Transcription
Today. If you want to have an accurate long-term pricing of S&P or home prices or or the jobs market, you have to have a very good view on AI. You have to have a very good view on politics and the way it's trending over time on geopolitics. Luckily, now we have a way to do that, which is prediction markets. You can actually capture each one of these dimensions independently, price them, get efficient pricing for each of these and then feed it back into our traditional asset prices.
Where's the future of markets? And we'll talk about AI in a sec, but very core level for us to move from AGI to ASI, we're going to have to take all of the data. I mean, literally from everything.
There's an incentive to be a super forecaster. Uber created an incentive to, you know, take your free time and go get people from point A to point B, which is very valuable. We are creating an incentive for people to go and seek out truth in the world. And it's amazing because like today we really have the largest community of these people, and that community is growing over time.
Hi, I'm Ral Pal, and welcome to my show, The Journeyman, where we travel to that nexus of understanding between macro, crypto, and the exponential age of technology. Now, I'm bringing back somebody who's become a lot more known than when he was first on Real Vision. He first came on Real Vision, I don't know, 2020, with this crazy idea that he was working on and had just launched a company called Kelshi. And the idea was prediction markets where you could start to predict not just where markets are going, but all sorts of things, whether it's economic data or political outcomes. And we talked about it back then, and it was a fascinating idea. I think he'd been on Real Vision a couple of times actually, and TK and I, I thought, God, that's a tough job to get it through all the regulation and do something, and he got there and built Kelshi. And Kelshi is an extraordinary success. He's a great guy, really thoughtful, and we really riff a lot on what this all actually means for markets, market pricing, how the power goes back to the people, how super forecasting is a new opportunity for people that they haven't realized, how companies can use this to tailor their risks. It's a much bigger thing than you imagine, and their entry into crypto and per has been another explosion. Super fascinating, very much aligned with where Real Vision is and where we're going. And I think you're just going to really enjoy the conversation with TK from Kelshi.
Join me, Ral Pal, as I go on a journey of discovery through the macro, crypto, and exponential age landscapes. In The Journeyman, I talk to the smartest people in the world so we can all become smarter together.
TK, my friend, good to see you back on Real Vision.
It's great to see you all. Very excited to be here. I can't remember when we, when you actually first came on Real Vision. It was maybe 2018, 2019.
It was, um, it was a while back.
That's when you first came, and you've been on two or three times, I think.
'21, maybe 2020. Uh, but yeah, it's been, we, the first time I came, I think it was really very early in the journey. I mean, we were really getting started, going through the regulatory, figuring out how to kind of exist, really.
I remember talking about it, thinking, how the hell are you going to get this? How are the exchanges going to allow this? How's it all going to work? 'Cause it was a brave bet.
Yeah. I mean, some of these things take a little bit of a, you often have to take this sort of asymmetric, you know, pretty asymmetric, and and and and, and you have to be willing to basically take the time. I mean, sometimes these things take a long time.
And stressful?
Stress, energy, time, a lot of faith. I mean, you have to basically have a belief in the thing that you're doing for a long period of time, even though a lot of people, you know, may not, uh, may not see it for, for not necessarily are negative about it, but they just may not see it. Uh, but here we are, you know, mix of luck, long, a lot of energy, a lot of time and dedication.
So let's go back and hear your story and the story of Kelshi, because, you know, I love for people to kind of anchor on the whole thing, because it's, it's all part of something bigger, not just where you are today, but how the hell you got here.
Yeah.
So what was your background first? 'Cause you, like me, worked for the evil empire of Goldman Sachs, I believe.
Oh, yeah, we did. We did. Uh, I don't usually talk about this, but I realized with tiny, this was actually a very important, uh, piece of my upbringing. But, you know, I was born in California and, and I grew up in Lebanon. Uh, and there were sort of two things that led to kind of, I think, foreign be is is is one, growing up in Lebanon, two, growing up with a single mom. And, um, what I, what I describe the environment, I describe it as a very volatile environment. You know, um, Lebanon has a lot of good and bad, both, and, and the, the uniqueness of Lebanon is, it, the good and bad can happen, um, in the same hour. You could be, and, and, you know, everything could be fine, you could go to bed, and vice versa. And people got very, the word is, you got very adaptable, like you could sort of mold yourself into a shape-shifting landscape pretty, pretty consistently, which later I learned is actually very important, uh, for being an entrepreneur.
Um, but then that sort of volatility, I think, led me to really love math. I, I became really obsessed with math because, you know, I, I think the best way to describe it, math is elegant in the sense that there's an answer. It's a closed form system that you can control. You can butt your head with the thing, and there's right or wrong, and, and it, it sort of helps you avoid the vagaries of real life, which is usually complex and messy, and, you know, there's, there's mostly no, no, no answers or no clean answers.
That led me to go to MIT. And then at MIT, you know, the math people were going, uh, uh, to the evil empire of Goldman and, and, and a bunch of other financial institutions. But, you know, Goldman was, um, was also formatted because in 2016, and, and, you know, I had discussed this with you when I, when last time I came on the pod, like, you know, the interesting thing is, like, if you look at financial history, a lot of markets started as, actually, it's interesting. You know, people talk about, oh, institutional markets, they have gone retail, but actually, the, the direction is usually the opposite. A lot of these markets to start as retail markets, like, you know, the, the first types of equities markets were started existing to give access to people. That was really how, how it started. And you can make the same like FX and, and liquid, even derivative, like commodity futures, like the grain, I mean, the farmers were retail, right? They were not highly, sort of instrumented institutions at the time. And what Wall Street did was essentially, when, when you start adding regulations, all that, it was essentially adding barriers to entry and, and complexities, like, like added complexity that is often times unnecessary. You know, it's like if something is called a
Because they can capture a gatekeeper premium by doing so.
Exactly. I mean, if, if something is called a credit default swap, and there's a bunch of regulations around it, also you need the wealth advisor, who needs a trade executor, who needs, and then now, you have a chain of five people that are basically eating a piece of that transaction. And what's interesting is, you know, the natural demand that we were seeing at Goldman was very simple. It's like, is Brexit going to happen or not? Is, is Trump going to win the election or not? And, you know, I tell this story often because it's so striking. The Trump trade was essentially a short on the S&P, and you can play out how that went, right? People were right about the prediction, and then they lost money.
Um, and so this idea of, you know, what Kashi is at the core, prediction, but, you know, I mean, we've seen prediction is really our act one. Now we're getting into perpetuals. I mean, the long-term vision is building the exchange that can house a much larger, broader set of financial instruments where people that people relate to, like take out all the complexity, make the instrument tied to the position.
Because almost all bets are second derivative of the actual bet you're trying to take.
Yes.
And that's that, all that, you know, yes, that leads to opportunity, but it's also more complicated than it needs to be. It's, it's noisy and it's imperfect, right? Like most views, a lot of views right now are exercised indirectly. There's always a layer of indirection. You know, even when people basically buy and sell stocks or stock options, like often times like I think earnings is going to overperform, or I think Elon is going to, you know, leave or stay, or there's all these factors. You can decompose a lot of these traditional financial instruments into specific factors, and it is too obvious. Like obviously trading the factor that you're really thinking about is the better answer. It's cleaner. It's less noisy, and you take less basis risk, right? Like less risk of your opinion being your opinion happening, and then the thing actually not capturing it.
Um, and, you know, you might be interested in this. You know, there's a paper from Kevin Hasset, who's, uh, who's currently in the administration in the economic council, and he, uh, uh, wrote about this idea of infinite markets. Have you ever read about this?
No.
It's a very interesting idea, but, but the idea at the core was basically society needs infinite markets for us to keep being efficient allocators.
Yeah.
Because so, so here's kind of one simple way to think about it. So today, if you want to have an accurate long-term pricing of S&P or home prices or or the jobs market, like some of the big indicators that we have, you have to have a very good view on AI. You have to have a very good view on politics and the way it's trending over time on geopolitics. And luckily, now we have a way to do that, which is prediction markets. You can actually capture each one of these dimensions independently, price them, get efficient pricing for each of these, and then feed it back into our traditional asset prices. Otherwise, the entropy is going to essentially grow over time because, you know, we are not, we don't have a good view on the on the on the legs of this tool.
Yeah. Yeah, because market pricing brings coherence, and that's what gets you around entropy, and is the signaling of pricing is actually one of the crucial factors of how to allocate any resources at all. People kind of don't realize how important price is, but price is almost everything.
It's, it's pretty much the only way, actually, right? Like, you know, the, there's an economist, Frederick Hayek, in 1945, at the end of World War II, and called, he talked about the knowledge problem. He's actually, in some ways, the inventor of prediction markets, or, or really this idea of using markets to gather information. But, and the knowledge problem was basically, look, most decisions are made centrally by a government or an executive team in a company, etc. But the information that's relevant is distributed, and it's often times dynamic and localized, and you need a way to surface it somehow, and market prices are the, the proven most effective way to do it. Open a free market on the thing, and then information will basically trickle up. And, and that is a profound idea. I mean, at the time, he called them information markets. Um, but it all goes back, you let the free market allocate or price something, and then that will be a better gauge than essentially any of the other gauges that you could use, because the incentive is very clear. You be, you're right, you make money. You're wrong, you lose money. And there's also something else bigger than that, and I think we may even talked about this last time, is the book Superforecasters, right? That was really instrumental in what I wanted to do with Real Vision. The whole idea is, if you educate a group of self-selected educated people, but experts in other stuff, not the thing you're looking at, they tend to outperform the experts once they have enough time to analyze it. And, and that has struck me as a really powerful idea, and it's proven time and time again that super forecasting, and it's essentially what Kelshi's done is create the ability because if you think about it, the economic data was always forecast by 15 people on Bloomberg.
Yeah.
But that is not a super forecaster, because they all have their own biases inherent in what they do for a living. But once you take super forecasters, which is anybody who wants to do the work, the amalgamation of that price is much closer to the truth than the experts are.
I mean, it's pretty incredible, right? So, so Tetlock's work was foundational because it gave a practical guidebook for how this can be done. And I think it's exactly what we said is also very profound because it's a pretty counterintuitive finding that domain expertise is not an important dimension.
That's right.
To predict where your domain is going. Like it's, it's, I mean, if you think about it, it's pretty crazy, right? Like, and, and now I think fast forward to like, what we built, the largest community of super forecasters.
Yeah.
Or want to be super forecasters, which is good, because over time you're training more and more, because these people are not say,
Because it's a built-in incentive mechanism. Money is the incentive mechanism that increases the quality of the output of the super forecasters.
Yes. And it also, now there's an incentive to be a super forecaster. Uber created an incentive to, you know, take your free time and, and go, you know, get people from point A to point B, which is very valuable. Uh, we are creating an incentive for people to go and seek out truth in the world. And that, and it's amazing because like today, we really have the largest community of these people, and, and that community is growing over time, because more and more people are graduating from, you know, hobbyists, or they do it for out of interest or fun, to like, you know, doing it in a more systemic way. And what we're, we're at a point where right now, and, and we should do this over time, you can ask any question from the system, like, you can send us a question that you're curious about the future, and they price it very, very quickly, the community prices it very quickly, um, and it will be more effective than any other alternative. Um, and, and this is the thing that excites me, and at the time really excited me when I started in 2018, because the, the country and the world, I think, is extremely more about like, it's going in, and the current direction of travel is polarization, bifurcation, extremism, um, you know, on, you know, social media has kind of fueled it. Like, if you, if you have a reasonable, down the middle take on, on, on, on social media,
Nobody's interested.
Nobody's interested. Say something crazy, and, you know, everybody's interested because it's clickbait, it's, it's, it's in, you know, and the opposite incentive structure works in prediction markets. That boring take in the middle makes money.
Yeah.
The one that is too opinionated, too extreme, too passionate, generally loses money.
Yeah. The tails are not, I mean, sometimes tails mispriced. Generally,
Because of normal distribution, generally the tails are, you know, generally you don't make money trading on the tails. If you do, that's when the real money gets made.
That's exactly right. But in, in this case, it's more, well, that's exactly right. But, but it's also even, I mean, you look at, in the sphere of politics, right? Like the, the, it, you know, one of the things that we released recently, I don't know if you saw it, the Kelshi American Power Index, KAPI. And it, it's basically the division for this to be the S&P for politics. And, and, you know, today, if you ask basically 10 people, hey, where do you think the country is headed? They'll be fully bifurcated, like basically based on what their social feeds are are are feeding them. And you see different Twitter feeds for different people. I mean, you know, one person will, you read their Twitter feed, and it's all like, you know, the Republicans are like crushing. The other one is the Democrats are crushing. And, and, and the vision behind that is like, well, we have all these prediction market data that answer discrete questions, which are, you know, who will win the election, who will win the Senate seat, who will win the House, etc. What if you take all of them, you know, win each, like the for each seat, and the margin of victory for all of these across the Senate, the House, the Supreme Court, the presidency, and aggregate them into one index that moves between plus 50 Republican, plus 50 Democrat, and oscillates between them over time, and then have it be a measure, a very mathematical measure based on, you know, the prediction of where the country is headed. And it actually works incredibly well. I mean, we backtested it. You see this year, you know, in February, March, started tilting Democrats at the peak of the Iran war. And then when, when, you know, the Virginia redistricting and, and the ceasefire talks have started, basically, we started leaning back a little bit Republican. But I want us to go more towards a world where we listen to markets and math more. We, we think a little bit more probabilistically and less binary about the world. But one of the issues we have is time horizon, because, you know, we saw it with the Iran war, we've seen it with various things, even with the Clarity Act, right? The market prices, it's not very good at pricing things with a certain time horizon in them. And I don't know if that's the setting of the question is not correct, in which case you've got a futures market that actually correctly prices, like an oil curve does, because it still still seems to price on current day news flow and people reassessing the odds as opposed to that slower moving longer end of the curve, which I think is going to be super valuable, but less people are focused on it yet.
Yeah, I think that's exact, I mean, that that's a very interesting question. You think about this a lot. I mean, you know, for example, for the Clarity Act, the bill passing now, we create, we sort of created a curve, so it's like, will it pass by each of these dates? So they can figure out, you know, is it going to be done by the summer, the fall, you know, next year, all of that. And, and because it's a little bit, sometimes you don't exactly know what's the natural expiry of something. Like now, election is easy because you know when it's going to happen. And that's the, but that's also why I'm say about perpetuals, and we can talk about it in the context, because some things don't have a natural expiry.
That's right.
Right? Like some things, you know, and, and we could, I'm sure we'll get into talking about perpetuals, but maybe just one point about that. Like, when Robert Shiller started talking about perpetuals in the '90s, the idea was like, look, some some underlyings have a natural end date, right? Like if you, if you're buying pork belly, that, you know, will expire at a certain date, and you're going to have to deliver it physically. And so the future has to have an expiry. Now, some things don't have a natural expiry. It's, it's kind of an arbitrary date that people are picking. Those should just basically stay open as long as basically the person wants to keep it open until the, you know, their opinion expires, like they want to cash out or close out the position, and they can do that. And, and I'm very excited about that because I think a lot of these more hazy questions that don't have a natural end date, I think will fit a perpetual structure better than, let's say, a future or prediction market structure, where like the, the answer is discreet at a certain date.
The complexity is adding in an unknown time horizon to an unknown outcome.
Yes.
I wonder how people will do with that at first, because it's kind of a whole new skill set to learn. You know, some people think like this naturally, like it's a macro person's general way of thinking. So, it's, it's quite intuitive to somebody else, it's not intuitive at all.
Yeah. I think like there's going to be a few use cases. I mean, look, I, I think like, if you talk about like, if we're talking about Bitcoin, per example, like I actually think that product is very simple, and that's why we're seeing the traction we're seeing, because, um, people think, look, I think Bitcoin is going to go up for some time, maybe sometimes they don't know exactly, you know, this month, next month, but for now, I think it's going to go up, and I feel good. And, you know, at some point, they're like, they don't feel, they feel like that that position, that view has materialized mostly, and then they can exit that position. So that's a natural, I think that's actually more natural than futures, because most people don't, I think Bitcoin is going to go up until end of July, right? Like they, they don't usually think.
And you don't have to, you don't have to add in dividends and cash flows and all the other stuff that makes the future more useful in some respects.
Yes, exactly, exactly. I mean, and often times what's happening right now is people that say, if you have like a six-month long view, you have to buy the monthly future and you have to roll over, so you pay fees six times.
Right. Perpetuals are just a better fundamentally a better product, and that's why they're so popular, um, outside of America. Like they've been very popular, and in a bunch of other jurisdictions. I mean, Hyperliquid, Finance, all these companies have done a great job. Um, so bringing them onshore was kind of an obvious, um, obvious next step. It took it. It's crazy how long it took. You know, he talked about perpetuals in in the in the '90s, and it was like, and now they're coming back, and it started with the crypto industry because, you know, and you probably have covered this a lot, but the crypto industry takes these incredible economic concepts and actually makes them a reality, a practical reality.
And, [clears throat] speedruns them like no other industry because of the behavioral incentives embedded in crypto. They speedrun everything to a breakage point, then learn what broke, and it gets rebuilt from that. It's an amazing process. It's, it's pretty amazing, and, and it's also, I think, just the nature of people that are in this space, they're just frontier, they're the frontier, they want, they want to tinker with things, they're interested. And, and I think that's what makes the, you know, it took me a while. You know, Kelshi didn't really start as a crypto company, right? And, no.
And, and we don't really say we're a crypto company now. It's interesting because actually our fast-growing category is crypto. People think it's sports and other, but crypto has grown 25x since the beginning of the year for us.
What? Why?
I, I look, I think a few things. I mean, a lot of people, especially when markets go one way or the other, you know, trading the spot gets much less attractive in a down market, whereas trading the derivative is much more interesting because you could have symmetrical views. You're really thinking about where things are going rather than like, I'm, I'm just long Bitcoin. And as the market matures, that's going to be, you know, the derivative market inevitably gets bigger. Um, so, so there is that. I think, look, perpetuals, the, the launch has been, I mean, it's the fastest growing product we've ever had. Uh, because, um, one, it's regulated in America. The people, what we've seen always, I mean, our playbook is, we take something that's generally in a theoretical thing in economic circles or offshore, like proven demand offshore, and we bring it in a regulated, responsible, safe way with the traditional regulated structure in America, uh, to make it, to make it go mainstream. And I think we've been very successful. Prediction markets, I think we're seeing the early success of perpetuals because I think, you know, a lot of Americans, like they prefer having the oversight, right? They prefer having a regulator they can call if something goes wrong. And, and I believe in that sort of division of roles, like I, I'm the operator, and I have someone overseeing me, making sure that I'm not overstepping, which I think is a good thing. Um, and, and, and I think specifically perpetuals, I think they're simpler. They're very accessible. The lower fees are very important. So anyone who trades futures now, it, it doesn't make much sense to keep trading it with with the rollover fees that you're paying consistently. And then a short and a long are symmetrical, right? Whereas it's kind of hard to short Bitcoin otherwise, especially for retail participants.
Where do perpetuals just grow to everywhere? One thing humans love is leverage. They love sex and leverage more than anything else. And, you know, perpetuals are leverage as well.
Yeah.
So you give them leverage, which gives them a different ability to price risk return. Okay, great. But obviously, some people are not very good with using leverage, but we have regulation for that. And, you know, certain responsibilities. But how far does this go?
So a few things. One, comment on leverage and sort of the principle that we we abide by. So actually, our perpetuals don't have more leverage than the traditional futures that the incumbent exchanges like CME and, uh, uh, list. We're using the same traditional and boring risk methodology. There's nothing new about that, and I think that's important. And, and, and maybe putting aside the regulatory, like, how do I think about leverage? Look, there's things that have inherent amount of volatility, you don't want to use too much leverage on that because then you may take it to an extreme. But things that don't have enough volatility, you want to get them to a baseline leverage, so it's actively trading.
You want to kind of normalize volatility.
Normalize volatility is the exact term, right? You want to normalize volatility. And, and I think people don't think about that enough, right? That's why sometimes you see people that like 200x leverage. I think that's too much. That's that's, you know, they're taking things to the extreme.
Well, that might work in European futures, I mean, SOFR futures, right? Which don't move.
Yes. Yes. That's exactly right. That's exactly right. And, and I think the, as something we think about a lot, like there's a few things that are, there's a few structural complexities. So, for example, if you look at agricultural products, the community itself, the farmers and the act committee, is not ready for 24/7, and they're not ready for, um, perpetual structure. And, and we, as a, as a company, we're kind of respectful of that, because we understand why they could be very anxious about volatility during the weekend, coming into Monday. And, you know, these are products that are touching like food security and, and, like the farmers. So I think we're generally careful with, uh, those types of products. Now, there's other products that, like, there isn't that sort of natural, like, I would say, like counterargument, right? There isn't, I mean, the counterargument is usually in comments saying, look, uh, this is bad for XYZ, and reason, but what the comment really cares about is, you know, making sure there's no fee competition. Like a lot of people that list futures don't like perpetuals because the rollover fees are 20% of revenue. So, you have to, you're going to end up having to kill that revenue with the perpetual, uh, competition. That's something that, you know, I'm personally don't think about much, like that's not my job. My job is, you know, compete in the open field. So, so hope over time, I think anything that's open-ended, whether it's equities or FX or or some types of energy, etc., I think they should end up moving to a perpetual structure. I think it's inevitable.
What about the old kind of, it was very common in the UK with spread betting markets, because you can take one football team against another, and with perpetuals you can do that in perpetuity as opposed to over the season, which is a kind of interesting idea as well, that doesn't exist.
It's a very interesting idea, and I actually, I mean, look, I, I think there's differences because I think the one is an OTC market, one is an on-exchange traded, and I've always found those to be different. And I also, I think they should be regulated differently, because in one of them, there's a house, and the house incentive is basically to win as much money from the customers as possible, right? Like the, the losses are going to the house, and vice versa. And yes, there's a vig and spread, but in what they do is they limit the winners, people that are very good at it, and they, you know, they promote the losers, whereas I think an on-exchange mechanic is more truth-seeking in nature, better pricing, right? Because you want the sharps, you want the smart people, you want the hedge funds, all of that. But the thing that you're talking about is very interesting, which goes back to Shiller's idea in the early days. So when he, he outlined a few examples of potential perpetual futures. So one is real estate.
Go long a city, go short a city.
That's right.
Makes perfect sense.
Index stuff.
That's right.
Makes perfect sense. You buy a home, you could basically hedge some part of that home. It's, it's, it's pretty amazing. Number two is human capital. So you could like structure a per on your future earnings and how well you're going to do.
I thought about that because tokenization is quite interesting when it comes to future earning streams. You could take a basket of people from MIT. You could short the basket against Harvard, let's say, or Stanford, whatever you're betting.
I like that trade. I like that trade. You can take a bet on a group of people and their future economic outcomes, which is a way of kind of creating an ability to, let's say, pay off student loans in advance, or whatever it may be. It's kind of interesting.
It's interesting because I think all of this goes into the bucket of efficient risk management and efficient resource allocation.
Yeah.
Right. It all goes in that bucket because markets, what they do is they add more transparency into any process.
Yeah.
Right. And you can apply it to anywhere. Like, how is insurance sold today? It's like, you, you call, you, you call, you know, the big boys, and they give you a price. You don't know how that price was done, and they get their premiums. Put that on a market. All of a sudden, everybody's competing out in the open. Everybody can see it. It's transparent, and then the pricing gets better. Everything gets more efficient, right? And so there's a lot of potential in that over time, in terms of having a real-time pricing on a larger number of things. Uh, you know, one, one example is, you know, I think a lot about, and one of the things I'm excited about right now is, is, uh, uh, the, the biotech companies, like FDA approval processes. And I don't know if you've looked much into that, but, you know, it, it, it, it's amazing how like 95% of these companies fail, and they get funded for so long, uh, uh, honestly, unnecessarily, often times the CEOs have a lot of sales leverage, and they're charismatic, and they can, you know, kind of milk it for a decade. But what if we had an efficient market that predicts the, the, that predicts whether a drug is going to succeed or not, right? Like, all, all of a sudden now, the leverage that on sales is much lower. You have a market that'll say, "Hey, like, it doesn't look like this thing is going anywhere." And it's also interesting for the patients, because the patients, the only resource they have right now is the people that are selling them the drug for their clinical trials. So obviously they're self-interested in like pushing the drug and so on and so forth. And, and, and I'm thinking a lot about what if we could structure a market in the right way that tells people, and look, you don't have to trust the market fully, but it's an additional data point where where this thing is going and how it's progressing. Um, and imagine applying that to a lot of other, like, basically everything.
The other thing that I've been sort of fixated on when I step away and think about where's the future of markets, and we'll talk about AI in a sec, but on a very core level, for us to move from AGI to ASI, we're going to have to take all of the data. I mean, literally from everything, right? Humanity scale data. And the Ribbit Capital article from, uh, Mickey, uh, Maler and the team, you know, he sent it to me beforehand and said, "Hey, can you critique this?" And I looked at it and thought, that is brilliant, this token factory idea. And then I just said, "Well, but Mickey, surely this is just a gigantic invisible marketplace of all of the information, because the agents are going to buy it, and they're going to have to price this stuff, and it's going to be valuable, whether it's for universities or individuals selling our data." And I just think there's something in what you're doing that relates to that, because that is going to be of a scale that we can't imagine. It's not the, you know, couple of quadrillion that the markets, financial markets are now. It's probably much larger, because the stakes are much larger, because it's civilizational scale intelligence, and therefore, um, you know, data becomes extremely valuable, and we don't really have a data marketplace.
I agree with that. I mean, the idea of a data marketplace has always been very interesting, and, and I think markets could actually help with a lot of that, because you, you, markets are a way to surface and summarize data. I mean, I always say it's interesting, we're in a world right now where we, we don't have a scarcity of data, like information is so abundant, uh, that actually we're at a point where like synthesis is becoming incredibly difficult. Like that, that's actually the, the core bottleneck to surface insight and truth and all of that.
Yeah. Compression is everything now. We can.
Yes. And markets are actually a way to compress.
That's right.
Right. The most compressed single thing down to a single point in time. It's, it's coherence down to compression down to one moment in time with all information available.
That's exactly right. You're getting one, you know, uh, uh, one number, right? And it can be represented with like, you know, it's between zero and 100. And it's like, actually very simple to digest, and, and, and it's effective. I mean, you probably have seen some of the calibration plots. The Fed put out a few, the Federal Reserve put out a few a few months ago, and, and there's some reporting on it. Like the calibration plots are near perfect. It actually works. Like it is an extreme, like when we say something has 80% chance of happening, it basically ends up happening 80% of the time. It's like pretty amazing. And so the more I think about it, the more it's interesting. I, I think part of why, I mean, one stat that's very interesting here is, you know, out of our active users, close to 80, more than 80% doesn't trade. They just look at the, they're coming in to use it as a newsfeed, and they're looking at the data, because I think you're in, in a world where like, there's all these news articles, and people on TV saying things, and politicians saying things, and Twitter is sort of like, you know, bunch of echo chambers that depending on where the algorithm takes you, and, and you don't even know what, people don't believe things they read anymore. Like, people don't believe anything anymore, right? And so, and this, this idea that like, I mean, they come to what they do is they read the headlines, or they read things.
Yeah. You become news. You become a source of truth in a world where nobody understands.
They become news with money, be with money, where people have skin in the game, and they get punished if they say stupid things, right? Like, it's attacks on, and, and it's increasingly hard to find that. And, and I, and I think that is part of the propeller of prediction markets of the last few years. I think when, when I think a lot about what, how did they grow so fast? I mean, right now, this is the fastest growing, uh, uh, industry. I think we're the fastest growing company outside of Anthropic right now. And, and I, and I think the reason is, is is that I think this idea that people are seeking better ways to filter information, because they don't really, like, we're getting overloaded with everything.
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And how, so I mean, there's, when you break down a market, there's a lot of different component parts, right? There's people making instantaneous price decisions. Let's call those market makers, high frequency traders, who are using algorithmic approaches to try and price this stuff. They're all learning because it's relatively new for everybody. So, you know, the market's quite inefficient. So, I'm guessing there's supernormal profits available for those who have better algorithms and stuff like that. And we've seen that in financial markets in the past. We've got the individuals who come in, who whether they're super forecasters or non-super forecasters, who are creating price points because of their reflection of that. How do we, again, I keep going back to the old macro issue of, sure, price is correct today, but the deterministic path to the future is where the money's made.
Yes.
Unless you're a market maker, in which case it's today's price.
Yes.
You know, can I take the bid from TK and, you know, offer it to RA and make a spread? Okay. Yes. But the real money is to be made actually on that deterministic path and the probability forecasting of that.
So when I think about the, so actually the, the, the people that are winning, you know, on on Kelshi and winning big, it's a, you know, it's like any competition. When you think about financial market people, people always ask the question like, well, is it 50/50 or people that win, lose? And the answer is no. If it was the case, then it would be a random like game of chance, right? Like, would it make, there's no skill in it then, right? And, you know, it'll be like, I don't know, we create a league like the NBA, and then, you know, we pick, we randomly pick who's going to win the finals at the end. That wouldn't make any sense, right? There's the small, it's usually like a small percentage of elite athletes, in our case, intellectual athletes, forecasting athletes, that end up being very good. The incredible thing about it, though, is not the usual suspects. It's not the fancy institutions, etc. It's these people that have spent 20 years, you know, unbiasing themselves and being calibrated and think very critically about the word, and, you know, if you try to create uniform characteristics between them, it's very hard to find, you know, across gender, age, uh, uh, income levels, Ivy League, no Ivy, there's no clear patterns.
Which is super forecasters was the same, right? It was.
It's the same. It's, it's beautiful. It's actually beautiful. Some random curiosity gene that they have that allows them to do this. Well.
Yeah. And some people, and some people train themselves too. Some people.
What about this idea of, because you said something interesting is the, the kind of super forecaster athletes, the superstars. I wonder if there's something bigger in that where you can back the superstars.
Yeah. People, and a lot of hedge funds ask us for the list and never share them. And, you know, but some people are really good at it, and, you know, and, and they get rewarded for it. But, but these people, to answer the prior question, the way they think about it is fundamentally, they're, they're, they're essentially trading value.
Right. They, they, they're not taking directional positions. Often what they're doing is, what is my fair value? I think this event has a 65% chance of happening, so I will buy it for anything on 62% and below, and I will sell it for anything at 67% and above. And that's that exercise that the market is constantly doing, and a lot of super customers are doing are the thing that brings it back to fair value continuously, right? And, and you have a lot of these. This is how the most kind of effective people and the people that are doing the most amount of volume do it. And yes, some people do it maybe with with less research, or they put less effort, and some people do it for fun. Some people do it, you know, for arbing between different markets and all of that. But that motion that I just described is the most important thing to get the calibration that we get. And they've gotten really good. It's like amazing. And, you know, for example, one of the traders, I mean, we had a bunch of traders that had bought it, but that's still trader Domer talks about publicly. He bought the pope who was at 1% on Kelshi, uh, the American pope, the who ended up being elected or chosen. And, um, you know, he didn't think he was going to win. He just thought 1% is wrong. He thought, and he described a lot of the process where like humans, they don't generally intuitively understand the difference between 1% and 10%. They have dramatically different. They're dramatically different, uh, uh, uh, risks, and we should treat them dramatically differently. The same way I think we fumbled COVID a little bit because, oh well, it's a, it's, we thought of it as a 1% event. I mean, this, the whole goes back to the fat tail thing, right? But it was not a 1% event. That was clearly a 10 to 20% event, which should have been incredibly alarming back in December of 2019, right? And, um, but some people are so good at it, and, and, and I think you want to figure out how to get more and more of these people, incentivize them to do what they do best. And, and, and on Kelshi, they've gone from being hobbyists, they would do it like, you know, hidden from their partners or something at the beginning, then the full-time job, then now they have companies dedicated to doing this, which I, it's part of what I find fascinating, because, you know, you have a huge community that's incentivized to truth-seek, that's basically they do as a job.
It's also interesting to see how biases stick over the probability distribution curve. Because like after 2008, everybody bought tail risk hedges for like five years.
Yeah.
Right. And you always had that left tail was overpriced.
Yeah. Yeah. Yeah.
So even with a huge market like whatever, whatever you were using the tail risk hedging in, that still maintained for a long time. It left a lot of people the ability to sell puts.
Yeah.
Or, you know, calls on.
Whatever it was. You know there's different ways of of expressing that trade. But it's interesting how biases stick in even with giant markets.
They always exist, right? Right. And there's a lot of people that like are are in the business of finding these biases that exists in the market and and then trying to counter them like buy the pre like sell the premium basically sell whatever bias premium exists. I mean one of the biases we always see there's always a yes no yes bias versus a no buys. People just like saying yes more than no. So you always see more natural flow which is a good thing. That's an optimistic thing for society, right?
And uh but then um there's one interesting phenomenon that actually Kevin Hazard also wrote a paper about and it was in theory. He had actually wrote a mathematical proof about it and then we see it in practice today. So that calibration plot that I discussed has a little bit of deviation around 50%, 45 to 50%. It it deviates a little bit and and that paper what it argued and I think we show it in practice now 5050 actually means one of two things. Usually it either means that people really believe it's a 50-50 event or it's a high entropy event. We don't have much information.
Yeah. They can't price it.
So we naturally like when we don't understand something very well, we naturally go to 50/50. But that that doesn't actually mean it's 50/50, right?
we just say, "Well, I don't know. It's 50/50. I don't know. It's usually equal to 50/50." But that's that's usually not right. That's a human bias.
Oh, that's super interesting. And we see in the markets 50/50 is where like when we say something is 50/50 we're the least accurate doesn't end up having 50 max and makes total sense. That's fascinating. So how as you keep rolling out new products and new prediction markets and new ways of doing what you've built. How do you find the liquidity for all of this? Cuz I mean you've got to be a huge liquidity suck because you need a lot of pricing. I think this is why the you know there's obviously the regulatory journey we had to go through that was a very long one to to get to where we are but the second challenge is really like liquidity it's it had marketplace it's a marketplace right you have a supply and demand problem now financial exchanges have a uniquely difficult marketplace problem because um um you know like the the analogy I like to give is like if you're on Airbnb and you you find a house you're good you you got a transaction you're good and adding more houses to Airbnb is not going to make you transact more. Whereas on a financial market, adding more houses, adding more liquidity will will also make you transact more. So, so you get like multiple second and third order effects of lack of liquidity and of abundance of liquidity. So, it makes a very hard problem to get rolling. But when the ball rolls, it's much easier. And and I think it took us a very long time to get that, you know, ball to to kick. But now we have enough of a large community of market makers and super forecasters and active users that put limit orders that it's easy to point them in different directions. Um because you know they make profits in a variety of different things in in our markets like crypto or sports or politics. But if you have an interesting question about AI, we can point them in that question and then they can price it pretty effectively. And that's what happens with scale. You can start playing with incentives. You can do a variety of different things to point people on the things that you want them to to trade.
And what about all of the competitors who've come up? Do they grab liquidity or add liquidity overall? UK arbitrage markets or I mean you're so much of a monster in the space in terms of size, but you know, let's see how it develops in 5 years whether it broadens out or not. Who knows? Maybe not.
Yeah. I mean, we're over 90% market share now and and it's going to it's going to reduce a little bit over time. It's inevitable. I mean, right, it has to. And that's a natural uh course but but what we found I mean it just it's it's a bit like crypto you know people always like oh there's so much competition but like I mean liquidity begets the credit of this markets it's it just that's by far the strongest force and the driver and so I don't think we're anywhere near the level of saturation or maturity of the market where like you know you're going to start seeing like cannibalization across people like um I think you're going to see competitors come and innovate new do new interesting things that will push our boundary and our understanding of these markets and and that's why I've always like I think being in a big market with a lot of competition is is very good much better than being in a smaller market with low low competition much much better. One of the things that we've been thinking about at Real Vision for a long time is okay, we all agree on the rise of the super forecast. We also agree that retail has been empowered finally to and crypto markets were one of the key drivers of that that pushed everybody forwards and opened up everything. And part of this is now me thinking, well, what we can end up doing is turning anybody into a hedge fund without all of the the complexity that goes with it. And [clears throat] therefore I could buy a tar token that gives me an economic representation of your performance. Right? That's collapsed everything from being Millennium with the regal legal regs the operations the capital allocation risk all that goes. I can now have 50 pods of people. And this is what we're thinking through for real vision is like, well, we could have 50 pods of real people that we can then allocate in real time to depending what time horizon, what risk profile we want. It collapses all of the structure of the pods at Millennium. It collapses all of the structure of the mothership of Millennium. And that applies to all asset management. And then you're adding in even more to that, which is like, oh, and here's a gazillion new instruments for people to express it on. I mean this gets very very interesting very fast to the future of what is asset management not just trading where you are today. I think asset management is upstream of everything.
but performance excellence right I mean you know there was a I forgot which news publication last week they sort of called it or apparently I mean I don't remember but or either I said it or they were quoting me but they called it like this idea of the rise of the new Wall Street like we're building a new Wall Street and and and
and I think what what you're getting at is exactly what I think this means when you broaden out the universe of instruments you're broadening out the universe of where people can play and win can participate and win right Because a lot of these our customer you ask them like could you go and trade on like traditional like S&P options today and they're like look I think there's no way to beat the information asymmetry with the hedge funds is impossible but I can win in forecasting inflation I can win in forecasting politics sports culture you name it all these instruments that like there is no reason for the Wall Street incumbents to have a natural edge and actually we're seeing in our data this is what's so amazing like our best inflation forecaster is a random dude in Kansas and he he's he's unbelievable like you know is systematized is he kind of AI driven or has he intuitive?
He doesn't share much. It's pretty but I think he's he's just been reading the news about the company for a long period of time. He's become very effective at it. He's become so good at it. And and when you broaden out the universe, the aperture of what could be participating, you take out all these kind of gates, make it simple for people to get started and do it, you're seeing a rise of much larger number of people that like are actually very competent and you know, you see like thousands of people that have become small pods like you described on Koshi that generate incredible returns basically truth seeeking like doing the work that they're doing and they don't need much. They don't need all the infrastructure that you mentioned. They don't need a lot of leverage.
Could they run capital for other people? I mean that's the interesting point
over time it's happening they're raising could it be a marketplace of super forecasters
that's what's in my head and that's what we've been working towards with real vision as well because I I think unbundling and unbundling is a kind of core driver of the universe and yeah you know what we need to get to is the unbundling of all of this all over again because we've now got the tools to do it we couldn't do it
agreed unbundling a lot of Wall Street I mean a lot of people are funding and like a lot of our some of the customers that have kind of graduated to becoming doing this really full-time are raising money, external money, because their track record speaks for themselves, right? And it's it's inevitable. And this is the beauty of there should be a marketplace for that.
Way of pricing capital
because it's it's a it's a it's a kind of you're driving things towards a meritocracy more and more, right? Like if someone can show results and put in the hard work, they don't need all the means of access. They don't need all like to get through all the hoops that are all the things are gatekeep from them right now, right? Because the reality is like, you know, if if you are grown within the millennium circle and the hedge fund, the big boys club, you're probably going to end up being one of those hedge fund managers and you're you're you're pretty geared to win in that traditional sense of the term. But there's a lot of talent out there. This is what's amazing. There's so much talent out there. I mean, crypto did a lot of has surfaced a lot of it. And and you know, I'm a strong believer in that not everybody will win. Not everybody wins the NBA. Not everybody wins an election. But I think creating as much of a like break down as much of the core barriers, create as much of a level playing field and a neutral playing field for giving anyone a shot to win is I I think what I'm most excited about when it comes to predation markets.
I mean, I totally agree. And breaking down all of these barriers allows a wider opportunity set, which actually goes back to your point you made in the very beginning is politics gets a little easier if people see that there's opportunity. You know, people are frustrated and we get that. Um the question is is how difficult is the fight with the incumbents to do it because the regulators are in the path? You know, you you've had to work with the regulators and we know there's you know, I'm not trying to get you into trouble here, but it it there's a lot of friction in your path and a lot of hurdles that will get put up because gatekeepers make a lot of money and what you're doing is creating a new business model and that's difficult. You know what I've learned over the years and and you know I've been kind of transparent about this like our path has been very hard especially if you want to do it the right way regulated way. you want to like change the system. If you want to do it outside the system and go, you know, that's easier because no one like no one cares and it's harder to make go mainstream. But if you want to change the system, it's very hard. And and what I've learned over time, look, I I I I'm a pro-regulation person to be clear. Like I I'm I think there's my view is generally like build a highway that is wide enough for competition and innovators to thrive and do the things they want to do and but make sure that there's a fence. You don't need to build a narrow highway where people are are choked. You want to build it wide enough, but do you have a fence so that people really, you know, make sure people that cannot do bad things, you know, misinformed customers, people, you don't you don't want people falling off the the the the cliff. Now, what I've learned over time is the regulatory equation is much more complicated and it's fundamentally uh business interest driven. Unfortunately, we got to a point where regulation often times there's like two types, right? Policy, make sure we're actually protecting consumers, etc. But the huge part of the equation is actually in common protection. Why? Because incumbent has been have been, you know, lobbying and doing decades long of exactly that regulatory capture and mode, etc. And you're seeing with perpetuals, you know, the CFC just got sued over the perpetual's approval. Um, and I I find it like to be a validating sign, right? Like when an incumbent is suing over a product instead of like um embracing it, that's kind of a good sign for the innovators.
If it's not, if it's proven to be a good high quality product and it's been tested, then it's telling you a signal is they're scared of it.
And look, some in comments, I would say it's not all in comments because some in comments choose the path of competing. They break the innovator's dilemma. They they figure out how to invest in those new new platforms and participate in them or they hire a team. They figure out how to compete, which is a good thing. Like that's actually what you want because they keep reinventing themselves and not rely on like you know the innovation from two decades ago. But then others unfortunately like sometimes choose to litigate and trying to squash the innovation or the competition out. But that's never the core. I mean at least in America that's never how like you're never usually on the right side of history there, right? Like it's hard. It's hard to compete. It's hard to innovate. But there's a lot of us, right? And and a lot of us have the incentive to do it. And that's the beauty of America. That's why this country works. And how do you get around stuff like I presume the binary options are banned for retail in the US while prediction markets are binary option markets.
They're not in the US. There's some parts of Europe but they're kind of I think a lot of Europe is reconsidering that.
Yeah. I mean
because there was a lot of kind of those bucket shop FX places that were wildly mispricing uh binary options and they
unregulated, right? There's a lot of unregulated. I mean this is the thing also it's like the un and crypto has survived a lot of this, right? like the the in a lot of these markets honestly this exists in financial markets exists in healthcare exists in a lot of markets
there is bad actors there's unregulated actors that honestly don't worry about risks like what I always tell any type of technology AI financial markets perpetuals they all come with risks and when operators are not aware of these risk or care you're going to end up having bad outcomes and that's why well let's not trust all the operators let's have a good regulated regime so that we have a regulator that's you know you know the elected by the people that essentially is is creating an oversight regime for these types of products.
Yeah. Then the issue is we've got global regulation and that's a mess. So, you know, as your push globally, you know, the US, you guys have done a phenomenal job, but outside of the US, it starts to become complicated because you've got th you know, I had Yoni Assa, you know, Yoni from um and and Yon's like, you know, we've had to deal with every [ __ ] regime to deal with to get some of this stuff done. And you kind of have to go that same journey. We have we have to do the same. I mean, we're always going to be regatory first and we're going to go through all the hardship of making it happen because it's the right thing to do. Um, and that's what it takes, right? If it was easy, everybody would do it, right? I mean, and I think it's not and and but but
that is the opportunity, but it is hard.
It is part of the opportunity. There's part of the opportunity. And the other thing I I still think that our principles are clear. Bring innovation, do it the right way, and have sound policy principles, right? On a long-term horizon, that trumps the incumbent politics. It trumps the politics because you're being sound. Right? Now, if you're being extreme in one way or the other, like you're saying unreasonable things, that is not going to withstand the test of time. Right? But if you're being sound on your principles, like how much leverage are you giving? Are you de-risking things in the right way? Do you have a proper risk model that works? All these different questions, if the answers are yes to all these different things, that will essentially over time, now maybe it doesn't happen as fast as we would like it to, but you win over time, right? Because you'll have the right answer. I really strongly believe in that. And you know, we're living proof of that, right? We spent four years and you remember getting regulated based on principles that most people didn't believe in. They said this would never be allowed by the government. But we were right. We always said these should exist. They can exist in a safe and responsible way. And here we are, right?
What was the thing that cleared that? What what was the
We had to sue the government. So that was part of it, you know, and [laughter] and so that there was that. But we won, right? We won, you know, and it was hard, you know, it's very hard to sue the government and ask the government to rule against itself. It's it is hard no matter what people say. But um if you're right, you're right, you know, and and at some point you get vindicated in one way or the other. The question is, are you going to wait enough to be vindicated? And we waited. And then and I think that's just the path of uh that's just how these things go. You have you have to persevere for a long period of time.
Another thing I was just thinking talking to you is you're sitting on a gold mine of data.
Yeah. Yeah.
How do you think about that?
Because it's obviously contentious, but it's not contentious. I mean markets sell data and you know if you think about the big exchanges they make more money from selling data than they actually do from
they do
other stuff you know
right now we're in mode of like give it away for free as much as possible and as open source as possible because we want like this part of the mission I want people to use data I want
it needs to grow first
it needs to grow and I I I want to train and it's happening this is the amazing thing like when I talk to parents for example that 25-year-old son or daughter are on couch she the consistent thing that they tell me that they're most excited about when they see that is that all of a sudden they're seeing their uh they have more um kind of like um substantive conversations about different topics with them because they're reading more, they're researching more, they're like what's happening with polish, what's happening with the economy and they prefer that over like you know spending time on Instagram scroll doom scrolling and and seeing some crazy stuff on there, right? And you're training a generation of people to think more probabilistically about the world, to think more critically about what's going to happen. And I mentioned I told you more than 80% of our customers use it for for looking at the probabilities of different things happening. As long as we train that, I think we win long term because our cultural win is starting to happen where you know people are what's the couch on this? What's happening here? What's the instead of this idea like I've always found that math would be the solution to this all these heated debates that we're having whether it's your dinner table in Thanksgiving or we're having at the debate stage in politics. It's all have become extremely extreme emotionally charged and maybe it's always been that way but I think this is the solution that that that is the potential antidote and as long as we get there I think we're going to do more than fine.
What about I'm I was just thinking through the banks then how do the banks think about all of this and what they can do with it. Obviously some of it's super interesting because you can hedge different risks and all of that stuff or you know or take different bets on different stuff. There's also about you know the [ __ ] economists who get everything wrong for years. you know, there's like a there's a bigger truth mechanism here, even though obviously there's always the CPI print or whatever the thing is. Um, I don't know, there's something in that. And there's also reminds me, I don't know if they used to do it on the trading floor in the US at Goldman, but on non-farm payrolls,
we would get the yellow stickies and we would post them from the top to the bottom. everybody on the floor. You put five pounds in at the time and anybody was there and we'd have like a hundred of these things up the wall and it was a winner takes all market. I just think there's something I don't know how the banks are going to deal with all this but it's super
I think look I the banks my sense and we talked to a lot of them and actually a lot of them are actually starting to embrace it faster than I think they embrace crypto and you're going to see that trajectory. So, if you predict that out of the year or two you're going to see much like the banks have embraced fiction markets much earlier than they're going to than they have embraced crypto in the crypto journey. uh because I think prediction markets I mean again remember I started from the the bank side this is where I really got the idea fromly because they're pretty disruptive in nature to their business model often times they are pricing they are doing a lot of work pricing these
uh non traditionally financial risk like what whether Brexit's going to happen non-farm payable like all these different questions and now you have a liquid market marketplace to price it so so at least on the data integration they're going to have to use it otherwise they're going to be left behind but we're starting to see a lot of demand to trade the products uh because that's how a lot of their trades are formulated. A lot of people want to get the JD Vance position, the the Rubio or the Gavin or the AOC position for 2028. That's the thing that they're trying to figure out how to position themselves in and instead of doing it indirectly, like how about you just buy the thing and don't take any basis for risk. That's too obvious. It's it's a better product. And so that I think by as we look at getting into the midterms and next year, I think you're going to see a lot more. I mean, the institutional adoption is happening, but you're going to see it throughout the banks as well.
Yeah. Yeah, I mean elections are going to be amazing for you in this whole process because it gets very interesting.
Um, so what's next for you guys? So you've launched the per, it's taken off like nobody's business. Where do they go and then where does the business go next?
Yeah, I mean we're very excited about perpetuals. I think that, you know, we're going to expand the number of perpetual uh futures that we start with digital assets, you know, Bitcoin and a few other um uh currencies, but I think
why have people used Kelsey as opposed to Hyperlquid or other exchanges? Is it because you're regulated?
Yeah, I think I think ease of access, it's regulated. It's, you know, I always say like whenever there's a regulated product and alternative, people prefer the regulated product alter like they they
Yeah, it's just easy.
It's it's easier, but it's also like I think it's just safer, right? People people don't like taking counterparty risk in general. Um and and and you you're not really taking much or you're taking significant less counterparty risk with a regulated business. So, uh so that's important. I think the and then obviously that holds true for institutions. Institutions generally like are much faster to I mean they don't really adopt unregulated products in mass.
Yeah.
Um, but like expanding our perpetual offering to more products is a is a huge priority. I think international expansion is the second and third is is accelerating the institutional traction that we're seeing right now. I mean, that's it. I think the growth in the first six month of of the year have been has been great. I mean, now it's just like got to drive it home and and and you know, integrate the banks the bro kind of halfway through the broker dealers and the FCMs you have the the the the kind of futures brokers and then we basically need to uh just get the other half
and the other people who price probabilities I mean there's two groups of people's one is is the acturies and I guess the insurance companies are still acturies at heart but there's there's something super interesting those markets as well
you know, we do price hurricane risk and stuff like that um
but it's pretty underestablished market because you don't have super forecasters. So you have, you know, only a few incumbents who are pricing markets and if you've got 10 different insurance companies, you haven't got an official market.
You're taking it, what we're doing is, you know, every time an over-the-c counter market has moved to on exchange rate, the market blew by like a factor of like 10 to 50x, right?
Uh and that's what we're doing. We're taking from an over-thec counter where you you call one broker or one person and they tell you what the price is and then you transact
uh to an on exchange traded product. And we actually seeing it over the last weeks. I mean, there's been a lot of buzz recently on the sports hedging on Koshi because people buy sports insurance. Now they're just doing it on the exchange because it's much better prices. And like there's teams that do it. There's I mean a bunch of bars that stock up on inventory ahead of the game. And then that's an economic risk that they're taking. If the team loses, nobody's going to show up and it's going to be, you know, a buzz. So they hedge out these risks. They're getting used to hedging out these risks which is which is great because you know they they soft smoothing their P&L to to to be able to you know against sort of different outcomes and actually hurricane is we're seeing across weather we're seeing in economic indicators etc. people prefer coming to us because it's much cheaper, much faster and specifically for hurricanes. With traditional insurance, oftentimes it takes two years to pay and you have to show the damages and people really want a fair instrument tells you this parametric. If the hurricane hits this town, I want to get paid and get paid immediately and I don't I want worried about how much I'm going to get paid. And people really prefer that product. We see this a lot around hurricane season which is pretty cool.
Yeah. Listen, what you're building is huge and I don't I think people still underestimate the size of what you're building.
I hope so.
You know, I I just think of it and again I go back to the conversation the rivet capital idea of token factories and in the end you are a gigantic token factories of global probabilities of all sorts of things. That is an incredibly valuable thing for whatever outside of the revenues that it makes and everything else. You're building a token factory of that is almost unassalable in terms of what it has. The information it holds within it and I just think that that's the start of something maybe much bigger overall is is what this allows for.
Yeah, look at this as token factories is is is amazing. But I agree I agree. I think like the idea of infinite markets token factory is this idea that like could you create an efficient market for all these questions? to stop, you know, uh, debating them or doing them in all these like obtuse, obscure ways.
Could you build a frontier model? Yes, because you have a very different data set,
a lot of data different
than anybody else has, right? You have a you because one of the hard things and you know I'm trading training AI in bits and pieces. Now in predictions it needs the falsification and you know did the prediction hit so it can learn. You have that at a scale of which nobody else has it across such a diversity of stuff. That's an interesting idea. You know, we've been thinking a lot about what to do with our data because, you know, the a lot of the labs, you know, right now we're giving them the data and they want it, but you know, there's a time where this could change. So, we're thinking about that a lot.
Don't give them the data because
it's a unique data set for sure. I mean, you know, and it's it's it's unique in the sense it's the only one that's forwardlooking in this specific way, right?
But it also trains models on what it takes to predict.
Yes. Yes. That's the That's the thing cuz I'm having to do this with a model I'm training not for short-term price stuff, but kind of long-term very complicated stuff, but it has to it has to meet these prediction points and how did it do and then it has to learn from why it failed and all of that. You've got that at scale. Yes, sure, people can do that from the S&P futures and all of that stuff, but you've got a lot more granular information than anybody else has in a way that the world is desperately going to need as you go through intelligence models beyond AGI. I don't know.
No, we're on the same page. We've been thinking about this internally. So, it's definitely been an interesting uh topic of conversation and I I would, you know, people should not be surprised if you end up doing something on that front. So, that's something we're thinking about.
Yeah. Well, listen, well done. And as we said, we followed this journey. I thought it's never going to happen. I thought CME and the CBOT and everybody going to kill us.
Oh yeah.
And you've done it. I mean, you've done it and it's amazing to see. And you know, it's just fantastic. So well done.
I really appreciate you and thanks so much for having me again.
Not at all. And I'll get you back at some point as well.
Absolutely. We'll talk soon. Thanks a lot.
Thanks.
So there you go. I mean, brilliant conversation. Um, just there's so much in it, so much to think about where where the world is actually going because what Tar is sitting on is signal. He's sitting on so much signal of of what's actually happening, where the world is going, how people are thinking about it. And not just the signal in terms of price, but the signal in terms of again we go back to that democratization idea. How anybody can become a hedge fund manager, how anybody can become a super forecaster, how anybody with some experience and the application of their intelligence can do really interesting things and how the structure and nature of markets is changing and how we're preparing ourselves more for the machine age as well. Anyway, great discussion. See you next time. So, you obviously like this video enough that you've got to the end. That's quite a big task, but listen, do me a favor. Hit the like and subscribe button and also check out what videos next because I think you'll love it. But if you want even more, and when I'm talking more, I'm talking about memberergenerated ideas, incredible alpha research, everything there to help you in your journey, just head to realton.com/join for the best financial intelligence out there and the pure alpha that's within the platform.