- 8 minutes ago
Prediction market platform Kalshi has grown into a multi-billion-dollar business thanks to retail traders putting money on everything from election outcomes to reality TV winners. But now the company wants institutional investors — think hedge funds and brokerage firms — to use the platform. Why the push, and will it work? BI's Dan DeFrancesco sits down with Kalshi's Head of Institutional, Andy Ross.
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00:10Hey, good morning, good afternoon, good evening, wherever you're watching us from, thanks for
00:15tuning in. I'm Dan DiFrancesco, lead writer for the BI Today newsletter. So prediction markets
00:20have exploded onto the scene in recent years from sports to politics to weather. Everyday investors
00:25have jumped at the chance to make bets on just about anything. And now, Kalshi sees an opportunity
00:30to get institutional investors and companies onto its platform. Today, we've got the man
00:35responsible for building out that business, Andy Rosh, Kalshi's head of institutional, joined
00:39the company this year after a long career on Wall Street. Andy, thanks so much for joining
00:43us today. Thank you for having me. Great to be here. Of course. So we've got a ton of questions
00:46we can get into. But before we get into that, just a quick reminder, we'd love to hear from
00:50you. Drop your questions, your comments in the chat, and we'll be sure to address them
00:54in the convo. So to start, Andy, I want to, you guys are doing great in the retail space,
01:00right? Spring, you raised a billion dollars. World Cup, massive boon for you. You're the
01:06biggest player in the U.S. market for prediction markets. Now you're going after Wall Street.
01:10So who are you targeting? Because that's obviously a very different market and demographic than
01:14the retail folks that you've been so successful going after.
01:17Well, I think, first of all, I guess there are a couple of things. So first of all, there's
01:21a huge amount of quality data that comes out of prediction markets. The users in those markets,
01:25we don't generate the data, but the users, the buyers and the sellers, predicting yes
01:30or no in these markets, give us a huge amount of information. That is valuable as alpha to
01:36pretty much everybody on the street. So first of all, it's like we've got a great quality
01:39data, give that to people. And then secondly, we've got people using it to trade, hedging.
01:44And we do that through a variety of ways. Firstly, you know, just trade on the market. But secondly,
01:49what Cartier does is work with people and say, what's the market that you want? What's the risk
01:53that you have? What's the problem that you're trying to solve? And let's build a market for you.
01:58Let's build a market that will help you make better decisions. Let's give you better data to make
02:03better decisions. And so to start with, it's a data product. Secondly, it's like a trading product around
02:09that. And then, so that's where we are. So when you talk about institutions, talk about
02:14institutions, I know, you know, there was an example earlier this year, a bar who was running
02:19a Knicks promo, hedged itself, right, which is really interesting. And then just this week,
02:25story about an ice cream shop that hedged itself with the weather, which also, side note, I don't
02:29know about you, I don't care what the temperature is, I'm eating ice cream. Yeah, me too. I love ice
02:33cream.
02:34Yeah. Look at my, I've got a dad blog for eating ice cream. I mean, the ice cream, the people
02:38that also,
02:38I don't do iced coffee during the winter. I don't get it. Weather does not temper my menu. But so
02:44those
02:44are really interesting examples. But obviously those, with all due respect to them, a little bit
02:47small potatoes, right? Is that the, when you talk about institutions, is it as low as that? And how
02:52big does it get? Or what do you view as the target when you're talking about this push into
02:56institutional firms? So I think there's a few things there, right? So to start with, what if, what would,
03:01think about the development of the futures market, think about to Chicago, think about even back to
03:05Netherlands, and it was informed, right? Is to allow individual traders to hedge their risk.
03:10And that's where it started. And then we've got a huge amount of liquidity now, and a huge amount
03:13of standardization, which is great. It generates product, and it generates risk, and it generates
03:17a lot of volume. Take the ags market. We don't have very much in the ags market, but it's a
03:22really
03:22interesting topic. There are about 30 products that really trade in future sense on the ags market.
03:28But there are hundreds, even probably thousands, of individual products that exist. So you need to be able
03:33to think about what are all of those use cases. And so what the prediction markets do is, because
03:39they're very simple products, because they're funded products, because they're a simple, you and me
03:42agree, you think it's 50% likelihood, I think it's 50% likelihood, we both put those 50% into
03:49an account
03:50that gets locked up in CFTC money. It's very low risk. It's very easy to generate a new product. So
03:56we
03:56can evolve and iterate new products quickly. So given all of that kind of structured stuff,
04:02yeah, sure. Little hedges that allow people to do sponsorships, whether it's hedges that allow people to do
04:08promotions, sure. That's really interesting and useful. Absolutely part of any footprint, and useful for
04:14society, useful for America Inc., for their corporations to be able to hedge things that
04:19previously they weren't. Being able to hedge makes your business better, makes you take more risk. It means you can
04:24run
04:25your business better. But clearly, that's not where the only place we want to be. And so we have some
04:30really interesting products. We developed a product recently, which was a market for an environmental
04:36hedge fund in California to do with solar tax rebates. And that ended up trading $600,000, $700,000, mainly
04:44in the
04:44block market. But that was a perfect hedge for a perfect situation for those people on that market. And so
04:50we
04:51generated real risk transfer. You know, that's not small, given the gamma associated with that is pretty big. The
04:57payoff function's large. Right. You know, any trade that you're ending up making, you know, $600,000, $700,000 from,
05:04or
05:04losing $600,000 or $700,000 from, it's a pretty big, pretty big trade. Yeah. And we don't have a
05:09lot of leverage in
05:10that, but the gamma makes that pretty big. And the way I would think about that, if you would think
05:15about that from a
05:16notional perspective, you might want to times that by 20 to think about that from a, how much risk you
05:20would trade on some sort of normal future or whatever. So they're pretty big trades. And we're
05:25just at the early stages of seeing that development of those markets. Yeah. So you, the way you broke it
05:31down, it's setting, I want to get back to the data aspect, because I think that's fascinating as well.
05:34But the way you break it down, you kind of have these contracts that you guys are consistently rolling
05:39out. Like recently, there was one about clinical trial pilots. Yeah. Right. And basically, the idea is,
05:44instead of having to bet on or make a, you know, assessment on a company, you can just make an
05:48assessment on a specific trial that they're doing. And there's a yes, no answer there. And then on the
05:53other hand, you have, like the example you gave with the block trade, a more bespoke, a more
05:57customized. Yep. Is it fair to say that maybe the customize is what you view as the path for
06:04Cal Street for the bigger fish? And the more, you know, the other contracts are more for like the
06:10everyday mom and pop shops or the SMBs that kind of want to get in and hedge themselves
06:14a little bit? Or do you see it as kind of either or? I actually, I almost see it the
06:20other way
06:20around. I think that the reality is that to be successful in an institution, you need a variety
06:27of things. Yeah. You need to get your data out to people. You need to have technology providers
06:31so that people can use the same kit that they're already using to trade. You need clearing brokers
06:35to be available to manage the risk onto the market. So there's a lot of bits and pieces
06:40that you need to go through before people can trade. And those are definitely things
06:43that we're being super successful actually in crunching through and getting people to
06:47connect to. But as you get those through, it means the number of people who can participate
06:52on the market, the number of people who can trade on the market just goes up and up. The
06:55amount of risk transfer that can occur on the market goes up and up. And so I think that
07:00the design structure is for individual small companies to be able to get onto the market
07:05and big companies, hedge funds, asset managers, banks to be able to trade that as well. Sometimes
07:11they'll be trading the same product, maybe payrolls, maybe an inflation product because
07:14that's a risk that we have. But maybe it's whether it's a product that someone wants to
07:19trade in an ice cream shop in Florida. Maybe someone else wants to trade whether because
07:24they've got a hurricane insurance that they want to manage the risk of in Florida. And so all
07:29of those can trade the same contract in the same space. And it's up to us to broaden the
07:34universe of people who can get into that market, not just individuals, but all of the corporates,
07:41the hedge funds, the asset managers, et cetera, that can do that.
07:45Right. What do you feel this is ultimately disrupting? Because you touched on a couple
07:50of things there, right? We're talking about banks that traditionally a company will come
07:53to them and say, I have this business, I need to protect this. And you also mentioned kind
07:57of the insurance aspect. You might go out and buy insurance. Where do you see this offering?
08:01And as you push into the institutional market, what's the area of business that you feel like
08:05is really disrupting that you feel like CalShe is coming in and trying to compete with?
08:10So I think, firstly, the ability to trade on an individual event is something that didn't
08:19exist really before prediction markets and especially CalShe. So if you were like, I'm from the UK.
08:25You might have picked that up in my accent. But we had this thing called Brexit where we
08:29voted to leave the European Union. And the reality of that was that two things. First of all,
08:37it was like, it's not going to happen. And the second thing was, if you're worried about
08:41it's going to happen, you need to short the stock market. And what happened is one,
08:46the European, the UK voted to leave. And two, the stock market went up rather than went down.
08:50So it's like the hedge was wrong and the prediction was wrong. Prediction markets give you an ability
08:55to trade that actual event. And that, I think, is just so useful for society. And so I don't
09:02think, necessarily, it competes with anybody. Because you've got this now, this way of expressing
09:08risk. Now, sure. Let's take an example. You might think that the payroll number is going to come in
09:13really spicy and hot. And payrolls drives a lot of things. It drives FX. It drives front end of the
09:19interest rate curve shape. Sure. So people might be worried about that. And at the moment, they might
09:23be going in and saying, well, I'm just going to do some hedging here. Or I'm going to take some
09:26FX
09:26option exposure on. Sure. You might find there's a little less of that. Because people come in
09:31and lift a large block in trading a payrolls number to get their payoff, their risk management
09:36of their position instead. But fundamentally, I don't think it competes with that. I think
09:41it's just an added source. So one of the examples, Carl, you have is what we call KPI markets.
09:45So take Tesla. How many cars? Is self-driving regulation going to be passed? Will Mr. Musk remain
09:52as CEO and chairman? Those are kind of atomization of the risk. I don't think that necessarily
09:57competes with an equity market. And I don't think it competes with an equity options market.
10:01It just adds another source of data, another way to express as an individual, as a company,
10:07whatever, your views on that market. So when you go to pitch these clients and you try to get more
10:11of these players onto your platform, is it you don't necessarily need to change your trading strategy
10:18or your risk management strategy at all? This is just in addition? Or is it some ways it can
10:22supplant some of it, do you think? I think threefold. One, you've got alpha generated
10:27out of the data, which I said at the front, which will help you, I think, with your trading
10:31strategy. So perhaps it's augmenting what you're doing. Two, I think that, yes, you can use it
10:38to add risk management layers to your trading to allow you to manage tail risks, to manage risks
10:48that were previously unhedgable, that you were taking a basis trade on, that you were thinking
10:52because, oh, I'm worried about payrolls, therefore I'm doing these seven trades. You don't know
10:56that those seven trades are actually about payrolls because, A, you've got to make a prediction
11:00on payrolls, but then, B, all of the underlying markets, which are on a sort of a second order,
11:05have got to behave in the way you think that they're going to behave.
11:07Right.
11:08Because it's fine to be right on payrolls, but if someone else says something else at the
11:11same time, like we're going to do tariffs or something, then everything could move and
11:15actually your hedge is the underlying product, you know, that you wanted vis-a-vis the payrolls
11:22number. And so I think it's additive. They're an additive for a risk management thing. I think
11:28that the perpetual products that we've launched, which are futures that don't expire, perpetual
11:34futures. I think they are somewhat competitive to futures products that, say, CME and ICE and
11:41others have, and who our viewers are competitors in that space. And I think, yeah, there could
11:47be a view of some cannibalization of that, but that's not to say that perpetuals are better
11:53than futures, and it's not to say that futures are better than perpetuals. What it's to say
11:56is that those products can be really good for risk transfer if you don't want to have to roll
12:01it every month or every quarter. And so I think there are some scenarios where things we've
12:05done at CalShe can be cannibalistic, if you will. But in general, I think we're adding a
12:12richness of data, a richness of trading opportunity to institutions. And frankly, what's super interesting
12:19is that institutions are coming to us. I've got a call later on with a very large institution.
12:24You want to say who? No. Thank you. Just in case. Thank you. And we are designing a product
12:32or a series of products for them specifically that they want us to launch because they want
12:36to get the information value associated with their existing portfolio out of these markets
12:42that we're going to launch for them. And so I don't think that's cannibalistic. That's providing
12:47alpha signals to trading in legacy asset classes as well. So they want you, they're going to go to
12:54you, and they want you to create a market that then they're going to look at the data on how
12:58that market trades, and that's going to inform their decision. So it's not even, the actual
13:00market you're creating isn't actually the hedge. It's who jumps in and starts betting on it,
13:04and then they're going to look at that, and that's going to assess another decision.
13:07Trading on it, yeah. Let's not use the word best. Derivative exchange.
13:10Sure, sure. So Roy in London has a question, or a statement. This institutional test is not whether
13:17prediction markets are interesting. It is whether they offer liquidity, reliable data, and risk
13:22controls that sit comfortably inside an existing trading stack. That is a much harder product than
13:27attracting retail volume. So I want to take a step back, and I want to break down these.
13:32I think Roy's right, by the way. Very clever man.
13:35Yes. So liquidity. Because the thing I wonder is, as you start to create these custom hedges,
13:45CalShe does not take a position, right? No. It is just a platform. It is bringing...
13:49CME or ICE or whatever. Right. It's connecting buyers and sellers. It's just connecting buyers and
13:52sellers. As you get more customized, you know, everyone has an opinion on where LeBron James is
13:58going to go, or who's going to win the World Cup, as we've seen, right? You get a lot of
14:00activity on
14:01that. But how do you navigate the liquidity problem when a specific company comes to you with a very
14:06specific hedge that they want to put on that? How do you get the liquidity on the other side when
14:10these... Hopefully, if things go well for you, these are big trades that they want to put on.
14:15So I'll take a step back and talk about data for a second.
14:21We measure the quality of the output of a prediction using something called a Breyer score.
14:25It's a mathematical term. And a Breyer score is a way of calibrating a model.
14:29And so let's say that something happens six times out of ten, and the model said it was going to
14:34happen
14:34six times out of ten, and that happens consistently, the Breyer score would actually be zero.
14:37Because the model is perfectly calibrated to actual events.
14:41If you take your iPhone out of your pocket, you look at your weather app, and that's probably
14:46got a meteorological model, probably got a Breyer score, like a day out, of about 0.1,
14:52which means roughly, using English rather than complicated maths, means roughly, then 90%
14:57of the time, it's about 90% right.
15:00So what Calci does is say, right, okay, we've got all of these markets.
15:04Now, if you take our markets, and we rerun this calibration recently, if you take all
15:07of these markets, and you look at markets that have traded over $50,000, so that's
15:13point one, one week, and we exclude sports markets and some of the culture, some of the
15:21mentioned markets, because they tend to, not because for any other reason, they just don't
15:24trade like a long way out.
15:26They tend to trade a lot more, right, near time.
15:29Short term, yeah.
15:30But if you look at those markets, one week out, on any market that's sort of traded, sort
15:35of 50,000 to 60,000, this Breyer score, calibration, comes in at 0.07, which means that one week
15:41out, the predictive value of the data, Calci's right, 93% of the time, it's 93% right.
15:49One week out, CPI, rates, you know, those type of things.
15:55So first of all, that's huge.
15:56And why is it huge?
15:57One, because it's got a massive alpha generation value in data.
16:00Right, sure.
16:00But two, what that means is that the market makers who are around that product go, well,
16:05that data's accurate.
16:06That data, that market's really well calibrated.
16:09So you've got liquidity on the screen, sure you have liquidity on the screen.
16:12Could there be more?
16:13Sure.
16:14Add more all the time as more people join.
16:15Sure.
16:16As more SCMs join, as more people have access.
16:18Sure.
16:19But at the same time, we've got people who are willing to do block trades over that calibrated
16:25market.
16:26I had a situation a couple of weeks ago, a large hedge fund in the office said, I'd like
16:30to trade US CPI.
16:31It's just going to happen in a couple of days.
16:33I said, but I don't know there's enough liquidity.
16:35I called up one of the market makers, I won't say which, and I said, right, I've got a hedge
16:39fund here, they want to do that.
16:40And they said, right, I'll make you $10 million of risk at the Calci price.
16:44I'll make you $25 million of risk one tick away from the Calci price.
16:48And if you want more than that, you need to give me a few minutes to assess the slippage.
16:52So the reality is there's liquidity on screen, but there's liquidity available off screen
16:58in blocks that is calibrated because these markets are so well calibrated to trade.
17:03And so I think our ability to both generate pricing and generate liquidity is actually
17:10really good.
17:11And it's on a really positive story.
17:14So your position is that the market makers ultimately will be able to come in and offer
17:19that liquidity.
17:19Because on the one hand, that's obviously what they do in the equities market and everywhere
17:22else.
17:23But on the other hand, those markets are deeper and they're able to get that risk off,
17:27right?
17:27Because they never really want to be long or short or anything.
17:30They always want to be even and kind of exist in the middle.
17:32That feels like it'll be a little bit trickier as they start to take on more and more of these
17:35custom hedges.
17:36Well, look, I don't want to speak for market makers, right?
17:39I'm a humble market practitioner.
17:44But I think their models are such that they can understand the multifactorial stuff.
17:48So I can, like, if I'm doing some payrolls number or some CPI number, I know how to hedge
17:52that in other instruments that exist in the market.
17:54And I'm comfortable enough that I can then get out of that risk.
17:57So I think they have a – so that would be my view on that.
18:02And I think that building liquidity takes time.
18:06And building liquidity requires all of that infrastructure to be in place, all of the connectivity,
18:12all of the pipes and plumbing to be in place.
18:14And we spend a lot of time just getting all of that – I wouldn't say dull, but important
18:19stuff done so that institutions can click a button and it's there.
18:25It's on the screen, the data.
18:26They can press a button and trade.
18:28That's how you build liquidity.
18:29That's how you build making and taking liquidity.
18:32And so I'm super confident about that trajectory, and I'm super confident that we can solve that.
18:37But not all markets are going to have infinite size of liquidity.
18:40And sometimes liquidity is going to be more than you need.
18:44Sometimes it's going to be less than you need, and then it will trade in block market.
18:47Do you have a timeline as far as when you'd like to – you guys a few weeks ago have
18:52done
18:52the block trade.
18:53You have done these others.
18:54Do you have a timeline on when you'd like to hit some of these goals as far as getting
18:57the more liquidity and anything you could share on that front?
19:00Because I know your bosses have talked about potentially – or there's been reports about
19:04a 2027 IPO.
19:05And I know this is all a big part of the future growth.
19:08It was talked about a lot in the funding round.
19:09So where do you give yourself as far as how quickly you want to grow that liquidity?
19:15Look, the reality is we're growing at an enormous rate.
19:19I think it's really hard to – pre-World Cup, I'd have said we were doing phenomenally well.
19:27I'd have said, look, the sports volume is a relative proportion of our volume is going
19:31down.
19:33And then the World Cup was just phenomenally successful, right?
19:38Yeah.
19:38And so the sports volume as a percentage went up.
19:40But it went up while everything else was also growing at the same time, right?
19:44So I think we're – in measuring liquidity, what do we mean?
19:49Like is it number of markets at the touch?
19:51Is it the depth at the touch?
19:52Is it the width of the market?
19:55So you've got different ways of measuring that.
19:57But we're super focused on understanding and measuring all of those.
20:01My sense is that there are a couple of things.
20:05One, we need to add some more SCMs because that, frankly, is the gateway to allowing other
20:09people.
20:10And I would say that – what would I say is –
20:12SCMs being the people that are going to help facilitate all this type of –
20:15Yeah.
20:15Like if you're in the U.S., you need to get a broker often that sits between the clearinghouse
20:20and you as a customer just either because that's your regulatory structure or that's
20:25what you need to run your business operationally, you don't deal with that yourself.
20:30And so I think that we've got a whole series of non-bank brokers.
20:34I think the key thing for me is that – what have I been saying to people?
20:38I've said the binary assessment point.
20:39The thing that I would say, the prediction market, yes, we're being successful on
20:43institutional is when we get bank FCMs joining.
20:46Get a bank FCM joining, then there's huge – they're doing it because their clients
20:51want to.
20:51There's palpable demand around that.
20:53Right.
20:53That's the thing that I think is the key sort of trigger point that I'm looking at.
20:57Interesting.
20:57Okay.
20:58So Steve in New York has a question about how will Cauchy ultimately distinguish its
21:02offering from competitors?
21:03And I want to take a step back because you have, obviously, the other prediction market
21:07types, but then also the folks that are writing this.
21:09We were talking before about a lot of this is what banks already do, right?
21:12And, you know, that you go to your local bank – not your local bank – you go to
21:15your big bank and you say, I have this business, I need to hedge it, and they write a bunch
21:18of contracts, and nobody sees anything, and you pay a bunch of fees, and then you hope
21:21that you're hedged.
21:22So I guess, what is it that you guys are doing that you feel like is really distinguished?
21:27Is it the speed?
21:28Is it the efficiency?
21:29Is it the cost?
21:30Is it the liquidity?
21:31I don't know.
21:31You tell me.
21:32What is setting Cauchy apart?
21:35Well, I think – I'm going to answer that question just – go back to Steve's question.
21:39I'm going to answer that slightly differently.
21:41I think that – you know, what do I view as a competitor?
21:44I view, like, ICE and CME as my competitors.
21:47That's how I view that.
21:48And I think that when people talk about prediction markets, there's an awful lot said and written
21:53about prediction markets.
21:54But just to be clear, I think there's a huge difference between an onshore prediction
21:58market and an offshore prediction market.
22:01So the onshore market, we do full KYC.
22:04We know who the people are.
22:05You turn up, you have to give your name.
22:06You have to give your address.
22:08You have to say, well, who you work for, right?
22:09Sure.
22:09Because ultimately, if you're doing clinical trials, you know, working for one of the pharma
22:13companies is fine.
22:13That would give you a little bit of an edge, I think.
22:15Yeah.
22:15Yeah.
22:16And so why do we do that?
22:17Because market integrity is super important.
22:19We, for instance, you know, we find people who we think are abusing the market because
22:24the data doesn't lie.
22:25We manage that data 24 hours a day.
22:27And we report people to the CFTC and the DOJ.
22:30And enforcement actions have come out of that.
22:33Yes.
22:34Sorry.
22:34Go ahead.
22:35I just wanted to step up because I think that's something we haven't touched on yet.
22:37But I think that's an important piece of this puzzle, right?
22:40Is that, look, there is some narratives out there.
22:43You know, people look at prediction markets and they say, oh, it's gambling or, oh, there's
22:47the insider trading or there's this, it's a legal gray area.
22:51These are things that make Wall Street squeamish, right?
22:54It makes them nervous.
22:55Like those type of narratives, not saying they're true or not true.
22:58I imagine that comes up a lot.
23:00Or maybe you tell me, does it come up a lot when you're going around to the street and
23:03trying to get them on the platform?
23:05And how do you answer those questions or those concerns?
23:08So, yeah.
23:09And just going back to Steve's question as well, I think, yes, it comes up a lot.
23:12And I have a fairly simple answer for that, right?
23:15If you want to try and do some market manipulation insider trading on CalShane, we will find you.
23:21We know where you are.
23:22And you'll go to jail.
23:24It's like taken.
23:25I will find you.
23:27I'm like rocking my Liam Neeson.
23:29Yeah, you are Liam Neeson.
23:30That was great.
23:30That was great.
23:32There's another guy you can sponsor.
23:33You know, get him on for the insider trading.
23:35There we are.
23:36Maybe that's a...
23:36That one's for free.
23:37I'm going to take that one.
23:38I love that.
23:39But, yeah, look, I think that's there.
23:42So you have to have market integrity.
23:44And then, you know, when people give us cash in the market, that doesn't sit on CalShane balance sheet.
23:48It doesn't sit in a tokenized deposit.
23:50It's like it sits in cash.
23:52And that sits in the CFTC segregated account.
23:56That money's locked up.
23:58It's not on CalShane's balance sheet.
23:59Right.
23:59And so we're using sort of the market infrastructure that you have,
24:02very analogous to CME or I.
24:04CME or I.
24:05So you're using that consistent clearinghouse market infrastructure.
24:08You're using that.
24:09That's what matters.
24:11Exchange structure that matters.
24:13And then finally, you know, contracts.
24:15We talked about contracts.
24:17When we design contracts, they have to be designed precisely.
24:22They have to have fallbacks in them so that everybody who's trading them understands what the fallbacks are.
24:26One of the markets we have is a crypto market.
24:28It says, will crypto be higher or lower every 15 minutes?
24:32And what we do is we take from a benchmark provider three exchanges, effectively the traded prices for three exchanges
24:45for one minute.
24:45And then we add those together and we say, that's what's going to be our benchmark price.
24:52Because I'm a futures guy.
24:54I don't like this concept that someone could bang the clothes on one market to move it for one second
24:59above a price to get paid off on CalShane.
25:01That would be market manipulation.
25:03So how we design our contracts, as well as all of the post stuff, like checking people and looking at
25:10the data and reporting people, you've got to design the contracts correctly up front.
25:13And being inside the CFTC regulation is fantastic for that because it's very clear, very specific.
25:19There are things you can and can't do.
25:20We also have our own rules and culture and how we want to scale for that.
25:23But that's the unique, I think, skill.
25:27That's the experience that you get with a regulated exchange like CalShane.
25:31You clearly put a lot of thought into that.
25:34Is this the toughest part of your job, you'd say, is when you make the pitch to Wall Street, navigating
25:38those conversations?
25:38Or is there something else that is a common question that comes up or a concern that's raised by these
25:43clients that you're trying to get on board?
25:45Look, I would say the hardest part when talking to sort of big banks is we've got 73 things going
25:54on, Andy.
25:55Love you like a brother.
25:56Love this market.
25:57But we've got 700 people who are also doing innovative things.
26:01And we've got some crypto stuff that we're doing that's innovative.
26:04And we've got we're changing this and we're doing that.
26:07And we've got AI stuff.
26:08And so it's getting your spot in the priority list, getting your spot in that top 10 of things that
26:16you're going to do.
26:16And so that requires a lot of energy from everybody in the industry to become one of those things there.
26:24And that's why I'm quite excited.
26:26I feel like we're doing really well at putting ourselves on that list of people care about this.
26:31People are connecting to it.
26:33People are wanting to to get with it and trade it.
26:35And that that feels like that's working.
26:39And then hedge funds and asset managers, as I say, it's about that they're starting with give me the data.
26:47And I can't tell you the number of conversations that I've had, which is give me the data.
26:52Great.
26:52Right.
26:53Wow.
26:53That's amazing.
26:54Explain how I can trade now tomorrow, please.
26:56Hmm.
26:56That's like the taster.
26:57That's the teaser.
26:58You get them on the data.
26:59And then it's like, OK, there's there's something a little bit more here.
27:02Yes, exactly.
27:03Huh.
27:03So Matthew in New York has a question about kind of the use cases on it.
27:06So he says, as the macro markets move, moves are increasingly driven by policy, regulatory,
27:11and political shocks rather than traditional fundamental cycles.
27:14I think we can all agree that's definitely true.
27:16Are your institutional clients using Kalski primarily as direct asymmetric hedging tools for tail risk?
27:23Or are they leveraging your implied probabilities as an alternative data signal to front run repricing
27:29in traditional asset classes?
27:32So there's a lot to unpack there.
27:33I would say both is the answer.
27:35So I think that the number of people who are yet trading tail risk hedges is low.
27:40But the number of people who are, you know, like asking us to look at markets, developing markets,
27:45looking at that, you know, because if something's got a 5% probability and then moves to a 10%
27:49probability,
27:50it's still a tail probability.
27:51But the chances of it happening have just doubled.
27:55Right.
27:56That's like, if I'm a risk manager or I'm a portfolio manager, I'm like, yeah,
28:00I think I want to look at that.
28:01What does that mean?
28:03You know, if my correlations are breaking down, what does that mean?
28:07I need to be able to think about that and manage that.
28:09So certainly we see that from a data side, possibly a bit more than the trading side.
28:14But then, yeah, I think we're starting to see people look at this as a way of diversifying their risk,
28:23as hedging tail risk, as providing insights.
28:26And if you're a macro guy, that's around the events we've just been talking about, politics,
28:34as well as payrolls and CPI and such events.
28:37But if you're an equity guy, maybe it's about some of those KPI things I was talking about,
28:41like whether regulation is going to be passed or whether a law is going to be passed.
28:45We have a market on whether the Genius Act is going to be passed, for instance,
28:48that people look at because it's hugely impactful for stable coins and bank revenues and such, right, potentially.
28:55Yeah.
28:55And so that gets looked at all the time as a tradable thing.
28:58And that's driving equity volumes and equity valuations.
29:02So is there a hedge there?
29:03Sure.
29:03Is the number of cars being delivered?
29:05Is the number of DoorDash deliveries made?
29:07Whatever.
29:08Those are all breakdowns of things that are happening in the real market, in the real world.
29:14Right.
29:15I'm curious with ultimately the end goal.
29:19Do you view, and I know I'm talking to the man in the seat,
29:23but do you view this ultimately usurping the retail business?
29:25That this is where the real sweet spot is for Kalshi?
29:31So I'm a relatively lone voice inside Kalshi, and I say the retail business I think is the frosting
29:38and the icing on the cake and the cherries, and that's fantastic.
29:41But I think that the institutional business is a really very tasty, very nice cake.
29:46Sure.
29:47And so, yeah, I think there's a hugely foundational business.
29:50I've said this before.
29:51I joined Kalshi because I think this fundamentally is going to change market structure over the next five to ten
29:56years.
29:57This is the biggest change in market structure, possibly even bigger than the changes after Dodd-Frank.
30:03This is the equivalent to me of electronification of markets.
30:07It's just generating a whole new world of asset classes and risks to hedge and manage,
30:12which will make society better because it comprise more risks,
30:17and it will make traders better because they can evaluate on a number of different elements that they previously didn't
30:24have.
30:24Right.
30:25Yeah, ultimately the possibilities are really endless here.
30:27It's kind of a choose-your-own-adventure.
30:29The one thing I wanted to touch on real quick before I let you go, and Andy, this has been
30:32great.
30:32So obviously on the retail side, a huge part of the business is sports.
30:37And we're also at the same time, you're pushing institutions.
30:40We're also seeing a lot of institutional involvement in sports ownership, right?
30:44You know, we just saw the Seattle Seahawks, Super Bowl champs, you know, get bopping out on VC folks.
30:50How do you – is that an opportunity?
30:52Because on the one hand, there's a lot of hedging that sports owners could do around their business.
30:57But on the other hand, it's a little bit – it's tricky.
31:01It's tricky.
31:01And I know there was something around the La Liga as far as them kind of putting in something
31:06around relegation because there's big revenue that comes with getting relegated or losing out of revenue.
31:11I guess – do you view that as an opportunity as far as institutions that you're targeting
31:15are also owning sports?
31:16Sports is a big part on your platform.
31:18Can there be some business there, or is that a little bit too shaky ground?
31:21No, look, I think that one of the challenges is that we have a conversation about sports.
31:28But, look, sports has phenomenally – got a phenomenal amount of money going through it.
31:31There's a huge amount of risk.
31:33Right.
31:33And often that risk is managed in bespoke OTC contracts.
31:39I remember working somewhere previously where we hedged some of our risk regarding a sponsorship deal
31:46with somebody where we did a bespoke OTC contract and kept trying to think,
31:49how do we book this and how do we margin this thing, right?
31:51And so managing risks around sponsorship, managing risks around promotion – if you're a company
31:59and you want to take insurance on being relegated, sure.
32:02I actually think that's a really good thing.
32:04Now, where the governing bodies of those sporting organizations are, I think it's – I would
32:13be not personally of the opinion saying that's bad because I think actually running those businesses
32:17and making those businesses better hedge is actually good for – in general, you don't
32:22want football clubs.
32:23You don't want baseball clubs blowing up because something's happened to them, right?
32:27So you want this – the hedge, I think, is an appropriate risk management tool.
32:33But neither do you want to be able to say, right, I'm going to put a hedge on that I'm
32:36going to get relegated, and then you sell all your players.
32:38Right.
32:39That's the concern.
32:40So you've got to have – I think that the market has not got – you've got to understand
32:45what's going on.
32:46But let's just be clear, insurance has existed in this space for a long time.
32:51But the insurance premium – and maybe that's an example of someone who's going to lose
32:54that – insurance brokers have taken a lot of premium out of those trades when they're
32:57arranging them.
32:58We're now producing a liquid price in a regulated exchange.
33:02That's – perhaps the insurance processes is more interesting because it's got nuances
33:07and – but the fundamental pricing point is now liquid on an exchange.
33:12And I think that's valuable for sponsors, corporate, treasurers, whatever.
33:16Are those conversations you're having on the – with the league officials?
33:19Because they've shown, obviously, interest – I mean, just about every American sports
33:22league has some type of partnership with sportsbooks.
33:25I understand very different business, not suggesting they're the same, but, like, they're
33:28clearly okay with some type of relationships as long as it's on their terms.
33:31Are those conversations you guys are having already or considering exploring?
33:35Those are not conversations that I'm having already, so let's put a lot of that down.
33:40I think that what – well, I guess a couple of things.
33:45But one I'll say on sports is that the fact that Calci doesn't create prices, I think,
33:51is a fundamentally huge difference.
33:53The market's setting.
33:53The market's setting the prices.
33:54So there's – when somebody wins and somebody loses, I don't – I'm indifferent, right?
33:59I – I've just created the market.
34:01Which is unlike the sportsbooks, which end up having a position one way or another.
34:04Correct.
34:04And that – if you win, they lose.
34:07And if they win, you lose.
34:08And so I think that, you know, there's a lot of – you know, CME doesn't mind whether
34:13people are buying or selling U.S. treasuries.
34:15They're just happy to ensure the liquidity is there.
34:18Right.
34:18And so I think Calci is indifferent to the price and indifferent, therefore, to the users
34:25and what they want to use on that market.
34:27And as long as it's sitting within the regulatory function, regulatory structures, that's really
34:34appropriate.
34:34But if we see or would see, and because we know who the various people are involved in
34:40the trade, see things that we don't like, as I've said, we know who's trading, we'll
34:44have investigations, we'll report them to regulators, et cetera, et cetera.
34:48Mm-hmm.
34:48Last one here before we let you go from Esnaz in Canada.
34:52You're talking a lot about the safeguards and stuff.
34:54They ask, what safeguards or transparency mechanisms do you find are most important or
34:58critical for institutionals to trust prediction markets?
35:02What's – when you get in these meetings, what's the one that they often want you to
35:05point to or the one that you point to that they maybe look a little bit more relieved
35:08in their seat?
35:09Yeah.
35:11So I think, first of all, they like someone with gray hair turning up, right?
35:14So I think that's the first thing.
35:16Okay.
35:17The second thing is we have a whole series of products, like sports is one product, politics
35:25is another product, economics is another product, companies is another, and so on and so forth.
35:30Weather, blah, blah, blah, crypto.
35:33And so what we have is controls within the exchange to say that you can have access to
35:38this section of the market, but not that section of the market.
35:41Yeah.
35:41So if you're turning up and you want to – you're a fund manager and you want your
35:45people to have access to trade on economics and that, but you don't want them to have
35:49a view to be able to trade the fund on the World Cup, we've got those controls.
35:52So you can set up controls.
35:55The second thing we do is obviously all of the operational stuff about who can access
36:00the accounts, who can wire money in and out, you know, the standard stuff all exchanges
36:04have.
36:05We have all of that type of thing, all exchanges and CCPs have.
36:09So I'd say those are the sort of key controls we spend a lot of time on.
36:15The last thing that I would say that is really interesting from our perspective is that we
36:20operate 24 hours a day, seven days a week.
36:23And that's one of those questions that people go, oh, that's quite hard.
36:27And I get that that's quite hard because if you've been used to trading something that's
36:31trading, you know, nine to five, five days a week, then it's different.
36:36But markets are trading 24 hours a day.
36:39Not always seven days a week, but trading 24 hours a day.
36:43And having a sports background, having that sports pedigree meant that we've had to figure
36:47out how do you move margin on a weekend?
36:49How do you, how do you, how do you transfer cash around at a weekend?
36:52How do you use stable coins?
36:54How do you use tokenized deposits?
36:55How do you use real time payment rails?
36:57How do you use that market infrastructure that exists and make that institutional?
37:01And so we've done a lot of work on that.
37:03I would say that we're really good on that.
37:06And so let's take our perpetual product for a second.
37:09We run that seven days a week and we call margin both intraday and overnight at the weekend
37:13and expect people to pay it at the weekend.
37:15Right.
37:15So people, if they don't want to have the infrastructure to show, they can put a buffer up.
37:18Right.
37:19But the reality is they're expected to pay that money at the weekend.
37:21And so we've calibrated our model where you actually move the money on a Saturday and a Sunday.
37:27And that's because we've designed that, we think, in a way that is the right market structure for risk management
37:33as we move to 24-hour, seven-day-a-week markets because I think that people are going to trade.
37:38And certainly AI is going to trade 24 hours a day, seven days a week.
37:41It doesn't need us to sleep.
37:42And so that, I think, is the right market structure, but it's not necessarily the right structure for now.
37:50So to your question of what's the biggest thing or one of the things I have to go through is
37:54how do you talk people through how they manage risk of having to work at the weekend?
38:00Hmm. Yeah.
38:00I mean, who wants to work on the weekend?
38:02I do get that.
38:02But ultimately understanding that it's kind of necessary to really kind of exist.
38:06I thought you didn't sleep.
38:07I thought you were 24-hour news, right?
38:09Yeah.
38:09Well, I don't sleep because I've got two little kids, but that's a whole other story.
38:13I think that's a good place to leave it.
38:14Andy, this has been great.
38:15I really appreciate you taking the time.
38:16Thank you for having me.
38:17Thanks to all of you for tuning in.
38:19Until next time.
38:21Bye.
38:50Bye.
38:52Bye.
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