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