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Bankless Nation, I'm here with John Wang from Kalshi.

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John, welcome to the podcast.

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Thank you for having me.

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John, is Kalshi a crypto company?

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I think so.

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Yeah.

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I think in the crypto world, like there's obviously an on-chain definition, like on-chain or crypto company.

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I don't think we're an on-chain company by any means.

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And there are on-chain prediction markets out there for sure.

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Um, but, uh, crypto is our second largest business line behind sports.

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Um, we have 90% market share in the crypto predictions world.

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Um, we, uh, a lot of our like biggest, you know, partners are in the crypto industry, like Coinbase, um, Robinhood crypto, like Phantom, um, and some others, uh, they route their crypto.

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orders and trades through us.

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And so I think we're pretty deeply embedded in the industry.

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And that's pretty much what my role is, is to help us get even deeper.

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Okay, so crypto is like there's the crypto sphere of influence.

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And I think what you're saying is Calci is somewhat inside the crypto sphere of influence in a number of different ways.

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But you're distinguishing it from Calci is not an on-chain company.

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Does Calci want to be an on-chain company?

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Ultimately, we just want to build like products that are super easy to use and accessible to people.

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Like normal people that don't necessarily, aren't necessarily super experts in crypto.

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our approach has always been to go the regulated route.

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I think US regulations are heading more towards being on chain with all the different legislature that's coming out.

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But at the current state of US regulations, it's not compatible.

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I think in several years, that's somewhere where we want to get to.

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But

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Product-wise, I think the products that we've been building have been either like around trading crypto, for example, the largest crypto companies in the world, I would say, are like Binance, Coinbase, Kraken, and...

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These centralized exchanges, they are rolled out allowing their users to trade the price of crypto.

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And that's pretty much what our crypto prediction markets offer to our users.

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We also have our new regulated PERPS offering, which is the first regulated perpetual futures exchange in the U.S.,

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that's like the first time essentially you have a perp app on the app store, you have your legal no VPN access for normal US users, kind of like your mom, your cousin, even like your friend could access it.

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And also US institutions can compliantly access it via like the type of infrastructure that they utilize.

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Also, I think,

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like the deposits and withdrawals aspects of being like a centralized exchange is a large reason why many people still use centralized exchanges.

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And for us, crypto is an important rail for depositing and withdrawing from the platform.

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So obviously we have like the ability to just deposit and withdraw stable coins or crypto assets in the US.

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But internationally, we're open in 140 countries

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The crypto rail is the only rail that we currently accept for people to come into platform, put their money in, because we found it's the most frictionless way to get like, you know, global monetary access and sort of the most frictionless way to convert from, you know, the local currency to the actual US dollar that we accept.

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I see.

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I see.

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So for CalShit to accept international customers, the only on-ramp that's viable and easy to integrate is like the stablecoin or local stablecoin, local fiat stablecoin on-ramp into CalShit.

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How much of CalShit's business volume and trading volume is from outside of the US?

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Like how dominant is that side of CalShit?

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Yeah, we're still predominantly a U.S. company in terms of user base.

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But I think the international side is a huge focus of ours.

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We are taking a somewhat unique approach there, which is obviously like,

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even in the US, there's these two paths to growing a prediction market, you know, six, seven years ago, which is you go offshore and you kind of take the unregulator out or you go onshore and work with the regulators in the US and kind of like,

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That's like the really hard, hard path, right?

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Like spending years just doing legal stuff while like shipping a product in beta and not even being able to market it and such.

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So we're kind of taking a similar long, long-term approach to our international markets as well.

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Where we're working with like either the regulators or like the largest brokers in each country.

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Um...

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to sort of embed our prediction markets inside their products, similar to how we've been embedding them into Robinhood or Coinbase.

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And so we've been able to secure deals with like Wealthsimple in Canada or like XP, which is the largest broker in Brazil.

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So overnight, like,

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It's the long game, but overnight we can essentially unlock like the entirety of like a country's tradable, like trader user base if we get some of these partnerships.

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But we're also doing a lot of like on the ground efforts to try and, you know, find a dialogue with each individual regulator.

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As Ryan and I have watched the growth of prediction markets, we have frequently used the comparison between CalShea and Polymarket as kind of like Tether and Circle.

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You have the compliant on-chain, on-shore version, which is the Circle.

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You know, it wants to work with the regulators, be very compliant.

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That's kind of the structural edge that Circle has.

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And then there's Tether, which is kind of like playing in the offshore euro dollar world, which is a very big world.

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And Tether has been able to grow pretty aggressively because it's actually not onshore and because it's not really constrained by the regulations.

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And we kind of took that same growth story between the two largest stable coins, Circle and Tether, and we kind of have applied them similarly to the prediction markets between Calci, the onshore version, and Polymarket, the offshore version.

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Do you think that that is an accurate comparison?

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And where do you think that comparison breaks down if it does?

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Yeah, well, it's always good to have some analogies to reason across off.

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But I think with stablecoins in particular, it's...

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the product ultimately is like selling the US dollar.

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And there's a much greater product market fit or like need for the US dollar, at least historically in like these third world country nations or offshore countries.

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So I think Tether has just found a greater pinpoint for the customer.

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And therefore like their growth internationally has been quite astronomical.

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Whereas with prediction markets, I think,

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It's less about like, you know, we're shipping something that is like US centric to the rest of the world.

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It's more about like each country and each type of really just group of people.

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They have different questions about the world that they care about.

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And ultimately, all our markets are just about creating like the types of relevant events and markets that people want to trade.

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obviously both, uh, like all the leading prediction markets in the world right now have mostly had us teams that are like focused on creating us specific markets.

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But we found like, um, even some of our, like, uh,

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markets in certain like whether it be like cricket um good great adoption internationally um the world cup was great for international adoption um crypto has been actually quite a strong like uh you know everyone in the world knows about bitcoin everyone in the world knows about eth

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And so that's also crossed a lot of borders.

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So no, I don't think it's exactly a one to, I think the analogy breaks down in terms of like what the product actually is.

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But in terms of the approach, I think, yeah, it could be somewhat similar.

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Although I think we are like, compared to like most regulated companies,

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like a Coinbase or a Circle or instead of other regulated company.

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Kaoshi is much leaner and much more aggressive than these other companies, in my view, just like my personal view.

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We...

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have a team of around 180 people, which is probably like 20 to 40 X smaller in terms of headcount than these other types of companies.

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And we're just have like an insane, insanely aggressive, like product velocity and shipping speed.

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And also even from the regulatory side, like we,

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We pushed to legalize prediction markets and perpetuals.

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For prediction markets, we actually had to sue the CFTC.

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So it's by no means like we're not really, you know, pushing for what's best for our customer.

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What's the steel man for why the onshore compliant strategy for prediction markets is the right one?

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The steel man?

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You mean like why it might be the right choice?

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Yeah, give me the argument.

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So like I think you could make two arguments.

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One is like the offshore version of the prediction market platform is going to be able to win based off of XYZ.

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Or you can make another argument saying the onshore platform for prediction markets is going to win because of ABC.

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I want you to give me the one where like, well, CalShare is the onshore prediction market platform.

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It's trying to lean into regulatory compliance and clarity and work with all the three-letter agencies.

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Why is that the best strategy?

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Why is that the winning strategy?

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Well, CFTC is a four-letter agency, actually.

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That's a good point.

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But we love our agencies.

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So...

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Yeah, the steel man, I would say, is you always have this choice of going, you know, offshore and like VPN.

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And that does actually, it does make like doing no KYC and stuff like that.

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It does make onboarding the like crypto native user base easier, I would say, because.

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they've jumped through these hoops before.

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It's kind of what they're used to.

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But for like the 99% TAM of the world, which I really think is the TAM that we should be trying to tap into at this stage where we're trying to find the marginal user to bring into the crypto industry or to trade...

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this like very exciting new instrument, well, not new, but like very exciting instrument that was born out of the crypto industry, Perpetual Futures, that is the user set that we should be hunting for.

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And the only way to tap into that user set, I would say is,

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You're able to like run paid ads on Facebook and Instagram, able to like put up billboards.

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You're able to partner with like household consumer names, um, and like, uh, find, get integrated into large brokers and financial institutions.

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Um, um,

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be on the app store.

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And like as you grow to a larger scale as well, you're obviously like under much more regulatory and compliance scrutiny.

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So I think it's really a critical thing to take this like onshore regulated approach if you want to tap into that user set, which I think is like the next user set that is up for the day.

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I've been trading crypto for almost a decade, and I've used so many different wallets, exchanges, aggregators, different front ends over the years, and I'm always kind of looking for the same thing.

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Just one interface with deep liquidity across a bunch of chains and assets where I can access all the markets like perps, earn yield, trade confidentially, and still control all my own funds.

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And I've never really found this experience.

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And I'm always switching wallets, juggling gas fees, and just getting eaten by slippage.

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Near.com is not that.

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I can do everything I want from any chain, and I keep all my activity confidential.

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I can even earn yield confidentially.

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It's the way crypto should work.

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The Near.com wallet is powered by Near, and it's moved over $25 billion cross-chain using post-quantum signing and has run over five years on mainnet with zero downtime.

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Get 20% of your trading fees back using the bankless link in the show notes, not investment advice.

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Self-custody won, but it still has a usability problem.

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This episode has been sponsored by BitKey.

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You talked about the Perps platform that CalShare is building out.

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Perps is a pretty competitive place to be in right now.

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Perps are pretty hard.

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Two of the best per platforms that I really pay attention to, Hyperliquid and LiDAR, have just some pretty insane technical chops to them.

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And they're really just becoming hyper-optimized around trading and the Perpetual as an instrument specifically.

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So what makes CalShe think that it can compete in this very competitive landscape around the Perpetual?

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Yeah, I mean, the landscape for perps is competitive, but I think even the larger landscape of futures is, I guess, even more competitive because there's tons of futures platforms out there.

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CME is an order of magnitude larger than even our perp exchanges in crypto right now.

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Yeah.

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So it's a very competitive landscape, but the reason why we are throwing our hat in the ring is because firstly, I think we can deliver a product experience on par with some of the crypto trading platforms that I personally am familiar with, you're familiar with.

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For example, we shipped a Kalshi Pro recently, which is the first official prediction market for a trading terminal, like released by a prediction market.

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But we also have like a PURPS Pro interface, which is like more similar to the types of interfaces that you'd see across the industry.

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And so our fees for that are quite competitive.

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Um, and our liquidity is actually, uh, it's, it's still, there is obviously like a ways to go, but, um, you can throw in like a six figure order size and not experience like too much slippage.

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Um, and we're still working to grow that even more.

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So from like a pure like trading execution, competitiveness of economic standpoint, you're at no disadvantage trading on Kaoshi Perps.

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And we're soon to launch like our non-crypto asset classes as well.

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I think it was announced that we filed for a gold and silver, which should be coming in a matter of weeks.

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And obviously, we're looking to expand to other asset classes beyond just that.

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And really, that is the frontier, right, for the perps industry nowadays.

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Like hyperliquid, I think around half of their volume nowadays is from these real world assets.

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And the center of all this real world asset liquidity is the United States.

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It's the U.S. retail and large U.S. institutions that are currently providing liquidity or trading on one of these traditional financial platforms that need to access like a regulated, easy to access U.S. platform.

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Yeah.

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But they so far haven't had the opportunity to sort of get the benefits and the innovations of perpetual futures.

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No needing to roll your futures, no expiries, cheaper costs.

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all these things they haven't had access to until now with Kaoshi.

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So I think in this like next frontier of real world assets, we'll also be able to sort of like, I think actually be the industry leader in terms of liquidity, access, distribution, and also just product experience.

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although, you know, we still haven't released it yet.

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So we can only celebrate it once we've done that.

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But I think that's the thesis at least.

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Mm-hmm.

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The last I checked, it was still just the Bitcoin perp contract that the CFTC had approved.

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Is that still accurate?

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Or what are the markets currently available on the Kalshi perp platform?

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Totally, yeah.

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So we get a CFTC approval, like this quarter, the 40.3 filing for every single new asset clause that we list.

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So the Bitcoin one essentially approved crypto as an asset clause for us.

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We now have like over a dozen crypto assets on our perp exchange.

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What are they?

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Just Bitcoin, ETH, Solana?

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What are the crypto perps that you guys have?

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Yeah, we, Bitcoin, ETH, we have Hype, we have Solana, Zcash, Near, SWE, Doge, um,

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XRP, if I haven't said that already.

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Did the approval of the Bitcoin contract from CFTC, did that give Kalshi the ability to, what was it called?

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Self-register or auto-register?

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Self-certification.

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Self-certification, thank you.

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Yeah, so you guys can self-certify crypto asset perps now.

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Yeah, exactly.

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Obviously, we have to run our own risk models that have been CFTC approved.

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So it kind of follows the same process that it would for a Bitcoin perp, but it is much easier to list something.

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So the Bitcoin perp gave you guys a framework that if the Bitcoin can be approved with these risk frameworks, then any other crypto asset that also passes the risks frameworks can therefore also be approved.

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Exactly, yeah.

202
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And I think our leverage limits are lower than other sort of offshore platforms.

203
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And there are trade-offs to that.

204
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Like obviously some traders don't want to, like they don't want to take like lower leverage limits.

205
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Based on our like sort of like data analytics on like on-chain and other platforms, yeah.

206
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only like 20 to 30% of users trade above like our leverage limit, which is like 6x.

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Most traders, we actually find they trade between 2 to 4x.

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So that captures like the vast lion's share of traders.

209
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So it's actually not as prohibitive as you might think.

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But for our like

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upcoming non crypto perps, the leverage limits for those will be much higher, given that they're like much less volatile of an asset class.

212
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So you'll actually be able to get similar leverage limits to the existing perp RWA platforms that you've been seeing out there via Kaoshi.

213
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And our economics or like our fees are pretty competitive, I think.

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compared to like Binance or like a Hyperliquid.

215
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We have lower fees at every year currently.

216
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What's the plan for the CalShaper platform to evolve from here?

217
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And just as a frame of reference, I'm pretty familiar with like the lighter roadmap, for example, or at least what they want to do

218
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And one of the things they really want to do is they want to get tokenized real world assets.

219
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So like a real basis for the perp to also trade on spot.

220
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So you have like three ingredients here.

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You have the actual tokenized equity or tokenized real world asset.

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You have a spot market also built into the platform.

223
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And then you have the perpetual itself.

224
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And with those three ingredients, you can really blossom into a bunch of different, like, optionalities, strategies, baskets, you know.

225
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It's kind of, like, open-ended in the permutations.

226
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And so that's how, that's, like, Leiter's opinion for how it kind of grows as a platform.

227
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Does CalShe also want to grow in that direction?

228
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Because you would also need to have, like, a spot market and then also try to have, like, a cash-settled underlying.

229
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What's the evolution plan for, like, the CalShe Perpetual platform?

230
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Spot is definitely something we've considered.

231
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And if it makes sense to add to it, for example, like margining in Bitcoin or like non-cash, that's pretty interesting.

232
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It depends on regulatory unlocks, but it's definitely something that I've been pushing for internally.

233
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In terms of like actual roadmap, I would say we're primarily concentrated on

234
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Well, firstly, we're rolling out a bunch of interesting incentive programs soon.

235
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So those would make it pretty attractive, I would say, to trade on our platform, also to trade specific coins.

236
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And also, if you're like a big trader,

237
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you can, you know, we'd like to make it such that our platform is like the best place for you to place your trades, most liquid, or like you don't have any troubles around order execution and stuff like that.

238
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Secondly, I think our Kaoshi Pro product we're leaning into pretty hard.

239
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So obviously like

240
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The perps side of things, we have like the trading view integrations and the types of other integrations that you might want to see with like a more traditional brokerage for stocks or options like a Moo Moo, a Tasty Trade, stuff like that.

241
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So providing like a product experience with parity to that user set.

242
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Yeah.

243
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And then also like cross-selling our existing predictions traders and acquiring new, like more advanced traders that might be interested in predictions.

244
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Like that's where we see our like differentiation being.

245
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And then we're working really hard on unlocking these new asset classes.

246
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As I mentioned before, like starting with gold and silver and metals.

247
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I think like perps is, where we lie with perps, like our perps product isn't just like shipping a great perps product, but it's also like how can we

248
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co-mingle it with the benefits of our predictions product.

249
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So on our Perps product, not only do we have like this, we have this Kalshi social, which is similar to like FOMO or like I think Robinhood social recently released something that looks similar to our platform.

250
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So that's quite exciting.

251
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There's like a troll box on Perps that is similar, almost like gives me flashbacks to BitMEX.

252
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back, you know, 2017, 2018.

253
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Um...

254
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But our predictions product itself, we have like these traders are able to price the odds of Bitcoin hitting a certain price, like predicting the price of Bitcoin on a hourly, daily, monthly, like annual basis.

255
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And we sort of distill those insights into our Perps product as well.

256
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So people are able to like see the odds on the chart in the inside section, like the stats around, like what the market expectation is.

257
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And that's like actually found that's helped a lot of our traders who might be, it's their first time trading perps ever.

258
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And these types of like market expectations or just like the way we package perps into like up or down instead of long or short and the way we like make leverage, you know, much more understandable for our user base.

259
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Like those types of things have helped a lot.

260
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Yeah.

261
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And I think we're going to keep leaning more into that in terms of our roadmap, which is like, how do we combine the best parts of PUPs and predictions together and build it to like a user base that is new to PUPs and they may be like a simple PUPs trader or like a more advanced day trader.

262
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Is there a vision of just like a single unified Calci platform where predictions and perps and that social feature that you were talking about is all kind of unified in one single interface?

263
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Because as I understand it now, like perps and the prediction markets are just not the same thing.

264
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A separate platform is siloed.

265
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Is there a grand unified version of Calci in the future?

266
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Or how do you guys think about just like the synergies of these products actually coming together

267
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So our

268
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perps, at least the simple product, is quite integrated into our app already.

269
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So if you go on our mobile app, we have a tab for perps.

270
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If you go onto our web app, we also have a tab for perps.

271
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And then the current bifurcation is more so with our simple experience and our pro experience.

272
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And we're working to combine that a bit more or make it a bit more seamless in switching.

273
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it is quite integrated.

274
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And I would say that we do want to provide like a pretty cohesive experience.

275
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Let's get into prediction markets, since that's the main bread and butter of Calci.

276
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There's this central trade-off around prediction markets that I think prediction markets just kind of have to figure out how to walk the line here.

277
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And what I'm talking about is prediction markets are accurate because they pay people who have private information to reveal it with their trades.

278
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That's kind of the whole point of prediction markets, if you have alpha,

279
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you can come to a prediction market, you can come to Kalshi, and you can sell that alpha to the market, and you're basically selling it to noise traders, the uninformed retail crowd.

280
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And so the retail crowd, the noise traders, they come and they basically fund the incentives for people with private market information to reveal their private market information to the market.

281
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And that's how we gain information from these prediction market platforms.

282
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But there's a tension here between if Kalshi or any prediction market platform, whatever, is too permissive with the insider trading, quote unquote, the alpha traders coming and selling their information to the market.

283
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If they're too permissive, prices are very accurate, but retail kind of just feels that the game is rigged and they can't really, it's not fair to them because they don't have any of the alpha and they're the ones financing the,

284
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the information coming into the market.

285
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On the flip side, if it's too restrictive, if like overly restrictive surveillance cuts off the informed flow from the market, the market degrades into just being like a sentiment poll rather than like actual news or actual information.

286
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And so there's a tightrope that a prediction market has to walk here where you do need to attract information

287
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retail customers to incent information to come to the market, but you can't allow for too much extraction from retail or else then the retail won't come.

288
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They'll just, all the fishes at the poker table will get milked and then they won't be able to come back.

289
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What's this strategy for CalShe to find the equilibrium between these two polarities?

290
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Yeah, that's a great framing.

291
00:29:07.638 --> 00:29:09.739
You know, I think it is definitely a spectrum.

292
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Where we sit on that spectrum is we are like a markets first company.

293
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Like ultimately we are building an exchange.

294
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One like strong byproduct of that is that people are using our website to get better informed about the world or like see what people, you know, the market is expecting, what people's consensus is currently.

295
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Um, and then also for traders who do have special, like, you know, insights into a certain topic or have done more research than others, um, are more like resourceful or curious.

296
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Um, they are able to also profit off of, um, that those, you know, their, their extra research and their curiosity.

297
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So we do draw a bright red line, um, about insider trading.

298
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And I think, um, yeah.

299
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There are also many markets that like it's like insider trading, I think is, you know, like there are many markets where like users would actually be able to do research and get edge without resorting to sort of insider information or quote unquote like private alpha.

300
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There are these types of things where as long as you're curious and resourceful and you can build systems, which are actually easier to build now in the age of clawed AI.

301
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We've seen a lot of traders just like do exceptionally well.

302
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Even in our like music char markets where you...

303
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might think that, you know, it's kind of like voodoo magic.

304
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It's kind of just like what you might think as kind of like an outside observer.

305
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But if you're in the trenches, you're like looking at these music charts all day

306
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we have this guy called Grande Top Ten.

307
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He's basically been like a music chart, like YouTuber, like ranking sort of type of guy and super in the weeds of Ariana Grande, Billboard charts, et cetera.

308
00:31:20.403 --> 00:31:20.603
Um,

309
00:31:21.805 --> 00:31:32.771
he's just consistently been able to find edge by being super involved in these communities and these different information sources.

310
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And so, you know, there are definitely fair ways to find edge.

311
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We have a ton of infrastructure around preventing insider trading from even happening in the first place, but also surveilling the markets and tracking it when it does happen.

312
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For example, like we have lists of politicians, people in their campaign groups or sporting teams, people who work at the sporting team, like people peripherally around them.

313
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There are like already these types of like people.

314
00:32:08.730 --> 00:32:29.827
surveillance platforms that offer these services to sports companies sports betting companies um prediction market companies and uh for stocks for insider trading there are companies that provide lists of like uh executives and all their associated people um

315
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So yeah, I think we've done a lot of work around preventing and enforcing against insider trading.

316
00:32:39.384 --> 00:32:53.947
And then there's this philosophical question that you mentioned, which is, is it even worth preventing insider trading if the goal is to be kind of this information-sports-it-truth type of platform?

317
00:32:53.967 --> 00:32:59.928
And so my response to that, and I thought about this a lot when I was joining Kalshi, is...

318
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Um,

319
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ultimately we want to service people at scale and scale our financial markets to their greatest ham.

320
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And at scale, right, that's when these types of markets work the best because you have the most people pitching in, you have the most accurate consensus, you have the greatest liquidity.

321
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And the only way you can achieve that is by preventing insider trading.

322
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The reason why insider trading is banned, for example, in the stock markets, you might think it's kind of like for an ethical reason, which there is definitely an ethical component.

323
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But the greater reason is actually like a market structure reason, which is like once you have a lot of toxic flow of like informed traders.

324
00:33:50.612 --> 00:33:53.673
coming in, market makers aren't going to quote anymore.

325
00:33:54.153 --> 00:33:57.174
Liquidity providers are going to pull their quotes.

326
00:33:57.554 --> 00:34:01.216
And therefore, no one will have a liquid market to trade, Yanks.

327
00:34:01.736 --> 00:34:03.796
And then you won't have a signal anyways.

328
00:34:03.816 --> 00:34:04.857
Yeah.

329
00:34:05.617 --> 00:34:13.321
And so you just have to draw this line against insider trading if you want to have market integrity and healthy markets that thrive in scale.

330
00:34:13.721 --> 00:34:19.505
Is insider trading properly defined for the prediction market use case?

331
00:34:20.665 --> 00:34:29.290
Maybe I should have looked into this a little bit better before doing this podcast, but like insider trading, I think, is very well defined for the securities context.

332
00:34:29.810 --> 00:34:33.052
Do you think that the definition of what insider trading is

333
00:34:35.469 --> 00:34:39.932
appropriately carries over in like a high fidelity way into prediction markets?

334
00:34:40.052 --> 00:34:54.242
Or do you think prediction markets as a platform could use an alternative definition of insider trading to be more permissive in certain types of markets or more strict in certain types of markets?

335
00:34:54.302 --> 00:34:57.964
Like, do you think we need to reconsider what insider trading means in the prediction market context?

336
00:34:57.984 --> 00:35:02.027
Or do you think that those laws are actually pretty well defined in the first place?

337
00:35:02.047 --> 00:35:02.147
Yeah.

338
00:35:02.665 --> 00:35:13.077
Yeah, well, the great thing is we actually defined like insider trade, what insider trading is on every market.

339
00:35:13.297 --> 00:35:17.922
And we flag those types of markets that are at a higher risk of insider trading.

340
00:35:18.463 --> 00:35:22.727
So Kalshi defines what insider trading is for its own markets.

341
00:35:23.408 --> 00:35:24.530
Is that what you just said?

342
00:35:24.910 --> 00:35:29.636
Well, no, there is a framework for defining insider trading at the regulatory level.

343
00:35:30.097 --> 00:35:41.911
But then when it comes to communicating and setting the bounds for our users, we have extra guardrails up at the market level.

344
00:35:42.732 --> 00:35:54.060
So, for example, on the UI, we say that politicians or politically associated persons, congressmen, et cetera, are not allowed to trade on our political markets.

345
00:35:54.481 --> 00:35:58.503
They can trade on our sports markets and stuff like that, but they can't trade on our political markets.

346
00:35:58.784 --> 00:36:01.345
They can't trade on any political markets.

347
00:36:01.385 --> 00:36:03.587
They can't trade inside the political category?

348
00:36:05.008 --> 00:36:07.590
Well, I'd have to check on the specific...

349
00:36:08.908 --> 00:36:14.273
because I think it depends a lot on like what type of person, political person you are.

350
00:36:16.055 --> 00:36:20.158
Also, I'm more so on the crypto commodities and perpetuals side of the business.

351
00:36:20.939 --> 00:36:26.143
But I think like generally we don't want

352
00:36:27.445 --> 00:36:31.086
people who are like in Congress to trade political markets.

353
00:36:31.146 --> 00:36:38.228
I think, I think I'm pretty sure that one, um, like 90% sure that one is true, um, that we, we prevent them.

354
00:36:38.848 --> 00:36:50.891
And so, um, yeah, like, uh, there, there's, there's like the preventative step and then there's like the, um, at the market step here on the UI.

355
00:36:51.591 --> 00:36:55.792
Um, and then even, even for like our markets, we, um,

356
00:36:56.869 --> 00:37:00.970
Like, as you mentioned, like, sometimes insider trading does happen.

357
00:37:01.210 --> 00:37:07.292
Like, there's no bulletproof solution to prevent insider trading in the stock market.

358
00:37:08.172 --> 00:37:10.573
Same thing applies in prediction markets.

359
00:37:10.733 --> 00:37:14.674
And there are different types of trade-offs and risks that we also face here.

360
00:37:16.035 --> 00:37:19.676
The best thing that we can do is to make the traders...

361
00:37:20.496 --> 00:37:32.487
our traders as aware as possible of like the risks that they're facing and like the types of precautions that we have put in place, just so that when you're entering this type of market that you're not called called off guard.

362
00:37:32.507 --> 00:37:32.688
Right.

363
00:37:33.328 --> 00:37:33.468
Um,

364
00:37:34.557 --> 00:37:40.181
And so we do have flags, like before you enter certain types of markets.

365
00:37:40.721 --> 00:38:02.196
I think sometimes on like our, some in different interfaces, like every single market, that it like, we just have kind of this like disclosure about like the risks of insider trading and you know, how to report it, how to prevent it and how we, what we do to prevent it.

366
00:38:02.656 --> 00:38:10.324
I do think it's interesting that prediction markets have run up against the whole notion of IP, intellectual property.

367
00:38:11.165 --> 00:38:15.509
And maybe to kind of go back and like set the same stage of the original question.

368
00:38:15.729 --> 00:38:17.812
We had the famous case of the 2024

369
00:38:19.573 --> 00:38:29.260
presidential election, the guy in France, I think, who financed a bunch of polls domestically in the United States to go get information.

370
00:38:29.500 --> 00:38:35.264
And so he paid, they paid, this one trader paid for a bunch of polls to be made in swing states.

371
00:38:36.605 --> 00:38:39.507
And like the nature of the poll was very precise.

372
00:38:39.968 --> 00:38:42.409
And this trader just got in this information.

373
00:38:42.469 --> 00:38:45.391
And then they, as a result of hearing those, the outcomes

374
00:38:49.134 --> 00:38:49.975
Is that insider trading?

375
00:38:50.275 --> 00:38:50.976
Absolutely not.

376
00:38:51.176 --> 00:38:52.217
Like, not in the slightest.

377
00:38:52.337 --> 00:39:03.486
That is a very motivated trader just being very shrewd and clever and extracting information from the world to make a trade on a prediction market.

378
00:39:03.506 --> 00:39:04.406
So is that insider trading?

379
00:39:04.446 --> 00:39:04.867
Definitely not.

380
00:39:05.327 --> 00:39:14.895
And then there's, like, other examples of, like, the Google employee who made a trade about when, like, the next Google model was going to get released.

381
00:39:14.915 --> 00:39:15.095
Yeah.

382
00:39:15.888 --> 00:39:18.317
Now, that information was owned by Google.

383
00:39:20.029 --> 00:39:20.530
in a sense.

384
00:39:20.810 --> 00:39:28.977
Like, Google, as the corporation, owns the information as to, like, what day of what month of what year is it going to release its next models.

385
00:39:29.057 --> 00:39:37.584
And, like, the Google employee came to some, I can't remember which prediction market platform, came to a prediction market platform and then sold that information to the market, if you will.

386
00:39:37.664 --> 00:39:41.027
Sold information, sold IP that wasn't his.

387
00:39:41.387 --> 00:39:46.632
I don't know if that counts as insider trading, because, again, insider trading is, like, typically in a securities context.

388
00:39:47.233 --> 00:39:47.373
But

389
00:39:48.578 --> 00:39:59.205
from a property rights perspective, it makes sense to me that that Google employee ought not have sold information that was owned in, again, in theory by the company.

390
00:40:00.065 --> 00:40:07.870
And it seems to be that like Kalshi, the private market is, is just, just sticking its finger up in the air and be like, that doesn't feel right.

391
00:40:07.910 --> 00:40:10.972
And so therefore we're not going to allow it to happen on the platform.

392
00:40:11.352 --> 00:40:12.493
But I'm wondering if, if,

393
00:40:13.422 --> 00:40:38.508
it would be better if we could actually create a framework of what insider trading is or intellectual property as it relates to prediction markets, if that needs to be something worked out by the regulators for the benefit of prediction market platforms because it would make your guys' job easier and you guys would actually have to regulate less if this was just like, I don't know, a law in Congress or something just stated as a rulemaking from the CFTC.

394
00:40:38.608 --> 00:40:39.508
What do you think about that?

395
00:40:40.520 --> 00:40:46.023
I would say all our public comments so far about this type of topic is that we're in full support of it.

396
00:40:46.203 --> 00:40:47.884
Like we want more clarity.

397
00:40:49.044 --> 00:40:58.549
We want the regulations to be there and clear and to protect our traders and to also, you know, satisfy people's concerns.

398
00:40:59.309 --> 00:40:59.810
And yeah.

399
00:41:00.630 --> 00:41:14.774
Really, it's just codifying the types of things that we've already been doing on our own, like extra steps that we've been taking purely because it's in the best of our interest to protect our traders and the integrity of our markets.

400
00:41:15.274 --> 00:41:25.397
Just so happens to be that it's also like the types of things that people want codified in actual wars in the regulatory world as well.

401
00:41:26.667 --> 00:41:28.728
So yeah, that's something we've been pushing for.

402
00:41:28.748 --> 00:41:31.788
We're very pro-regulation when done the right way.

403
00:41:31.808 --> 00:41:39.070
And when it comes with benefits such as giving everyone a better sense of clarity.

404
00:41:39.450 --> 00:41:50.672
Now, I really like your point about the best market structure is the most fair one, which is an argument for a more restrictive constraint on...

405
00:41:51.512 --> 00:41:54.335
alpha traders, traders with alpha, traders with information.

406
00:41:54.835 --> 00:42:09.908
And so like you need to be, in my previous example, you really need to be the person who does a lot of effort, makes a lot of work to find information in the world, fair information in the world that anyone could have aggregated through whatever means possible.

407
00:42:10.068 --> 00:42:15.332
And then now you have that alpha, now you get to sell that to the market because you harvested it from the real world, as opposed to somebody

408
00:42:16.293 --> 00:42:17.575
actually doing insider trading.

409
00:42:17.955 --> 00:42:20.337
And so one is fair, one is less fair.

410
00:42:20.417 --> 00:42:25.943
And I take the point that the more fair version of the prediction market creates a more healthy market structure.

411
00:42:26.363 --> 00:42:30.548
You attract more market makers, retail feels that it's more fair and less extractive.

412
00:42:31.669 --> 00:42:38.159
But also at the same time, I do think that just like a little bit of insider trading is good too.

413
00:42:38.399 --> 00:42:39.160
Just a smidge.

414
00:42:39.340 --> 00:42:44.568
Just like just on the line, across the line of like what insider trading is.

415
00:42:44.949 --> 00:42:46.591
On occasion, just because like,

416
00:42:47.412 --> 00:42:48.153
That's the whole point.

417
00:42:48.193 --> 00:42:53.858
And this is something that Robin Hanson says, who's like one of the originators, progenitors of like the concept of prediction markets.

418
00:42:53.898 --> 00:42:56.260
It's like, yeah, like this is how we get information out.

419
00:42:56.280 --> 00:43:01.124
This is why the, from an information perspective, this is how we attract it.

420
00:43:01.344 --> 00:43:07.309
And prediction markets can bring more information into the world if they're allowed to do this.

421
00:43:07.830 --> 00:43:11.213
And they're, in addition to prediction markets, there's whole like,

422
00:43:11.773 --> 00:43:24.197
second, third, fourth order consequences of like different layers on prediction markets that could be built if this was the case, things like futarchy, for example, need this information to come be financed and come into the market.

423
00:43:25.197 --> 00:43:27.218
And so like, how would you respond to that?

424
00:43:27.258 --> 00:43:35.420
Just like, what if we just were allowed just a smidge of insider trading in order to really lean into the information side of prediction markets?

425
00:43:35.800 --> 00:43:44.696
Those types of prediction markets, they actually were the predominant type of prediction markets before, I guess, like...

426
00:43:45.835 --> 00:43:49.658
like Kaoshi really took off commercially over the past two to three years.

427
00:43:51.680 --> 00:44:12.318
Prediction markets, they originated from being kind of like either this play money or like, like not, not really like commercially scalable thought experiments by like academic institutions and research think tanks to get to what you just said, which is like the, this like a sort of a

428
00:44:12.698 --> 00:44:20.645
really accurate beacon of truth where people, they don't really have any, like many rules, I guess.

429
00:44:21.306 --> 00:44:29.353
And so I guess like my answer is like, yeah, if you have that, then it'll probably look something like that.

430
00:44:29.453 --> 00:44:37.060
And it probably won't look like a multi-billion dollar asset class that is like very liquid and traded by a lot of people.

431
00:44:37.908 --> 00:45:05.633
Um, and so it's, it's, uh, you're just going to get into this kind of like cycle of, um, you know, not increasing your liquidity and, um, your scale and being forever kind of constrained to like a much smaller scale as like a thought, a nice thought experiment, but not super, I guess, useful, um, beyond, uh, beyond the pure, like, uh,

432
00:45:07.772 --> 00:45:10.134
number that you create, if that makes sense.

433
00:45:10.454 --> 00:45:19.061
Let's talk about what prediction markets want to be when they grow up versus more or less kind of like what they are today in their current form.

434
00:45:19.541 --> 00:45:29.589
In the current form, sports trading across all prediction markets is more or less the dominant category for prediction markets, something like 80, 70 to 80% of like trading volumes in like the sports category.

435
00:45:30.523 --> 00:45:36.805
Obviously, prediction markets as a platform want to be more than an alternative to like the sports books, you know, sports books.

436
00:45:36.885 --> 00:45:54.712
And currently where prediction markets are valued in the two digit billion dollar value range, like the 10, 20 billion dollar value range, that kind of positions prediction markets as just like a valid and upgraded competitor to sports bookies, to like the FanDuel, the DraftKings of the world.

437
00:45:55.532 --> 00:45:58.817
But I think everyone who's paying attention to prediction markets wants more from prediction markets.

438
00:45:59.217 --> 00:46:08.791
And prediction markets themselves are trying to like look towards the CME, you know, something in the three digit billion dollar valuation, like the 100, 200, 300 billion dollar valuation.

439
00:46:09.953 --> 00:46:15.737
And that also comes with that some level of financial utilization, some sophistication.

440
00:46:16.117 --> 00:46:22.701
We're talking about insurance companies and financial hedge funds coming in.

441
00:46:22.961 --> 00:46:31.407
And I would guess you would see a very big drop in sports trading volume because everything else grew.

442
00:46:31.587 --> 00:46:37.891
Like, I don't know, the weather or more markets around the Federal Reserve, things like this.

443
00:46:38.985 --> 00:46:49.974
How do we get from where we are today, where the prediction markets just kind of look like an upgraded version of sports betting venues to competing with a CME?

444
00:46:50.034 --> 00:46:51.876
What's the plan from getting A to B?

445
00:46:51.916 --> 00:46:57.581
That is our ultimate goal is to be the largest exchange on the planet.

446
00:46:57.961 --> 00:46:59.382
So I make derivatives, for example.

447
00:47:00.330 --> 00:47:24.119
And our positioning is that we're kind of like the CME or the New York Stock Exchange in that we're taking a very strong regulated approach, but we have the mix of also being a very fast shipping tech company while being kind of like a very aggressive consumer growth company as well.

448
00:47:25.500 --> 00:47:30.684
And so being able to own the trader relationship has been quite important.

449
00:47:31.305 --> 00:47:33.507
I think it's been important to the growth of Robinhood.

450
00:47:34.088 --> 00:47:37.691
It's been important to the growth of IBKR as well.

451
00:47:37.751 --> 00:47:40.433
So we have that as a differentiating factor.

452
00:47:40.573 --> 00:47:43.056
We own the trader relationship.

453
00:47:43.656 --> 00:47:50.742
We also, I think, have a leading position in the two, I would say,

454
00:47:52.307 --> 00:48:02.813
newest asset classes when it comes to the traditional global financial scene, that are like instruments, I guess, being prediction markets and perpetual futures.

455
00:48:03.594 --> 00:48:07.296
So at least from like a regulated onshore perspective.

456
00:48:07.756 --> 00:48:15.161
So that's like our foot in the door when it comes to really having a fighting chance at getting to that stage.

457
00:48:15.821 --> 00:48:19.043
And taking that institutional approach,

458
00:48:20.630 --> 00:48:37.601
like motion and seeing it all the way through, um, is something that we're currently like allocating a lot of our time to, um, we've been doing a lot more block trades and, um, doing a lot more, uh, sort of, uh, broker relationships as well.

459
00:48:37.721 --> 00:48:42.404
Like we're in basically all of the largest broker, broker platforms in the U S now.

460
00:48:43.285 --> 00:48:43.485
Um.

461
00:48:44.910 --> 00:48:53.453
We've plugged into a lot of the SCMs, which is kind of like the infrastructure or trading terminals that a lot of these large hedge funds and institutions utilize.

462
00:48:54.873 --> 00:48:59.654
We've done some interesting hedges as well through like our weather markets.

463
00:48:59.694 --> 00:49:03.695
We had like an ice cream shop do stuff there for the World Cup.

464
00:49:04.376 --> 00:49:09.037
There were dozens of bars that hedged promotions through Kaoshi.

465
00:49:10.197 --> 00:49:11.698
So they would offer, for example, like,

466
00:49:13.799 --> 00:49:21.185
free drinks for everyone if the US won the World Cup like for that game that night.

467
00:49:21.485 --> 00:49:25.008
And that proved to be quite successful and actually like

468
00:49:26.412 --> 00:49:32.916
have a lot of utility when it comes to like hedging out the risk of these types of conversions.

469
00:49:33.296 --> 00:49:46.705
But we've also had like much more serious large trades, like, you know, seven to eight figure trades based on our clarity odds and block trades happening through our platforms as well.

470
00:49:46.945 --> 00:49:49.607
Whether, you know, the odds of whether the clarity act will pass.

471
00:49:52.164 --> 00:49:59.432
But beyond that, I would also push back against like Kaoshi being like a primarily sports business currently.

472
00:50:01.273 --> 00:50:11.584
Firstly, we have Perps, which is doing an order of magnitude more volume in the first month than any of our prediction market.

473
00:50:12.765 --> 00:50:37.413
uh markets i guess like since launch um perhaps are just like a monster in terms of volume but our crypto prediction markets are actually very large very large part of our business like i think they're 20 to 30 percent of total exchange volume now and that's just for crypto um excluding you know politics economics we recently launched a lot of um

474
00:50:38.485 --> 00:50:45.789
the same types of markets and user interface and like our growth, uh, motions got kicked off for our commodities markets.

475
00:50:46.669 --> 00:50:51.532
Um, I think we're going to see a similar growth trajectory as our crypto market prediction markets there.

476
00:50:52.312 --> 00:51:04.458
Um, and so if, you know, we see another 20% category from there, um, with commodities, I think sports quickly go from where it is now to becoming like only 20 to 30%

477
00:51:08.340 --> 00:51:12.584
Yeah, so far, like, commodities markets have done really well.

478
00:51:12.624 --> 00:51:22.311
Like, they've grown at a rate of 100x within the first few days compared to, like, when we first launched our crypto markets.

479
00:51:23.072 --> 00:51:32.160
I think we've learned a lot of lessons from scaling the crypto side of things, and now a lot of people are interested in trading gold, silver, oil instead.

480
00:51:32.180 --> 00:51:33.140
Yeah.

481
00:51:34.041 --> 00:51:36.082
So I think that's going to be super interesting.

482
00:51:36.122 --> 00:51:40.803
And, you know, perps is entirely like a non-sports category.

483
00:51:42.404 --> 00:51:45.064
So that's going to diversify us more.

484
00:51:45.104 --> 00:51:53.107
And then on our like political markets, we've been taking a more researchy approach to it.

485
00:51:54.047 --> 00:52:08.882
similar to like a Bloomberg or like even like a Citrini or something like that, where we're creating like indices around our prediction markets, like batching them together and weighting them.

486
00:52:09.623 --> 00:52:13.847
So you can actually trade, like we have this thing called K-PAL, which is kind of like the S&P 500, but for like,

487
00:52:15.210 --> 00:52:16.751
the US political landscape.

488
00:52:17.672 --> 00:52:27.298
And then seeing how like different shifts in macro and in political developments affect that index.

489
00:52:27.958 --> 00:52:36.764
So there's a lot of stuff that we're doing that makes us a much more diversified platform than sports.

490
00:52:36.804 --> 00:52:44.189
And I think currently as well, crypto is just such a large part of it that it's by no means only a sports platform.

491
00:52:44.788 --> 00:52:46.409
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500
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506
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507
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511
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512
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514
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522
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524
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525
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Prediction markets have this thing where they're similar to crypto in the sense that they are just, they're very bottom up.

526
00:54:43.589 --> 00:54:49.214
Prediction markets as an instrument just feels like it all, it just organically naturally starts with retail.

527
00:54:49.294 --> 00:54:52.356
And as more retail comes, larger and larger participants arrive.

528
00:54:53.437 --> 00:55:04.309
And my question is how far we think that we can take prediction markets up that stack, like how far up the pyramid of capital can prediction markets really, really go.

529
00:55:04.930 --> 00:55:11.397
And back in 2017, I think when the crypto industry's imaginations about what crypto could do was at its wildest.

530
00:55:12.018 --> 00:55:23.520
we all kind of imagined this idea that prediction markets ultimately would kind of just like democratize or make very efficient markets for...

531
00:55:24.970 --> 00:55:28.833
The end industry, like the classic example is like the farmer, right?

532
00:55:28.853 --> 00:55:35.417
The farmer needs to like hedge an entire season of weather to protect the value of their crops.

533
00:55:35.457 --> 00:55:49.265
And if their crops dies because it's a desert, the farmer gets paid all the same because of some bet that was placed on like the rainfall in the region over this month of time.

534
00:55:49.505 --> 00:55:53.488
And maybe it's not the farmer making that bet, but a farmer buys insurance.

535
00:55:54.188 --> 00:56:02.553
And the insurance company can sell insurance to that farmer at a better rate because of prediction markets, because prediction markets allow for this like grand hedging.

536
00:56:02.894 --> 00:56:21.546
And so it's not the farmer, it's not the end farmer, it's not like the retail farmer person that's making this bet, but it's this massive, sophisticated, quant orientated insurance company that's using prediction markets and whether to be able to sell insurance to this farmer at a much cheaper, more beneficial rate to the farmer.

537
00:56:22.465 --> 00:56:24.686
It's like this idealized version of a prediction market.

538
00:56:25.627 --> 00:56:31.970
And my concern about prediction markets is they kind of feel like a retail instrument.

539
00:56:32.991 --> 00:56:37.854
Like inherently, like the prediction market is just like a really good platform for retail.

540
00:56:38.374 --> 00:56:48.760
And as we get further and further up the capital stack, it gets harder and harder for large financial institutions to use prediction markets to make very precise decisions

541
00:56:49.140 --> 00:56:52.921
opinions and express very precise trades about the market.

542
00:56:52.941 --> 00:56:54.481
Like hedging is a very precise thing.

543
00:56:54.521 --> 00:57:02.303
And so if you want to hedge something, you need to make sure that the event contract that you buy is actually doing the hedging that you want it to do.

544
00:57:02.803 --> 00:57:08.684
And prediction markets, at least so far, seem kind of blunt in that pursuit.

545
00:57:09.205 --> 00:57:10.885
And so the broad question is,

546
00:57:12.857 --> 00:57:35.050
How far do we think prediction markets as an instrument can get sophisticated to attract, you know, the largest and then the larger and largest amounts of capital in the world to become more like the CME, you know, like quadrillions of dollars of yearly volume trading hands about very precise hedging and create financial opportunities and make finance more efficient.

547
00:57:35.311 --> 00:57:40.734
How far do we think we can go and just like simulate for us like how we actually get there?

548
00:57:40.894 --> 00:57:48.944
You know, I think it's this, this like retail first adoption is pretty symmetric across all types of new markets.

549
00:57:49.104 --> 00:57:49.325
Like.

550
00:57:49.784 --> 00:58:02.133
You need early adopters and speculative capital to bootstrap liquidity and interest in new markets before it reaches the scale that institutions are able to size into.

551
00:58:02.153 --> 00:58:07.396
I think we are at that scale now where institutions can actually come in.

552
00:58:08.137 --> 00:58:10.959
And we've seen this institutional adoption happen.

553
00:58:12.540 --> 00:58:16.263
For example, and I think they can make very precise trades.

554
00:58:16.824 --> 00:58:23.630
Our first block trade, for example, was by some Houston-based environmental hedge fund.

555
00:58:24.330 --> 00:58:32.978
And they wanted to hedge against whether a specific price for May carbon allowance auctions in California would occur and

556
00:58:35.580 --> 00:58:47.585
There was a counterparty for that and multiple traders that were able to come in and sort of like help provide liquidity for that trade and price it.

557
00:58:47.725 --> 00:58:48.085
And so...

558
00:58:50.457 --> 00:59:03.462
You are able to reach out to the Kalshi team if you're an institution, ask us to create a market for a specific hedge or contract or idea that you have, and we can spin that up for you.

559
00:59:03.482 --> 00:59:05.623
It can be very bespoke.

560
00:59:06.825 --> 00:59:19.517
And then that market is then available to the rest of the world to go and price and provide liquidity to, to give you like a more efficient price than you otherwise would.

561
00:59:20.198 --> 00:59:24.502
So ultimately the bet that like we're making here is that

562
00:59:26.203 --> 00:59:51.848
Once you take this OTC structured products market, which is basically bilaterally negotiated deals in dark markets, and you bring them into the light, into what we call lit markets, like openly traded marketplaces, that increases the TAM and the activity and reduces the barrier to entry by an order of magnitude like 10x.

563
00:59:53.149 --> 01:00:07.202
So we can, for the institutional world, I think we can take this, like the entire OTC industry, bring it into prediction markets, take the entire structured products industry, bring it into prediction markets, and then create a much more liquid product.

564
01:00:08.118 --> 01:00:11.141
and more readily accessible version of it.

565
01:00:11.742 --> 01:00:16.868
And we're still, we are iterating on like the types of feedback that institutions give us.

566
01:00:17.008 --> 01:00:25.998
For example, like getting margin on prediction markets is probably our top requested feature for our event contracts.

567
01:00:26.058 --> 01:00:27.600
And that's something we're working towards.

568
01:00:28.521 --> 01:00:28.741
Um...

569
01:00:30.937 --> 01:00:48.344
I think in the meantime, our perps do provide that margin, and a lot of institutions have found that to be valuable as well to get capital-efficient exposure to these types of assets they want without having to roll their contracts.

570
01:00:48.364 --> 01:00:49.585
So, yeah.

571
01:00:50.792 --> 01:00:59.123
Yeah, I think we are climbing into those, you know, later stages of the capital stack.

572
01:01:00.004 --> 01:01:07.013
And there are like the crypto and commodities, politics types of markets.

573
01:01:08.235 --> 01:01:14.380
especially politics, for example, you're not able to find, you're really not able to enter those types of contracts anywhere else.

574
01:01:14.400 --> 01:01:20.206
Like Kaushiki is the only place that you can get that type of hedge.

575
01:01:20.266 --> 01:01:31.276
And politics is just so central to the way that our markets have been functioning

576
01:01:32.337 --> 01:01:51.572
over the past year, that it is really crucial for any hedge fund to establish some sort of, you know, position in prediction markets if they want to achieve, like, the best, you know, risk parameters or pricing efficiency across their portfolio.

577
01:01:51.973 --> 01:02:00.419
There's been this, like, mirror image of Polymarket and Calci with, like, with partnerships and, like, announcements

578
01:02:01.260 --> 01:02:06.383
I don't really remember this happening too much recently, so maybe it's a thing in the past, but I still want to ask about it.

579
01:02:06.423 --> 01:02:12.387
Is like Kalshi and Polymarket both announced like a partnership with XAI inside of the same week back in 2025.

580
01:02:13.007 --> 01:02:17.510
Like both announced being like the official partner of the NHL inside the same week.

581
01:02:17.610 --> 01:02:21.873
Like first Kalshi was the official prediction market partner of the NHL.

582
01:02:21.893 --> 01:02:23.654
Then like the next day Polymarket announced it.

583
01:02:23.754 --> 01:02:26.155
You guys both announced like this pop-up grocery store thing.

584
01:02:26.175 --> 01:02:26.936
There's just been this...

585
01:02:27.616 --> 01:02:29.118
If CalShe does it, Polymarket does it.

586
01:02:29.139 --> 01:02:30.641
If Polymarket does it, then CalShe does it.

587
01:02:30.861 --> 01:02:35.248
And that happens consistently for over a year.

588
01:02:36.289 --> 01:02:37.031
Why did that happen?

589
01:02:38.420 --> 01:02:40.781
It must be infuriating to see that from the outside.

590
01:02:41.661 --> 01:02:42.941
I'm just so confused.

591
01:02:42.961 --> 01:02:45.042
It's more infuriating to see that from the inside.

592
01:02:45.922 --> 01:02:46.582
It's like a whole bit.

593
01:02:47.042 --> 01:02:52.003
Honestly, I think it's just what happens when you have two big companies pushing each other.

594
01:02:52.023 --> 01:02:57.925
And it's kind of like two teams rowing their boats, right?

595
01:02:57.945 --> 01:02:58.525
Like you're just like,

596
01:02:59.436 --> 01:03:03.600
you're just like growing really hard and it makes you perform better.

597
01:03:03.620 --> 01:03:10.366
I think it has subsided a bit over the past like six months maybe.

598
01:03:10.386 --> 01:03:24.958
I guess we've just, I mean, honestly, like if you look at the metrics, we've really grown to be like four to five times larger, at least in crypto, we're 10 times larger than them in volumes.

599
01:03:25.038 --> 01:03:26.399
And so, yeah,

600
01:03:27.718 --> 01:03:34.604
Yeah, like, it's just, we're, like, not, I guess we're no longer competing as hard for the deals.

601
01:03:35.885 --> 01:03:38.127
Usually partners just, like, go with us.

602
01:03:39.328 --> 01:03:50.098
Otherwise, we're, like, otherwise, like, those deals are getting overbid heavily and people are just, like, burning money in the air.

603
01:03:51.219 --> 01:03:54.281
But I think, yeah,

604
01:03:55.478 --> 01:04:09.685
Yeah, we've also found our own lane a bit more, you know, like we're focused more about perps on perps, we're focused more on institutional adoption, we're focused more on growing our computer and commodities markets.

605
01:04:10.725 --> 01:04:11.126
And yeah.

606
01:04:12.583 --> 01:04:23.007
I think Polly has not, at least in the areas that I've talked about, they haven't really got into the same stage that we have yet.

607
01:04:23.327 --> 01:04:31.931
So we're still the first to rip a compute forward curve and grow our compute markets.

608
01:04:32.671 --> 01:04:36.892
Our perps platform, we got regulated and released first.

609
01:04:36.952 --> 01:04:39.673
I don't think Polly's has come out of beta yet.

610
01:04:43.043 --> 01:04:48.626
on the institutional side, we've just seen a lot more adoption, block trades, hedges happen through us as well.

611
01:04:48.806 --> 01:05:03.332
So yeah, I think we're just, we're ultimately probably pulled ahead and are no longer like fighting as hard over like tits and tats day to day, but looking more at like,

612
01:05:04.312 --> 01:05:07.576
the larger types of businesses that we can expand into now.

613
01:05:07.796 --> 01:05:18.606
One rumor that I heard was that the, like, I don't know if it was the NHL specifically, so I'm not calling them out specifically, but like there were so many of these where like some third party organization, like a sports league or whatever,

614
01:05:20.588 --> 01:05:23.270
both would partner with both prediction markets.

615
01:05:23.450 --> 01:05:27.732
One rumor that I heard was that like they could smell the competition.

616
01:05:27.873 --> 01:05:36.258
And so they would offer like they would bid it up between both Calci and Polymarket and extract from from both platforms.

617
01:05:36.698 --> 01:05:43.483
So it was actually like kind of like the NHL again, not trying to pick out on the NHL, but it was like the NHL as an example, just saying like, oh, like,

618
01:05:44.523 --> 01:05:54.186
We'll let you guys be our prediction market partner and then also go back to your rival and allow you guys to bid up the opportunity and then just accept both.

619
01:05:54.607 --> 01:05:57.888
Was there any sort of malice by any of these third parties?

620
01:05:58.948 --> 01:06:05.230
Is there anything to that rumor about a third party smelling blood in the water and swimming like a shark?

621
01:06:05.570 --> 01:06:07.391
Honestly, I don't know about the NHL deal.

622
01:06:07.431 --> 01:06:08.611
I wasn't part of that deal, but...

623
01:06:10.815 --> 01:06:17.698
I think in general, like that type of activity or it's just like, it's like something you do.

624
01:06:17.778 --> 01:06:21.961
If you have two job offers, you're going to like try to make them give you a higher offer.

625
01:06:23.401 --> 01:06:26.083
We haven't seen as much of that in the past six months.

626
01:06:26.483 --> 01:06:26.763
Okay.

627
01:06:27.463 --> 01:06:27.943
Just a rumor.

628
01:06:28.164 --> 01:06:30.365
Oh, but it did have stuff like that did happen.

629
01:06:31.349 --> 01:06:36.654
I mean, it was like, I was dealing with that type of stuff when like, just like random creators that had like 20K followers.

630
01:06:36.774 --> 01:06:37.775
Yeah.

631
01:06:37.795 --> 01:06:39.857
Like everyone thinks so.

632
01:06:40.538 --> 01:06:43.401
Everyone thinks that, you know, they can just like play us.

633
01:06:43.421 --> 01:06:44.482
Command the price, right?

634
01:06:44.542 --> 01:06:46.503
Yeah, it kind of worked for a bit, but maybe, yeah.

635
01:06:46.664 --> 01:06:48.786
Like not so much anymore though.

636
01:06:49.146 --> 01:06:49.306
Yeah.

637
01:06:49.526 --> 01:06:49.666
Cool.

638
01:06:50.327 --> 01:06:51.228
John, thanks for coming on the show.

639
01:06:51.468 --> 01:06:51.849
Thank you, man.

640
01:06:52.673 --> 01:06:52.933
Take care.

641
01:06:53.033 --> 01:06:54.134
Bankless H, you guys know the deal.

642
01:06:54.174 --> 01:06:56.356
Crypto is risky, so are prediction markets.

643
01:06:56.476 --> 01:06:59.079
But the risk is why we are here.

644
01:06:59.139 --> 01:07:02.362
The institutions have landed, so we are going even further west.

645
01:07:03.042 --> 01:07:03.723
This is the frontier.

646
01:07:03.743 --> 01:07:06.105
It's not for everyone, but we are glad you're with us on the Bankless journey.

647
01:07:06.325 --> 01:07:06.726
Thanks a lot.