EARLY ACCESS - "We Want to Be Bigger Than the CME" | Kalshi's John Wang

TRANSCRIPT
David:
[0:03] I'm here with John Wang from Kalshi. John, welcome to the podcast.

John:
[0:07] Thank you for having me.

David:
[0:09] John, is Kalshi a crypto company?

John:
[0:12] I think so. Yeah, I think in the crypto world, like there's obviously an on-chain, definition, like on-chain or crypto company. I don't think we're an on-chain company by any means. And there are on-chain prediction markets out there for sure. But crypto is our second largest business line. behind sports. We have 90% market share in the crypto predictions world. We, a lot of our like biggest, you know, partners are in the crypto industry, like Coinbase, Robinhood Crypto, like Phantom, and some others, they route their orders and trades through us. And so I think we're pretty deeply embedded in the industry. And that's pretty much what my role is, is to help us get, get even deeper.

David:
[0:58] Okay, so crypto is like there's the crypto sphere of influence. And I think what you're saying is Calci is somewhat inside the crypto sphere of influence in a number of different ways. But you're distinguishing it from Calci is not an on-chain company.

David:
[1:11] Does Calci want to be an on-chain company?

John:
[1:13] Ultimately, we just want to build products that are super easy to use and accessible to people. Like normal people that aren't necessarily super experts in crypto. And so our approach has always been to go the regulated route. I think US regulations are heading more towards being on chain with all the different legislature that's coming out. But at the current state of US regulations, it's not compatible. I think in several years, that's somewhere where we want to get to. Product-wise, I think the products that we've been building have been either.

John:
[1:58] Around trading crypto, for example, the largest crypto companies in the world, I would say are like Binance, Coinbase, Kraken.

John:
[2:08] These centralized exchanges, they are all about allowing their users to trade the price of crypto. And that's pretty much what our crypto prediction markets offer to our users. We also have our new regulated perps offering, which is the first regulated perpetual futures exchange in the US. 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. And also US institutions like can compliantly access it via like the type of infrastructure that they utilize. Also, I think like the deposits and withdrawals aspects of being like a centralized exchange is a large reason why many people still use centralized exchanges. And for us, crypto is an important rail for depositing and withdrawing from the platform. So obviously we have like the ability to just deposit and withdraw. Stable coins or crypto assets in the US. But internationally, we're open in 140 countries. 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 global monetary access and sort of the most frictionless way to convert from.

John:
[3:36] The local currency to the actual US dollar that we accept.

David:
[3:41] I see, I see. So for CalShit to accept international customers, the only on-ramp that's viable and easy to integrate is like the stable coin

David:
[3:49] or local stable coin, local fiat stable coin on-ramp into CalShit. How much of CalShit's business volume and trading volume is from outside of the US? Like how dominant is that side of CalShit?

John:
[4:03] Yeah, we're still predominantly a US company in terms of user base, But I think the international side is a huge focus of ours. We are taking a somewhat unique approach there, which is obviously like 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 unregulated route or you go onshore and work with the regulators in the US and kind of like, that's like the really hard path, right? Like spending years just doing legal stuff while like shipping a product in beta and not even being able to market it and such. So we're kind of taking a similar long-term approach to our international markets as well, where we're working with like either the regulators or like the largest brokers in each country, to sort of embed our prediction markets inside their products, similar to how we've been embedding them into Robinhood of Coinbase. And so we've been able to secure deals with like Wealthsimple in Canada or like XP, which is the largest broker in Brazil. So overnight, like 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. 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.

David:
[5:31] As Ryan and I have watched the growth of prediction markets, we have frequently used the comparison between Calci and Polymarket as kind of like Tether and Circle. You have the compliant on-chain, onshore version, which is the Circle, you know, who wants to work with the regulators, be very compliant. That's kind of the structural edge that Circle has. And then there's Tether, which is kind of like playing in the offshore euro dollar world, which is a very big world. 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. 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. Do you think that that is an accurate comparison and where do you think that comparison or yeah, that comparison breaks down if it does?

John:
[6:31] Yeah, well, it's always good to have some analogies to like reason across off. But I think with stable coins in particular, it's, the product ultimately is like selling the US dollar 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. So I think Tether has just found a greater pinpoint for the customer and therefore their growth internationally has been quite astronomical. Whereas with prediction markets, I think it's less about like.

John:
[7:11] You know, we're shipping something that is like US centric to the rest of the world. It's more about like each country and each type, type of really just group of people. They have different questions about the world that they care about. And ultimately, all our markets are just about creating like the types of relevant events and markets that people want to trade.

John:
[7:35] And so obviously both like all the leading prediction markets in the world right now have mostly had U.S. Teams that are like focused on creating U.S. specific markets. But we found like even some of our like markets in certain like whether it be like cricket, good, great adoption internationally. The World Cup was great for international adoption. crypto has been actually quite a strong, like everyone in the world knows about Bitcoin. Everyone in the world knows about ETH. And so that's also crossed a lot of borders. 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. But in terms of the approach, I think, yeah, it could be somewhat similar. Although I think we are like, compared to like most regulated companies, like a Coinbase or a Circle or instead of other regulated company. Kaoshi is much leaner and much more aggressive than these other companies in my view, just like my personal view. We 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.

John:
[8:53] And we're just have like an insane, insanely aggressive like product velocity and shipping speed. And also even from the regulatory side, like we pushed to legalize prediction markets and perpetuals. For prediction markets, we actually had to sue the CFTC.

John:
[9:11] So it's by no means like,

John:
[9:15] We're not really pushing for what's best for our customer.

David:
[9:18] What's the steel man for why the onshore compliant strategy for prediction markets is the right one?

John:
[9:25] The steel man, you mean like why it might be the right choice?

David:
[9:30] Give me the argument. So I think you could make two arguments. One is like the offshore version of the prediction market platform is going to be able to win based off of X, Y, Z. Or you can make another argument saying the onshore platform for prediction markets is going to win because of ABC. I want you to give me the one where like, well, Calci is the onshore prediction market platform. It's trying to lean into regulatory compliance and clarity and work with all the three-letter agencies. Why is that the best strategy? Why is that the winning strategy?

John:
[10:03] Well, CFTC is a four-letter agency actually.

David:
[10:07] That's a good point.

John:
[10:07] But we love our agencies. So yeah, the steel man I would say is you always have this choice of going offshore and VPN. And that does actually, it does make like doing no KYC and stuff like that, it does make onboarding the crypto native user base easier, I would say, because they've jumped through these hoops before. It's kind of what they're used to. But for like the 99% TAM of the world, which I really think is, the term 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, this like very exciting new instrument or 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. And the only way to tap into that user set, I would say, is you're able to like run paid ads on Facebook and Instagram. You're able to like put up billboards. You're able to partner with like household consumer names and like get integrated into large brokers and financial institutions.

John:
[11:22] Be on the app store. And as you grow to a larger scale as well, you're obviously under much more regulatory and compliance scrutiny. So I think it's really a critical thing to take this onshore regulated approach,

John:
[11:38] if you want to tap into that user set, which I think is the next user set that is up for the day.

David:
[11:45] You talked about the Perfs platform that CalShe is building out. Perfs is a pretty competitive place to be in right now. Like, perps are pretty hard. Two of the best perp platforms that I really pay attention to, Hyperliquid and LiDAR, have just some pretty insane technical chops to them. And they're really just becoming hyper-optimized around trading and the perpetual as an instrument specifically. So what makes Calci think that it can compete in this very competitive landscape around the perpetual?

John:
[12:12] 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. CME is an order of magnitude larger than even our perp exchanges in crypto right now. 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 like, some of the crypto like trading platforms that you know i personally am familiar with you're familiar with, for example we shipped a kalshi pro recently which is the first like uh official prediction market for trading terminal like released by a, 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. And so our fees for that are quite competitive and our liquidity is actually, it's still there's obviously like a ways to go, but, you can throw in like a six figure order size and not experience like too much slippage. And we're still working to grow that even more. So from like a pure like trading execution.

John:
[13:38] Competitiveness of economic standpoint, you're at no disadvantage trading on Kalshi Perps. And we're soon to launch like our non-crypto asset classes as well.

John:
[13:49] I think it was announced that we filed for gold and silver, which should be, coming in a matter of weeks. And obviously, we're looking to expand to other asset classes beyond just that. And really, that is the frontier, right, for perps, the perps industry nowadays. Like, Hyperliquid, I think around half of their volume nowadays is from these real world assets. And the center of all this real world asset liquidity is the United States. It's the U.S. retail and large U.S. Institutions that are currently providing liquidity or trading on a lot of these traditional financial platforms that need to access like a regulated, easy to access U.S. platform. But they so far haven't had the opportunity to sort of get the benefits and the innovations of perpetual futures.

John:
[14:43] No needing to roll your futures, no expiries, cheaper costs, all these things they haven't had access to until now with Kaoshi. So I think in this next frontier of real-world assets, we'll also be able to sort of, I think, actually be the industry leader in terms of liquidity, access, distribution, and also just product experience. Although, you know, we still haven't released it yet, so we can only celebrate it once we've done that. But I think that's the thesis, at least.

David:
[15:20] The last I checked, it was still just the Bitcoin PERP contract that the CFTC had approved. Is that still accurate? Or what are the markets currently available on the Kalshi PERP platform?

John:
[15:32] Totally, yeah. So we get a CFTC approval, like this quarter 40.3 filing for every single new asset clause that we list. So the Bitcoin one essentially approved crypto as an asset clause for us. We now have like over a dozen crypto assets on our perp exchange.

David:
[15:48] What are they just really quickly? Just Bitcoin, ETH, Solana? What are the crypto perps that you guys have?

John:
[15:54] Yeah, Bitcoin, ETH, we have Hype, we have Solana, Zcash, Near, SWE, Doge, XRP, if I haven't said that already.

David:
[16:06] Did the approval of the Bitcoin contract from CFTC, did that give Kalshi the ability to, what was it called, self-register or auto-register?

John:
[16:17] Self-certification, yeah.

David:
[16:18] Self-certification, thank you. Yeah, so you guys can self-certify crypto asset perps now.

John:
[16:24] Yeah, exactly. Obviously, we have to run our own risk models that have been CFTC approved. So it kind of follows the same process that it would for a Bitcoin perp, but it is much easier to like list something like...

David:
[16:38] So the Bitcoin perp gave you guys like a framework that like 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.

John:
[16:50] Exactly, yeah. And I think, you know, our leverage limits are lower than other sort of offshore platforms. And there are trade-offs to that. Like obviously some traders don't want to, like they don't want to take like lower leverage limits based on our like sort of like data analytics, on like on chain and other platforms, only like 20 to 30 percent of users trade above like our, leverage limit which is like 6x most traders we actually find they trade between 2 to 4x so that captures like the vast lion's share of traders so it's actually not as prohibitive as you might think but for our like, 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 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 calci and and our economics or like our fees are pretty competitive i think, compared to like Binance or like a Hyperliquid. We have lower fees at every year currently.

David:
[18:01] What's the plan for the CalShare Perp platform to evolve from here? 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. And one of the things they really want to do is they want to get tokenized real world assets. So like a real basis for the Perp to also trade on spot. So you have like three ingredients here. You have the actual tokenized equity or tokenized real world asset. You have a spot market also built into the platform. And then you have the perpetual itself. And with those three ingredients, you can really blossom into a bunch of different like optionalities, strategies, baskets, you know, it's kind of like open-ended in the permutations. And so that's how, that's like Lighter's opinion for how it kind of grows as a platform. Does CalShe also want to grow in that direction? Because you would also need to have a spot market and then also try to have a cash settled underlying.

David:
[19:00] What's the evolution plan for the CalShe perpetual platform?

John:
[19:03] Spot is definitely something we've considered. And if it makes sense to add to it, for example, like margining in Bitcoin or non-cash, that's pretty interesting. It depends on regulatory unlocks, but it's definitely something that I've been pushing for internally.

John:
[19:21] In terms of like actual roadmap, I would say we're primarily concentrated on, well, firstly, we're rolling out a bunch of interesting incentive programs soon. So those would make it pretty attractive, I would say, to trade on our platform, also to trade specific coins. And also, if you're like a big trader, 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 you don't have any troubles around order execution and stuff like that. Secondly, I think our Calchi Pro product we're leaning into pretty hard. So obviously the perps side of things, we have the trading view integrations and the types of other integrations that you might want to see, with more traditional brokerage for stocks or options like a Moo Moo, a Tasty Trade, stuff like that. So providing like a product experience with parity to that user set. And then also like cross-selling our existing predictions traders and acquiring new like more advanced traders that might be interested in predictions. Like that's where we see our like differentiation being. And then we're working really hard on unlocking these new asset classes. As I mentioned before, like starting with gold and silver and metals levels.

John:
[20:47] I would i think like perps is where we lie with perps like our perps product is isn't just like shipping a great perps product but it's also like how can we co-mingle it with our the benefits of our predictions product so, on our perps product not only do we have like this like we have this calci social which is similar to like fomo or like i think robin hood social recently released something that looks similar to our platform so.

John:
[21:17] That's quite that's quite exciting there's like a troll box on perps that is similar almost like gives me flashbacks to bidmex back you know 2017 2018 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 an annual basis. And we sort of distill those insights into our perps product as well. 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. 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. 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 much more understandable for our user base. Like those types of things have helped a lot. 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 PURPS and predictions together and build it to like a user base that is new to PURPS and they may be like a simple PURPS, trader or like a more advanced day trader.

David:
[22:40] Is there a vision of just like a single unified Kalshi platform where predictions and perps and that social feature that you were talking about is all kind of unified in one single interface? Because as I understand it now, like perps and the prediction markets are just not the same thing, a separate platform is siloed. Is there a grand unified version of Kalshi in the future? Or how do you guys think about just like the synergies of these products actually coming together?

John:
[23:08] So our perps, at least the simple product, is quite integrated into our app already. So if you go on our mobile app, we have a tab for perps. If you go onto our web app, we also have a tab for perps. And then the current bifurcation is more so with our simple experience and our pro experience. And we're working to combine that a bit more or make it a bit more seamless and switching. but,

John:
[23:38] It is quite integrated, and I would say that we do want to provide a pretty cohesive experience.

David:
[23:45] Let's get into prediction markets, since that's the main bread and butter of Calci. 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. And what I'm talking about is prediction markets are accurate because they pay people who have private information to reveal it with their traits. Like that's kind of the whole point of prediction market is like if you have alpha, 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. 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. And that's how we gain information from these prediction market platforms. 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. 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 information coming into the market.

David:
[25:05] 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. And so there's a tightrope that a prediction market has to walk here, where you do need to attract 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. They'll just, all the fishes at the poker table will get milked and then they won't be able to come back. What's this strategy for Kalashie to find the equilibrium between these two polarities?

John:
[25:47] Yeah, that's a great framing. You know, I think it is definitely a spectrum. Where we sit on that spectrum is we are like a market's first company. Like ultimately we are building an exchange. 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. And then also for traders who do have insights into a certain topic or have done more research than others, are more resourceful or curious, they are able to also profit off of.

John:
[26:33] Their extra research and their curiosity. So we do draw a bright red line about insider trading. And I think there are also many markets that like it's like insider trading, I think, is, There are many markets where users would actually be able to do research and get edge without resorting to insider information or quote-unquote private alpha. 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. We've seen a lot of traders just do exceptionally well. Even in our like music chart markets where you might think that, you know it's it's kind of like voodoo magic that's it's kind of just like what you what you might think as as kind of like an outside observer but if you're in the trenches you're like looking at these music charts all day, we have this guy called Grinny Top Ten he's, basically been like a music chart like youtuber super like ranking sort of type of guy and super in the weeds of Ariana Grande, Billboard charts, etc..

John:
[27:51] He's just consistently been able to find edge by being super involved in these communities and these like different information sources. And so, you know, there are definitely fair ways to find edge. We have a ton of like infrastructure around preventing insider trading from even happening in the first place, but also surveilling the markets and tracking it when it does happen. 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. There are already these types of surveillance platforms that offer these services to sports companies, sports betting companies, prediction market companies. And for stocks, for insider trading, There are companies that provide lists of like executives and all their associated people.

John:
[28:55] So yeah, I think we've done like a lot of work around preventing and enforcing against insider trading. And then there's this like philosophical question that you mentioned, which is, is it even like worth preventing insider trading if the goal is to, be kind of this like information source of truth? Type of platform. And so my response to that, and I thought about this a lot when I was joining Kalshi is.

John:
[29:25] Ultimately, we want to service people at scale and scale our financial markets to their greatest ham. And at scale, 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. And the only way you can achieve that is by preventing insider trading. 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, 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 coming in market makers aren't going to quote anymore liquidity providers are going to pull their quotes, and therefore like no one will have a liquid market to trade yanks and then you won't have a signal in any ways, And so you just have to draw this line against insider trading if you want to

John:
[30:27] have market integrity and healthy markets that thrive in scale.

David:
[30:31] Is insider trading properly defined for the prediction market use case? Maybe I should have looked into this a little bit better before doing this podcast, but insider trading I think is very well defined for the securities context. Do you think that the definition of what insider trading is appropriately carries over in like a high fidelity way into prediction markets? 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? Like, do you think we need to reconsider what insider trading means in the prediction market context? Or do you think that those laws are actually pretty well defined in the first place?

John:
[31:19] Yeah, well, the great thing is we actually defined like insider trade, what insider trading is on every market. And we flag those types of markets that are at a higher risk of insider trading.

David:
[31:33] So Kalshi defines what insider trading is for its own markets. Is that what you just said?

John:
[31:40] Well, no, there is a framework for defining insider trading at like the regulatory level. But then like when it comes to sort of communicating the and setting the bounds for our users we have like extra guardrails up at the market level so for example we, on the ui we say that politicians or politically associated persons congressmen etc are not allowed to trade on our political markets they can trade on our sports markets and stuff like that but they can't trade on our political markets.

David:
[32:12] They can't, they can't trade on any political markets. They can't trade inside the political category?

John:
[32:18] Well, I'd have to check on like the specific, Because I think it depends a lot on like what type of political person you are. Also, I'm more so on the crypto commodities and perpetuals side of the business. But I think like generally we don't want people who are like in Congress to trade political markets. I think I'm pretty sure that one, like 90% sure that one is true, that we prevent them. And so, yeah, there's the preventative step and then there's the at-the-market step on the UI. And then even for our markets, as you mentioned, sometimes insider trading does happen.

John:
[33:08] There's no bulletproof solution to prevent insider trading in the stock market. Same thing applies in prediction markets and there are different types of trade-offs and risks that we also face here. The best thing that we can do is to make the traders, 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 off guard, right? And so we do have flags, like before you enter, certain types of markets, I think sometimes on like our, some in different places, 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.

David:
[34:02] I do think it's interesting that prediction markets have run up against the whole notion of IP, intellectual property. And maybe to kind of go back and like set the same stage of the original question, we had the famous case of the 2024 presidential election. The guy in France, I think, who financed a bunch of polls domestically in the United States to go get information. And so he paid, they paid, this one trader paid for a bunch of polls to be made in swing states. And like the nature of the poll was very precise. And this trader just got in this information. And then as a result of hearing those, the outcomes of the polls, they made a very large position on Donald Trump. Is that insider trading? Absolutely not. Like not in the slightest. 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. So is that inside trading? Definitely not.

David:
[35:05] 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. Now that information was owned by Google in a sense. 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. 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. Sold information, sold IP that wasn't his. I don't know if that counts as insider trading because again, insider trading is like typically in a securities context

David:
[35:47] From a property rights perspective, it makes sense to me that that Google employee ought not have sold information that was owned, again, in theory, by the company. And it seems to me that, like Kalshi, the private market is just sticking its finger up in the air and be like, that doesn't feel right. And so therefore, we're not going to allow it to happen on the platform. But I'm wondering if 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 a law in Congress or something just stated as a rulemaking from the CFTC. What do you think about that?

John:
[36:38] I would say all our public comments so far about this type of topic is that we're in full support of it. We want more clarity. We want the regulations to be there and clear and to protect our traders and to also satisfy people's concerns. And 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. 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. So yeah, that's something we've been pushing for. We're very pro-regulation when done the right way.

John:
[37:27] And when it comes with benefits such as like giving everyone a better sense of clarity.

David:
[37:33] Now, I really like your point about the best market structure is the most fair one, which is an argument for like a more restrictive constraint on alpha traders, traders with alpha, traders with information. 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

David:
[38:02] Through whatever means possible. And then now you have that alpha and now you get to sell that to the market because you harvested it from the real world as opposed to somebody actually doing insider trading. And so one is fair, one is less fair. And I take the point that the more fair version of the prediction market creates a more healthy market structure. You attract more market makers, retail feels that it's more fair and less extractive. But also at the same time, I do think that just like a little bit of insider trading is good too. Just a smidge, just like just on the line, across the line of like what insider trading is on occasion, just because like, that's the whole point. And this is something that Robin Hanson says, who's like one of the originators, progenitors of like the concept of prediction markets. It's like, yeah, like this is how we get information out. This is why from an information perspective, this is how we attract it. and prediction markets can bring more information into the world if they're allowed to do this. And in addition to prediction markets, there's whole second, third, fourth order consequences of 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. And so how would you respond to that? 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.

John:
[39:29] Those types of prediction markets, they actually were the predominant type of prediction markets before, I guess, like Kaoshi really took off commercially over the past two to three years. Prediction markets, they originated from being kind of like either this play money or like, 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 this like sort of really accurate beacon of truth where people, you know, they don't really have any like many rules, I guess. And so I guess like my answer is like, yeah, if you have that, then it'll probably look something like that. 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. And so you're just going to get into this kind of cycle of, not increasing your liquidity and your scale and being forever kind of constrained to a much smaller scale as a nice thought experiment, but not super,

John:
[40:45] I guess, useful beyond the pure number that you create, if that makes sense.

David:
[40:52] 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. 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. Obviously prediction markets as a platform want to be more than an alternative to like the sports books, you know, sports books. 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

David:
[41:32] Competitor to sports bookies, to like the FanDuel, the DraftKings of the world. But I think everyone who's paying attention to prediction markets wants more from prediction markets. 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. And that also comes with that, some level of like financial utilization, some sophistication, like we're talking about insurance companies and, you know, financial hedge funds coming in. And you would, I would guess you would see a very big drop in sports trading volume to the, because everything else grew, like, I don't know, the weather or, you know, more markets around like the Federal Reserve, things like this. 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? What's the plan from getting A to B?

John:
[42:31] That is our ultimate goal, is to be the largest exchange on the planet. So I make derivatives, for example. 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 like fast shipping tech company while, being kind of like a very aggressive, like a consumer growth company as well. And so being able to own the, like the trader relationship has been quite important. I think it's been important to the growth of Robinhood. It's been important to the growth of IBKR as well. So we have that as a differentiating factor. We own the trader relationship.

John:
[43:20] We also, I think, have like a leading position in the two, I would say, like newest asset classes when it comes to the traditional global financial scene, that are like instruments, I guess, being prediction markets and perpetual futures. So at least from like a regulated onshore perspective. So that's like our foot in the door when it comes to really having a fighting chance at getting to that stage. And taking that institutional like motion and seeing it all the way through is something that we're currently like allocating a lot of our time to. We've been doing a lot more block trades and doing a lot more sort of broker relationships as well. Like we're in basically all of the largest broker platforms in the US now.

John:
[44:13] 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. We've done some interesting hedges as well through like our weather markets. We had like an ice cream shop do stuff there for the World Cup. There were dozens of bars that hedged promotions through Kaoshi. So they would offer, for example, like free drinks for everyone if the U.S. Won the World Cup like for that game that night. And that proves to be quite successful and actually like have a lot of utility when it comes to like hedging out the risk of these types of conversions. 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. Whether, you know, the odds of whether the clarity act will pass.

John:
[45:16] Beyond that, I would also push back against like Kaoshi being like a primarily sports business currently.

John:
[45:23] Firstly, we have Perps, which is doing an order of magnitude more volume in the first month than any of our prediction markets, I guess, like since launch. Perps 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, you know 20 to 30 percent of total exchange volume now and that's just for crypto, excluding you know politics economics, we recently launched a lot of, the same types of markets and user interface and like our growth motions got kicked off for our commodities markets, i think we're going to see a similar growth directory as our crypto market prediction markets there. And so, you know, we see another 20% category from there with commodities. I think sports quickly go from, where it is now to becoming like only 20 to 30% of the exchange volume. And yeah, so far, like commodities markets have done really well. Like they've grown at a rate of 100X within the first few days of compared to like when we first launched our crypto markets. 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, or oil instead.

John:
[46:49] So I think that's going to be super interesting. And, you know, perps is entirely like a non-sports category. So that's going to diversify us more. And then on our like political markets, we've been taking more researchy approach to it, 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, It's like batching them together and weighting them so you can actually trade. We have this thing called K-PAL, which is kind of like the S&P 500, but for the U.S. political landscape. And then seeing how different shifts in macro and in political developments affect that index. So there's a lot of stuff that we're doing that makes us a much more diversified platform than sports. 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.

David:
[47:54] Prediction markets have this thing where they're similar to crypto in the sense that they're very bottom up. Prediction markets as an instrument just feels like it just organically naturally starts with retail. And as more retail comes, larger and larger participants arrive. 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? And back in 2017, I think when the crypto industry's imaginations about what crypto could do was at its wildest, we all kind of imagined this idea that prediction markets ultimately would kind of just like democratize or make very efficient markets for crypto.

David:
[48:41] The end industry, like the classic example is like the farmer, right? The farmer needs to like hedge an entire season of weather to protect the value of their crops. 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. And maybe it's not the farmer making that bet, but a farmer buys insurance. 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. 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.

David:
[49:37] It's like this idealized version of a prediction market. And my concern about prediction markets is they kind of feel like a retail instrument. Like inherently, like the prediction market is just like a really good platform for retail. 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 opinions and express very precise trades about the market. Like hedging is a very precise thing. 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. And prediction markets, at least so far, seem kind of blunt in that pursuit. And so the broad question is,

David:
[50:26] 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, like volume trading hands about very precise hedging and create financial opportunities and make finance more efficient. How far do we think we can go and just like simulate for us, like how we actually get there?

John:
[50:54] You know, I think it's this, this like retail first adoption is pretty symmetric across all types of new markets. 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. I think we are at that scale now where institutions can actually come in and we've seen this institutional adoption happen. For example, and I think they can make very precise trades. Our first block trade, for example, was by some Houston-based environmental hedge fund. And they wanted to hedge against whether a specific price for May carbon allowance auctions in California would occur. And 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. And so...

John:
[51:59] 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. It can be very bespoke. 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.

John:
[52:27] So ultimately, the bet that we're making here is that 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. make sure you're like 10x. 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 and more readily accessible version of it. And we're still, we are iterating on the types of feedback that institutions give us. For example, like getting margin on prediction markets is probably our top requested, feature for our event contracts. And that's something we're working towards.

John:
[53:33] I think in the meantime, like our perps are like, do provide that margin. And a lot of institutions have found that to be valuable as well to get, you know, capital efficient exposure to these types of assets they want without having to roll their contracts. So yeah. Yeah, I think we are climbing into those, you know, later stages of the capital stack. And there are like the crypto and commodities, politics types of markets, especially politics, for example, you're not able to find, you're really not able to enter those types of contracts anywhere else. Like Calci is the only place that you can get that type of hedge. And politics is just so central to, the way that our markets have been functioning over the past year that it is really crucial for any hedge fund to establish some sort of, position in prediction markets if they want to achieve the best risk parameters

John:
[54:44] or pricing efficiency across their portfolio.

David:
[54:47] There's been this mirror image of Polymarket and Kalshi with partnerships and announcements. 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. Kalshi and Polymarket both announced a partnership with XAI inside of the same week back in 2025. Both announced being the official partner of the NHL inside the same week. Like it was first CalShe was the official prediction market partner of the NHL then like the next day Polymarket announced it you guys both announced like this pop-up grocery store thing there's just been this if CalShe does it Polymarket does it if Polymarket does it then CalShe does it and it's that happens like consistently for like over a year why did that happen?

John:
[55:33] It must be infuriating to see that from the outside.

David:
[55:36] I'm just so confused It's

John:
[55:37] More infuriating to see that from the inside yeah it's like a whole bit honestly I think it's just what happens when you have two big companies pushing each other and like it's kind of like two teams like rowing their boats right like usually.

John:
[55:53] You're just like growing really hard and it makes you perform better. I think it has subsided a bit over the past like six months, maybe. I guess we've just, I mean, just 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. And so, yeah, like it's, it's just, we're, we're like not, I guess we're no longer competing as hard for the deals. Usually partners just like go with us. Otherwise we're like, otherwise like those deals are getting overbid heavily and people are just like burning money in the air. But I think, yeah, it's, it's, 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 compute and commodities markets. And I think Poly 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. So we're still the first to grip a compute forward curve and grow our compute markets. Our perps platform, we got regulated and released first. I don't think police has come out of beta yet.

John:
[57:21] On the institutional side, we've just seen a lot more adoption, block trades, hedges happen through us as well. So, yeah, I think we're ultimately probably pulled ahead and are no longer fighting as hard over, tits and tats day-to-day, but looking more at the larger types of businesses that we can expand into now.

David:
[57:43] One rumor that I heard was that the, 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, both would partner with both prediction markets. One rumor that I heard was that like they could smell the competition. And so they would offer like they would bid it up between both Calci and Polymarket and extract from from both platforms. 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. 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. Was there any sort of malice by any of these third parties? Is there anything to that rumor about a third party smelling blood in the water and swimming like a shark?

John:
[58:40] Honestly, I don't know about the NHL deal. I wasn't part of that deal. But I think in general, that type of activity or it's just like it's like something you do if you have two job offers you're gonna like try to make them give you a higher offer, we haven't seen as much of that in the past six months.

David:
[58:58] Okay just a rumor oh but it did stuff like that did happen

John:
[59:03] I mean it was like I was dealing with that type of stuff when like just like random creators that had like 20k followers, like everyone thinks everyone thinks you know they can they can just like play us.

David:
[59:15] Command the price

John:
[59:16] Right Yeah, it kind of worked for a bit, but maybe, yeah, like not so much anymore though.

David:
[59:22] John, thanks for coming on the show.

John:
[59:23] Thank you, man.

David:
[59:24] Take care. Bankless Nation, you guys know the deal. Crypto is risky, so are prediction markets. But the risk is why we are here. The institutions have landed, so we are going even further west. This is the frontier. It's not for everyone, but we are glad you're with us on the Bankless Journey. Thanks a lot.