Forecasting the Future with Kalshi: America’s First Regulated Prediction Market

In this week’s episode of No Priors, Sarah sits down with Tarek Mansour, CEO of Kalshi—the first CFTC-regulated prediction market exchange in the U. S. They dive into Kalshi’s recent victory to legalize election betting, explore ethical questions around trading on elections, and discuss whether prediction markets can offer more accuracy than traditional polls. Tarek shares insights on the history of futures markets, the line between gambling and financial trading, and the psychology behind betting. Plus, Sarah makes a live election bet, and Tarek reveals some of Kalshi’s most intriguing markets. Sign up for new podcasts every week. Email feedback to [email protected] Follow us on Twitter: @NoPriorsPod | @Saranormous | @EladGil | @MansourTarek Show Notes: 0:00 Introduction 1:22 Sarah makes a live election bet on Kalshi 3:35 Getting approved and regulated by CFTC 5:48 Going up against the CFTC to legalize election betting 7:21 Debating the ethics of trading on elections 8:12 Gambling vs. trading 9:12 Context and purpose of futures markets 12:38 The human psychology behind speculating /Humans conditioned to risk taking 17:17 Building a healthy exchange and scaling liquidity 19:30 Introducing leverage and working with clearinghouses 22:29 Polls vs. prediction markets 24:59 Conditional markets 26:38 What makes Kalshi’s markets accurate 31:29 Tarek’s insights on the most interesting trades and markets on the platform

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:05Sarah Guo?

  Hi listeners and welcome back to No Priors. Today I'll be talking with Tarek Mansour, co-founder and CEO of Kalshi. Kalshi is a recently CFTC-regulated prediction market exchange that's changing how people forecast future events like the upcoming US election, the weather, the date of arrival of AGI, and the jobs report. Tarek started Kalshi after studying at MIT and working at Citadel and Palantir. We'll discuss what a prediction market is, if it's a threat to democracy, building a regulated exchange, and how Kalshi fits into the broader financial ecosystem. Welcome, Tarek.

• 0:40Speaker 01

  Great seeing you, Sarah. Thanks for having me.

• 0:42Sarah Guo?

  It's gonna be a super exciting, small number of weeks before the election. Can you please explain to anybody who hasn't been on it yet, what is Kalshi?

• 0:50Speaker 01

  Kalshi is actually the first legal platform in the US where you can basically bet yes, no on any future questions. The thing that's really cool is like, we've basically created a financial instrument where the thing that you're actually buying or selling or trading or betting on is not a stock, it's not a bond, it's not a commodity like oil, it's something more intangible. It's actually whether an event is gonna happen or not. So on Kalshi, you can basically buy shares of whether it's gonna rain tomorrow, whether TikTok is gonna get banned, whether Eric Adams is gonna get fired as New York mayor, or whether Donald Trump is gonna win the next election.

• 1:20Sarah Guo?

  Okay, cool. I feel like the easiest way to get a sense is like, let's make a trade. I'm gonna share my screen. Okay, here I am. You got Kalshi?

• 1:28Speaker 01

  Yeah, so it's kalshi.com/elections. So this is actually our live election forecast page. You can see that Trump is up 55, 45 right now, and 19 days left. So we'll see how that evolves. You can go, yeah, I think you're clicking. So this is the election market. I'm actually gonna let you figure it out.

• 1:49Sarah Guo?

  No, no, I understand here. I think, you know, Trump at 55%, that feels underpriced to me. Let's go in on it. $267. Oh, I got, I have 150 in cash, I'm gonna go all in on this. Feels, it feels like a trade I wanna make. Um, let's see, what happens? Market closes when the outcome occurs. Two hours after closing. I'm ready.

• 2:22Sarah Guo?

  Did that just happen?

• 2:23Speaker 01

  Yeah, it's done.

• 2:25Sarah Guo?

  Oh, wow. Okay. Wow, you're gonna bankrupt me. This is too easy.

• 2:28Speaker 01

  Yeah, I mean, it's pretty cool, right? So I think like, the cool thing about this is like, you can actually also sell it before. So if you click on Donald Trump right now, you can see your position.

• 2:39Speaker 01

  Or on the, yeah, right here. And then you can see your position, and you can actually exit it if you want to. So you can sell at 55 if you wanted to. You should now. But, uh, so right now, obviously, if you sold it directly, you'd just be paying, paying the spread, paying the bid ass. But if things move, if he, if his odds go up in a, I don't know, in a few days or tomorrow or whatever, you can sell it at a profit. The other thing that's actually really cool, and we launched this just now, is now you have a bet on Trump, you also, like, only get paid interest on that bet. So it's, it gets deposited in money markets, in US treasuries, and you get paid 4.1% interest while sitting there waiting. And so it's cool because usually people say like, hey, these are kind of zero sum type things, like you either win or lose.

• 3:20Speaker 01

  Whereas in here, like, whether you win or lose, you're getting paid interest while waiting.

• 3:25Sarah Guo?

  Excellent. Excellent. I will go deposit more of, you know, my total wealth given, given money market accounts now. You recently were involved with a long-term kerfuffle with the CFTC to get regulated trades on political events. So you've been at this for, I think, six years as a company?

• 3:47Speaker 01

  Yeah, five and a bit, yeah.

• 3:49Sarah Guo?

  Five and a bit, okay. It's a totally insane thing to try as a startup to, you know, go up against the CFTC. Can you talk about that?

• 3:58Speaker 01

  We hold two core beliefs. I think, one, prediction markets have the potential to be the next large thing in financial markets. I do genuinely think that, like, if you think about it from first principles, like, people like to take exposure on things. They like to speculate. They, sometimes they wanna hedge. They like, or, you know, it could be either betting or hedging, but... But it feels like the current instruments are a bit like, you know, you have things like, okay, you have stocks, that's fine, but you also have like options and futures, they're all just so loaded. It's like so Wall Street-y and like people don't really care. But if you think about like prediction markets, what they do is like they achieve a similar similar sort of like urge or they, I think they're targeting a similar market, but instead of like these kind of traditional boring financial instruments,

• 4:42Speaker 01

  you're taking positions on things you care about. Like I have a view on the weather, I have a view on climate, I have a view on AI, which a lot of people have a view on now. And then you can basically take a stick in that. So I think that one, they're gonna be very big, I think so. And then two, I have yet to see a financial market that has gone really big without being properly regulated. I have yet to see that in history. It's always like you have to do it legally, safe, compliant. So our core approach from the start is like legal and safe and compliant and trusted first. A bit like Coinbase, how Coinbase approached crypto, and I've always liked their approach. And so before we launched anything, we spent actually, you know, close to three years getting regulated upfront by the CFTC. So we've written a lot of the regs. We actually spent, you know, literally 14, 16 hours a day for a year and a half, doing nothing else other than writing law and regulations

• 5:27Speaker 01

  for how prediction markets could be regulated in the US. And we got it done with the CFTC and we got approved. So we were the first actually a market in history that actually could do prediction markets legally in the US. So that was one, step one. The thing that we fought over is that after we got approved, the one thing they didn't want us to do is the US election. There's just so much taboo. I don't know how to explain it. It's like a part of it is in is Congress, there's a, there's a vocal minority in Congress that just hates them. And I, maybe we can talk about this in a bit, they believe that they're gonna break democracy and this is gambling. I obviously totally disagree with that. But it was funny because, you know, our board at first was like, well, this sounds like a horrible idea. Like when we, when Juan and I brought it up to Alfred and from Sequoia and NYC, we're like, hey, we're gonna sue the government, a regulator.

• 6:12Speaker 01

  And they're like, we, it's never a good idea, it's just a bad pattern. But we took the risk. And it was brutal, it was really brutal. Like going up against the federal government is, is, is super tough because it's like the plane, the balance of field is so tilted. The standard to win for you is so much higher than the standard to win for the government. But we won and winning felt pretty good. I think the win was worth all the years of pain. And I think maybe this is how it is for, I think, any entrepreneurial journey. It's like you go through all the pain for so long, you have to endure. And then the ups, the highs are so high that it makes it all worth it. So we won this month. And the cool thing now is like, it's the first time in a hundred years that betting on the election,

• 6:56Speaker 01

  trading on the election is actually legal in the U.S. It's finally back to actually being legal. And this time it's actually regulated and we're the only ones that can run it.

• 7:04Sarah Guo?

  You just, I think, like seeded a whole bunch of threads that we should talk about. Like, what is, uh, maybe we'll start with one that I think is important. What is the argument against trades on elections? Like, what is the sort of ruining democracy concern?

• 7:22Speaker 01

  Yeah, it's two arguments. One, you know, there's a question like, is this gambling? And then the second one is, could they ruin the perception of elections?

• 7:30Sarah Guo?

  Is there a reflexivity in this?

• 7:32Speaker 01

  Exactly, exactly. Reflexivity, I think that's the right term. Like, could some weird thing go in a loop? So let me address one by one. So I think the gambling piece is super interesting. I love, I love history and I really love financial history. Like, when I got into the business, one of the big reasons, like, I loved sort of, how did we come up with all these instruments? I worked at Goldman, so that, like, have you ever been to a Goldman Sachs trading floor? Or any, any?

• 7:53Sarah Guo?

  I used to work at Goldman, so yes.

• 7:54Speaker 01

  Oh, okay, so great. So I mean, you see, like, it's so weird. Like, you have like hundreds of traders sitting behind laptops trading things like options and swaps. And the question that always comes to mind is like, how do we get here? Like, it's insane. But the thing that's interesting is most financial instruments, really the vast majority, in the early days, they were called gambling. Like, that was the consistent thing against it. It's like a form of speculation or gambling and then it's bad for society. An example I love to quote when it comes to the gambling piece is like, so in 1905, when grain futures got legalized in the U.S., it was a Supreme Court decision. And grain futures, now we think of it as like the most boring, like, financial, like, you know, hedging, farmers, like, you know. But at the time, they actually would call it gambling. It was like this new asset that people were like, hey, a lot of people are speculating, so it shouldn't be allowed.

• 8:39Speaker 01

  And then the court decided like, no, fine, some speculation is happening. Like, it does happen in the stock market, but that doesn't mean these markets are not important. And I think it's the same thing here. It's like, it's crazy to me to think that like, taking a stake, a position in the election is the same thing as like betting on the dice roll. Like, that doesn't make any sense to me. Elections are real, that people have economic consequences coming out of the elections, and people may wanna hedge it, or people may wanna, even the forecast is important enough for it, for these markets to exist.

• 9:06Sarah Guo?

  I think actually, it's like worth contextualizing a little bit, like, why futures exist to begin with.

• 9:11Speaker 01

  Yeah.

• 9:11Sarah Guo?

  Right? You, you mentioned like hedging, but just to sort of complete the, the basic story there, like going all the way back to like Japan, Doji no Rice Exchange, like, the original function of futures markets, as I understand them, was like for farmers to hedge price changes, right? You know, even before 1905 US, US grain futures. And so smoothing out, or allowing people who have real economic stake in something to protect themselves was the original premise. What is the difference between like gambling and, and trading?

• 9:46Speaker 01

  So I guess, let's differentiate into two things. There's a stock market, and the function, why it exists. And by the way, a lot of people, you know, I mean, I don't wanna make this political, but I have to because my business has been pretty political, but like, those are the ones of the world, even though the stock market has a lot of speculation, and we should limit it in a variety of different ways. That would be, that's a horrible idea, we should not do that. But the reason it exists is capital allocation, right? You're, you're moving capital from people that have it to people that need it, very simply. And that makes it worthwhile to exist. And that's why hedge funds exist, and that's why all these, you know, we have Wall Street. The futures market, the derivatives market, where, is a bit different. It's not capital allocation, it's risk transfer. And, and I love that notion, I love that notion so much. It's like, it's, it's even more neat. It's like you're transferring risk from people that like have it but cannot bear it,

• 10:31Speaker 01

  to people that don't have it but can bear it. They, they want to diversify, they wanna buy it, etc. And this, this applies to, to the, yeah, to the example of grain futures, or rice futures, or, or pork belly futures, the, the kind of really old school stuff. And the interesting thing in these markets, like, farmers are hedging, like you said. Their, their ability to hedge allows them to have more forecastability, like, hey, I'm, I'm, I'm planting a batch now, what price am I gonna be able to sell it at in the, in the fall?

• 10:55Sarah Guo?

  It makes it a higher quality business to have that forecast ability to.

• 10:58Speaker 01

  Without it, you have too much unpredictability, and what happens with unpredictability is you have less of these businesses. It becomes a harder business to run, so you get lower supply of grain. So, you know, we just actually established that no grain futures today would have resulted in higher prices for bread. That sounds like a horrible thing for society, actually. It's a good thing that we have them. Now, that is different from gambling, right? Like grain prices, or hurricanes, or Brexit happening or not, or election, Trump versus Kamala winning, that's a risk that exists already, right? Like, it's not like you and I are creating this risk so that we can bet on it. This exists already. And some people, like, if you're on a climate tech company, you're obviously better off if Kamala wins than if Trump wins.

• 11:41Speaker 01

  If you're on a crypto company, you're better off if Trump wins than Kamala. You have a real tangible binary risk that you may want to insure against. That's very different from you and I going and doing a roulette spin so that we can speculate. That is an activity that's recreational. That, I don't have strong views on gambling or not. I think people should be able to do whatever they want with their money. But that's different. That does not have benefit for society that go beyond just having fun, right? And so, yes, I think hedging is a core pillar. But then there's actually another thing that people don't talk about. It's called price basing in these markets, which is it gives you an indication of price, right? Like, farmers without a futures market have no idea what this thing is going to sell for in the fall. The futures market actually gives them an indication of what it's going to sell for. And I think the prediction markets take it a step further.

• 12:25Speaker 01

  It's actually the price is equal to probability. It's even cleaner. It's like, who's going to win? Right now, it's saying 55% Trump. Is TikTok going to get banned? I think, I forgot right now. I think by May, it's like 35%. Doesn't look like it's going to happen. All, like, you're pricing the future. And I think that's another really neat concept, because if you price the future, then you can, you're smarter, right? Like, you can make better decisions about what's going to happen. If you're a TikTok creator, now you're not going to, you know, the likelihood of TikTok getting banned is a life or death situation for your business, basically.

• 12:57Sarah Guo?

  They are related.

• 12:59Speaker 01

  Yeah.

• 12:59Sarah Guo?

  Right. I mean, I have graduated from poker to informed investing.

• 13:04Speaker 01

  There is speculation in all markets. That's a fact, right? And speculation is like, you bring some money to make more money, and, you know, it's something you don't really control. Without it, you don't get a liquid market, right? If people don't have that, they're not doing that. You don't, the market is not going to have any activity. It's impossible. And so, that's been a kind of rule of markets. Like, you have to have speculation. You have to have some of the degens. You have to have some of the informed. You have to have a little bit of everything to have a vibrant marketplace. People love to speculate. So, we started different forms of speculation slash betting slash gambling before we even could write. Most people don't know this. We actually used to play games, like we used to do it with rocks, like. And then, you know, people get a reward if the rock comes your side and you pay something if it doesn't.

• 13:48Speaker 01

  Uh, and that was before we had actually like a language. It's probably some, something related to evolutionary psychology. It's interesting because when you confine it to the, okay, I'm, I'm placing a bet on Trump or I'm placing, you know, I'm, I'm betting on something specific. You know, sure, you, you kind of, we grasp was like, this is people betting on something. But I, I think like if you broaden a bit more to, to life, like we are constantly making decisions. Where you're, we're risk adjusting, we're taking risks, sometimes not taking the risk is another form of risk. Like, like life is risky. You walk outside, you might get hit by a bus. You're taking risks by walking outside every single day. I, I believe we have been conditioned to risk taking. Humans are conditioned to risk taking. You know this thing that Nassim Taleb talks about? When you're evaluating risks, like your grandma is better than most data scientists. Have you, have you ever?

• 14:31Sarah Guo?

  No, no, no, explain.

• 14:32Speaker 01

  So, so basically there's this whole thing in like measuring risk where unless you're talking to like a PhD or a research lab that's extremely specialized in a very specific form of risk. Asking your grandma is actually a better rule of thumb than actually doing any data analysis. Like COVID was a typical, like you had a bunch of people, you know, like the, you know, the midwif meme, like they did a bunch of analysis like, hey, COVID and it's probably the view dying is lower than a bus and whatever. And if you ask your grandma, the guy would be say like, hey, wear a mask or stay at home. I guess there's two insights. One, generally speaking, don't listen to data, data scientists. Data science is mostly bullshit. Health papers and stuff like, like most of them are just total garbage.

• 15:11Sarah Guo?

  What makes them garbage?

• 15:12Speaker 01

  It's just so easy to fit the data and it's so hard to actually make sure, like check how the data and like, it's just.

• 15:17Sarah Guo?

  Reproducibility and just.

• 15:19Speaker 01

  Reproducibility or the sampling is, and even if it's reproducible, there's so many things that could go wrong and the incentives are off. And you have to publish in nature. So you have to do all sorts of weird things. It's true that grandmas are surprisingly good at, at, at risk management. They have a very good intuition of risk. Humans, we've evolved to be pretty fairly cer- fairly good with risk, actually. And, and even current society actually rewards risk takers better than non-risk takers, right? Like you see it everywhere. Is it actually that much more risky to place a bet on something you're interested in? Or even something that's totally garbage, like, you know, in a casino than starting a company? Like I, I think about these things a lot, like I would argue starting a company is even crazier. So how do casinos actually advertise their products?

• 16:03Speaker 01

  They, they like show you the one person that made. Three hundred thousand dollars in the slot machine. People get excited and everyone goes and does it. And you know, everybody knows the art, et cetera.

• 16:13Speaker 01

  Well, it still kind of does the same thing if you think about it. Like, you know, we, they show like Airbnb and Coinbase. And then you have like a flock of people basically going and start a company. Um, now the big difference is obviously starting a company is actually net positive for society versus like playing on a slot machine is not. But I'm, I'm talking more about the notion of risk. Like, we all love taking risks. It's just more fun. Living a life where you're taking a risk is just such a superior life than one where you're just not taking any, right? Um, so yeah, take more risks. I'm taking a lot.

• 16:42Sarah Guo?

  Yeah. I believe generally the principle, I think it depends on what the profile of risk is. And I think Nassim Taleb is a, is a, you know, fundamentally pretty conservative or, you know, technophobic in some ways. And I'd be like, hey, man, like, I am investing in AI. My grandma cannot take these risks, right? So, so I, I think it depends.

• 17:03Speaker 01

  I mean, he's more on the short side. He, he's like more the pessimistic negative side.

• 17:07Sarah Guo?

  Uh, conscious is a, a fascinating business. You used to work at Citadel. You are starting this market from scratch. I think the day we are talking, you know, like there's sixteen million in on the election plus nine hundred fifty dollars.

• 17:21Speaker 01

  Yeah.

• 17:21Sarah Guo?

  Talk a little bit about how you think about designing a, a healthy market.

• 17:26Speaker 01

  Yeah, I mean, we just launched the election. It's, we're, we're obviously launching, uh, pre-late, uh, because we just won the lawsuit. Yeah, the markets just take time. They need catering, they need watering, but they grow and they, they're growing. I mean, actually we're growing like, I think the last two days have been like six X day over day in terms of like signups and in terms of, uh, uh, uh, volume. So it just takes time, but it's, I think it's ramping up very fast. Exchanges are notoriously very difficult businesses to build. There are some of the hardest, uh, because you have the marketplace angle, uh, which is always hard. And exchanges like you have to bring in the liquidity and that's really hard to ramp up and takes a long time.

• 17:58Sarah Guo?

  How do you think about retail versus like large market makers and institutional masters?

• 18:02Speaker 01

  I think of it as more of falling on a spectrum that goes from like lots of trades, small size to less frequent trading, but big size. So I think the way that the market evolves is like because we have lower liquidity now, we target retail and then we scale our liquidity as we scale with retail and then we scale type of customer over time. You build an initial layer of liquidity and we already I think have that at Kalshi where like now we have this community, this very dedicated community of people that forecast these events, they price them and then as they price these different events, you know, like will it rain tomorrow, is climate change getting worse or better, is COVID gonna come back? As you price them, the like the mere fact of getting a price, you can ramp up liquidity. You can get more and more liquidity over time and as you get more liquidity, you attract

• 18:45Speaker 01

  the large institutions that may, if you're a big institution, you wanna hedge against cyber risk or a new bill that may pass in Congress that you hate or other. So it's I think a progression. That's how we think about it. Election specifically, we're seeing a lot of institutional flow. It just said like we're a bit late in the game, but the institutions take time, compliance take time to onboard, but we're seeing a lot of institutional flow. There is demand for like $10 million, $20 million, actually there is demand even up to $100 million trades. We have three weeks, so we're gonna have to figure out if we have enough time with our compliance departments to onboard to Kalshi. But if we do, I think we'll see $100 million trades. It's gonna be really cool.

• 19:19Sarah Guo?

  How do you think about leverage?

• 19:21Speaker 01

  So there's a few things like this is a like a risk on product, right? This is not like a if you buy, you know, S and P, it doesn't move like maybe like 0.5% on typical day, right? It moves more like 10% on a typical day. So it's already pretty volatile. We have been thinking about how could we basically introduce margin and leverage into the system because when you introduce leverage, there's more trading, right? Like $1 can create much more trading activity and we want to introduce more leverage over time, but the system gets riskier. A little bit of context, so we own now, as of this year, actually, one of the like

• 20:01Speaker 01

  there's a handful of clearing houses in the US that can actually clear, that can move and hold dollars for trading. For trading derivatives, like this happened after 2010. So when the crisis happened, Dodd-Frank came in and says, every like trading of derivative has to go through central clearinghouses. And the reason for that is like you and I cannot trade with each other anymore like banks used to do. We can't be counterparties because if I and what happened then is I defaulted, then you defaulted, then Alpha defaulted, then Kelly defaulted, everybody started defaulting, all the banks defaulted, and it was bad for the entire economy. Now it's all centralized in one place where the US government can see the risk and then that one place can basically like manage that risk appropriately. That's clearinghouses.

• 20:46Speaker 01

  So we actually, as of this year, we own one of the handful. The question is like, when do we, when and how do we introduce the ability for people to take positions without putting all the cash upfront? But now you're introducing credit risk, right, into the system? I want to do it. I want to do it with the next, maybe 12 to 18 months. But we're going to have to get really smart on sort of like, like, okay, if Sarah shows up to the exchange, like, how much leverage should we give you? Should we let you do 10 to 1? Should we let you do 100 to 1? Should we let you do only 2 to 1? That becomes, like, that's a tough question to answer, actually.

• 21:19Sarah Guo?

  Yeah. I mean, it feels like there's a lot of decisions to make there, right?

• 21:23Speaker 01

  Yeah.

• 21:23Sarah Guo?

  Guaranteeing trades, enforcing margin requirements. Exchanges and clearinghouses are very complex. And so if you think about, what's a good, like, maybe the 2008 futures bubble?

• 21:34Speaker 01

  Yeah.

• 21:35Sarah Guo?

  Like, there are versions of this that are less healthy. And also, like, speculation is going to exist in any market. And, you know, people want liquidity, right? So I think it's a really interesting problem to go solve.

• 21:47Speaker 01

  If you add leverage, I mean, if you let, if you let people just do it without pre-funding, you definitely expose the system to risk. Again, like, risk is fine. We just need to figure out how to manage it. And I think for us, like, this is one of those things, like, where the government is actually very, very tough on us and clearinghouses to do. Like, we really need to be kind of really buttoned up to get this, to get this done. And I think we'll do it. I think we're just have a lot of work to do to get there. Because things can go really wrong when they do go wrong, right? Yeah, I mean, 2008 was pretty bad.

• 22:17Sarah Guo?

  Uh, maybe like just thinking about, you know, the coming election. How should people think about prediction markets versus polling?

• 22:25Speaker 01

  There's a lot of confusion around this. Polling is asking people who they're going to vote for, right? Like, so, so. Assume you can go to, you can survey every single person in Pennsylvania, and then ask them, you know, um, who are you gonna vote for? And then you count it all up, and then you get that Trump is 51% of people and Kamala is 49% of people. Then you, it's guaranteed that Trump is gonna win Pennsylvania, right? Like, that's a guarantee. Now, obviously polls don't work like that. Polls are biased, a lot of them are biased. You should not trust most of them. There's a few that you can trust, but assuming the unbiased ones, like, they don't survey everyone in Pennsylvania. How about you, they survey a good sample, hopefully well done. And then they tell you, we think that it's gonna be 51, 49.

• 23:11Speaker 01

  The 51, 49, that 1% difference of polling that Trump has over Kamala,

• 23:17Speaker 01

  that's definitive, right? That's Trump winning. That's like, you know, if the poll is reasonably accurate, that, that, you know.

• 23:25Speaker 01

  Prediction markets are not doing the same thing, right? Prediction markets are just pricing the odds of Trump versus Kamala winning, right? They are for, like, they're just giving a probability. We think there's a, you know, today, right now, it's 55% chance that Trump is winning. That does not mean that Trump is up 5% on average over Kamala on the polls nationally. That, that, that's not what it means. The other thing that people need to understand is that if Trump polls 1% higher than Kamala or vice versa, prediction markets are more volatile. They're gonna move more than 1%, right? They're gonna give Trump a higher probability or Kamala a higher probability based on the polling. So, it, people are misinterpreting the data and, and, and like, think, people say like, oh, like,

• 24:07Speaker 01

  Trump has a 10-point lead or like 8-point lead over Kamala. That's incorrect. That's not what the market is saying. Trump does not like, Trump now is more likely, like, it's a coin flip, but it's a biased coin flip that's biased towards Trump to win. You're still flipping a coin flip. It's slightly more likely to go heads than tails, but it could still come tails. And people are, I think, really confusing that.

• 24:31Speaker 01

  And you see it right now, right? And over the last week, you know, the, the sentiment, people are misinterpreting what these prediction markets are saying. I think people maybe don't understand odds that well. There's some education we need to do.

• 24:42Sarah Guo?

  Yeah, well, because there is pricing, not just prediction, right?

• 24:46Speaker 01

  Correct.

• 24:47Sarah Guo?

  Yeah, I think you can you can kind of assemble this from different events on Kalshi now. But I I want to make a this is just a random feature request for you. I want to make a million dollar event trade. That is, if there is disruption in the Middle East before the election, more money on Trump at up to these odds. I want a conditional event trade. By the way, that's not a political opinion. That's just a

• 25:09Speaker 01

  That is a fact.

• 25:10Sarah Guo?

  It's a trade.

• 25:11Speaker 01

  Yeah, yeah, but I think additional markets are actually the next one of so internally also. Most of our engineers really want conditional markets ASAP. We want to do them. I don't know when, but definitely the next few months we're going to do conditionals because I love like I really love conditionals. Like I love this idea of like you basically what you're saying is like it like it. And it's a question that people ask like, is the Middle East war a good thing for Trump or a good thing for Kamala? I mean, you know, and who does it favor? And then you can extend it to a lot of other interesting questions, right? Like if Trump wins, what will happen to GDP? What will happen to inflation? If Kamala wins, what will happen to GDP? What will happen to inflation? And you can extend that to everything, right? If Canada X wins, what will happen to crime rates? What will happen to S and P? What will happen to trade types?

• 25:55Speaker 01

  Like conditionals actually are so neat because it's all about incentives, right? Like, you know, markets don't lie. That's the beauty of markets, right? Like markets don't tell anyone what they want to hear. They don't tell anyone what they don't want to hear. Like markets just do their thing. And the reason they don't lie is there is money on the line. You can trust one thing in this world is people like making money and they do not like losing money. You can trust that as long as you trust that markets do a fair job at doing this, right?

• 26:21Sarah Guo?

  And as a question done in the like, like very specific context of this one market. Is there a level at which you'd say that Kalshi is better at predicting the outcome of this election than all polling? From a liquidity perspective, or you're just like, we're there like we're, you know, it's de minimis scale.

• 26:42Speaker 01

  Oh, no, we're definitely there. We're definitely there. You should definitely listen to prediction markets. I think Kalshi is unique, even compared to other prediction markets, is that it's Americans and it's regulated. So you know that no, like, there's no weird thing going on. There's no foreign influence. There's no tampering. There's no Wall trading. Like, it's all here. It's Americans. There's regulatory oversight on top of it. Like, government is overseeing everything. So Kalshi has this unique thing, and there's institutional adoption. So it's not, like, there's no, because people ask me, like, do you have a crypto bias? Or do you have a Trump bias? The answer is no. Like, we have large market makers like Susquehanna Sig and a few others that are confidential. And so I think actually Kalshi is a pretty accurate gauge. Right now, 55% is what I would call fair value.

• 27:27Speaker 01

  That's the correct odds of Trump winning. That doesn't mean Trump will win, but, you know, Trump is more likely than not to win right now. So I'll give you a few examples. Like, we have been the most accurate forecast for inflation over the last two years, which is really hard to forecast. We're better than Bloomberg. We're better than the Economist survey. Wall Street is starting to use us instead of any other alternative. We predict the Fed decisions better than anything else. We predicted TikTok. We predicted Boeing CEO and what was gonna happen to him. We predicted the Omicron wave, more accurate than any alternative. And then you have a long tail, like, we predict the weather these days. Like, we can predict daily weather more accurately than most weather stations. And it just really-

• 28:06Sarah Guo?

  Is there any intuition for that? Like, the rest of it, I'm like, oh, you can have more, like, the market has the data, right? Like, the weather one, I'm like, man, I've looked at weather modeling and, like, it's a very hard problem. Like, how could that be true?

• 28:22Speaker 01

  Here's why. So weather, the other one is earthquakes. Actually, we also predicted, we did a good job, like, there was the tsunami or the earthquake in Japan, and we kind of did a good job predicting, like, when and how a next one will hit. Earthquake is obviously insanely hard to predict. You cannot do it. But I, and what I say, like, the statement I made was not like we are always accurate or we're super accurate. What I made it, what the statement I made is that we're more accurate than alternatives. And the reason is actually very simple. It's like-

• 28:51Speaker 01

  Okay, let's talk about earthquakes or weather. Earthquakes, you, right now, the alternative is like you go to an expert and the expert makes a prediction. That's it. And if the expert is wrong, there's no impact, like, no consequence. And if he's right, you know, people, you'll gain more followers on Twitter and people are gonna wanna listen to it. Great. When you open a market, this expert that may have an opinion, but there's also a bunch of other experts, maybe also a bunch of random, I don't know, people that read the news and are interested in earthquakes. If you bring them all into a marketplace and you incentivize them to actually be right, what they're gonna do is scout, you know, scout for information. They enter anyone that can find information and then trade it into the market. Bring it into the market. That's what markets do so well, right? Like, they do what we call information aggregation or dissemination.

• 29:36Speaker 01

  So you go and do research and then bring it to the market. And then if enough people do it, you get market efficiency. You get an efficient pricing. And if it's not someone who's smarter, that has information, that disagrees with the market, should also, is incentivized to come and trade against it, to bring it back to efficiency. So that's the intuition, right? It's think of it as like wisdom of the crowd plus skin in the game. You combine those two, you actually end up having, it's like a better mechanism to forecast anything than like trusting anybody saying stuff on TV, essentially. And that's why it works for the weather, because people are incentivized to be right. They wanna make money.

• 30:09Sarah Guo?

  What is the process to add a new market to Kalshi?

• 30:12Speaker 01

  It takes 24 hours now. So that was actually a really difficult one, because our first market that we ever listed took us 18 months.

• 30:20Speaker 01

  And that's what it takes other exchanges, like when CME wants to trade a new grain future, S and P future, takes two years. We had to shrink down the tech, the regulation, the ops for that. And now we, like, we literally just compounded over time and now we can do it in 24 hours. So a lot of our team comes up with markets, like what's trending, what's valid, what are people talking about? But 50% of our markets actually come from our users. So we have this thing called Market Builder on the site and the app, where people can just build a market and make the case like, hey, I think this should be up. And then we list it within 24 hours. It's weird because if you know whether the movie is going to be good or not beforehand, now you have a forecast of whether a movie is going to be good or not before it gets released. If it's bad, now the movie producers are not going to be able to juice the week of box office before the reviews go out, essentially.

• 31:04Speaker 01

  So really now you're applying market efficiency upfront. You stop wasting people's time and money if they think the movie is going to be bad.

• 31:10Sarah Guo?

  Yeah, that's a fun one. So I assume working at Kalshi, you cannot make trades on Kalshi.

• 31:17Speaker 01

  I can.

• 31:17Sarah Guo?

  Yeah. Are you allowed to describe the trades you are interested in or would make?

• 31:23Speaker 01

  Yeah, I can. I mean, so, well, actually, I cannot trade on Kalshi. I can't trade on any instrument other than stocks because I run a regulated exchange.

• 31:29Sarah Guo?

  Okay.

• 31:30Speaker 01

  Yeah, which kind of sucks, but, oh my God, there's so many that I like. I would definitely, so I would definitely participate in anything that's around, like, a year-long economy, like what the Fed interest rate is going to be and inflation. I love all things around tech. So I love actually, like, forecasting whether CEOs are going to be around for the next year or not. And we have it for all major tech companies.

• 31:57Sarah Guo?

  What tech CEO do you think is going to be out by the end of next year?

• 32:01Speaker 01

  So I don't think that way, actually. I think, so, for example, I don't think like yes or no necessarily. I think what's underpriced. I think Elon leaving Tesla is pretty underpriced. Or like stepping down and having someone run it.

• 32:15Speaker 01

  Like, it says, you know, I mean, now this year is close to dawn, but 2% chance, like 1 in 50? I don't know.

• 32:23Sarah Guo?

  You think it's higher than that?

• 32:24Speaker 01

  Yeah, like if Trump wins and assigns him to be Secretary of, you know, of the government. Like, I mean, this is not financial advice, like, you know, this is not, but this is me personally. 2%, 1 in 50, like, sounds too low. Like, that, like, and that's a 50x multiplier. Like, yeah, I think the odds are more closer to, personally, I think, like, closer to 15%, 15, 20. So that's one. I think people like, these are really hard to price, so people like misprice those quite a bit. And then I would also, like, probably do, I would do weather. I've, I've never thought, I've never understood the appeal, but now I understand it a bit better. It's so cool because you can do it every day, so it's repeated game, and you can better, get better every day. And I love that. That's cool.

• 33:04Sarah Guo?

  Where does the information come from weather? Where would you begin?

• 33:08Speaker 01

  I've heard from some of our users. I know there's a team that scrapes satellite data. They actually figured out how to get satellite data and like, you know.

• 33:18Speaker 01

  But it's not just about like what the weather is gonna be. It's like a bunch of atmospheric things and then they correlated with what the weather is gonna be.

• 33:26Speaker 01

  So I think that's one. There are interesting things around like, you can basically create a bunch of time series, like basically cyclical climate patterns. Like you can model, like it's all about modeling, okay, what, how the climate cycle looks like and seasons. And like there's different frequencies for seasons and day, day, daily fluctuation. And then also like, like yearly and decade long fluctuation. Then also like this millennium. So you can do a lot of stuff like that. But then after you just have to tweak and search and research and find niche places where people like to make predictions. And there's a lot to do there.

• 34:00Sarah Guo?

  Do trading firms recruit off of Kalshi leaderboards yet?

• 34:03Speaker 01

  Yeah, they do.

• 34:03Sarah Guo?

  Okay, yeah.

• 34:05Speaker 01

  They ask us a lot also, but, but I mean, there are people that consistently, like there are people that are making hundreds of thousands of dollars a month on, on weather, weather alone. The dude who's forecasted inflation the best, so we have hedge funds, we have pop shops, we have Wall Street people, everybody. There's the, the best forecaster over the last 18 to 24 month is, is a random dude from Kansas. Never traded in his life, just likes to read the news. And this man just knows what inflation is gonna be like. It's insane.

• 34:33Sarah Guo?

  Awesome.

• 34:33Speaker 01

  It's incredible, yeah. But they do cool stuff like they, not him, but there's a team that correlated, for example, like how late the lights are on at the BLS with

• 34:45Sarah Guo?

  That's so funny.

• 34:45Speaker 01

  The jobs data.

• 34:48Speaker 01

  I mean, how do you even come up with that? I don't know, but people come up with stuff like that.

• 34:52Sarah Guo?

  Well, this is so cool. I love the idea of opening the aperture of the types of risks that people can go price in the world and, and transfer. And so it's good to hang out. I'm such a nerd about markets and it's a really cool thing you guys have done.

• 35:05Speaker 01

  This is really fun. I love doing the pod. Thanks so much for having me. This was really, really fun.

• 35:09Sarah Guo?

  Congratulations on the, the progress so far and good luck to all our Kalshi traders on the election.

• 35:17Sarah Guo?

  Find us on Twitter at NoPriorsPod. Subscribe to our YouTube channel if you want to see our faces. Follow the show on Apple Podcasts, Spotify, or wherever you listen. That way you get a new episode every week and sign up for emails or find transcripts for every episode at no-priors.com.