Go back

Why Susquehanna Is Building a Prediction Markets Business

31m 56s

Why Susquehanna Is Building a Prediction Markets Business

The podcast explores prediction markets’ evolution with Jeremy Mallitz, head of prediction markets at Susquehanna International Group (SIG). SIG acts as a key market maker, providing liquidity across sports, politics, and economics, and aims to shepherd institutional investors into the ecosystem. Mallitz explains that market makers bridge gaps between buyers and sellers across time and size, essential for bootstrapping liquidity in new markets. SIG’s culture of embracing risk allows it to take positions, even when not neutral, leveraging prediction markets’ price discovery and super forecasters to set fair prices on low-volume contracts. This enables SIG to offer large hedges for institutions, such as airlines hedging snowfall. Institutional adoption faces challenges including awareness, compliance, and legal issues, but SIG is creating multiple access points (e.g., block trades, swaps). Currently, sports dominate volume, but non-sports markets are growing faster. Mallitz emphasizes that hedging use cases are critical for the ecosystem’s future, with SIG uniquely positioned to facilitate them due to its risk appetite and quantitative models. The conversation highlights the potential for prediction markets to become useful for economic hedging, beyond pop culture or sports bets.

Transcription

6483 Words, 35320 Characters

English
All thoughts is brought to you by Vanneck. For years, investors basically forgot about real assets, energy, gold, and infrastructure, but look at what's driving markets now. Central banks loading up on gold, massive capex cycles, currencies doing weird things, these assets are at the center of it. Rax, the Vanneck real assets ETF is an actively managed one-stop shop for real assets spanning gold, commodities, natural resource equities, and more. Go to vanneck.com/raaxpod to learn more fun disclosures later in this episode. A new chapter in global growth is being written and much of it is happening in Africa. Africa needs to invest. There are deals to be done and business to be won. I'm Jennifer Zabisajep. Every week on the next Africa podcast, we track capital flows and political shifts shaping the continent's future. The digitalization of Africa is good at power to grow. Reading the world of something like HIV is possible. Opulation growth is so enormous in Africa. Listen to next Africa on Apple's Spotify or wherever you get your podcasts. Hello and welcome to another episode of the AdLots podcast. I'm Jill Weisenthal. And I'm Tracy Allaway. So Tracy, we're still rolling out shows from our live show on May 28th in New York City at City Winery. As we discussed in our last episode from this show, it had a sort of future of markets, future of trading theme to the night's conversation. Right. And if you're talking about future of markets and trading, we have to talk prediction markets. Yeah, that's right. So in addition to the fact that there is the quote, AI trade unquote, the other big thing going on in markets is the sheer explosion of instruments with which people can trade. Right. So it's like you have stocks and bonds and options. And then the options are to get a more exotic, like zero-day options, which you love and so forth. But now it's like if you could think of something that would resolve in some way, whether it is snowfall in New York City, Tesla deliveries or how long a half-time show is at the Super Bowl, there probably is a way to bet on it. Right. And so one of the big questions is whether or not these markets are going to take off from an institutional perspective, whether or not you're going to see more professional investors get into the business of betting on not just snowfall in New York, but maybe half-time shows and that sort of thing. But that said, we do have some institutional participation in the market already because you have market makers that are starting to come in to try to make these markets more liquid. Yeah, but you really said the key thing here, which is we know there's like a ton of liquidity for like the sports betting, et cetera. Like that's not the problem that needs to be solved. Right. It's these other things where in theory, these might be useful instruments for hedgehogs, some sort of economic risk, maybe not the Taylor Swift one or the half-time show ones, but some of these other ones. But like in theory, some of these contracts could be useful for hedging. And so the question is, yeah, but will anyone use them? And so on this discussion, we really had the pleasure of someone who has on very little media in general and who is right in the heart of trying to essentially solve this chicken and egg problem, listen to our conversation with Jeremy Mallitz, the head of prediction markets at Suscahana International Group. All right. Why don't you tell us just let's start really simply what does the prediction markets desk at Suscahana do? So essentially the main function that we do is market making. So we're the main liquidity provider or one of the main liquidity providers on quite a lot of platforms. And that means we're providing liquidity and everything from sports to economics to politics. But I'd say also a big part of what we do is we were the first institution that got involved in prediction markets in the first place. So we're really trying to have a role of kind of being a shepherd for other institutions as they get involved. So I'd say it's a two-pronged goal, really, of providing the liquidity for the ecosystem to help it to grow and then bringing others into the ecosystem, which I think has been one of possibly even the more important role of what we've done to this point in time. Wait, can I ask an even simpler question, which is I kind of feel like Suscahana is like the sales force of the finance world where I have this vague idea of what you do, but also not really. What does Suscahana do? Well, my wife asked me the same thing, but it's her birthday by the way, so I haven't heard her. It's incredible that you're here. I know. I owe her big time. So we're primarily a market-making firm and our bread and butter has always been options. So we make markets in pretty much every option, equity options, but obviously we trade a lot of instruments across a lot of things. And we just, we have a culture overall that's very much looking for new opportunities and thinking about things and probabilities and kind of, you know, it all starts from Jaffioss our founder. He loves things like prediction markets. So, you know, we have a lot of random businesses at Suscahana all over the place. You wouldn't believe the number of things that we do randomly. And it all comes back to the same culture we have of thinking in Bayesian probabilities and trying to think of everything in terms of break it down into what the odds are, but the bread and butter remains market-making. And we try to use that to kind of make a market or bring a market to any asset class we're looking at. Let's talk about, okay, there's some contract out there. Who is going to win the Texas primary like, let's just say. Why, you know, and so there's an exchange and there's an instrument and it's either going to end at 100 or zero, etc. Why does this market need market makers? Why can't it be entirely peer-to-peer such that if all of us in the room just wanted to trade, we make a price amongst each other on an exchange. Why is a market maker an important part of the infrastructure for this to work? So, if you have a market where you have an insane amount of people that are all trying to trade all the time, you might be able to make it work without a market maker. Okay. But what a market maker is really doing is it's helping to bridge the gap between the different people who are trying to trade. So, Joe, you might want to trade now and Tracy might want to trade in an hour. But if there's no, but that doesn't help you if she's not there now. So, we're basically saying, hey, we're going to be there when you want to trade and then we're going to wait and when Tracy wants to trade, we'll take the other side of it. So, we're basically a function that matches the buyers to the sellers across time and also across size. So, how big does your balance sheet have to be dedicated to this particular business? How sizable are you with an entity like Calche? So, it really depends on the way that you do it. There's a lot of small independent groups or just individual people who are able to be out there and they make markets and their goal is to try to balance it and they have to think a lot about capital. We are very fortunate that capital isn't generally a constraint for us. So, that's one of the things that it's an advantage for us, but it's also something we can bring to the market. We can provide much, much larger size on things. It's why we're well suited to bootstrap a market and to do institutional type size because we're not constrained by capital in that way. And do you generally try to stay like risk neutral? No. I think that is pretty deeply in our culture that obviously all things equal. We would like to be risk neutral, but we're willing to put ourselves out there and wear a position. And in general, on our options trading, we tend to wear house a lot of risk for the street. Sometimes there's just something where everyone needs to hedge risk in one direction and someone needs to be on the other side of that. And that's an important function in prediction markets, especially when you think about use cases such as hedging where you've got some global risk to the world. Everybody needs to hedge that risk on one side. Someone needs to be on the other side. And we're willing to hold ourselves out there to do that. And there's a lot of pieces that go into being able to do that. Obviously, when you're not neutral on a risk basis, you have to be more confident that you're right. But that's a big part of what our team has driven to build. So this sort of leads into the next question. And it's maybe the multi-billion dollar question of prediction market, which is, okay, we know that there is a huge amount of the prediction markets business, which is just sports betting under a slightly different form. But you mentioned hedging, and this gets to the core question, which is in theory, there are a lot of instruments on these prediction market platforms that could be useful hedging instruments for corporations, say a market on snowfall in New York City, which might affect an airline or something like that. Maybe they want to hedge that. When I look at the platforms currently, I see a price for snowfall, but I don't see anywhere near the volume level that say, would really justify an airline you see $150,000 in volume on whether there'll be between six and eight inches of snow. That's obviously nowhere near deep enough for a serious economic actor to participate in. So where are we on that in terms of the promise of actually useful instruments for hedging? Right. So when we first got involved in prediction markets, our real role was to bootstrap the liquidity. There were no institutions yet, and it was largely going to be a retail product. We were bootstrapping for large volume retail liquidity. Now our next challenge is we want to bootstrap institutional liquidity. So yes, you might look at a market that doesn't seem like it has enough volume for an institution to hedge tens of millions of dollars of risk. But that's part of the reason that I'm out here doing a podcast today is we're trying to make sure that people start to understand this is viable. And we're putting ourselves out there that we will be willing to put that kind of risk. And we can put out that kind of risk on a contract where far less volume is traded. And that's because what the prediction markets really provide is information. It's a price discovery mechanism. So you have this phenomenal community of super forecasters that exist on a prediction market. And it doesn't take as much volume as you would think to get to a fair price. And that allows us to say, hey, OK, we've got a reasonably fair price on this prediction market. Maybe it's only traded $100,000. But we know that there's been a lot of smart people that have looked at this. We can do our own internal vetting at the same time also. And now we're comfortable going out there and saying, we're confident enough in this price because of the price discovery mechanism that will make tens of millions of dollars of risk to a company that needs to hedge its risk of what-- some regulation or straight-of-form moose or whatever it is that's happening in the world. So someone needs to go out and do that. And I think we're kind of uniquely positioned because of our culture of saying, yes, we are willing to take that risk. And yes, we want prediction markets to grow. What if your conversation's been like with institutional players so far? Like, what do they say is there main either constraint or, I guess, reluctance to get on some of these markets? So the first piece is the exact thing that you just brought up awareness. They look at the markets and they might say, well, I don't see how we could actually hedge some of these things because there's not enough volume and liquidity to which our response is, we will be the liquidity. Then the other question is, OK, well, we sort of need our compliance to get comfortable with this. This stuff is so new. What's the legal landscape? What, how do we get this stuff even over our firewall? I think institutions were always going to be the slower moving player relative to retail. And so that's why we really want to sort of hold some of their hands to go through this and figure out a lot of different ways that they can use prediction markets. Some of it might be an institution connects to a prediction market platform, does a block trade on an exchange with us. It could be that a trade goes up often exchange as a swap, but it's licensing the exchange market data. And we're trying to create as many different setups as possible so that people can do these trades. And we're going to basically be the facilitator to say, OK, you need a hedge. We're going to figure out how to let that happen. So this is really important. So if I look at a contract and I see a number they're like $150,000, it's possible that there was a trade, an off-platform trade, a much bigger size that was not printed on that, but that was more by let swap form. And that's currently happening. It is possible. I'm not going to go and say that that's a big thing that's happening yet. We're trying to build out the infrastructure to have as many options as possible, because we want institutions to start moving. And the more they do it, the more they're going to-- If an institution, again, let's go to the airline hedging snowfall, would they have a relationship with you? Would they go through a prime broker who then has a relationship with you? What is the actual chain of phone calls or whatever that have been? So it can be both. But ultimately, when I think of what we're really good at and what we're not really good at, we're not necessarily the best in the no-every-single airline customer business. So we want to work with a lot of those other intermediaries. That could be a broker. It could be a bank. It could be an insurance company. The people who have those relationships and are in the business of constantly advising, this is what you should do. We understand we want to work with them. And they could have a very important role in helping to be a part of the infrastructure that gets it from the customer with the risk to us being the ones that have the other drivers. [MUSIC PLAYING] Data centers need electricity. AI needs copper, reshoring needs steel. And gold's run may tell you something about how the world is repricing money and debt. All of those point back to real assets. The RACS ETF is an actively managed one-stop real-asset shop from gold to commodities to natural resource equities, adjusting his conditions change. Visit vanneck.com/raaxpod to learn more. An investor should consider the investment objective risks, charges, and expenses of the fund before investing to obtain a prospectus and summary prospectus, which contains this and other information, visit vanneck.com. Please read the prospectus and summary prospectus carefully before investing. RACS is distributed by Vanneck Securities Corporation Distributor. A live short daily news podcast focused on just one story. But right now, you probably need more. On up first from NPR, we bring you three of the world's top headlines every day in under 15 minutes. Because no one's story can capture all that's happening in this big, crazy world of ours on any given morning. Listen now to the first podcast from NPR. Joe's chosen a pretty reasonable contract. I would say, for his example there, but are you committed to making markets in all the contracts available on these platforms? Because I'm thinking about the return of Jesus Christ or will aliens invade? How would you even go about making markets? Making markets of time show. Right. Yeah, so we don't make everything. And honestly, we're not the best to make absolutely everything. Some of the things that you might say, something perhaps in pop culture, we're probably not going to be that good at it relative to others. There are certain things that-- Are you trying to build that capacity up? Well, we'll see. But there is a community of a lot of people that can make a lot of these types of markets. And what we want to do is we want to scale our capacity with our technology, our quantitative models, our very trader-driven insights that we have in our capital. That's where we're going to add the most value to an exchange. If something just requires a bunch of people to dig into it, the universe of all the different super forecasters, we're probably not as necessary. So you probably don't need us to know something about when Taylor Swift is going to get married. But the fact is that the things that have the most economic value tend to be the things that need us the most. And so that's really where we try to play. And I think it's great that the ecosystem has these complementary forces of the community of all of the super forecasters and then the people like us who both have different skill sets. Do you see right now-- so again, people say, yeah, these are just sports betting, et cetera. And then maybe every two years or every four years, there's some election activity. Maybe there's some trades that are sort of like crypto derivatives, et cetera. When you actually look at today's volume of activity, do you see a meaningful shift towards what polite people who wear suits would say like real things? Is that happening? It is. Yeah. And so when you look at the volumes, obviously, there's a real percentage of the volume. More than half the volume certainly is sports. Yeah. And there's a reason for that. Sports has been a big market in the United States for a long time. And it's happened in kind of a fractured way across a lot of different states. And there are certain states where you can't do it. And it's a different regulatory system everywhere. But there was a big market that existed. And then prediction markets basically came around. And they provided a better way for sports to trade. So it was natural that there was going to be this massive base from the start. But what we're seeing is it's dragging up all of the other things. So it's brought awareness to prediction markets. And the more we see that, the more we see everything else growing. And by the way, a lot of that other stuff, the real market, they're growing at a faster rate than sports, just from a lower starting point. And our goal now is really to boost that with the hedging cases, which that's growing too. But it's not a huge part of the market as of now. And we understand it needs to be from an ecosystem perspective. It's essential that those hedging trades become a much larger part of what the market is. So if you're a market maker for an event contract, that's something like the Fed is going to raise rates or hold or lower or whatever, that's pretty similar to something that you might see in traditional markets. But can you explain it to us from a mechanical perspective, how different the market making process would be for a prediction market contract versus a traditional option? Right. So honestly, there's not a one size fits all because there's so many different things out there. So if you're thinking about what's the Fed going to do next, there are instruments that capture that reasonably well. And same thing is what's the price of the S&P 500 going to be at the end of today, for example. There are other instruments out there that capture that reasonably well. And really, this is just distilling it into a way that might even better capture the idea someone has. There's like quirks to the other types of things that you might have that are the proxies. So we can translate what's happening in the traditional financial markets, two prediction markets. For other products, is this random one-off event going to happen in the world? Is the straight-of-formus going to be open by the end of August? Is Kierstarmer going to be out as Prime Minister? Yeah, we're that stuff requires a lot of independent research, but the good news is that there's so much information contained within the prediction market itself. So one of the core market making principles we have is, you know, it really honestly comes from, you know, kind of a thing we teach with poker of understand what other people know and what other people are doing we can learn from the markets seeing where they are. This is what all these other super forecasters know we can combine that with our internal research and then get to a number. So that's, you know, some things kind of have to be we draw it up and figure it out like that. Some stuff is we can use the information that's in other markets and some stuff is we're going to build a brand new model to figure this thing out because that's kind of in our that's kind of in our DNA to say like all right here's a random thing. But you know, how are we going to have to figure out compute right let's let's figure out how to model compute and you know we'll build it. So one of the concerns or one of the things that people talk about with prediction markets is the possibility of insider trading and you know like. Obviously like when I think of like a market making firm or some of these firms that do a lot of slow and volume you just sort of assume there's a lot of noise and all sort of washes washes out right. So how does it change you like you have to think like if there are participants in the market that are like not just forecasters here like not just people who are good at predicting things but deeply informed slow where they maybe just know the answer already are you able to spot that are you able to sense that and does that change how you think about risk management within a given market. Right so I guess the insider trading is definitely something that that comes up and there there's certainly been plenty of articles that are written about it. I think there's a couple of things to point out there the first one is that there's actually really two types of prediction markets that it's not always clear to people what the distinction is but there's the regulated prediction markets such as calcium such as raw there exchange that just launched such as you know CME has one and and polymarket has a regulated exchange. And then there's the crypto based decentralized finance platforms and those are you know they don't have KYC right and their crypto based their defi so I think most of what you've seen the vast vast majority where people find something that's insider trading based is on the defi platforms because there is KYC on the regulated space and that that's what you know we are participating in the regulated space. So that's the first important thing is if you're in the regulated space you're much more protected. The other thing is you know insider trading is something that does exist everywhere and there's a mechanism that works to to sus it out and that's reporting from the people that are in the market generally one of the things that we're always paying attention to is what are the incentives of the person on the other side of the trade. And someone's insider trading it's a lot more obvious that okay well what are the incentives they don't make sense the thing then happens and okay we can make a pretty decent Bayesian update that like this is probably insider trading and report it and it's actually easier in prediction markets because this stuff is more obvious there's a million reasons that someone can buy Apple stock but like there's not that many reasons that someone can buy like is Maduro going to be going to be out. If you see a lot of people slamming that right you okay right so it's actually easier to spot this stuff and by the way like one thing we're extremely happy about is the DOJ is now even going after the you know the crypto based platforms where you know people kind of I think they kind of knew people probably thought they were safe you're not safe in crypto and actually everything's on the blockchain right so you'll get caught so there is an infrastructure especially in the regulated space but also now in the unregulated space for catching people that do it and I think that's why you don't see more like that's what stops insider trading. People don't want to get caught. This is new people probably thought like oh I can do it in crypto and we'll get caught now they're like oh I am going to get caught. Okay aside from insider trading one of the other concerns or criticisms of prediction markets is the idea of you could have whales basically in the market like people with a lot of money who are willing to spend it to perhaps like influence a particular probability with the hope of I guess influencing the ultimate outcome. You must have pretty good visibility into order flow like how realistic is that concern from your perspective. Honestly I don't think it's something that's really come up for us to this point in time like there are concerns we have around certain things in in prediction markets but realistically like there's a lot of people in prediction markets with deep pockets certainly us and we're pretty good as I said understanding the incentive who's involved and if someone's going out there and trying to move a market to like influence an out to influence an out. You know if it's I guess it depends on what the outcome is if it's an outcome that's easy to influence we try to avoid those markets in the first place we don't trade like mentioned markets right someone could put a bunch of money on something and then you know on this podcast perhaps and then say Joe how is a little right but is everyone is everyone know like a mentioned market is like will Joe Tracy or Jeremy say the word like dogecoin and exactly that's like it's crazy right so whatever. So we're not going to we're not going to participate in those if you're worried about something like that like probably shouldn't trade those either like they're more on the on the side of just like this you know if people want to punt around and then find we're not in those but for more serious markets I don't have that much concern if there's someone trying to do that. That there you know if it's if it's not manipulable particularly it's something that's real and someone's just trying to move the market the marketplace is probably going to figure it out and take the other side of it and if they can actually influence the outcome in a meaningful way then it probably need probably to think about what the settlement mechanism is and you know those are the types of markets we try not to get involved in but I don't think you see a whole lot of that in the market. So as you mentioned you're not you don't make a market in every market and some things are more logical do you have when you say okay you're market maker for Kelsey do you have a list of like this is what we do and don't or is it like like I'm sort of in my mind the way I think about your role a little bit like a Lloyd's of London in the sense that it's like okay so someone has some risk and then they call you up and they like can you make us a price for this. So is it a set list or is it like you take it as you see it yes okay we can make a market no we know this is not something we're going to participate in on a sort of like per market base right so it's a little both there are some markets that we do all the time we we sign up for obligations we're going to be out there all the time 24 seven. And then there's some things that we kind of do on a more ad hoc basis like you know you it comes up it's important we think we have can have a meaningful role in the market and we just figure out how to get involved in it so little both. I don't know if you read it but there is a piece in I think it was the New York Times this week about sharps in the prediction market you know you definitely read yeah people who are making all of this was oh yeah that's right okay so you better have read it I have read it okay but there was someone quoted in there who is like an independent trader. And they said they interviewed at sesquahana but the firm said that like sesquahana is not allowed to scrape certain data or it has certain data restrictions and I guess that made the job unappealing to this guy because he doesn't seem to have taken it but like what are your data restrictions exactly so we're we're you know we have a large franchise and a large reputation that we need to take care of so we're not going to violate the terms and conditions of a website. Right if you're if you're a random person who's doing it like you you probably can do that and you're probably not going to get in trouble more likely than not although that's certainly not like people like putting in URLs that haven't gone live yet right and they have some feel they test them out like it's not even necessarily I mean that's a thing that can happen plate but it could just be like you have a website that has terms and conditions that says like you're not permitted to scrape this data right and some and like you know plenty of people scrape the data right and we're not going to say that we're not going to say that we're not going to do that. Right and we're not going to scrape that data like we're not going to violate the terms and conditions of a website so we hold ourselves to a more conservative standard when it comes to those types of things so I think that I think that person was probably just referring to hey you get restrained restrained in some ways if you want to work for us in the usual like institutional things like we're going to be very careful when it comes to things around our reputation but you know but I think that like that's probably you know there's a lot of advantages to working here as well. I know this isn't a prediction markets question per se but like do GPU markets that we talked about first half of the show do they have the sort of contours of what to you look like could be something very actively financialized market. Absolutely I mean it's something that the prediction markets are looking at and really what when I think about what's made prediction markets so different like what actually changed yeah it's the speed to market. So we say more about this so you know it's funny when we first started wanting to get involved with prediction markets of like a little bit of an origin story where I have a friend who was a CFO of a musical instrument company during the first China trade war he was worried that their company might go out of business because they imported instruments from China and we I was like well I'm a macro trader I could hedge this it's what I do all the time we actually tried to list a product and it took about a year and it was just too slow and then you know where do you try to do that. Where do you try to list it. We tried to list it with my ex and you know just that was the process for listing a future and now we got now we you know prediction markets came around and that process went to a day or even inside of a day. So I think really that's the most that's the real valuable thing. thing that happened with prediction markets. And I think that with compute, you see this ability of prediction markets to potentially move very quickly. So they can launch a product. There are products on prediction markets that have compute. And these other things that kind of look like compute, you might say DRAM prices. People worry about that all the time, right? The shipping costs. These things that are kind of like a commodity, but they don't really have a commodity. So, the system markets can be speed to market, and the system works in that way. So, I absolutely think it's something we're thinking about. And I think they can totally have a role in that ecosystem. So just going back to the very beginning of this conversation, your head of macro trading at Suscola, sorry, I can't say head of macro without cracking up. You're head of macro trading, but also prediction markets at Suscola, which is like kind of an unusual combined role. Like, what is the idea there? Is there some synergy between those two markets that you're trying to capture? You know, honestly, it all just comes down to the election. You know, as head of macro, I had sort of a niche for trading the election. And I kind of got exposed to prediction markets because they were trading in Europe on Betfair, and we would be, you know, European entity, and we were involved with it there. And I saw the value of it. And I think 2016 election was like a place that it was really valuable because people had these massive risks they wanted to hedge. People would do it with these proxy products, banks would put out baskets of like, "But do all these, put together all of these names." And the broad market consensus in 2016 was that the market was going to be down 5 to 7% if Trump won. And it turned out the market was up. You was like five minutes ago. It was like five minutes ago. Yeah, but yeah, by the end of the next day, it was up, right? And so the, you know, the hedge didn't work, but we saw like the prediction market worked. Like, if you, if you actually just hedge this in the prediction market, it would work really well. So honestly, there's not, it doesn't seem like there's that much synergy. It's more just it evolved out of that of saying like, "Hey, we're involved in this space and we see how valuable prediction markets can be and we really want to make it happen." And so I think that it's really just kind of an evolution as opposed to this is how we would draw it up from scratch. Yeah, everyone's still like, get one of those like basket trades. Or it's like trade this basket. We could do $100 million. Right. And this, you know, D-Ram winners, D-Ram losers basket. Anyway, Jeremy Mallett's head of prediction markets is Eskihana. Thank you so much for that. Thank you so much, Travis. That was our conversation with Jeremy Mallett's of Susquehana recorded live at our New York show. I'm Tracy Alloway. You can follow me at Tracy Alloway. And I'm Joe Wasnthal. You can follow me at the stalwart. Follow our producers, Carmen Rodriguez, Ed Carmen Arman, Dashobennet, Edashbot, Kale Brooks, Ed Kale Brooks, and Kevin Luzano at Kevin Lloyd Luzano. And for more AdLots content, go to Bloomberg.com/AdLots, ribidaley newsletters, and all of our episodes. And you can chat about all these topics 24/7 in our discord discord.gg/AdLots. And if you enjoy AdLots, if you like it, when we do these live shows and ask Susquehana if they can make markets in alien invasion contracts, then please leave us a positive review on your favorite podcast platform. And remember, if you are a Bloomberg subscriber, you can listen to all of our episodes absolutely ad free. All you need to do is find the Bloomberg channel on Apple podcasts and follow the instructions there. Thanks for listening. [Music] Start your day with Marketplace Morning Report and me, Kimberly Adams. In 10 minutes or less, I'll explain the day's economic news, why it matters, and what it means for the way you live and work. Tune in each weekday morning for independent award-winning journalism that brings clarity to the economy. Listen to Marketplace Morning Report on your favorite podcast app.

Podcast Summary

Key Points:

  1. Prediction markets are expanding beyond sports betting into areas like economics, politics, and weather, with potential for institutional hedging.
  2. Susquehanna International Group (SIG) acts as a market maker, providing liquidity and helping bootstrap both retail and institutional participation.
  3. SIG is willing to take on large risk positions, using prediction markets’ price discovery and super forecasters to set fair prices even with low volume.
  4. Institutional adoption is slow due to awareness, compliance, and legal hurdles, but SIG is building infrastructure (e.g., block trades, swaps) to facilitate it.
  5. Over half of current volume is sports, but non-sports markets are growing faster, and SIG aims to boost hedging use cases for economic value.

Summary:

The podcast explores prediction markets’ evolution with Jeremy Mallitz, head of prediction markets at Susquehanna International Group (SIG). SIG acts as a key market maker, providing liquidity across sports, politics, and economics, and aims to shepherd institutional investors into the ecosystem. Mallitz explains that market makers bridge gaps between buyers and sellers across time and size, essential for bootstrapping liquidity in new markets.

SIG’s culture of embracing risk allows it to take positions, even when not neutral, leveraging prediction markets’ price discovery and super forecasters to set fair prices on low-volume contracts. This enables SIG to offer large hedges for institutions, such as airlines hedging snowfall. , block trades, swaps).

Currently, sports dominate volume, but non-sports markets are growing faster. Mallitz emphasizes that hedging use cases are critical for the ecosystem’s future, with SIG uniquely positioned to facilitate them due to its risk appetite and quantitative models. The conversation highlights the potential for prediction markets to become useful for economic hedging, beyond pop culture or sports bets.

FAQs

The desk primarily acts as a market maker, providing liquidity on platforms for sports, economics, and politics. It also aims to shepherd other institutions into the prediction market ecosystem.

Market makers bridge gaps between buyers and sellers across time and size, ensuring liquidity even when counterparties aren't available simultaneously. This is crucial for markets without constant high trading volume.

While sports betting dominates volume, prediction markets also cover economics, politics, and unique events like snowfall or regulatory changes. They aim to provide useful hedging instruments for institutions.

Institutions face awareness issues, compliance hurdles, and concerns about low liquidity. Susquehanna addresses this by offering to provide large-scale liquidity and working with intermediaries like brokers or banks.

It uses quantitative models, trader insights, and capital to price contracts, focusing on economically valuable events. It doesn't cover all contracts, relying on community super forecasters for niche areas like pop culture.

Yes, non-sports markets are growing faster from a lower base, with increased interest in hedging and economic events. However, sports still represents over half of current volume.

Chat with AI

Loading...

Pro features

Go deeper with this episode

Unlock creator-grade tools that turn any transcript into show notes and subtitle files.