Creating prediction markets (and suing the CFTC) with Tarek Mansour and Luana Lopes Lara

Transcript

I brought some Brazilian beers. This is great. I'm going to try a Brazilian beer, though. Fantastic. Do you want a Brazilian beer or Guinness? Well, I think I need to have Guinness. You need to have Guinness. We lost Tarek already. It's been one minute. Tarek Mansour and Luana Lara are co-founders of Calci, one of the new prediction market firms that rose to prominence in the November 24 elections. They spent four years pre-launch fighting for regulatory approval to build the first onshore prediction market in the US, and now trade more than $10 billion each month in prediction contracts. [SPEAKER_00] Cheers. [SPEAKER_00] Cheers. What is this that we're drinking, Luana? [SPEAKER_00] It's a Brazilian beer. Okay. [SPEAKER_00] It's our most famous Brazilian beer, I would say. Very light. I don't know if you like it. [SPEAKER_02] I like it. So what is the split between you guys, maybe in terms of responsibilities, but more interestingly in terms of outlook? Well, we actually come from the exact same background. We studied math and CS at MIT, same internships, everything. But I'm a very, very optimistic person. Love taking risks. I think everything's going to work out. He's very paranoid, more on the negative side. So it's always a very good balance, I think. And I think that realists, outside of what we do day to day, that's really the difference between us that works out. [SPEAKER_00] Yeah. [SPEAKER_01] I mean, there's a little bit of background. So I was going to be a trader. That was really what I was going to do. And when you're a trader, you probably, I don't know if you've ever met or spent enough time with the persona, but it's expected. [SPEAKER_03] John is a secret trader. [SPEAKER_03] At heart, yeah. [SPEAKER_01] But if you're a trader, you're an expected value calculator. I think about these tail really bad outcomes all the time. And Luana oftentimes doesn't. And I think this is the thing that actually leads to great outcomes. [SPEAKER_02] Okay. So I want to ask about that starting out, because this is really interesting. You guys started Calci and for several years were not able to operate until you got CFTC approval. And that's interesting where just one, most companies don't start out that way. And secondly, I feel like the Silicon Valley standard that people sometimes trot out as a criticism is the PayPal, Uber early days model, where you start doing the thing and maybe retroactively a structure is put on top of it, but you do ask forgiveness rather than permission in the very early days. And so can you just tell a little bit the story of how you started and that approval process? And then I want to get into whether that generalizes to other companies. [SPEAKER_00] Yeah. I think that the approach we took from the start was that financial services or healthcare, I think you can't ask for forgiveness. I think there's a big difference between losing people's money, see what goes wrong. An FTX example can go very wrong with healthcare. There's a lot of other massive examples of it going wrong. And we wanted to do things the right way. Because also when we look at the market, we thought the biggest question to be answered was not, is this going to grow? It was, can we do this legally in the US? And we were like, let's just actually address the biggest problem first and go from there. And I think the strategy for a long time, people looked at it as the wrong strategy. I think up until we won the election lawsuit, everyone was saying, the folks that went out offshore, they're doing a lot better, they're growing a lot more. And I think once we won the election lawsuit and proved that the legal interpretation we had was right and we could do the company as we wanted in the US, I think it just really, really took off. What were the timelines here? So when did you start and when did you win the election lawsuit? [SPEAKER_00] Right. So we started the company in 2019. We started in 2019. And then it took us three years to be able to get regulated and launch. I think it was 2022 at that point. And then we won the election lawsuit at the end of 2024. And that's when we really started ramping up. [SPEAKER_01] There were a lot of overlaps between the timelines. But maybe going back to the question and maybe we can talk a little bit more about the history afterwards. But I think it was a two-step process. One, it was a pragmatic thing, which is we felt like to get proper mainstream adoption and institutional adoption, the elephant in the room was, could we do it in a regulated, credible and safe way? Because it's a complex marketplace. You're moving people's money. And we're like, we have to solve that problem first. That is the hard problem to solve. And that will be the road to success. The second thing was a bit more principled. We were what excited us. When we created this one page on Google Docs, and we wrote a set of things like, why should we do this company? And why are we so excited about this? We wanted to build the next generation New York Stock Exchange. We wanted to build a financial market that is in the US, that is credible, that is regulated. We were not very excited about this idea of building something offshore, and so that was really important because it's, what kind of company do you want to build? And why are you doing this in the first place? There's many paths to success. We just weren't very excited about the other idea. We wanted it to be here. [SPEAKER_02] You're the first CFTC approved prediction markets at any scale. [SPEAKER_02] Yes. [SPEAKER_02] Yes. [SPEAKER_02] And still to this day, all the contracts are individually approved. [SPEAKER_02] And so. [SPEAKER_02] Yep. Yep. [SPEAKER_01] We were not very excited about this idea of building something offshore. [SPEAKER_01] And so that was really important because it's like, what kind of company do you want to build? [SPEAKER_01] And why are you doing this in the first place? There's many paths to success. We just weren't very excited about the other idea. We wanted it to be here. [SPEAKER_02] You're the first CFTC approved prediction markets at any scale. [SPEAKER_02] Yes. [SPEAKER_02] Yes. [SPEAKER_02] And still to this day, all the contracts are individually approved. [SPEAKER_02] And so. [SPEAKER_02] Yep. [SPEAKER_00] Yep. [SPEAKER_00] We, every single contract we file with the CFTC and they have 24 hours to stop it. [SPEAKER_00] Yeah. [SPEAKER_02] Okay. So they get a real time feed of the contracts. Exactly. Yeah. [SPEAKER_01] Yeah. [SPEAKER_01] And it was a very long journey to get to where we are in terms of the contract process and how it works. [SPEAKER_01] Because you got to imagine the first time we walked into the building, actually the picture is right here. [SPEAKER_01] This is the first time we ever walked into the CFTC. [SPEAKER_01] You walk in and you're talking about this idea and it's, you got to imagine the regulators had started spinning. [SPEAKER_03] Mm-hmm. [SPEAKER_01] It's like, you're talking about things that don't have a financial underlying. [SPEAKER_01] And then there's this idea of potentially tens of contracts, hundreds of contracts a week. [SPEAKER_01] Now we're there, but there's all these things where the model wasn't really set up for this. [SPEAKER_01] So a lot of the process was actually like this iterative process. [SPEAKER_01] Yes. [SPEAKER_01] We're trying to figure out how to actually regulate this as you get feedback from the regulators and what can we do to satisfy the concerns. [SPEAKER_01] So it was a bit like building a product, but you're not building it for a customer. A regulatory market fit in a way. [SPEAKER_03] And so now you've gotten comfortable with you shipping them unless they know. Right. [SPEAKER_03] Have they said no to anything recently? Not, well, the biggest they said no to was the elections. That's why we had to end up suing them. They said no for two years. Yeah. But at this point, I think we've worked with them for so long that we know exactly what we can do and cannot do. So we don't do anything around war, assassination, those things that we don't do. [SPEAKER_00] So within the parameters that we've worked with them, it's a lot faster. So sorry, the election lawsuit was, they were willing to approve contracts generally. [SPEAKER_02] They were not willing to approve contracts around who would win the election, which is a pretty popular prediction market contract. [SPEAKER_02] Yeah, yeah, yeah. [SPEAKER_02] At the US presidential election. [SPEAKER_02] And so you sued the CFTC? Yeah. [SPEAKER_02] Your own regulator. [SPEAKER_02] I mean, and. Which is generally not considered a best practice. [SPEAKER_01] It was, I mean, okay. So we started talking about the election market at the end of 21. And we started engaging with policymakers, talking with Congress, a bunch and the regulator. And yeah, I think it's a good idea. It's a good idea. But then they weren't moving. We started noticing like, okay, something is off. By the end of 22, they sort of delayed the approval till after the election, what we call a pocket veto. That was brutal. So that was one of the hardest times in the company where we had to lay off a bunch of people. But the harder part of this is that your team and some of your investors or majority of investors kind of stopped believing in the idea. Yeah. Yeah. Yeah. But believing in the strategy, the idea, and it's a bit like, this is getting unhealthy. You know, you guys should do something else. Clearly this is not going to work out. But we could not get ourselves to do something else. We just couldn't. And so we're like, okay, we're going to try again. End of 22. So imagine the team is at an all time low in morale. They're waiting for a new strategy. Bunch of people left. Bunch of people got laid off because we had to downsize. [SPEAKER_01] And our message in that next standup was actually, guys, here's the 23 strategy: we're going to try again. [SPEAKER_01] We're going to do the same thing. [SPEAKER_01] Same thing. [SPEAKER_01] But this time it'll work. [SPEAKER_01] And exactly. [SPEAKER_01] But this time it's going to work, even though every inch of evidence was pointed in the other direction. [SPEAKER_01] And I will say a lot of this is her, the, I wanted this to happen so bad, but my rational brain was like, gotta listen to these people. [SPEAKER_01] And Luana is much more dogmatic. [SPEAKER_01] So we try again. [SPEAKER_01] End of 23, they block it again. [SPEAKER_01] And I was really at the point where I'm like, Okay. Prediction marketing is just not going to work. Yeah. It's just, and then when I was like, well, the only thing we can do right now out of the entire range of possibilities, we've got to sue the government. And yeah, at the beginning, it was like, this is crazy. And when we took it to the board and I, you know, we had Alfred and Michael at the time, [SPEAKER_02] and they're all like, well, Alfred, Lynn and Michael, [SPEAKER_02] Cybal from YC. [SPEAKER_02] Okay. And I remember that board meeting, it took a few board meetings, but it took, you know, a few times at the beginning. [SPEAKER_02] Yeah. [SPEAKER_01] It's just, and then when I was like, well, the only thing we can do right now out of all entire range of possibilities, we've got to sue the government. And yeah, at the beginning, it was like, this is crazy. And when we took it to the board and I, we had Alfred and Michael at the time, [SPEAKER_02] and they're all like, well, Alfred, Lynn and Michael, Cybal from YC. [SPEAKER_02] Okay. And I remember that board meeting, it took a few board meetings, but it took a few times at the beginning. I was like, well, we have to tell you guys, it's a bad idea. These are all the ways it's a bad idea. Cause you're a regulator. You're a 25 people company. The government can do anything. They can shut you down, take out the license. It is true. So where does it work? And even if you win, you will probably lose. You will end up getting killed in the process. And it took a few times and I remember very vividly, there was a meeting we had internally before talking to the board. And this was the night before we had lined up the lawyers and everything. And I got cold feet. I was like, let's just focus on getting a clearing house where you could focus on financial products. We can focus on all these other things. We don't need to tank it all on this and really bet the farm on this. And I remember, Luana and that call, I forgot the exact wording, but it was something along the lines of, are you fucking kidding me? [SPEAKER_00] That sounds like me. And I realized like, all right, I'm not going to win this fight. But the other part of me is like, we got to do this. I knew, and so we go on the board and the response was basically, it's an anti-pattern. It's a bad idea, but a lot of great companies are built by an anti-pattern. There's something off that is weird, that happens. And maybe this is yours. [SPEAKER_02] Yeah. [SPEAKER_02] It's a good way of putting it that every company is different in some new way. And so, yeah, this could be yours. What was the basis for the decision where you won the election last year? Like, was there any interesting policy angle? [SPEAKER_00] Right. So the whole point is that the government cannot stop any type of contract unless it makes a finding that's against public interest. And it has to fall within certain categories of war, terrorism, assassination. And the CFTC was taking the stance that they were trying to fit elections into any of these things. They're like, oh, elections might be illegal on the state law. And because betting on elections, there's this one state that in bucket shop law, they try to find something to stop it. And we knew we were very clear on the law, elections have economic impact. If the elections have economic impact, they need to be allowed to trade on a futures exchange or derivatives exchange. And it was basically, I think what the lawsuit did is it told the CFTC that they couldn't just do whatever they wanted. And that kind of like- [SPEAKER_02] The categories of prohibitors, it needs to actually fall under one of the prohibited categories. [SPEAKER_00] Exactly. Which elections did not. Right, exactly. [SPEAKER_01] And I think that's important because the law, the thing that we always say, the law applies to companies, but it also applies to the government. [SPEAKER_01] Right. [SPEAKER_01] Right. [SPEAKER_02] Well, you should make your point about maybe suing the government under the radar. [SPEAKER_03] Well, I think certainly in crypto and in prediction markets, it's this unique thing of suing the government. But I was sort of surprised to realize that Coinbase has sued their primary regulator. In GovTech, SpaceX, Anderl, Palantir all had to sue for various reasons. So it seems like it's actually more common than Silicon Valley conventional wisdom. [SPEAKER_02] Yeah. [SPEAKER_03] So what advice would you have having dealt with that kind of thing to people out there trying to build businesses? Like what sort of situation would you think is right to actually make that kind of move? [SPEAKER_01] I think it's a sort of no other option situation. [SPEAKER_01] So it's still painful. But did you actually have no other option? Because couldn't Caltech have done fine without elections? I mean, elections are obviously very helpful because they're such a big shiny thing, but I presume elections are not a majority of contracts today. [SPEAKER_00] I think it was just too important and maybe that's dogmatic or whatever, but it's like, it is the Holy Grail of the market. It is the one where you could see the use case of the data the best. And you can see the use of the- And you can see the 2024 election, right? The polls were completely wrong. And the markets were so much better at bringing that sort of information. And I think that it's the shining example of why these markets are good for good and we need to have them in the US and regulated, which other markets just won't have. [SPEAKER_03] So to John's point on PayPal and Uber and asking for forgiveness, there were other prediction markets operating and showing real usage offshore. And so I'm wondering how much did that help demonstrate that election markets weren't against the public interest? Like, did that factor at all into the court case? Like the fact that people were already doing it? [SPEAKER_01] I don't know. But I mean, specifically on the court, it was much more grounded in the law. In the law. Yeah, the law. Reading our law is the Commodities Exchange Act. So that's one of the financial statutes. The other one is the Securities Exchange Act. And reading it and really interpreting it and is the regulator overstepping. And I think for us, it was a good way to learn. Because we could not learn about our product because we took this regulatory first approach. [SPEAKER_03] Like the fact that people were already doing it? [SPEAKER_01] I don't know. [SPEAKER_01] But specifically on the court, it was much more grounded in the law. Yeah, the law. Reading our law is the Commodities Exchange Act. So that's one of the financial statutes. The other one is the Securities Exchange Act. And reading it and really interpreting it and is the regulator overstepping. And I think for us, it was a good way to learn, right? Because we could not learn about our product because we took this regulatory first approach, where we will ask for permission first before doing something. And so in some ways, it was helpful that you could have some data, some evidence that could guide our decisions over time. And I think it also helped educate some people about the existence of prediction markets. Right. And they are here. Here's how you can use them, et cetera. But I don't think offshore players really help from a policy perspective. [SPEAKER_00] Right. [SPEAKER_02] Could CalShift have been started 10 or 15 years prior? [SPEAKER_02] Or was there some moment of openness in the CFTC? [SPEAKER_02] Was there some tech enablement that was required? [SPEAKER_02] Were stablecoins required? [SPEAKER_00] I do think that there is a part of it that crypto at the time was Augur and there was some very early prediction markets. [SPEAKER_00] I think that the existence of that made the CFTC also be like, we need a legal regulated alternative to this. [SPEAKER_00] Because before you could just say no to things. [SPEAKER_00] I do think that played a role, but maybe 5%, maybe 10%. [SPEAKER_00] I don't think it's more than that. The broader thing is, I think there's always intellectual interest in prediction market. And I think that started in the 50s. It is a better source of signal than most other mechanisms of getting signal. Right. But there wasn't a real pain, I think 10, 15 years ago in the way that there is pain in the last few years. And that pain, I think, is a sort of the country is more polarized. I would say the world is more polarized. Social media has really bifurcated social feeds. Clickbait is rampant. The incentive structure for most things that we read these days is clickbait, whether it's a lot of traditional news or social media or other. So there was more of a pressing problem, I think, that helped create the wave and this sort of adoption that you're seeing in prediction markets that I don't think happened or would have happened 15 years ago. Because the problem wasn't that painful. [SPEAKER_00] Yeah. And that's because most of our users, 80% of our users are actually just looking, consuming information. [SPEAKER_00] They're just coming in and seeing who's going to win the Texas primary and seeing the polls are saying they're tied, but they're not tied and all those things. [SPEAKER_00] And that consumption of information is way more important and relevant now. [SPEAKER_02] Okay. So you were saying algorithmic feeds, CalShift markets do very well on algorithmic feeds and just maybe people wouldn't have been as interested as 10 or 15 years ago. [SPEAKER_02] Yeah. I think there's a meaningful and accelerating rise of distrust in traditional sources of information. And so you need a new one. Yeah. And this does work, right? The incentive structure for a prediction market is truth, right? It is more volume. It is more liquidity, which translates to better and more accurate forecasts. [SPEAKER_01] And it took a few iterations for people to start trusting it. [SPEAKER_01] But as you start building a track record, people start trusting it and they're never going to use a better product, right? [SPEAKER_01] Well, to the point of substantive volume, can you guys give us the outline of Cal... It seems like it's grown very quickly. So volume in February was 10.4 billion. [SPEAKER_02] So dollars of contracts traded. And that's up 11x over six months, I think. Wow. [SPEAKER_01] I mean, since August, September. [SPEAKER_01] It's growing so quickly, you don't even bother to go back a year because that's just ancient history. [SPEAKER_01] Yeah. [SPEAKER_02] I mean, a year ago, it really is. [SPEAKER_00] It's like we just had, for example, one sports market. [SPEAKER_00] We only had the Super Bowl in February. [SPEAKER_00] Yeah. [SPEAKER_00] I mean, it's growing very fast. Yeah. Fastest growing company outside of it. Yes. I think so. [SPEAKER_03] And we compete with, I think, even some of the top AI companies. I don't know what Cursor and Anthropic's latest numbers are. But I think 11x is very quick, even in AI. It's quick. [SPEAKER_02] So we are a marketplace. It's a true marketplace that has all the attributes of, you know, network effects. So what happens in those situations is that users retain better because there's more diversity and more liquidity. Their participation and volume grows over time, which obviously grows their usage, but it also grows other people's usage because there's more liquidity in the system. And then they share it more with other people because the product is getting better. Yeah. And so the sort of trifecta of factors is leading to this sort of growth. When some of your early growth depended mostly on other brokers, and I think you've evolved that mix today. What's the broker mix? [SPEAKER_03] And how do you think about that? [SPEAKER_03] Is there a broker in this context? [SPEAKER_03] Like Robinhood. [SPEAKER_03] I don't know how much. [SPEAKER_02] I don't know how much you want to say. [SPEAKER_02] Well, you should explain what that is, which is interesting. [SPEAKER_02] I mean, the... [SPEAKER_02] I can explain the broker part, but I don't know what we want to share on the numbers part. [SPEAKER_00] But basically... [SPEAKER_00] That was a tough one. [SPEAKER_00] That's why we look at each other and I was like, all right. [SPEAKER_01] That mix today. [SPEAKER_01] What's the broker mix? [SPEAKER_03] And how do you think about that? [SPEAKER_03] Is there a broker in this context? [SPEAKER_03] Like Robinhood. [SPEAKER_03] I don't know how much. [SPEAKER_02] I don't know how much you want to say. [SPEAKER_02] Well, you should explain what that is, which is interesting. [SPEAKER_02] The... [SPEAKER_02] I can explain the broker part, but I don't know what we want to share on the numbers part. That was a tough one. That's why we look at each other and I was like, all right. So because we're an exchange and Clearinghouse, we basically function like the New York Stock Exchange. [SPEAKER_01] You can never be here for her. Yeah, exactly. The Chicago Mercantile Exchange. [SPEAKER_03] So brokers can connect to us, right? [SPEAKER_03] So you can go to Robinhood to trade stocks. You can go to Robinhood to trade on Couch Union. Same with Coinbase or whatever. And it's always been part of how we think about... [SPEAKER_00] We always wanted to be an exchange and a Clearinghouse first. [SPEAKER_00] And actually connection to a Goldman Sachs or a Robinhood is very important for how we thought about this ecosystem as a whole. [SPEAKER_00] In the beginning of last year, we launched the first broker partner that we had. [SPEAKER_00] It was actually Robinhood and then Webull. [SPEAKER_00] And at the start, when we were starting to ramp up, the brokers were a very big part of how we started growing, which was actually great because the brokers bring so much demand. [SPEAKER_00] Then we get all the market makers to come in because they want to trade against the retail flow. [SPEAKER_00] And then we could buy ourselves time to ramp up the direct product to where it is now. [SPEAKER_00] But how you think about it is, we really are the core is an exchange and a Clearinghouse. [SPEAKER_00] And then you can access us through our app, website, API, but also any broker. [SPEAKER_00] We're investing more into institutional now, international brokers. [SPEAKER_00] So you can be in Brazil and you can trade on Cauchy, all those things. [SPEAKER_00] They're coming soon. [SPEAKER_00] But on the numbers, you can take it. [SPEAKER_00] Maybe we won't share numbers, but the direct, what we call direct, Cauchy Direct, which is our Cauchy.com, Cauchy app, the consumer business, that has grown, that has dramatically outpaced the rest, our other intermediated or broker business. [SPEAKER_01] And I think it's just that the brand has gone mainstream. I think people, when they think about, have a difference of opinion on something, it's becoming synonymous. So, oh, let me pull up Cauchy and see the odds or let me place a position on Cauchy. And there's just a lot of organic growth now. [SPEAKER_01] And I think that's going to continue over the next few months. [SPEAKER_01] You're describing how you grow the individual retail side of the market, whether people coming through brokers like Robinhood or people coming directly to the Cauchy website. [SPEAKER_01] There is also, when you're in an exchange like this, you have to spin up market making. And in the end, the New York Stock Exchange doesn't have to think too much about market making because the economic incentive is there. And so when something is at large scale, that's not as big of an issue. [SPEAKER_02] But I'm curious what that was like in the beginning. [SPEAKER_02] Were you guys doing the market making? [SPEAKER_02] Did you work with market making partners? [SPEAKER_02] Now, how do you incentivize market makers to participate? [SPEAKER_02] I'm curious what the market making scale up has looked like. [SPEAKER_02] So there's actually two groups of contracts on markets on Cauchy, and they behave very differently, and the market making incentives are actually pretty different. [SPEAKER_02] So you have the long tail of markets, right? Like the ones like, well, One Direction have a reunion or, you know, all those things. And they are actually very hard to price, and because there's not necessarily a lot of demand, we actually have to incentivize market makers to come in. [SPEAKER_00] And there's liquidity incentives, all those things for them to come in. [SPEAKER_00] And I think it's actually how we think about how to build our moat long term. [SPEAKER_00] It's how do we get very sustainable, solid liquidity in this long tail of markets. [SPEAKER_00] So we can get like, I think 10,000, how do we get to 50,000, 100,000 markets with still. [SPEAKER_00] But on the other side, you have the more classic crypto sports, all of those guys. [SPEAKER_00] And on that side, it's actually a lot easier to market make, because you have very clear proven demand. [SPEAKER_00] It's a lot easier to price. [SPEAKER_00] So the market making incentives on this side is actually, we don't pay them for it. [SPEAKER_00] We just rebate fees, but they have very, very hard conditions to meet. [SPEAKER_00] They need to have uptime of certain amounts, spreads and top of book size and all of those things. [SPEAKER_00] Because we see it more as incentivizing stability of the book than it is incentivizing them being there. [SPEAKER_00] So what does incentivizing stability of the book mean? [SPEAKER_00] For example, if you think of a live game or if you're trading an hourly crypto. [SPEAKER_00] You actually don't want the price flying around a whole bunch if there's no new information. [SPEAKER_02] Right, exactly. [SPEAKER_00] Or even if there is, right, if someone is about to sort of touch down, you don't want the book to just have no liquidity whatsoever. [SPEAKER_02] You want it maybe to go a little bit wider, but you want people to be able to trade. [SPEAKER_00] And actually, when we go into the intermediating model, the brokers come with expectations that they have from traditional markets. [SPEAKER_00] Right, so they are expecting we want this spread and this size at any point in time. [SPEAKER_00] It doesn't matter. [SPEAKER_00] So we need to go to the market makers. [SPEAKER_00] And how do we incentivize this? [SPEAKER_00] Even though if you think about it you should just let the markets do whatever they want to do. And if they're going to go way wider because they need to, it is. [SPEAKER_00] But we have to play with incentives in a way to, for all of our users, including the brokers. [SPEAKER_00] So during those moments when the spreads would normally blow out wide, are market makers losing money then and they're cross subsidizing to the other parts where it's more stable? [SPEAKER_00] Well, now there's so much demand that I don't think they're losing. You can make money on spread even if the spread is a little lower. [SPEAKER_00] But that's the point of the program, right? [SPEAKER_03] It's like you have to think about all the benefits you get in this program. Even though if you think about it, you should just let the markets do whatever they want to do. And if they're going to go way wider because they need to, it is. But we have to play with incentives in a way for all of our users, including the brokers. So during those moments when the spreads would normally blow out wide, are market makers losing money then and they're cross subsidizing to the other parts where it's more stable? Well, now there's so much demand that I don't think they're losing money. You can make money on spread even if the spread is a little lower. But that's the point of the program, right? [SPEAKER_03] It's like you have to think about all the benefits you get in this program. And then even if you're losing a little bit in this time, having the benefits is worth it. So you want tight spreads all the time for the major markets. That's what market stability means. And that actually takes work to engineer. [SPEAKER_02] It's hard to get there. You have to. [SPEAKER_02] But there's more to it. [SPEAKER_00] So I think the magic and the uniqueness of, I would say, or the special thing about prediction markets is that a lot of the liquidity is not what you consider a market maker. Right, right. It's people. And so this goes back to the whole point. So maybe let's just go back to first principles, right? There was the regulatory thing that we figured out. But then there's a liquidity problem, which historically is a bit like we said, the New York Stock Exchange or the CME. Okay, they're like, we're going to create a grain future. We're going to take two years to figure out what it looks like. And we're going to call all of our buddies, the 50 market makers that we all know. We all hang out at Christmas parties together, et cetera. We're going to get them ready. And they're going to start helping us get this product launched. And then we're going to market it for the next three years. And then it's just the same thing. The liquidity is there. But prediction markets is really different because now you have to create liquidity in these products on a weekly, daily, maybe even hourly basis. How do you do that? Right. It's much more dynamic. There's new things all the time. I think it's counterintuitive to people that you have to incentivize market makers to create liquidity. Because in the Stock Exchange, you don't have to incentivize high frequency trading firms to create sub-second liquidity. They are very excited to take on that project themselves and build the high speed interconnect between New York and Chicago to accomplish that. [SPEAKER_02] And so is this just the stage that prediction markets are at or is there something fundamentally different? [SPEAKER_02] I think this is where I was talking about, which is this idea that you need. So maybe finishing that line of thought and then I'll get to the answer there. You now have a model where you need liquidity to be built on the fly, much faster, much more dynamically. Right. And the market makers, the traditional Wall Street market makers are not geared up for that. It's not that they can spin up a new desk to price politics or price culture in an hour. Right. And so, but this is the part that gets really interesting, which is this goes back to the foundational principles around prediction markets. It's that a lot of these markets, the people that will price them the best may not actually be the experts or the authority figures that you usually would think about. It's actually random people that live. Right. Internet anons. Yeah. Exactly. The super forecasters. Those are extremely dispersed. You cannot find a clearly defined demographic of who they are. And I think that the thing where we got to now and that took a very long time when you had to incentivize is we have the community. Right. A strong community of super forecasters that are on Cashtag that can help price these things extremely effectively and fast. When you don't have, but it took a while to get them incentivized and come in and spend the time and resources to take it from a hobby to a part-time job. [SPEAKER_00] Now it's a full-time job because the pie is so big. And a metric that we can share is actually when you think about traditional market makers, the biggest percentage on the platform of a traditional market maker is less than 5% of the maker orders in that market that have matched. Of the liquidity. Of the liquidity. [SPEAKER_00] Sorry, say that again? [SPEAKER_01] Yeah. [SPEAKER_01] So less than 5% of the orders. So people come and make orders. Less than 5% of the ones that match actually come from the big institutional market makers you'd think about. I see. Over 95 are. Peer-to-peer. Peer-to-peer. [SPEAKER_00] Or funds that have two people that just got stuck. Which is unusual for you. [SPEAKER_00] How many of those small full-time little shops are there? [SPEAKER_00] There's over 2,000 people that are market making. [SPEAKER_03] People slash small shops. [SPEAKER_03] Yeah. [SPEAKER_00] [SPEAKER_00] On a specific. [SPEAKER_00] I think what Matt's getting at is, who is a market maker on Calci? There's all these Jane Street conspiracy theory memes. [SPEAKER_00] Is it Jane Street? [SPEAKER_02] That's my Twitter feed. [SPEAKER_02] Or is it some guy in his garage drinking Red Bull at 3 a.m. [SPEAKER_02] Right. [SPEAKER_02] Market making. The guys in the garage are the most crucial. And you're saying those are 95% of the flow. [SPEAKER_02] They're extremely crucial to the acquisition because they price fast. They're monitoring the situation. [SPEAKER_02] Yeah. [SPEAKER_01] All the time, right? They're the original situation monitors. [SPEAKER_02] Yeah, yeah, I see. Calci is built on people who are monitoring the situation. And so in those guys, one example I'll give. So the best inflation forecaster on Calci over the last few years is not any of the institutions or the big name hedge funds. It's this guy who lives in Kansas, never traded financial markets before, just reads the news and just knows how to predict inflation. All the time, right? They're the original situation monitors. [SPEAKER_01] Yeah, yeah, I see. [SPEAKER_01] Calci is built on people who are monitoring the situation. [SPEAKER_01] And so, in those guys, so one example I'll give. [SPEAKER_01] So the best inflation forecaster on Calci over the last few years is not any of the institutions or the big name hedge funds. [SPEAKER_02] So this guy who lives in Kansas, never traded financial markets before, just likes to read the news and just knows how to predict inflation. [SPEAKER_01] He can feel it. And you have so many of these people. I would say a few thousands that are formally committed, but there's tens of thousands of these people that know a bunch of different topics and they're actively pricing these things and they do it as a full-time job and they get rewarded for that. You need to talk about my favorite user. Oh yeah. Or. [SPEAKER_00] Well, I have a new favorite user, by the way. Okay. [SPEAKER_00] Each of you can tell us your favorite user. I was thinking about this this morning. Who's your new favorite user? [SPEAKER_01] The Wall Street Journal article about the tax guy. [SPEAKER_01] Oh yeah. [SPEAKER_00] That's true. He's a good candidate. But no, my favorite user is this Ariana Grande super fan. [SPEAKER_00] And he found Calci during the election season. [SPEAKER_00] He's like, I don't like the elections. Whatever. [SPEAKER_00] Then he found our billboard ranking markets, charts. [SPEAKER_00] He's going to work on important markets. [SPEAKER_00] Important markets. [SPEAKER_00] To me, very important. [SPEAKER_02] And he's made over $150,000. [SPEAKER_00] He's getting every single thing. [SPEAKER_00] He paid back student loans. [SPEAKER_00] He put himself through a master's degree, bought a car and all those things. [SPEAKER_00] And he just loves these markets. [SPEAKER_00] And he's never really traded, never done anything like that before. [SPEAKER_00] But it's the first time that he actually has a way to monetize this very compulsive hobby that he had on music charts. [SPEAKER_00] And he's able to do it. [SPEAKER_00] And he's also very, very nice to us on Twitter. [SPEAKER_00] So I like him. So I had many over the years, but I shift a lot. [SPEAKER_01] He's not loyal. [SPEAKER_01] See, I'm loyal to my guy. [SPEAKER_01] Well, I love all of our users. [SPEAKER_00] But there was an article last week in the Wall Street Journal about a tax accountant who was very active on Calci, Alan. [SPEAKER_01] And you know, when Doge came around and there were a lot of talk about how much they could cut, he actually read a bunch of tax codes and statutes, just dug extremely deep and then realized there is no way they could hit the targets. [SPEAKER_01] Even if, he really kind of deterministically realized. [SPEAKER_01] And then he basically talked to his wife and he's like, I have extremely high conviction in this trade. [SPEAKER_01] I know, and it's a bit like Michael Burry with The Big Short. [SPEAKER_01] So this guy put a big short, but on Doge this time. [SPEAKER_01] Right. [SPEAKER_01] And it was big. [SPEAKER_01] Like he really went all in and he won. [SPEAKER_01] Yeah. [SPEAKER_01] And it's just one of those amazing showcases of what this can do. [SPEAKER_01] Like now you have a market that if you have that sort of knowledge, which maybe oftentimes is esoteric, I'm assuming none of us have read all these tax codes. [SPEAKER_01] You can actually go out in the world, do research, get smarter about the world, and then get rewarded for that. [SPEAKER_01] And that's awesome. [SPEAKER_01] Right. [SPEAKER_01] You know, an early field of AI was poker bots. [SPEAKER_01] Are you seeing any good AI market makers? [SPEAKER_01] When you say no one's read all these tax codes, I mean, no one except Claude. [SPEAKER_02] That's fair. [SPEAKER_02] That's fair. [SPEAKER_02] We should ask. We are seeing increasingly more people using agents to trade. So that's definitely. Especially on the API side. [SPEAKER_01] On the API side, it's very big. [SPEAKER_01] And you know. Like, do you have users who are successfully running market making businesses that are mostly agentic? Users don't exactly tell us their strategies. But you talk to them. [SPEAKER_02] Generally, yes, yes, yes. [SPEAKER_02] But I mean, it is. [SPEAKER_02] The way I think about it is, do we think Rentech back in the days was using agentic models? I'm talking about Renaissance to trade. Yeah, the early versions of them. Right. [SPEAKER_01] And so I think they're just evolving and they're getting better. [SPEAKER_01] And most of our traders in their stack have some sort of summary and synthesis module that's AI driven. [SPEAKER_01] Yeah. [SPEAKER_01] I guess what I'm curious about is fully autonomous, no human in the loop, consuming information and providing a market based on that. [SPEAKER_01] That feels like it's coming quite soon. Even if it's an LLM with Claude making a market. Yeah. I don't know if there's a full. I know that, for example, there's a lot for international elections just on translating all documents, polls and being able to do all of that. [SPEAKER_00] But I don't know if it's all fully. [SPEAKER_00] We don't know if the models are there yet. Right. That's, and so, you know, we launched Calci Research recently, which, and one of the threads that we want to work on is we're talking to some of the research labs to create a new benchmark around which models actually predict the future better. [SPEAKER_01] Right. [SPEAKER_01] Which could be a unique benchmark around are these models developing some understanding of the world that goes beyond memorizing old patterns. [SPEAKER_01] And I'm honestly excited to see how it goes. [SPEAKER_01] And what's the eval for that? [SPEAKER_01] We don't know yet. But I don't know if it's all fully we're doing, so we don't know if the models are there yet. Right. That's, and I was, so we launched Calci Research recently, which, and one of the threads that we want to work on is we're talking to some of the research labs to create a new benchmark around which models actually predict the future better. [SPEAKER_01] Right. Which could be a unique benchmark around are these models developing some understanding of the world that goes beyond memorizing old patterns. And I'm honestly excited to see how it goes. And what's the eval for that? [SPEAKER_01] We don't know yet. But I think you can let the models run, make predictions on same set of markets for a month or two and see which ones perform, percentage of predictions that were correct, P&L over time, et cetera. [SPEAKER_01] Yes. Yeah. Okay. Another market making question. So sports bookies have this need to crack down on what in their industry is called sharps. [SPEAKER_02] Yeah. You know, people who are too good. Where people don't think so much about this dynamic, but for a sports bookie, the best possible punter is someone who is unsophisticated, bets on their home soccer team's game irrespective of the odds. [SPEAKER_02] Exactly. And just wants the home team to win or whatever. [SPEAKER_02] And the worst kind is someone who's super sophisticated, finding the narrow markets. Because for a bookie, maybe they're making odds on 10,000 different markets. [SPEAKER_02] Yeah. [SPEAKER_02] They only need to be wrong once or twice for people to choose which they play on. And so they presumably can't be right on all the odds that they're offering. And these sophisticated people go find those. And so what happens is they basically use behavioral signals to identify if you just signed up and you're betting on your home sports team's game, that's good. And if you appear to be really sophisticated with all the signals that they would use. Exactly. They shut them down. But it's interesting, right? You think I'm just booking on the bets on the odds that you're offering. But if you're too good, they'll shut you down. It's maybe like card counting in Vegas. Do you have this dynamic with sharps? I would have thought no, that you just are fine with it. But do the market makers worry about too sophisticated counterparties on the other side? [SPEAKER_02] The sharps are the market makers. I mean, they're super forecasters. We don't limit any winners. We don't have any of the, we want all the winners. [SPEAKER_00] Please come sharps. Well, we need the sharps because how do you get market accuracy without the sharps? Right. This is the difference of the. [SPEAKER_01] Well, yes and no, right? Because what you want is different because the sharps can snipe. They can just turn up once when the odds are wrong, grab a big win and then disappear. [SPEAKER_02] Whereas what you're describing is you want during the game or during the election, you want narrow spreads all the time. And so providing good market making is different than being right. But a lot of the sharps can actually do better if they provide market making and become part of the liquidity. So this is the big difference, which is very important. [SPEAKER_02] Maybe a disclaimer, I don't gamble. I trade, which I've always found a difference. And I think gambling is this idea where the business model is you are the house and your revenue is your customer's losses. So a lot of the dynamics that you describe has to be true because your incentive is well, somebody is making money. I got to stop them because they're making me lose. That just goes straight from my bottom line. And the opposite is true. If somebody is losing money, I got to figure out how to bring them back. There's a very different model from traditional financial markets where the structure is you have to incentivize fairness and transparency. That's the structure. You want to create fair rules of the game for people to participate. Maybe Matt is better than Luana and maybe Luana is better than Matt. And they can battle it out. They can figure it out. You think the incentive system is very different where you do not monetize on some zero sum, another person losing, the way a casino does. You monetize on transaction fees. [SPEAKER_02] The best outcome for us is that people think this is fair. They have good prices. They have stable liquidity. I'm going to go there. But of course, for us to get there, we also need to incentivize different players differently. So that's why, for example, a lot of the liquidity programs come into effect. They're okay, if you're providing liquidity, you're taking a lot more risks because you're putting yourself out to be sniped. Then we're going to lower your fees. But if you're taking and you're going to snipe, you're going to have higher fees so you can pay for that activity. So in a lot of ways. You use fees to incentivize pro-social behavior? Exactly. And I think that's actually how we see a lot of how financial markets actually do the same thing. [SPEAKER_02] Financial markets do the same. The same thing. But it's more balancing out the marketplace so that people that are providing value to the marketplace have, you know, a little bit more tilt. [SPEAKER_01] And then people that are taking away value have a little bit less. What behavior is pro-social and what behavior is anti-social? [SPEAKER_01] Well, insider trading is anti-social. Right. [SPEAKER_02] That's a big one. [SPEAKER_01] Yeah, yeah. [SPEAKER_00] And illegal. But, you know, it's and sniping is part of it, right? [SPEAKER_01] You need people that all of a sudden have gained some information edge and they do it in traditional financial markets all the time, right? But to have liquidity and make sure that people are there and they're investing the resources, they have to get, as you said, some incentives. But the interesting point, I think, and I think this is part of why prediction markets are being adopted so much is people like this idea that if your edge is proportional to your research, how informed you are, how much time and energy you put into this. [SPEAKER_01] Yeah, yeah. And illegal. But it's, and look, sniping is part of it, right? You need people that all of a sudden have gained some information edge and they do it in traditional financial markets all the time, right? But to have liquidity and make sure that people are there and they're investing the resources, they have to get some incentives. But the interesting point, I think, and I think this is part of why prediction markets are being adopted so much is people like this idea that if your edge is proportional to your research, how informed you are, how much time and energy you put into this. [SPEAKER_01] And I think that only exists in prediction markets or traditional financial markets, except that for a lot of people, traditional financial markets, they're just less interesting, right? In here, you're researching about doge and what's going to happen or the election and how people think about elections and how they vote. That, at least to me, feels a little bit more interesting than anything about IBM's quarterly earnings every quarter. Kalshi has built a new kind of marketplace where real world outcomes are traded. Whether the U.S. will confirm whether aliens exist before 2027. You have thousands of participants opening, transferring, settling their positions all in real time. [SPEAKER_02] And underneath it, as you can imagine, there's a complex multi-party flow of funds. [SPEAKER_02] That choreography on Kalshi is powered by Stripe Connect, onboarding participants, processing payments, routing funds, managing payouts. [SPEAKER_02] When money movement becomes programmable, new products or even new market structures become possible. [SPEAKER_02] So, if you're building something new with complex money flows, Stripe Connect was built for you. [SPEAKER_02] Sorry, guys. [SPEAKER_02] No, no, no. Let's talk different market verticals. [SPEAKER_03] And I think today everyone gets elections, they get sports, they get economic indicators. But I think you can look at prediction markets as this kind of search function across the set of interesting markets humanity wants to trade. [SPEAKER_03] And it's a weird artifact that the CME used to green light wheat and oil and corn. [SPEAKER_03] But now you get to green light a thousand markets a day. [SPEAKER_02] So, what do you think we're going to find as we do that? [SPEAKER_03] One thing that we're very excited for, we're actually starting to go in the direction of things like watches and bags and all of those things that are more going to the collectible side. [SPEAKER_03] They're actually able to do derivatives on those things. [SPEAKER_03] One thing that you should talk about is the GPU. [SPEAKER_00] Yeah, I feel compute could be a huge market. [SPEAKER_00] Compute is very, and I think what we're thinking a lot about is that there's a lot of these types of things that function better as a more traditional future. [SPEAKER_00] Things that don't have a binary, will it be at this price? Yes or no. [SPEAKER_00] But it's more an actual future. [SPEAKER_00] You can have margin. [SPEAKER_00] You can have more institutional grade liquidity and all of that. [SPEAKER_00] And I think that's a great example of when we start going more outside of binary markets and more into the traditional ones. [SPEAKER_00] Then what we're doing is expanding that from grain to compute. [SPEAKER_00] So, it strikes me that obviously the futures markets that have worked best are these large commodity categories. [SPEAKER_00] Because we're in an era where humanity is spending more money than it's ever spent before on a new commodity category. [SPEAKER_03] And the other traditional markets don't seem to be attacking compute. [SPEAKER_03] So, the way that we think about it, we want to be the biggest derivatives exchange in the world, right? [SPEAKER_03] And for that, when we think about product roadmap, there's four things that matter. [SPEAKER_03] The first one is breadth of topics of markets, right? [SPEAKER_00] So, we think about compute, we think about sports, we think about elections, we think about securities, we think about all of that. [SPEAKER_00] The second bucket is really market structure. [SPEAKER_00] So, right now, we only have the binary yes, no. [SPEAKER_00] We want to have things like futures, swaps, options, all of that. [SPEAKER_00] The third one is really margining systems. [SPEAKER_00] Right now, it's very bad. [SPEAKER_00] You have to put all the money up front. You have to tie up all the capital. [SPEAKER_00] Which makes a lot of, for example, will a hurricane happen this year? [SPEAKER_02] Very, very bad for you to be actually market making or selling those contracts. [SPEAKER_00] It doesn't make almost any sense capital wise. And then the last one is liquidity. [SPEAKER_00] And what we think about is if we win these, we have the broadest set of markets, we have the broadest set of market structures. We have great margin and then good liquidity, we're going to win on everything that we do. [SPEAKER_00] So, everything that we do in the company needs to be in one of these four buckets. And I think a lot of the topic side is how do we actually match the right topic with the right market structure, the right margining, and how do we make sure that it's all coming together. [SPEAKER_00] But you're completely right. I think that being able to build all the margining systems, all those things from scratch, we're going to be able to do margin models a lot faster and list a lot of these new markets a lot faster. Because of your direct mobile app interface and the fact that you target a lot of retail, do you worry that the markets you're going to gravitate towards are the ones that are most interesting to just retail? And how much do you think about as opposed to the pro markets? [SPEAKER_00] The institutional markets, right? [SPEAKER_03] I think of compute as much more of an institution to institution market. [SPEAKER_03] So, how do you think about building liquidity and interest up market? [SPEAKER_03] Yeah. [SPEAKER_03] We almost divide the company again. It's we divide the markets into sports, crypto, and everything else. [SPEAKER_00] But in how do we make what we have great but pursue very new things? Because I think what got Kalshi here was not the regulatory side. It was really that we're just pushing what is the next thing. It was elections and then after elections, sports. [SPEAKER_00] And for us, we need to be pushing what the next thing is and doing that very well. And I think that if we stop doing that, we're not going to win. [SPEAKER_00] The company's structured so we have the market operations, we have the engineering side, all of that, that's set up for maintenance and improvement of what we have. [SPEAKER_00] And then the new teams like institutional, the margin team, international that are pushing forward. [SPEAKER_00] And we just try to find a balance on those teams and then a platform layer that is the core exchange and compliance and all of that. [SPEAKER_00] But it is tricky because we're still 120 people to do it. [SPEAKER_00] It was elections and then after elections of sports. [SPEAKER_00] And for us we need to be pushing what the next thing is and doing that very well. [SPEAKER_00] And I think that if we stop doing that, we're not going to win. [SPEAKER_00] The company's structured so that we have the market operations, we have the engineering side, all of that, that's set up for maintenance and improvement of what we have. [SPEAKER_00] And then the new teams like institutional, the margin team, international that are pushing forward. [SPEAKER_00] And we just try to find a balance on those teams and then a platform layer that is the core exchange and compliance and all of that. [SPEAKER_00] But it is tricky because we're still 120 people to do it. [SPEAKER_00] Are you seeing pull already on the institutional side and certain topics? [SPEAKER_00] Yeah, no, for sure. [SPEAKER_00] And I think that we actually just launched a week ago this thing called BlockTrades. [SPEAKER_03] I don't know if you know BlockTrades. [SPEAKER_00] It's a very institutional way to do it where I can call you and negotiate a trade and then we go and put it in the exchange versus trying to do everything that way. [SPEAKER_00] So we're trying to build a lot of features to start getting more in the institutional side. [SPEAKER_00] Are they trading the same things that are on the Kaoshi retail or are you offering new types of products for them? [SPEAKER_00] Yes and no. [SPEAKER_00] So whenever they're interested in something, there's a lot of interest, there was a lot of interest on the tariff situation. [SPEAKER_03] Is there going to be a tariff or not? [SPEAKER_00] A lot now with the petroleum, the reserve and how that's going to go. [SPEAKER_00] So whenever we hear we want to trade this market, we just list it directly and then it's accessible to everyone. [SPEAKER_00] But I do think there's going to be a very big gap on what the institutions are going to end up trading versus not. [SPEAKER_00] But we just list it to everyone. [SPEAKER_00] It's very cheap for us at this point to lease new markets. [SPEAKER_00] That's it. [SPEAKER_00] In the early days of Uber, it wasn't bad for the taxi business because it was just excess capacity and serving unmet need. But then after a while it was bad for the taxi business. [SPEAKER_00] Are there existing businesses that will feel the effects of Kaoshi and other prediction markets because it's a bigger market, there's more liquidity? [SPEAKER_02] I can think about the existing futures exchanges, maybe Kaoshi is a better place to hedge your soybean prices or what have you. [SPEAKER_02] There's sports bookies, obviously. [SPEAKER_02] There's political polling firms where maybe you can get the same information way cheaper. [SPEAKER_02] So who do you think will start feeling the effects of prediction markets because they have been in some way superseded? [SPEAKER_02] Yeah, there's that funny meme of the guy knocking on the door and it's the Grim Reaper meme? [SPEAKER_02] Yeah, yeah. [SPEAKER_00] So we don't want to do that. [SPEAKER_00] But I think that a lot of what you mentioned, right? I think that just traditional betting that we talked about, all the issues that that industry has that we're very different from. There is traditional futures now going way more into their space. So I think there's going to be a difference there. There is the political polling that I think since the last election, there's just a lot of campaigns that are using our data and all that. There's parametric insurance. Once we have margin, we can start going to more hurricane after disaster insurance, all of that side. Is there a tragedy of the commons with the polling? [SPEAKER_00] Part of the reason the prediction markets are accurate is because they interpret the polls. Right. [SPEAKER_03] So if people stop using polls, in some sense, polls are the sensor that you get to the polls. [SPEAKER_03] And then the prediction markets are the mathematical interpretation of the polls. [SPEAKER_03] Yeah, my take is that polls are just going to get a lot better. [SPEAKER_03] Because what people are going to be is okay, I can make money if my polls are right. [SPEAKER_03] So I'm just going to commission this poll and I'm going to do this. And now you can actually compete a lot of polling models into one market. It's 538 did the meta poll interpretation. Exactly. And you can have one number that's aggregating all of that. [SPEAKER_02] And even in the last election, there was someone that actually did this. They commissioned a specific poll to do nearest neighbors type of thing. [SPEAKER_00] It was different type of poll. [SPEAKER_00] And then they were able to make a lot more money in the markets. [SPEAKER_00] And that's the whole point of having money and skin in the game aligns the incentives with truth. And then the polls are not just paid for like tell me what I want to hear, but the real numbers. So I think it's complimentary. [SPEAKER_00] Same with the news. [SPEAKER_00] A lot of people are prediction markets will destroy the news. [SPEAKER_00] I think it's way more complimentary. [SPEAKER_00] It's when you're talking about an election, you're going to give your opinion. [SPEAKER_00] The market's not going to give you an opinion. [SPEAKER_00] You still need the commentators, but they're going to be able to show a number and be this is what the forecast is. [SPEAKER_00] And this is my opinion on it. [SPEAKER_00] I don't think the opinions are going to disappear. [SPEAKER_00] You guys referenced insider trading earlier. [SPEAKER_00] And there's just the policy question as to what the right policy should be around insider trading when it comes to prediction markets. [SPEAKER_00] I think it's pretty nuanced. [SPEAKER_02] It's nuanced from the stocks case, right? [SPEAKER_02] Where famously there's lots of, you see SEC enforcement actions all the time against things that aren't allowed. [SPEAKER_02] But there are cases where a hedge fund can have proprietary satellite data of the Walmart parking lot and use that to trade earnings. And that is information that only that hedge fund has, but that is permissible. [SPEAKER_02] Right. [SPEAKER_02] And so similarly, I think there's a complex set of line drawing exercises here where presumably we don't think government officials should be trading in advance of military actions. [SPEAKER_02] Right. [SPEAKER_02] What about leading up to the Super Bowl, predicting the Bad Bunny halftime show length? [SPEAKER_02] I mean, people have that information. [SPEAKER_02] Yeah. [SPEAKER_02] And so where do you think the lines should get drawn on insider trading? Yeah. And you said it perfectly. It's a very complicated question. And it's a complicated question for stocks way more and to a bigger scale than it is in prediction markets. The line that we take now is that we follow what the federal law is. So it's basically if you have an agreement. [SPEAKER_00] And these are CFTC rules? [SPEAKER_00] Well, CFTC and SEC. Okay. [SPEAKER_02] They both have it. [SPEAKER_02] People have that information. Yeah. And so where do you think the lines should get drawn on insider trading? Yeah. [SPEAKER_02] And you said it perfectly. It's a very complicated question. [SPEAKER_00] And it's a complicated question for stocks way more and to a bigger scale than it is in prediction markets. The line that we take now is that we follow what the federal law is. So if you have an agreement. And these are, sorry, CFTC rules? [SPEAKER_00] Well, CFTC and SEC. [SPEAKER_02] Okay. They both have it. [SPEAKER_00] So if you have signed an agreement that says you cannot share some part of data. So if I work at the Bureau of Labor Statistics and I have in my confidentiality, then I'm not able to say what the inflation number is before it is released, you have a duty not to share that data. But if you know that they're going to be rehearsing the Thursday before the Super Bowl and you're outside and you hear Lady Gaga singing, that's fine. And that's the same thing that a lot of hedge funds do with Starbucks and people know that there are more people, fewer people in the store. And that's the point. It's that markets are very good at incentivizing information. We want information to come to the markets, but we don't want it to be unfair. And if you have access to it in an unfair way, you should not be trading on it. [SPEAKER_00] Okay. So you cannot trade on information or you have some duty to hold that information confidential. [SPEAKER_02] Right. We actually take it even a step further. For example, if you are a government official, if you're in Congress, you cannot trade on bills passing, even though I don't know if they have an agreement. [SPEAKER_00] Famously, Congress people can trade on stock. Right, right, right. So we're actually taking a step further there. Yes. [SPEAKER_00] And we're working with a lot of the regulators because it's a very new problem for them and for us, but we have an entire surveillance division that is looking at every single flag. They pretty much don't sleep and they just try to figure out everything. And we put out two cases two weeks ago of two insiders that because we're regulated, we're able to charge them a lot of fines. So we charge them over five times what they made and all those things they're banned from and all that. [SPEAKER_00] What's very interesting to me about these stories is that you guys were doing that where with the public equities markets, the SEC is extremely enthusiastic about enforcing their insider trading doctrine. Just what has the CFTC been like on this topic? It's a great question. [SPEAKER_02] So the CFTC, you can think about it at three steps, right? The first step is our own surveillance and enforcement. Then the next step is it goes to the CFTC and their own surveillance and enforcement. The last step, if needed, goes to the Department of Justice. Yeah. And I think that the biggest difference is when people look at the SEC cases, most of the time they take a long time because the exchanges do their research and their investigation and they put some fines, they block someone, and it goes through the process. So it's still like that. Every single trade on Kalshi goes to the CFTC. They have every single thing, every single case goes to the CFTC for them to review. So they might take action. We don't know. But now the ball will be able to. [SPEAKER_00] Okay, so you refer cases to the CFTC. [SPEAKER_00] We refer cases to them. [SPEAKER_00] Yeah. [SPEAKER_00] But we do our first step of our first level of protection there. [SPEAKER_00] I'm curious, there are clearly markets where nobody knows the answer yet of some event in the future. So it's impossible to insider trade. [SPEAKER_00] Right. [SPEAKER_03] And then there are markets where a single person can change the outcome. [SPEAKER_03] Right. [SPEAKER_03] Like the mentioned markets in a speech. Or maybe a sports player doing a specific number of shots. So how do you think about that spectrum? Are mentioned markets a bad idea because they're inherently gameable? [SPEAKER_03] Or are they limited in scale fundamentally because… [SPEAKER_03] Mentioned markets like the Brian Armstrong Coinbase earnings thing and stuff like that. [SPEAKER_02] That's the worst example. [SPEAKER_03] But yes, I think that… Well, I think mentioned markets are actually great. [SPEAKER_00] If you think about the Fed, right? The amount of hedge funds that are just sitting down being like, is he going to tilt his head this way or this way? And if he does that, it means he's not very sure. Fed meeting minutes are the original mentioned markets. [SPEAKER_00] Exactly. That's actually pretty much the… And it's because we just know that specific words being used mean very specific things and it can move the market so much. [SPEAKER_00] Yes. The same thing with Trump, right? If Trump says we're going to war, that's going to move the markets a lot. Right? Or if he says things like tariff. Yeah. Everyone else moves the market a lot. Even in… [SPEAKER_00] Yeah, just a lot of… [SPEAKER_00] Everywhere, things that people say move markets and move a lot of different things. So I think the mainstream market is very important. Obviously, the person that is working on the speech or that is saying the speech cannot trade. And that's how we enforce it. Like if you are Gavin Newsom and you are… There's a market on what you're going to say, you cannot trade it and your staff cannot trade it. That's part of the political cuts that we do there that they cannot trade. But I think that's the point. It's that if there is a way to restrict some players in the market so that the market's fair and the market's positive and there's an economic utility for it, the market should exist. [SPEAKER_00] Yeah. [SPEAKER_00] We shouldn't say that okay, there are five people that could manipulate the market and the market shouldn't exist. Then you'd say the stock market shouldn't exist, right? [SPEAKER_01] So I think it's more about how do we build a system that is strong and resilient enough… [SPEAKER_00] Yes. [SPEAKER_00] …and with the right prohibitions that you can have the market. [SPEAKER_00] Yes. [SPEAKER_00] …the other big debate you guys are in the middle of is just about sports contracts generally. [SPEAKER_00] Yes. [SPEAKER_00] …and the market's positive and there's an economic utility for it, the market should exist. [SPEAKER_00] Yeah. [SPEAKER_00] We shouldn't say okay, there are five people that could manipulate the market and the market shouldn't exist. [SPEAKER_00] Then you said stock market shouldn't exist, right? [SPEAKER_01] So I think it's more about how do we build a system that is strong and resilient enough… [SPEAKER_00] Yes. [SPEAKER_00] …and with the right prohibitions that you can have the market. [SPEAKER_00] Yes. [SPEAKER_00] …the other big debate you guys are in the middle of is just that about sports contracts generally. [SPEAKER_00] And I was trying to reason about my own thoughts here on this debate where on the one hand, the criticism is that with more sports gambling comes proven bad effects. [SPEAKER_00] You can measure some of the bad effects that it has on people. And we have this, especially in the US, where there was a lot of legalization of sports betting over the past 10 years. [SPEAKER_02] Mm-hm. [SPEAKER_02] And there's some data on that. [SPEAKER_02] On the other hand, I have no real issue with alcohol despite the fact that it has a similar distribution where many people enjoy it. [SPEAKER_02] Right. [SPEAKER_02] And then there's a very bad set of outcomes for a small fraction of the population. [SPEAKER_02] Right. [SPEAKER_02] And so I feel the societal discussion of the morals of alcohol and the morals of betting are different despite the fact that it's similar shape to the distribution. Mm-hm. And just thinking from my experience, online sports betting has been legal in… …well, legal is a complex term, has been available in Europe… Right. …for a very long time. [SPEAKER_02] …for a very long time. [SPEAKER_02] Since the start of the internet. [SPEAKER_02] I knew there was all these cross-border hacks in Malta, and now it's a bit more regularized. [SPEAKER_02] But it's been available to people who wanted it for a long time. [SPEAKER_02] Mm-hm. [SPEAKER_02] And life goes on. [SPEAKER_02] You know? [SPEAKER_02] And it hasn't led to any major societal collapse over there. [SPEAKER_02] But clearly, this is one of the big debates that rages around Calci. [SPEAKER_02] And so I'm curious how you guys think about increasing access to sports contracts and the effects there. [SPEAKER_02] Right. [SPEAKER_02] Well, there's a lot of parts to what you're saying. [SPEAKER_02] I think that the way that we think about sports, how we decided to first list sports, is obviously something that a lot of people are interested in. [SPEAKER_00] Mm-hm. [SPEAKER_00] That's unquestionable. [SPEAKER_00] But also there's something that a lot of people do a lot of research and know a lot about. [SPEAKER_00] And there aren't traditional ways for you to make money on that, that are actually good. [SPEAKER_00] Or we talked about the winners, they get cut and all those things. [SPEAKER_00] And it doesn't really work. [SPEAKER_00] And regardless of whether people like that some people bet or dislike that some people bet, people bet. And it's just about what is the best way for them to have access to something that they can get exposure to sports. And I think that the whole point of markets versus a bookie is that markets are just objectively better. Right? I think that it's almost, I've never heard someone make a case that a state-by-state regulated casino is actually a good thing. I'm actually hearing nowadays that a lot of the paid propaganda by the gambling guys trying to say that. But if you push them to questions. And just to put numbers on that, the order of magnitude rake for sports betting companies is around 10%. And the order of magnitude for prediction markets is 1% or a few points. Right. [SPEAKER_02] But the predatory part doesn't even come from that. For sports betting, if you start losing, because they want the losers, they don't want the winners. [SPEAKER_02] If you start losing, the first thing that they're going to do is give you a bonus. They're going to be like, oh, here it is. [SPEAKER_00] Oh, look at that. Oh, I'm going to go fun. [SPEAKER_00] We were talking about kind of sports. [SPEAKER_00] And what they do is you start losing and then they're going to give you $1,000 for you to come back. [SPEAKER_00] Or a deposit boost and all those things so that they can hook you to keep you coming back because they want to incentivize the losers. [SPEAKER_00] We don't do anything. The people losing the most money are the most profitable for sports bookies. Yeah. [SPEAKER_00] Which creates a bad incentive. [SPEAKER_02] [SPEAKER_00] And we don't have that at all. [SPEAKER_02] And I think that the whole point is there's a moral question. Some people are going to go into Robinhood or Coinbase or whatever and speculate on stocks and speculate on crypto and whatever they want to do. [SPEAKER_00] And some people want to speculate on sports and they should have access to the best possible thing for that. [SPEAKER_00] And right now, it's just the sports books are just not it. [SPEAKER_00] And we firmly believe that what we do in our markets are significantly safer for all of that. [SPEAKER_00] And if you just take a stance of prohibiting, it's similar, you said alcohol, right? [SPEAKER_00] It didn't change. [SPEAKER_00] People just went to a speakeasy and drank. [SPEAKER_00] And people are just going to go offshore when there's way less protections. [SPEAKER_00] There's none of the self exclusion, the deposit limits, all those things that we do. They don't have any information about them. [SPEAKER_00] And it's actually very bad for them. [SPEAKER_00] So I think it's just this prohibition concept just never really works. [SPEAKER_00] It's also the whole policy discussion around this stuff is also very interesting when it kind of reminds me of in Canada, all the liquor stores are run by the government, or at least in British Columbia. [SPEAKER_00] And you have the government saying this must be very carefully controlled, but also we will sell it to you as a revenue source. [SPEAKER_02] And obviously, that's much more of a factor in lotteries and things like that. [SPEAKER_02] It's all about money at the end of the day. [SPEAKER_02] The states want their money, the casinos want their money. [SPEAKER_02] It's just, yeah, it is what it is. [SPEAKER_00] Speaking of sports, one thing we were talking about while you were gone was just what interesting new verticals are there going to be? [SPEAKER_00] And so I'm just curious, which ones are you most excited about? [SPEAKER_00] Well, I think that anything around dissecting a stock into its more atomic components. So this would be betting directly on NVIDIA GPU shipments versus… Yes, or like Resolve deliveries or whatever. [SPEAKER_01] Like their earnings, because the… [SPEAKER_03] And then you can expand that to things like, okay, dissecting the macro economy. [SPEAKER_02] The states won their money, the casinos won their money. [SPEAKER_02] It's just, yeah, it is what it is. Speaking of sports, one thing we were talking about while you were gone was just what interesting new verticals are there going to be? And so I'm just curious which ones are you most excited about? Well, I think that anything around dissecting a stock into its more atomic components. [SPEAKER_03] So this would be like betting directly on NVIDIA GPU shipments versus… [SPEAKER_03] Yes, or like Resolve deliveries or whatever. [SPEAKER_01] Like their earnings, because the… [SPEAKER_03] And then you can expand that to things like, okay, dissecting the macro economy. [SPEAKER_01] Like what are the main factors that are influencing the economy broadly? [SPEAKER_01] Like AI, and have a series of questions to price what's going on with AI. [SPEAKER_01] Things like health scares like COVID and so on. [SPEAKER_01] But where things get really interesting is this idea where… [SPEAKER_01] So there was a paper written by Kevin Hassett around this idea that as society gets increasingly more complex, our asset prices, our understanding of asset prices will naturally decay. [SPEAKER_01] Entropy will go up because the things that influence or the vector that the number of factors… [SPEAKER_01] It's a much higher dimensional vector for any given output. [SPEAKER_01] Becomes very high dimensional, right? [SPEAKER_01] And if those dimensions, you don't have a good understanding of X1 to Xn, you cannot get a good estimate of Y, right? [SPEAKER_01] And so the paper basically says you need infinite markets. [SPEAKER_01] And prediction markets are a discretion of infinite markets, which is you have to have a market for each one of these Xs so that you can then take that back into pricing traditional asset, getting good traditional asset prices. [SPEAKER_01] And an example of that this last week, there was the… [SPEAKER_01] Citadel put out a research report, right? [SPEAKER_01] And it got a surprising amount of… [SPEAKER_01] People got obsessed with that. [SPEAKER_01] Yeah, I would say it got a surprising amount of love and interest. [SPEAKER_01] This is the AI 2028s we're all doing. Yeah, like 38% unemployment. [SPEAKER_01] I think there's a little bit of a society wants to believe that AI is going to end us all. [SPEAKER_01] I think right now there's a bit of that. But this is where the, and that impacted markets, right? [SPEAKER_01] The stocks got, there was a sell-off. [SPEAKER_01] And so we launched a prediction market on that. [SPEAKER_01] And before that, Citadel came out with a rebuttal and we launched a prediction market on that. [SPEAKER_01] And the odds are 10%, right? [SPEAKER_01] So… [SPEAKER_01] Of the economic scenario that they predicted being true by 2028. [SPEAKER_01] It's three out of five things. [SPEAKER_02] Yeah, yeah. [SPEAKER_02] So they have five conditions if three hit. [SPEAKER_00] Yeah, if three out of these five conditions hit, you could reasonably say that okay, this outcome has somewhat materialized. [SPEAKER_00] Yeah. [SPEAKER_00] And it's just 10%. [SPEAKER_01] Five out of five is much lower, right? [SPEAKER_01] So that is important. [SPEAKER_01] Yeah. [SPEAKER_01] If you can put that back into pricing models, maybe the markets wouldn't have reacted that. [SPEAKER_01] Maybe people wouldn't have sold off DoorDash. [SPEAKER_01] Because at least I believe, but you don't have to trust me, maybe you should trust markets that this sort of analysis around DoorDash was actually quite poor. [SPEAKER_01] Yeah. [SPEAKER_01] So one thing you're envisioning is this world where everything has a price all the time. [SPEAKER_01] And I'm curious, is that a good world to live in? [SPEAKER_01] And I would note that Stripe, I think, benefits from being private and not having the real-time price and smoothness for employees and comp and all that. [SPEAKER_03] Which is, by the way, the biggest… [SPEAKER_03] There's some noise in the, sub-second pricing. [SPEAKER_03] Right, because clearly sentiment swings publicly. There's, on average, in the long run, it's a truth-telling machine, but in the short run can be a panic. So I was just curious for you guys to think about, is that the world we want to live in? [SPEAKER_03] I mean, we're obviously biased because we love markets. [SPEAKER_03] We think markets are good. [SPEAKER_03] So we're definitely biased here. But I think our view on this is that it's always better to have more data than less data. If you don't think the data is good, if you don't think the second-by-second stock price is good, you can just choose to ignore it. [SPEAKER_00] It might, the world might not just ignore it, but you can… I think CEOs of public companies would say it is not always possible to choose to ignore it. I guess that's fair, that's fair. But in a way, it's better to have the data and then use it as an input to something than not. [SPEAKER_02] But when we say we want to have prices on a lot of things, it doesn't mean everything. There are a lot of things that we wouldn't do, like wildfires we don't do, war, terrorism, assassination. Those things are bad and there's a moral side of these markets and we're not going to ever go there. But in general, in a world of social media, you don't know what's true anymore. My feed is like, is it real? Is it not real? Did this happen? It's just better to have a source, an unbiased source of information that you can use it for other things. [SPEAKER_00] And I think that value is there, but I don't know what you're saying. [SPEAKER_00] Well, I think that maybe the simple frame for this is you are increasing market efficiency for all these questions. [SPEAKER_00] Right? That's what this is happening, right? [SPEAKER_00] It's including potentially some events or things that relate to maybe private companies. [SPEAKER_00] And I was just thinking about the question, it's an interesting question, why do companies go public? [SPEAKER_00] Right? And why is it important to get a real-time market price? [SPEAKER_01] Because there are downsides. Sometimes markets are erratic. [SPEAKER_01] Sometimes they overshoot in either direction. [SPEAKER_01] But the market on a long enough time horizon is a good allocator. [SPEAKER_01] It's a good weighing mechanism. It's a good allocator of capital. [SPEAKER_01] Right. [SPEAKER_01] And I don't really see that. I just think that pricing a lot of these questions will just increase efficiency, make our allocating function better over time. [SPEAKER_01] And there will be some net losers, right? Like some people that maybe capital shouldn't be allocated to. Right? [SPEAKER_01] It's also a good feedback loop, right? Like if you're a CEO of a public company and you announce something and it just keeps going down, [SPEAKER_01] Because there are downsides. Sometimes markets are erratic. [SPEAKER_01] Sometimes they overshoot in either direction. [SPEAKER_01] But the market on a long enough time horizon is a good allocator. [SPEAKER_01] It's a good weighing mechanism. It's a good allocator of capital. [SPEAKER_01] Right. [SPEAKER_01] And I don't really see that I just think that pricing a lot of these questions will increase efficiency, make our allocating function better over time. [SPEAKER_01] And there will be some net losers, right? Some people that maybe capital shouldn't be allocated to. Right? [SPEAKER_01] It's also a good feedback loop, right? If you're a CEO of a public company and you announce something and it just keeps going down, you're like, okay, maybe I'm wrong. And I think the same thing you see with politicians where you can see in the live debate, if they say some answers and they see their prices going lower, they're like, well, maybe the answers aren't great. [SPEAKER_01] And I think a lot of these things, when we see even the use case of prediction markets in government, a lot of it is conditional markets, right? They can say, if we pass this bill, will unemployment go up or down? [SPEAKER_02] And you can price these things for better decision making and just a tighter feedback loop tied with good incentives. [SPEAKER_01] Do you guys feel like we have started this? Clearly we have seen the effects of social media on politics, where politics is a different game now and different politicians are popular and the political discourse is changed by the existence of, first Twitter and now to some extent short form video. Do you guys feel like we have seen the effects on politics of prediction markets yet? [SPEAKER_01] Definitely. I mean, the... [SPEAKER_01] What are they? [SPEAKER_00] Well, the candidates are using the prediction market prices to inform... Sure, but that could just be a handy thing. Whereas again, I think with social media, the candidates are different. The debates are different. Reflexive. Reflexive. Yeah, yeah, yeah. Reflexive. I do think that what the markets are good at is that they are more unbiased by party dynamics. So if there is an underdog that the public really likes, there's a lot of maybe a party that's like, we don't like this guy, we like this guy from the establishment, but the markets are very good at actually showing the real odds for that person. Okay, so you think the party machines have lost a little bit of power? I think you can shine more light into what people really want, which might not be necessarily what the parties want to put forward. [SPEAKER_02] I don't think we've seen that necessarily yet, but I feel like if I were to say, for example, the Texas primary, and I think that the polls were saying one person was really going to win, another person that was way higher on prediction markets won. [SPEAKER_02] And I think, right, and I think a lot of it was more like they give a more fair view of the state of the race than a lot of the party. [SPEAKER_02] Well, I think that we do see this a lot with also there's the piece where people use it and react in real time to certain things. [SPEAKER_02] But I think there's some degree of depolarization. [SPEAKER_01] And that's what Luana is alluding to. [SPEAKER_01] And in some ways, it's an antidote to social media. Social media has really polarized. [SPEAKER_01] When you have two candidates running for a Senate race, we're sort of set, right? [SPEAKER_01] Your feet is set. [SPEAKER_02] Either your feet is saying the Republican candidate is awesome or the feet is saying the Democrat candidate is awesome. [SPEAKER_02] Prediction markets have don't really have that. [SPEAKER_01] Because the people that are engaging in this are not in the sort of who's best, who's great and who's... [SPEAKER_01] I think what you're saying is social media feeds ultimately try to resolve upfront. [SPEAKER_01] They're like, I need to figure you out. [SPEAKER_00] Are you a Democrat? [SPEAKER_00] Are you a Republican? [SPEAKER_00] What post should I show to you? [SPEAKER_00] And pretty quickly, people have complained about this phenomenon where you end up down a particular rabbit hole because they have pigeonholed you as this type. [SPEAKER_00] And you're saying prediction markets do not have that phenomenon. There's a little bit of a reverse phenomenon. [SPEAKER_00] It's like, are we feeling too certain about this person? [SPEAKER_00] And I think that depolarizes things because the dimension is not we're not one dimensional anymore, which is Republican Democrat. [SPEAKER_00] And that's what you're seeing and what you're hearing about. [SPEAKER_00] Now it's like, well, this guy is cool. [SPEAKER_01] Right. [SPEAKER_01] And that's Tatarico. [SPEAKER_01] And maybe he might do good in Texas, even though he's a Democrat. [SPEAKER_01] And you know... [SPEAKER_01] The same thing happened with the New York mayor situation, right? [SPEAKER_01] Everyone was like, Cuomo is going to win a hundred percent. Cuomo is going to win. [SPEAKER_01] There's not even a chance. [SPEAKER_01] And we were just seeing Mondani's odds going up. [SPEAKER_01] And I think the progressive message was really working with New Yorkers and the markets were really seeing that uptick and that decrease in polarization really comes from people taking a step back and being like, who do I actually think is going to happen? I'm incentivized the right way. [SPEAKER_02] There's a bit of an Iowa, New Hampshire effect here for presidential elections in the U.S. There's some big name leading into the election. [SPEAKER_02] Maybe it was Hillary Clinton in 08. [SPEAKER_02] And then Iowa and New Hampshire are measurements of the sentiment of those two states, but they also create narrative. [SPEAKER_02] Right. [SPEAKER_02] And I think what you guys are saying is prediction markets create this Iowa, New Hampshire effect where they can create narrative in a way that changes the ultimate outcome. [SPEAKER_01] I don't know if it changes the ultimate outcome. I wouldn't say it changes the ultimate outcome. [SPEAKER_01] I think it sheds light into what the ultimate outcome is going to be. [SPEAKER_01] Because if this... [SPEAKER_01] And potentially changes it. [SPEAKER_01] Well, I think... There clearly is some flexibility, right? [SPEAKER_01] I mean, there's always, but it's like with the polls too, right? [SPEAKER_01] Like the... [SPEAKER_01] Yes. [SPEAKER_01] I mean, there's polls. Aren't you guys hiding your lamp under a bushel here? [SPEAKER_00] You're like, well, we're not changing anything here. You're just... I just think that the one thing I will say, the reason why we're like... Prediction markets are a big deal. It's okay to say they'll change things a little bit. [SPEAKER_02] High odds don't always correlate to a good outcome. [SPEAKER_02] So you saw Mamdani when his odds were 94% on Kalshi. [SPEAKER_01] There's always, but it's like with the polls too, right? Yes. There's polls. [SPEAKER_00] Aren't you guys hiding your lamp under a bushel here? You're like, well, we're not changing anything here. I just think that the one thing I will say, the reason why we're like prediction markets are a big deal. It's okay to say they'll change things a little bit. High odds don't always correlate to a good outcome. So you saw Mamdani when his odds were 94% on Kalshi. The thing that he was messaging pretty consistently, and I think there was a little bit of worry there. It's you gotta show up. Right? Because if you're very high odds, that could also lead people to be like, okay, this isn't it. Yeah. So it's not as clear. Yes. [SPEAKER_01] And I don't think this changes things more than polls changes. Right. Does that make sense? Yeah, yeah. The response is more in a vacuum, yes. [SPEAKER_02] Yes. If you had nothing else, if you didn't have social media, if you didn't have news, if you didn't have any of that, yes. But because we have all these other things and you add prediction markets to it, the impact model. [SPEAKER_01] But I want to make one point that I think is actually very interesting. And we're seeing this often. We'll be the judge of that. Okay. You can judge that. Let me know if it's interesting. But a lot of times when you see people start participating in prediction markets, they get more engaged in the underlying. Yeah. They legitimately just get more informed. It pulls people in. It pulls people in, but to do research. Now you have some skin in the game or you're about to put some skin in the game, you read, everything changes. You're not just saying something crazy on Twitter anymore. You're putting money. Yeah. And now it's let me read. Let me actually figure out, oh, who's this person? What's happening? Are they pro this? Are they against this? What's their view? And you go, because it's amazing because this happened a bit in the New York race, right? Or it happened a bit with Brexit. People voted for Brexit because, oh, no, we want Brexit. And after they voted for it, they're like, oh God, wait, I don't think we wanted this. Wait, we didn't even understand what we were voting for, right? And I think this heightened engagement engages people further to learn and understand. You know, in sports, if you ask a lot of the leagues, they would tell you the same thing. [SPEAKER_01] But people got more engaged with the statistic. Which player is good? What's happening? What happened is already happening in sensitive politics, which is a good thing. I think that I'm going to say something that I'm going to call a fan of saying. I think that politics are going to get better because you're going to have a way faster feedback loop on the messaging and the policies. Right now, when a candidate says 10 things and they win or they lose, you're trying to make one assessment of so many things that the candidate did. Yes. And did that go well or not? And which point was it? And even if you do a poll, it's always delay. It is a very specific sample. But now you can have real time of they said this, what was the response? [SPEAKER_01] And you can get that and have that faster feedback loop, which I think makes startups great. Right? You're able to iterate very fast. And I think if candidates are able, everyone wants to win at the end of the day. And if they're able to optimize their message to what people really want and what policies people want, I think they're going to end up being better because they're just going to know what people want better. It's you get a score on all of the different things you've done, not one score that's encompassing. Which is when you ship a new feature, you're able to have 10 metrics and you're like, okay, this went up, this went down. And you're able to markets can contribute to that, but also to a lot of other things as well. Music with charts, when someone listens to the song and they're like, definitely not going to hit number one. You're like, okay, that was that song. So we should do something else. [SPEAKER_01] Do you guys try to use prediction markets in any way internally to make decisions? [SPEAKER_01] Every single decision we make is always probability. Even the election lawsuit, right? When we're doing it, it's like... But that's you guys evaluating the probability. Yeah. Do you ever think about creating markets for your employees to participate in? We have one net. Yes. Which is as a regular exchange, we can't trade. But we do it for internal polling. There's a separation of church and state thing there. Exactly. And so we've been asking that, we've been working with regulators, could we do something small? Could we do small dollars where you know, because obviously that's one that we really want to implement. And you can't even dog food the product, I guess. And dog fooding the product. Right. [SPEAKER_01] Which is a big deal. Which has been hard. It's hard. Everyone's on the demo. And employees cannot trade in their personal capacity? They can't. Not at all. [SPEAKER_00] Interesting. Yeah. But yeah, that makes it very hard for you. As you say, you just can't dog food your... You can't try the product. Right. People at Facebook use Facebook and that's how you make the product good. [SPEAKER_01] Right. Right. So that's why it's so important for us to just be asking the users all the time. [SPEAKER_00] Yeah, yeah. [SPEAKER_01] Oh, that's so interesting. [SPEAKER_00] Everyone's on the demo. [SPEAKER_00] And employees cannot trade in their personal capacity? [SPEAKER_00] They can't. Not at all. [SPEAKER_00] Interesting. Yeah. But yeah, that makes it very hard for you. As you say, you just can't dog food your... [SPEAKER_03] You can't try the product. [SPEAKER_03] Right. [SPEAKER_03] People at Facebook use Facebook and that's how you make the product good. [SPEAKER_01] Right. [SPEAKER_01] Right. [SPEAKER_01] So that's why it's so important for us to just be asking the users all the time. Yeah, yeah. [SPEAKER_01] Oh, that's so interesting. Yeah. [SPEAKER_01] It sucks. [SPEAKER_01] But the power users, the super forecasters are a lot of what influences where it goes because they're very engaged. [SPEAKER_01] They're very loved. You guys presumably spend a lot of time with those power user super forecaster types and just have them on speed dial. [SPEAKER_01] They're there day one. [SPEAKER_01] They're there day one, so... They want to make sure they're happy. [SPEAKER_02] Last question. Where do you guys want to see prediction markets policy go? Like when you're talking to someone in government or if you had a magic wand, what are you arguing for? [SPEAKER_02] So our sense as a company, and I think this may differ a little bit from your average tech company or big tech company. [SPEAKER_02] We are pro innovation. [SPEAKER_02] Innovation needs to happen in America. [SPEAKER_02] We have to lead and we have to do it right. [SPEAKER_02] And we have to win. [SPEAKER_02] All the things that Americans want to do or we need to win as a country we should have here. [SPEAKER_02] But we're also pro regulation. [SPEAKER_01] At a higher level principle, there's usually this tension, you know, generally policymakers want to regulate and... I think you're maybe more like a traditional financial firm in that way, right? Where maybe Silicon Valley, a lot of firms grew up in an unregulated way, but financial firms have always had a regulator and that's just a fact of life. [SPEAKER_01] Yes. [SPEAKER_00] It's just a constraint for you to work with. [SPEAKER_02] So it's part of the culture. [SPEAKER_02] And we spent four years getting regulated upfront. [SPEAKER_02] So it's part of it, but we believe in regulation. I think it's important because regulation is a bit like insurance. It's protecting you from things going wrong and bad times. And so when I think about where this lands? I think anything that is oriented around preserving these in America and making sure we win, but then elevating the fairness and transparency of the markets, right? Anything that's oriented, how do we make it more fair? Ban insider trading, add more restrictions on government officials, members of Congress trading on information they shouldn't trade. [SPEAKER_01] I'm obviously a big fan of banning insider trading from members of Congress. [SPEAKER_01] We talked about it, yeah. [SPEAKER_01] But... [SPEAKER_01] Presumably you mean just banning trading, period, for a member of Congress. [SPEAKER_01] I think it's not a bad idea. [SPEAKER_01] Yeah, that's how we think. [SPEAKER_01] But I think... [SPEAKER_01] And then things around creating social fairness and transparency, because of all the questions that we asked, if people are trading on politics, let's have all the trade data be as public as possible so anyone can audit it, anyone can see it, which is a good thing, right? Right. You know, imagine a poll where you can check every single person that was... [SPEAKER_01] And the general public can check who was polled and what the sample was like. [SPEAKER_01] And then anything around customer protection. [SPEAKER_01] And because that is important long term in the sense that when you build a consumer product and it goes mainstream, there is a massive burden on the companies to educate. [SPEAKER_01] And you've seen it over and over. [SPEAKER_01] In our case, you want to make sure that people know what they're getting into. [SPEAKER_01] They're not overextending themselves in terms of how much they're trading. [SPEAKER_01] They're not getting into an area of discomfort. [SPEAKER_01] And how do you handle that? We can do as much as we can do on the marketing and on the product side. [SPEAKER_01] But we need policymakers and regulators help to make it an industry standard, but also help us elevate ours. [SPEAKER_01] And by the way, we're pro that even classic retail brokerages should also be adopting a lot of these customer protections that we're talking about that they don't. [SPEAKER_01] And I think that every retail trading platform should be taking a lot of these steps. [SPEAKER_01] So yeah, that's our general view. [SPEAKER_00] And we hope that this is the direction that things take because you can have a variety of views. [SPEAKER_01] Right. And some people believe that any type of speculation should be banned, whether it's in the stock market or crypto or prediction market. [SPEAKER_01] We don't believe that. We think that would be a bad outcome for all the reasons, because there's a lot of upside to having liquid markets and a variety of different things. But also because if you ban it, you're actually heightening the risks that you're trying to prevent, because now that activity is going offshore. Right. And where you cannot monitor it or police it or do anything to protect it. Awesome. Well, thank you guys. [SPEAKER_01] Thank you. I've reviewed the input, but it appears to contain only speaker labels without any actual spoken text or content to clean. To clean a transcript, I'll need the actual dialogue or speech content between the speaker labels. Could you please provide the transcript with the spoken words included? people bet. And it's just about what is the best way for them to have access to something that they can get exposure to sports. And I think that the whole point of markets versus a bookie is that markets are just objectively better. Right? I think that it's almost, I've never heard someone make a case that a state-by-state regulated casino is actually a good thing. I'm actually hearing nowadays that a lot of like the paid propaganda by the gambling guys trying to say that. But if you push them to questions. And just to put numbers on that, the order of magnitude rake for sports betting companies is around 10%. And the order of magnitude for prediction markets is, you know, 1% or a few points. Right. But the predatory part doesn't even come from that. Like for sports betting, if you start losing, because they want the losers, they don't want the winners. If you start losing, the first thing that they're going to do is give you a bonus. They're going to be like, oh, here it is. Oh, look at that. Oh, I'm going to go fun. We were talking about kind of sports. And what they do is you start losing and then they're going to give you $1,000 for you to come back. Or like a deposit boost and all those things so that they can hook you to keep you coming back because they want to incentivize the losers. We don't do anything. The people losing the most money are the most profitable for sports bookies. Yeah. Which creates a bad incentive. And we don't have that at all. And I think that the whole point is like, there's a moral question. Like some people are going to go into Robinhood or Coinbase or whatever and speculate on stocks and speculate on crypto and whatever they want to do. And some people want to speculate on sports and they should have the best, the access to the best possible thing for that. And right now, it's just the sports books are just not it. And we firmly believe that what we do in our markets are significantly safer for all of that. And if you just take a stance of prohibiting, it's like similar, you said alcohol, right? It didn't change. People just went to like a spigeezy and drink. And people are just going to go offshore when there's way less protections. There's no, none of the self exclusion, the positive limits, all those things that we do, don't have any information about them. And they're going to actually, it's actually very bad for them. So I think it's just this like prohibition concept just never really works. It's also the whole policy discussion around this stuff is also very interesting when it kind of reminds me of in Canada, all the liquor stores are run by the government, or at least in British Columbia. And, you know, you have the government saying this must be very carefully controlled, but also we will sell it to you at the revenue source. And obviously, that's much more of a factor in lotteries and things like that. It's all about money at the end of the day. The states won their money, the casinos won their money. It's just, yeah, it is what it is. Speaking of sports, one thing we were talking about while you were gone was just what interesting new verticals are there going to be? And so I'm just curious, like, which ones are you most excited about? Well, I think that anything around dissecting like a stock into its sort of like more atomic components. So this would be like betting directly on NVIDIA GPU shipments versus… Yes, or like Resolve deliveries or whatever. Like their earnings, you know, because like the… And then you can expand that to things like, okay, dissecting sort of the macro economy. Like what are the main sort of like factors that are influencing the economy broadly? Like AI, and like have a series of questions to price what's going on with AI. Things like, you know, health scares like COVID and so on. But the sort of where things get really interesting is this idea where… So there was a paper written by Kevin Hassett around this idea that like as society gets increasingly more complex, like our asset prices, our understanding of asset prices will naturally decay. Like entropy will go up because the things that influence or the sort of vector that, you know, like the number of factors… It's a much higher dimensional vector for any given output. Becomes very high dimensional, right? And if those dimensions, you don't have a good understanding of X1 to Xn, you cannot get a good estimate of Y, right? And so the paper basically says like you need infinite markets. And prediction markets are a disnotion of infinite markets, which is like you have to have a market for each one of these Xs so that you can then take that back into pricing traditional asset, getting good traditional asset prices. And an example of that this last week, you know, there was the… The Citrini put out a research report, right? And it got a surprising amount of… People got obsessed with that. Yeah, I would say it got a surprising amount of love and interest. This is the AI 2028s we're all doing. Yeah, like 38% unemployment. I think, look, I think there's a little bit of like a society wants to believe that AI is going to end us all. I think right now there's a bit of that. But this is where the, you know, and that impacted markets, right? Like the stocks got, you know, there was a sell-off. And so we launched a prediction market on that. And well, before that, Citadel came out with a rebuttal and we launched a prediction market on that. And, you know, the odds are 10%, right? So… Of the economic scenario that they predicted being true as a 2028. It's three out of five things. Yeah, yeah. So they have like five conditions if three hit. Yeah, if three out of these five conditions hit, you could reasonably say that, okay, this outcome has somewhat materialized. Yeah. And it's just 10%. Five out of five is much lower, right? So that is important. Yeah. If you can put that back into pricing models, maybe the markets wouldn't have reacted that. Like maybe people wouldn't have sold off DoorDash. Because at least I believe, but you don't have to trust me, maybe you should trust markets that this sort of analysis around DoorDash was actually quite poor. Yeah. So one thing you're sort of envisioning is this world where everything has a price all the time. And I'm curious, like, is that a good world to live in? And I would note that Stripe, I think, benefits from being private and not having the real-time price and smoothness for employees and comp and all that. Which is, by the way, the biggest… There's some noise in the, you know, sub-second pricing. Right, because like, clearly, sentiment swings publicly. Like there's, on average, in the long run, it's a truth-telling machine, but in the short run can be a panic. So I was just curious for you guys to think about, yeah, is that the world we want to live in? I mean, we're obviously biased because we love markets. We think markets are good. So we're definitely biased here. But I think our view on this is that it's always better to have more data than less data. If you don't think the data is good, if you don't think like the sub, like whatever, the second-by-second stock price is good, you can just choose to ignore it. It might, the world might not just ignore it, but you can… I think CEOs of public companies would say it is not always possible to choose to ignore it. I guess that's fair, that's fair. But in a way, it's like, it's better to have the data and then use it as an input to something than not. But when we say like, you know, we want to have prices on a lot of things, it doesn't mean everything. There are a lot of things that we wouldn't do, like wildfires we don't do, war, terrorism, assassination. Those things are bad and like, there's a moral side of these markets and we're not going to ever go there. But in general, it's in a world of social media is like, you don't know what's true anymore. My feed is like, is it real? Is it not real? Did this happen? It's just better to have a source, an unbiased source of information that you can kind of use it for other things. And I think that that value is there, but I don't know what you're saying. Well, I mean, I think that like, maybe the simple frame for this is like, you are increasing market efficiency for all these questions. Right? Like that's what this what's happening, right? It's including potentially some events or things that relate to maybe private companies. And I was just thinking about the question is an interesting question like, why do companies go public? Right? And why is it important to get like a, you know, real time market price? Because there are downsides. Sometimes markets are erratic. Sometimes they overshoot in either directions. But the market on the long enough time horizon is a good sort of allocator. It's a good weighing mechanism. It's a good allocator of capital. Right. And I don't really see that like, I just think that like pricing a lot of these questions will just increase efficiency, make our function, our allocating function better over time. And there will be some net losers, right? Like some people that maybe capital shouldn't be allocated to. Right? It's also a good feedback loop, right? Like if you're a CEO of a public company and you announce something and it just keeps going down, you're like, okay, maybe I'm wrong. And I think the same thing you see with politicians where you can see in the live debate, if they say some answers and they see their prices going lower, they're like, well, maybe the answers aren't great. And I think a lot of these things, when we see even the, for example, the use case of prediction markets in government, a lot of it is conditional markets, right? They can say, if we pass this bill, will unemployment go up or down? And you can price these things for better decision making and just like a tighter feedback loop tied with good incentives. Do you guys feel like we have started this? Like clearly we have seen the effects of social media on politics, where politics is a different game now and different politicians are popular and the political discourse is changed by the existence of, I mean, first Twitter and now to some extent short form video. Do you guys feel like we have seen the effects on politics of prediction markets yet? Definitely. I mean, the... What are they? Well, the candidates are using the prediction market prices to inform... Sure, but that could just be like a handy thing. Whereas again, I think with social media, like the candidates are different. The debates are different. Reflexive. Reflexive. Yeah, yeah, yeah. Reflexive. I do think that what the markets are good at is that they are more unbiased by party dynamics. So if there is an underdog that the public really likes, there's a lot of like, maybe there's like a party that's like, we don't like this guy, we like this guy from the establishment, but the markets are very good at actually showing the real odds for that person. Okay, so you think the party machines have lost a little bit of power? I think you can shine more light into what people really want, which might not be necessarily what the parties want to put forward. I don't think we've seen that necessarily yet, but I feel like if I were to say, there was a, for example, the Texas primary, and I think that the polls were saying one person was really going to win, another person that was very, way higher on prediction markets won. And I think, right, and I think a lot of it was more of like, they give a more, a fairer view of the state of the race than a lot of the party. Well, I think that we do see this a lot with also, well, there's sort of the piece where people use it and that sort of react in real time to certain things. But I think there's some degree of depolarization. And that's what Luana is alluding to. Like, and in some ways, it's an anecdote to social media, like social media has really polarized. Like when you have two candidates running for a Senate race, we're sort of set, right? Like your feet is set. Like either your feet is saying the Republican candidate is awesome or the feet is saying the Democrat candidate is awesome. Prediction markets have, don't really have that. Because the people that are engaging in this are not, are not in the sort of like who's best, who's great and who's, you know. I think what you're saying is social media feeds ultimately try to resolve upfront. They're like, I need to figure you out. Are you a Democrat? Are you a Republican? Like what post should I show to you? And pretty quickly, I mean, you know, people have complained about this phenomenon where you end up down a, you know, particular rabbit hole because they have pigeonholed you as kind of this type. And you're saying just prediction markets do not have that phenomenon. There's a little bit of a reverse phenomenon. It's like, are we feeling too certain about this person? And like, and I think that depolarizes things because the dimension is not, we're not any, we're not one dimensional anymore, which is like Republican Democrat. And that's where you're, what you're seeing and what you're hearing about. Now it's like, well, this guy is kind of cool. Right. And that's Tatarico. And maybe he might do good in Texas, even though he's a, he's a, he's a Democrat. And, and, you know, and. The same thing happened with the New York mayor situation, right? Like everyone was like, Cuomo is going to win a hundred percent, a hundred percent Cuomo is going to win. There's not even a chance. And we were just seeing Mondani's odds going up. And I think it's just the progressive message was really working with New Yorkers and the markets. We're really seeing that, that uptick and that, that decrease in polarization really comes from people taking a step back and being like, who do I actually think is going to happen? I'm incentivized the right way. There's a bit of like an Iowa, New Hampshire effect here for, you know, in presidential elections in the U.S., there's like some big name leading into the election. You know, maybe it was Hillary Clinton in 08. And then Iowa and New Hampshire are measurements of the sentiment of those two states, but they also create narrative. Right. And I think what you guys are saying is prediction markets create this Iowa, New Hampshire effect where they can create narrative in a way that changes the ultimate outcome. I don't know if it changes the, I wouldn't say it changes the ultimate outcome. I think it sheds light into what the ultimate outcome is going to be. Because if this. And potentially changes it. Well, I think. There clearly is some flexibility, right? I mean, there's always, but it's like with the polls too, right? Like the, yes. I mean, there's polls. Aren't you guys hiding your lamp under a bushel here? You're like, well, we're not changing anything here. You're just like. I just think that the one thing I will say, the reason why we're like. Like prediction markets are a big deal. It's okay to say they'll change things a little bit. High odds don't always correlate to like a good outcome. So you saw Mamdani when his odds were 94% on Kalshi. The thing that he was messaging pretty consistently, and I think there was a little bit of worry there. It's like, you gotta show up. Right? Like, because if you're very high odds, that could also lead people to be like, okay, this isn't it. Yeah. So it's not as clear. Yes. And I don't think this changes things more than polls changes. Right. Does that make sense? Yeah, yeah. The response is more like in a vacuum, yes. Yes. If you had nothing else, if you didn't have social media, if you didn't have news, if you didn't have any of that, yes. But because we have all these other things and you add prediction markets to it, like the impact model. But I want to make one point that I think is actually very interesting. And we're seeing this often. We'll be the judge of that. Okay. You can judge that. Let me know if it's interesting. But a lot of times when you see people start participating in prediction markets, they get more engaged in the underlying. Yeah. They legitimately just get more informed. It pulls people in. It pulls people in, but to do research. Now you have, because you have some skin in the game or you're about to put some skin in the game, you read, everything changes. You're not just like saying something crazy on Twitter anymore. You're putting money. Yeah. And now it's like, let me read. Let me actually figure out, oh, who's this person? What's happening? Like, are they pro this? Are they against this? What's their view and everything? And you go, because, you know, it's like amazing because this happened a bit in the New York race, right? Like, or it happened a bit with Brexit. People voted for Brexit because, oh, no. We want Brexit. And after they voted for it, they're like, oh God, wait, I don't think we wanted this. Wait, wait, we didn't even understand what we were voting for, right? Like, and I think this heightened engagement, like, you know, like it engages people further to like learn and understand. You know, in sports, basically, if you ask sort of like a lot of the leagues, they would tell you the same thing. But people got more engaged with the statistic. Which player is good? What's happening? What happened is already happening in sensitive politics, which is a good thing. I think that the, I'm going to say something that I'm going to call a fan of saying. I think that politics are going to get better because you're going to have a way faster feedback loop on the messaging and the policies. Right now, when a candidate says 10 things and they win or they lose, you're trying to make one assessment of like so many things that the candidate did. Yes. And did that go well or not? And which point was it? And even if you do a poll, it's like always delay. It is a very specific sample. But now you can have real time of like, they said this, what was the response? And you can get that and kind of like that faster feedback loop, which I think makes startups great. Right? You're able to iterate very fast. And I think if candidates are able, everyone wants to win at the end of the day. And if they're able to optimize their message to what really people want and what policies people want, I think they're going to end up being better because they're just going to know what people want better. It's like you get a score on all of the different things you've done, not one score that's encompassing. Which is basically like when you ship a new feature, you're able to have like 10 metrics and you're like, okay, this went up, this went down. And you're able to, markets can kind of contribute to that, but also like, I think to a lot of other things as well. Music with like charts, when someone listens to the song and they're like, definitely not going to hit number one. You're like, okay, that was that song. So we should do something else. Do you guys try to use prediction markets in any way internally to make decisions? Every single decision we make is always probability. Even the election lawsuit, right? When we're doing it, it's like... But that's you guys evaluating the probability. Yeah. Do you ever think about creating markets for your employees to participate in? So we have one net. Yes. Which is as a regular exchange, we can't trade. But we do it like internal polling. There's like a separation of church and state thing there. Exactly. And so we've been asking that, we've been working with regulars, could we do something small? Like, could we do small dollars where...so that, you know, because obviously that's one that we really want to implement. And you can't even dog food the product, I guess. And then dog fooding the product. Right. Which is a big deal. Which has been hard. It's hard. You know, that... Everyone's on the demo. And employees cannot trade in their personal capacity? They can't. Not at all. Interesting. Yeah. But yeah, that makes it very hard for you. As you say, you just can't dog food your... You can't try the product. Right. People at Facebook use Facebook and that's how you make the product good. Right. Right. So that's why it's so important for us to just be like asking the users all the time. Yeah, yeah. Oh, that's so interesting. Yeah. It sucks. But the power users, the super forecasters are a lot of what influences sort of where it goes because they're very engaged. They're very loved. You guys presumably spend a lot of time with those power user super forecaster types and just have them on speed dial. They're there day one. They're there day one, so... They want to make sure they're happy. Last question. Where do you guys want to see prediction markets policy go? Like when you're talking to someone in government or if you had a magic wand, what are you arguing for? So our sense as a company, and I think this may differ a little bit from like, I would say like your average tech company or big tech company. So we are pro innovation. Innovation needs to happen in America. You know, we have to lead and we have to do it right. And we have to win. Like we have to be, you know, all the things that Americans want to do or we need to win as a country we should have here. But we're also pro regulation. And so, and a higher level principle, like there's usually this tension that, you know, generally it's like, you know, it's like the policymakers like want to regulate and... I think you're maybe more like a traditional financial firm in that way, right? Where maybe Silicon Valley, you know, a lot of firms grew up in unregulated way, but financial firms have always had a regulator and that's just a fact of life. Yes. It's just a constraint for you to work with. So it's part of the culture. And I mean, again, we spent four years getting regulated upfront. So it's part of, but we believe in regulation. Like I think it's important because, you know, regulation is a bit like insurance. It's like, it's protecting you from things going wrong and bad times. And so when I think about like, okay, where this lands? I think anything that is oriented around preserving these in America and making sure we win, but then elevating the fairness and transparency of the markets, right? Anything that's oriented, like how do we make it more fair? Ban insider trading, add more restrictions on, for example, like, you know, government officials, members of Congress trading on like, you know, information they shouldn't trade. Now I'm obviously a big fan of like banning insider trading from members of Congress. We talked about it, yeah. But, um... Presumably you mean just banning trading, period, for a member of Congress. I think it's not a bad idea. Like, you know... Yeah, that's how we kind of think. But I think... And then things around like, you know, loving, like creating also a social fairness and transparency, because of all the questions that we asked, like if people are basically trading on politics, let's have all the trade data be as public as possible so anyone can audit it, anyone can see it, which is a good thing, right? Right. You know, now you don't know, like imagine a poll where you can check every single person that basically got... And the general public can check who was polled and what the sample was like. And then anything around customer protection. And because that is important long term in the sense that like, when you build a consumer product and it goes mainstream, there is like a massive sort of like burden on the companies to educate. And you've seen it like, you know, over and over. And in our case, you know, you want to make sure that people like know what they're getting into. They're not like overextending themselves in terms of like how much they're sort of trading. They're not like getting into an area of discomfort. And how do you kind of like, you know, we can do as much as we can do on the marketing and on the product side. But like, we need policymakers and regulators help to basically make it an industry standard, but also help us elevate ours. And by the way, we're pro that I think that like even the classic retail brokerages should also be adopting a lot of these customer protections that we're talking about that they don't. And I think that every every retail trading platform should be taking a lot of these steps. So yeah, I mean, that's sort of our general view. And we hope that this is sort of the direction that things take because, you know, there's kind of you can have a variety of views. Right. And some people believe that like, hey, like, you know, any type of speculation should be banned, whether it's in the stock market or crypto or prediction market. We don't believe that like, you know, we think that would be a bad outcome for all the reasons, because there's a lot of upside to having liquid markets and a variety of different things. But also because if you ban it, you're actually heightening the risks that you're trying to prevent, because now that activity is going offshore. Right. Like and where you cannot monitor it or police it or do anything to protect it. Awesome. Well, thank you guys. Thank you. That's fine. 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