you're going to like the person pretty much forever. And if it's negative the first time, you're going to hate that person pretty much forever. It's going to be so hard to get your — and you know how hard it is for us to change opinions. We don't like changing opinions. The guys that are really good at prediction markets, the women and guys that are very good at prediction markets, are the ones that like resist it. They're the ones that are like, why do I believe what I believe? Let me go seek out the opposite side and see what they believe and why they believe it. And like I'm always calibrating. Am I too certain? Am I not certain enough? And by the way, they're not — when people say, you know, people are betting on Kalshi. Sure, people are betting and they're the same way they bet on the stock market and the same way they bet on anything else. But a lot of what they do is they trade in the sense that like they're buying low and selling high. They think, you know, you could buy Republicans or Democrats. The same people are buying Democrats or Republicans winning the Senate, not because that's what they want to happen, that's because they're thinking what will happen. And right now, for example, a lot of people tell me, I think Republicans are underpriced for winning the Senate. I think the odds of Republicans are like 36% right now. That's underpriced, right? And they maybe like buy at 36 and then if it goes up to, you know, 50, they'll sell it at that point. And they're not thinking, they don't wait till the election. They basically buy and sell, buy low, sell high. They're always figuring out where the value stands. And that's a very different type of thinking than the sort of emotional clickbait that we have on Twitter. You know, on Twitter and social media, you don't get rewarded for truth. You get rewarded for, you know, if you put out a bunch of misinformation, you don't get punished. You actually get rewarded. You get more likes. In prediction markets, if you trade based on misinformation, you get punished. You lose money.
So do you have a top 50 earners that you look at who have made the most money?
I love to have that. Yeah, we have top — I mean, we really look at the top 15,000 because we have 30 million customers now.
And what does a top make? Are there people —
There's people that make millions of dollars, people that make tens of millions of dollars.
And some of them are regular people or well-known people?
They're pretty much all like — the vast majority are regular people. Like people think that Wall Street is outperforming on Kalshi, but we are a new Wall Street. We're enabling a much broader people. You know The Big Short, you know those two guys that were in the basement?
You remember those two guys? The guys that are in the basement that were — was it Lone Pine Capital or something like that? I forgot the — the ones that like the two kids that were in their mom's garage and then they were like — I do. So the guy goes to him and talks to him. I remember those guys.
Pull it up. Pull up in the images so people can see the two boys in a basement. Just type in next to Big Short basement. Yeah.
No, in the movie. Type in in the movie. I think it should just do like two. Yeah. Loan — what was it called? Loanpine Capital or something like that? I forgot.
Okay. Keep going. I'll find it. I'll send it to them.
Uh, no, not that. Not that. Yeah, but I think those guys are the — you know —
No, it's not. It's not this one. It's some — it's one I think, I forgot what the name is. Maybe it's not Lone Pine. It's something Capital.
Charlie Geller and Jamie Shipley from Brownfield Capital.
Brownfield. Brownfield. Yes. And that's the customer. It's the people that are like, you know, looking at the world and trying to get smarter about the world. And that's prediction markets like financial markets. What do they do? They incentivize people to go out and get smarter about the world and get more diligent. And if they do the analysis and they get smart, they get rewarded for it because they're bringing information to an open market. And people tell me always like, well, how is this different from gambling, right? Like how is that — what is the difference, right? And I always say it's actually a very simple structural difference. You know, back in the day when society — when we got grain futures, which I think now we all see it as a financial instrument, a boring financial instrument, society thought it was gambling. Why? Because farmers were betting on the price of grain. Some farmers were betting, some farmers were hedging, and like how do we decide that this is gambling versus not gambling? And the way they decided — like yes, some people are speculating. Do people bet or gamble on Robinhood? Certainly they do a form of it. The question is not whether there's some behavior that's like this. The question is like, are you doing it on an open competitive marketplace that rewards you for being smarter and for knowledge, or are you betting against a sports book or a casino that actually doesn't reward you? It rewards you for basically losing money, right? Like the person that gets a suite at the casino is not the card counter that's actually trying to be smart and like do smart things. It's the person that's basically losing a lot of money to the book and has signs of addiction and is, you know, is in there for the entertainment. And those are regulated differently and treated differently because the markets have a lot of positive externality, which is the forecast, right? That's why we look at the forecast of what's going to happen in the midterms or a sports event or other. And then some people are actually using it, and I think you're going to like this, they're using it — not they're putting a position not to speculate to make money, they're putting it to hedge themselves as a form of insurance.
So you know, so when grain futures came around, they were helpful because of the prediction. They would tell the farmers, here's how much you can sell your — here's the prediction of prices in six months. So how much you can sell for. And then hedging, which is like farmers would basically short the price of grain so that if the price of grain goes down and they lose revenue, the short pays them the offset of the revenue, right? And so you see this on events, right? Like for example in hurricanes in the Keys in Florida —
Because it's like buying a stock and buying a put at the same time, option.
Same thing. It's the same as buying insurance. So like a lot of people in the Keys in Florida, they buy yes on our hurricane markets as a way to basically get paid if the hurricane hits their town instead of going to insurance companies because insurance companies don't insure a lot of these homes. The other — sports is a big source of hedging for us. So last week there was an article and there's, you know, hundreds of businesses that do the same. We have a restaurant chain that owns 25 bars and they made their math that they make $120,000 if the Dodgers make it past the playoffs. You know why? Because, you know, if they make it, you're going to have a lot of customers that come watch the games and they sell, and $0 if they don't, or like much lower. So what did they do? They basically shorted the Dodgers. They bought no on the Dodgers making it past the playoffs. So that the event contracts, the hedge pays them the revenue loss. It offsets the revenue loss. So now they're $60,000 up.
But that's very important. It's very deep.
It's brilliant and it's critical.
That's because why grain — you know, people — why did Congress step in and create a nationwide model and regulation for grain futures? Why are they so important? Even though people are betting on the price of grain, like when people are saying it's gambling, imagine farmers had less predictability of their business in six months. What would they do? They would invest less. They'd get less lines of credit. Predictability in business is one of the key — anyone who's run a business would know this. Would you pick a cash flow that's zero or $120,000, or you pick a cash flow that's $60,000? Either way, you'd pick the predictable cash flow. And the reason is that you can give it better loans over time. Predictability helps you invest more certainly for the future. And so over time, this is what derivative markets do. As we get smarter about what's going to happen, who's going to win the midterms, we can make better decisions and then hedge all the things that impact us negatively over time, which helps promote investment as well.
So, is there a way for somebody to get good at Kalshi where, hey, let me teach you how to be a better trader on Kalshi? Is there things like that as well on how to succeed?
It's a skill, right? It's a —
Maybe let me ask this question. Who is — for sure — without giving a name? Again, I'm not looking for names. I just went on ChatGPT and asked the question who the top 10 traders on Kalshi — these are some of the names that came up. VM Markets 951, uh, can you go back to it? You know, Loss Buck. And so the win rate to the right is what matters the most to me, right? 55%, 73%, 41%. Does this mean based on the position they make, that's how often they win?
Yeah, win rate is like — yes, exactly. Out of each position you take, how often is the right position.
Is the highest ever public on the reported profits?
We have people that are making like over — I mean, this year we have people that are making over $100 million this year.
And they're like not even 30 years old.
And no one knows who these people are.
They're pretty secretive.
It's like the Brownfield Capital is the —
Yeah. Yeah. Yeah. I mean, we — and by the way, it's not like we have a lot of people that are making millions and they tend to be more like private. By the way, that's not everybody. That's why I always say people tell me about — there's a lot of people that lose for sure. It's a competition. How many people win the NBA finals?
Is it an 80/20 split? What's the number?
By the way, here's what's interesting. What percentage of hedge funds outperform the S&P every year?
That's a — it's a much smaller number.
20%. 80% underperform the S&P. 80% of hedge funds lose against their benchmark.
80% of hedge funds, right? But that's — but hedge funds are benchmarked against the S&P because you know if you're below S&P you're losing.
But like in the reason it's — financial markets, including prediction markets, whether it's sports or weather or politics, etc., it is a skill-based game. If it was a game of chance, it'd be 50/50. 50% of people would win and 50% of people would lose, which by the way, like is what you would see in a casino or whatever. But because it's a skill, some people are going to put more effort and get better at it over time.
Guy made a hundred million this year so far.
It's — now he has a small team. It's like a few people on the team.
So, do you think it's going to get to a point where a Kalshi person is going to make a billion? It's going to be —
I mean, we could get — I mean, it's like the markets, right? Jane Street and these guys make billions of dollars in the open market. So as the market grows, I mean, now we're doing a trillion dollars of volume a year. So as the market, you know, as the market grows, it's going to be —
Yeah. Okay. What number shocked you the most? You just said we're going to do a trillion. How much did you guys do during the World Cup? I mean, I don't know what it was.
We did — I mean, yeah, we — I don't know. We're bigger now than we were at the time, actually. So —
You did a billion, billion and some. Yeah, I think that was July. I mean —
That's one game, right? Welcome home. Yeah, that month. I mean, we're doing right now — we have because we have prediction markets, we have perpetual futures, traditional commodity futures. I think the prediction markets are annualizing something like 600 billion a year and then the rest is 400 billion. So we're like around a trillion dollars of annualized volume. But —
And what is the business model? How —
Take a small fee. So that's the key. I mean, this is also the difference of being a market versus a sports book. A sports book business model — that's why, you know, betting and gambling people don't like in society. It's a way to — your revenue is equal to your customers' losses. So what do you do? You figure out who the winners are and you ban them. You find the card counter and what do you do with them? You kick them out of the casino. And so if anyone is doing smart research, you incentivize them not to. You push them out. If anyone has signs of addiction and they keep losing money and they're not — they're doing it like without really thinking, you incentivize them to keep doing it. That's how you get rewarded and you give the bonuses and promos so you can keep these losers coming back. Markets. I am a marketplace. You are matching you as a buyer to somebody who's selling to you. And if you open, for example, the Senate or any of the sports markets we have, you know, if you go down a bit and you click on Democrat party up. Oh, no. Yeah. Right here. And then you — yeah. If you look at this, if you go down a little bit. Yeah. Right here. No. Yeah. Right. Right in the middle. The top — the asks is — if you scroll slightly up just so that we see — yeah, right here. The asks are people that are selling and the bids are people that are buying. It's the same as the stock market. This is what a New York Stock Exchange looks like. And we match buyers and sellers. And I take a small percentage. So if people trade, let's say, $1,000 here, I'll take 0.7%. So I'll take, you know, seven — let's call it $7, right?
Is that relatively the number?
Yeah. It's like the New York Stock Exchange. Exactly. Yeah. And I think that like that is key because I do it whether somebody wins or loses. In fact, actually, I want the card counters or the smart people. Like the New York Stock Exchange wants the smart traders. Why? Because the smart traders are the ones that create efficient markets and accurate prices. No one would use my forecasts if it's not calibrated over time. Those people that are very skilled are — and that's why the difference in model is so important.
It's like poker. You're not the enemy. Unlike blackjack where the enemy is the casino. Here —
It's different from poker in one other sense is we're discovering the prices of something that has real human impact. So on poker, when people are like, you know, betting against each other, you're not learning anything because you know what the probability of a card flipping is. Here you're learning this idea of price discovery. You're learning the prices. If you go back up to the chart, that chart, you would never like, you know, have a chart on which poker hand is going to play next because you know that chart is a fixed probability. It's a — you know, whereas here we're like that positive externality of getting smarter about the world is what makes markets different.
Okay. So let's just say — walk me through it. If somebody right here puts $100,000 on no, 37 cents, Democratic party. What does that mean?
So if you look at it here, you — if you — yeah, on the right, if you click on dollars on the all the way to the right just a little bit. Yeah. Right here. Right? Shares. And then if you type in 1,000 shares in the thing, it tells you immediately. So you're buying 1,000 shares. The average price you're going to get filled at is 64. And you're going to pay 600, let's say, $50 after fees. And you're going to get paid $1,000 if you end up being right. Now, now you own those thousand shares. They're not shares of a stock or shares of like oil futures. They're shares of, you know, the Democrats winning the Senate. And then in a few weeks if that goes up to like let's say 75%, you can sell those shares and you get like —
You're not even waiting till the end.
11%. That's what most people do. Vast majority of them. They're buying and selling.
What percentage doesn't wait till the end?
Of the volume? I think it's like 70%.
70% doesn't wait till the end.
Yeah. I mean, because they're traders, like they're trading, they're figuring out — like a lot, again, it's you and I discussed this, there are people that are in the middle. A lot of these guys are like also like, you know, I sometimes joke they're kind of swing voters because like they're dispassionate about the outcome. They're unburdened by ideology. They're like thinking, 'Okay, the Democrats are a little bit too overpriced or underpriced right now. So if I think it's overpriced, I'm going to sell.' I think it's like a stock. But that level of rigor is markets.
Okay. So let me ask you. So today, today's a special day. Why? Brazil election, president, Bolsonaro, Lula, right? Day one you guys had him at 80%.
And if you go to it, widen it a little bit more. Yeah. So day one, go back to like two days ago. Go back two days ago. You had him at 87%. That's about two weeks ago. A week ago, but that's fine. 87.5. Yeah, 75. So, and all of a sudden, this flips.
Lula wins 15 out of 17 districts that were doing the counting of the votes said Bolsonaro is going to win. Last minute, he pleads with the Supreme Court to open up the voting in areas that are pro Lula. And all of a sudden, he comes out of nowhere, wins. I don't know how many — gets plus 10.6 million. This has never happened in history, right? So for you, when you watch it, because you have data that we don't have, what do you speculate is going on there?
This is what's important to understand. There's two things. One, a market doesn't create new data. A market aggregates all the data, right? Like Apple stock doesn't run the product for Apple, right? Now Apple stock is at $100 a share today, let's call it. If Apple does a series of actions, like for example, if some bad regulatory action comes out that they were doing something bad in some of their factories, what's going to happen to the stock? It's going to go down. Why? Because new information has come to light that is now going to be priced in by the market. The market is going to absorb that information in real time. If Apple releases a bunch of great products over the next three weeks, what's going to happen to the stock? It's going to go up. So what — and this is always important — markets, what they do is they absorb new information in real time. They're an aggregate of — and in the elections it's of the polls, the news, candidate quality. If a candidate has a scandal, what's going to happen to their odds? They're going to tank. So markets, that's what they do. They do a very good job at summarizing all the information that's out there. And you know that the incentive to summarize it is clean because there's no partisan lens or bias. Like why is Fox saying something or CNN saying something? There's a partisan lens in here. Whereas the only lens of a corporation — markets — that people are trying to get to ground truth because if they're closer to the truth, they're going to make money. If they're further from the truth, they're going to lose money. Now, sometimes there's a new piece of information that's very material, right? Like if a candidate is doing very well, but then the scandal happens, they're going to tank very quickly. And that's what happens. There's a big new shift that happened yesterday on the election, which —
Could you guys pinpoint what it was or could —
I think a big shift happened when the — I think the extensions I think started happening, but I hadn't looked at it quite yet. But the more interesting way to evaluate the prediction markets, I think if you go back to the calibration plot, I think it's — we have it open, yeah, right now, if you go down a little bit, is this. So if you zoom in a little bit on some of these charts, that's what we call a calibration plot. So you cannot evaluate prediction market accuracy on one market. There's a study on like 2 million markets that's public, anyone can replicate it, where it says what is the probability that we're saying something is going to happen with and how often does it happen. So if you say something has 20% chance, it doesn't mean it's not going to happen. It means it's going to happen one in five times. It's going to happen two in 10 times. It's going to happen 20% of the time. Right. Got it. And that's so important. It's like sometimes the — if you run the race 10 times, what's going to happen? It's going to happen one out of 10 races. It's not — and so that's what shows you in the plot, which is actually very accurate. It's like when we say something has 20% chance, it actually does happen 20% of the time.
So on the back end, what did it show to you guys? Did Kalshi know that there is a possibility that Lula wins?
There was a 25% chance, one in four possibility that Lula wins, and data was, you know, looking at all the prevailing factors, and that changed obviously dramatically when the new material information came to light. But like again, if Lula — if you play that election four times and Lula wins zero out of those four times, then we would be wrong. He should win one out of those four times, and that happens. And so what I say with the midterms right now is people ask me, oh, how do you evaluate the midterms? Like look at 100 races that it's predicting and assume that the — you know, it's saying that the Republican is winning 50% of the time or like 40% of the time. How many of those 100 races should go Republican? 40. It shouldn't be zero. It shouldn't — it's not like every one of those races should go Democrat.
Yeah. And that one makes more sense because it's a volume of races, right? You're not dealing on one.
That's right. But you have to look at elections over time. It's a probabilistic model, right? A prob — like right now we're saying the Senate is going to go 64% Democrat, 60 whatever that — it's like a three-sided coin where two sides are Democrat, one side is Republican. And it's a three-sided die that has three sides. Two Dem, one Republican. If you roll that die, you can still land Republican. One in three chances. It's not a poll. And people really confuse markets with polls because polls are what do you — what are you going to vote for? It's checking who's going to vote for what. Markets are what is the probability? What do you think will happen that something will happen?
So of the guy that does 100 million, does he do a lot of trades? Is it personal — so it's not one, it's like diversifying or is that kind of a —
For sure. For sure. Got it. It's very diverse. You're trading. You're trading in and out and you're — and those are the guys that make the markets accurate. Those guys would never be allowed on a sports book. Why? Because if they were making that amount of profit, who is it going from?
Yeah, it's a very different model. You brought up the casino as a way to move money from people to the casino.
So, who hates you? Who is the enemy? Is it the casino? Yes. Because who are the top three enemies of you in the casinos?
Mainly casinos at the... I mean, like some of... Yeah, because I think that they are the ones that are pushing the states to come after us, and because they want a monopoly on this too, right? Like that's how you know they... that's a model that's more transparent. It's healthier, but also it's a market. Like, you know, institutional... we have institutional clients using Kalshi signals, but also using it to hedge against different events. You can now use a sportsbook to hedge against different events like that will never happen.
Yeah. So we were doing an event in Las Vegas, and I don't know if this got to you or not, MGM Grand Arena, we got the big Vault conference, and while we're doing that, all of a sudden, last minute, they're like, 'You can't have cash here.' We're like, 'What does that have to do with anything?' Kalshi cannot be a sponsor. Said, 'Kalshi can't be a sponsor.' No, they can't. Said, 'Kalshi, it's our sponsor.' They're... No, you can't. You can't have Kalshi in here. So, what is the feud with MGM and...
They want a monopoly on this too. I mean, some industries, you know, don't want more transparency into something.
You don't think they want more trans...?
Yeah, because think about it. Like, if we have an open market where that is where winners can win, actually that incentivizes people to do research and get better at the thing. And now it compares to the model where like every time you do a little bit of research, you get punished for it, you get kicked out of the casino. What does that tell people actually? 'Oh, I'm getting really screwed with these odds. These odds are terrible. They're giving me bad odds.' All these... And then also they want a monopoly on it. It's big business now, and they feel like, 'Oh, we should have a monopoly on this too.' That's the age-old question. Why do the taxis go after Uber? Is it because Uber was worse for a customer?
It's never what it is. It's never what this is about. It's never about... because I'm actually, you know, and by the way, this issue of young men and addiction, I think it's a very real issue. And I've been always saying the beauty of Kalshi is I don't make money off the people that are like losing money and getting addicted, etc., as much as DraftKings does because, you know, the sportsbooks, they're betting against those customers and so they need them. They keep getting more of them over time. In the prediction markets, if somebody's losing all the time, they're losing it to somebody else. And so, in my view, I always tell the federal government is like, if you're worried about customer protection, let's regulate this and let's put sensible guardrails where like people that are using it in a way that's dangerous for them and irresponsible... We use tools to add friction to their accounts and make sure that we're giving them, you know, 'Hey, you lost a lot. Relax, stop. Maybe you have to take a pause, maybe you have to exclude yourself and move on.' Guess who is the most against those types of things? Casinos.
Those are the most profitable customers. And those are the people that are going out publicly saying, 'Oh, you know, the prediction markets are the issue with young men.' Prediction markets are never the issue with young men.
How much money did they lose to you?
I don't think they are, because 70, 80% of our volume is the sophisticated money. They're doing modeling. They're doing all this sort of thing. Those guys are banned from the casino anyways.
The smart traders cannot be in the sportsbook. You said 80% of them only have a public school diploma, right? Or...
So I'm saying this is a separate stat, which is 80% of the volume comes from a small percentage of people that are doing very highly... like a lot of research, a lot of analysis.
Got it. So the 24% or the banking wealth, they know what they're doing. These guys are in the space.
Yeah. And those guys, the point is like, it's not a high percentage as you'd imagine. People would think, 'Oh, but...' It's not. It's actually 50% of our customers worked in retail.
So one of... Yeah, that's absolutely amazing. But so it's like anyone can... like if you put the effort, you can win. Now look, not a lot of people put the effort. A lot of people just do it on the side or...
Yeah. Like research, time, energy. You have to read a lot about what's going on in Texas, who's voting how. I'm going to break down the different demographics. Like you have to get deep the same way that you get deep on a stock. If you're a bank analyst at Morgan Stanley, what are you doing all day? You're doing quantitative analysis, qualitative analysis. You're doing surveys. You're polling. You're researching the stock. Is the product going to work? You're asking customers, 'Do you like the product? Do you hate the product?' And then based on that information, you go and say, 'Oh, I think the stock is overpriced or underpriced.' And you trade based on that.
And that's how you make money. You get rewarded by the open market for that information that you brought. That's the same thing that's happening here, but you're doing it on a much broader set of things. Is inflation too high? Is this sports team going to win or not? And that provides us a public good that is this bottom-up, people-driven forecast of what's going to happen in the world.
So I asked a question here. I said, 'How much money have casinos lost to Kalshi?' I'll read it to you. You can pull up the same question. See what it tells you. Um, how much casinos have already lost. In a January 2026 analysis, Citibank estimates that prediction markets have diverted approximately 5% of legal sports betting volume. This translates to $8 billion in annual betting volume redirected to prediction markets. Approximately $800 million in potential annual sportsbook revenue assuming a 10% sportsbook hold. 1.3 billion in potential state gaming revenue for taxes diverted since 2025. Does that sound about right?
Yeah. I mean, like the CEOs of DraftKings and FanDuel in their quarterly earnings said that there's less than 1% cannibalization from prediction markets.
And they're right about that. Yeah.
So why are they so worried about you?
You know, there's a message like in the casino, by the way, and this is certainly true for casinos. Like, no one is deciding to go and trade on Kalshi versus like going with their buddies and have a few drinks at the casino. It's not... If anything, actually, the people that we kind of... if we really did that study, we're analyzing Robinhood and like the NASDAQ and like people that are like in the financial markets that like now have another financial tool and a financial instrument, but on things that they relate to. Because a lot of people, like when they trade in options, zero-day expiry options on S&P or NASDAQ, they think they don't have an edge against the big Wall Street guys.
Whereas this is the same thing. You're buying and selling, you're trading in an open marketplace, but on things that you may have an edge. People read the economy, people read politics, people like the weather, and they do studies on the weather. I mean, our best... by the way, there's some analysis, an independent school did a study on our weather markets. It shows that it's 10% more accurate than the weather stations. Think about that. We're 10% more accurate than the weather stations at predicting the weather. And that's because of our customers. Like, they're doing all sorts of crazy analysis on weather patterns, etc. We just did an ad with Shane Gillis on this. I don't know if you saw it. People loved it.
With... is that the one with Manning or...?
No, it was the one with Shane and Danny McBride.
It came out on Friday. It's fun, but it's, you know, it's a whole skit about how Shane... they're both weathermen.
And then Danny McBride keeps getting it right, you know, they're both weathermen and Danny McBride keeps getting it right and Shane gets it wrong.
Two phenomenal guys to get to do this.
They're a lot of fun. Yeah.
So, the DraftKings CEO Jason Robbins in August 2026 said only 1%. And he also said 80 to 90% of prediction markets volume in states with legal sportsbooks came from professional traders and institutions.
Rather than traditional sportsbook customers.
So then why do they hate you? Then why do they...
He's right. I mean, it's not just about them. It's the broader casino, because I think that casinos feel like they should also get a monopoly on this. So they want...
Are they in the space or are they not in it yet?
They want to get into it, and like... it's too late for them. It's always interesting, you know, a lot of these guys, the casinos, first they came to us and they were figuring out if there's a way for them to get into it. Then they realized they're too late.
When did they come to you first time?
And then what did they say? Can we work together?
They were figuring out if there's a way for them to get into the space, etc. Then a lot of them realized that they were late. So what do they do? They're like, 'Let's litigate.' You know, it's always litigate, legislate. And then when you finally realize that this is here to stay and the consumers have adopted it and they, you know, they don't want to change it, you finally innovate. But the state versus federal is never about customer protection. They're trying to ban prediction markets. Why? Because prediction markets... why are markets regulated at the federal level? Why is the New York Stock Exchange regulated at the federal level or the grain futures, even though states wanted to regulate as gambling?
Because you need a large global liquidity pool. You need a large diversity of participants. Imagine having 50 New York Stock Exchanges where in Oregon you can only buy Tesla stock from someone in Oregon.
It wouldn't make any sense. You wouldn't be able to get there as much as you want. You would get worse prices. It would be completely inefficient. It's the complete opposite of free markets, right? If free market is get everybody on a uniform set of rules and have people in Texas trade against California, how would we even get our prediction if the people in California are the only ones trading, only trading against Californians for the Texas election? It would never work.
Is it too late for them? Because if you think about the language learning...
I'm of the view that you should always innovate because even if you're late in a market, do it anyways.
Yeah. The market is always big. I'm a positive thinker, right? And if they wanted to get... but I think it's a bit different because the professional traders are not going to really... they don't abide by the traditional casino or sportsbook. Like, my biggest competitors are like Robinhood and Goldman over time, because the customers are the same: those professional traders that Jason is talking about. He's right, 80, 90% are coming from professional traders, and he's right about that because those are traders that otherwise are trading in equities and commodities and...
Would you get into their space or are you not touching what they're doing?
You have no interest to get into what casinos are doing?
No, no, no. Gaming is completely different.
Because there's no price discovery coming from it.
So then what's the upside for?
I'm building the modern-day financial market. That's what I'm building. I'm building the next-generation CME, the Chicago Board of Trade, because historically, why do markets exist, right? They give us predictability for an industry, and once that industry matures, it needs instruments to manage that unpredictability for lenders, for certainty, for investment. How do we start? We started grain futures. Why? 100 years, 150 years ago, because the American economy was primarily agriculture. Then we moved into industrializing. So what do we get? Oil futures, metal futures, things that are basically inputs and outputs of the industrial phase. Then we move into interest rate swaps and interest rate futures and credit and all these other indices, S&P futures. Why? Because banks and the services sector started growing, financial services became bigger. And to me, Kalshi is a generalization of that. Do we believe there's economic impact from politics, from sports, from weather, from all these different things? Certainly. And do we need an industry to help predict the risks around those different industries? For sure, over time. And that demand is going to only grow, and Kalshi in some ways generalizes the stock market.
Who would Kalshi take business away from if it's not sports gambling? Who would it be?
I believe these things tend to be more additive than people make it out to be.
Yeah, I think so. Because like liquidity begets liquidity. So when I add... so, okay, there's a farmer in California a month or two ago. He's in the goat herding business. He's a goat herder. He has 3,000 goats. Why do these goats exist? They eat the grass that usually leads to wildfires. Okay. And that farmer, you know, he had a risk, which is that there was a bill in the legislature in California that was going to up goat herding wages from $70,000 to $240,000. It's going to drive him out of business because he can't afford these things.
More than 3x. So it's going to drive him out of business because how could you afford these wages?
He went to insurance companies, 'Can you please underwrite this risk for me?' What did they say? 'No, there's no way.' Who is in the business of underwriting these different risks? So he came to us like, 'Can you list a market on it?' Like, certainly within 2 hours the market started trading. We have, you know, again, 30 minutes, we have a hive mind that can, you know, price it, says that there's 10% chance of this thing happening. If you search for goat herder, you'll see it directly. Goat herder. Yeah. First one.
And then he bought $50,000 at 10%, which pays out $500,000 if the bad thing happens, as a hedge, as insurance. And it happened, and he got paid $500,000 that he's now using to diversify his business and stay afloat for another 18 months.
He put 50k on Kalshi, he made a half a million dollars.
As a hedge. As a hedge because he's now... he has to pay all different... so he's offsetting some of the additional cost.
Who are we taking business from there?
Nobody. We're bringing liquidity to a much larger set of things that wouldn't have been liquid otherwise. Like when a sports business, a bar or a marketer comes and puts a hedge on Kalshi to hedge themselves against sports risk, what is their alternative historically? Like going and doing it on DraftKings? They were never going to do that on DraftKings. It doesn't make any sense. They need a financial instrument that is traded on an open market where people are going to compete and provide them competitive bids and ask competitive pricing, so they can book it on their financials as a financial instrument and like place that hedge as a real hedge. And so it's a new market that's being created that basically creates more opportunities to price risk and manage risk.
Well, who is an enemy? Who is not happy with Kalshi?
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I generally feel at my core like elites will always not love it because I think that's really what we're over... like 80% of our customers are active, they don't trade. So 30 million customers that have trading accounts, but really close to 100 million in America that like use it for the forecast. You see it on Fox, CNN, you see it, the campaigns are all using Kalshi.
80% use it but don't trade. They use it for the information.
They use it for the information.
That's a public good that comes out of markets. Would a sportsbook be able to... 80% of my customers don't use...
What is the information that you're getting out of it, right?
But that's what markets do. They surface information to people. And but here's the key thing about it.
Elites will never love these markets and they'll always attack us. That's why we often get attacked in the press, etc. Because like it's the first time that information is flowing from people bottom up. There's no gatekeepers. There's no elite. We're not listening to a handful of people telling us here's the truth and here's not what's true. We don't have gatekeepers of the truth. The truth here is being produced by millions of American people putting money where their mouth is, having skin in the game.
Okay. So how about Fanatics? How about Robinhood? How about state gaming regulators? How about those guys? Would they...
I think it's... Look, I think we always say like we're happy to engage. Like I always tell states, it was never about... if people want to tax us, people say, 'Oh, we're avoiding taxes.' That's not at all true. I've always told states, if you want to tax us at a sensible rate, I'm actually not the type that is completely against taxes. I'm fine with it. Let's come to a reasonable deal. This is a very fast-growing industry, and look, if there's ways where we can promote more education and like fund education resources or education in general or healthcare, I'm all for it. I actually... that's my personal view. I'm a free markets guy and I love capitalism. But at the same time, I think things are a little bit too out of whack. There's too much wealth inequality right now. We have to adjust it a little bit to make sure we bring in more people into the system. I think when people are out of the system and they're sitting on the sidelines, it's normal that over time they're going to bubble up feelings that they don't like the system because, you know, if I was out of the system, I don't like it either, right? And so that's my view.
And then if there's really... if people are worried about consumer protections, if we feel like there's not... and I'm a pro-regulations guy, I think there needs to be sensible guardrails around any market. Why? Because you need to make sure that it's fair. If a marketplace is not fair, there's corruption in a marketplace, what happens? People stop trusting it. Why would you ever participate in a marketplace that is not fair, where the guy on the other side may have a knife and you don't, right? Like that's unfair. And so I'm a believer in regulation. I tell states, look, let's have a good-faith discussion. If you think that we are regulated at the federal level, we spent the first four years getting regulated, but if you think there should be additional consumer protections in your state, let's have a conversation about that. We're open to it, as long as it doesn't hamper on the free markets principles of a federally regulated exchange.
Are you in all 50 states right now?
Except for Nevada, which you're going to...
Makes sense. You know, they got... Do you think you'll ever get in there or...?
I think, you know, it's bubbling up. There's some litigation. There's litigation that's going on. And I think, you know, we feel very good about like, you know, the way that this needs to be regulated, which is federal. And I think that there's a bit of kind of... I think there's some confusion, plus, you know, the casino lobby is doing a lot of work right now, I guess.
Interesting. How about Polymarket?
Look, I think I like competition. I think competition is great. And you know, we have competition from Polymarket. We have Robinhood. We have, you know, the big banks are getting... they've announced they're getting into the prediction market space, which is exciting. I mean, we just announced a partnership with S&P, which is the largest...
And the NBA.
What I'm excited about is the largest financial data provider on the planet. It's, you know, and I think...
The difference I have with Polymarket is we took a regulatory-first approach to building the business. I wanted to build it in America, the American exchange, pro-regulation, regulated first, and I got regulated as a financial market and like have all the right rules around banning insider trading, banning manipulation, making sure minors are not on the product, all the kind of sensible guards that it needs to be. And I spent the first four years doing that, right? They just launched offshore and then started growing before... and you remember this a few years ago, Polymarket was the brand. It wasn't Kalshi.
