Pod Insights Odd Lots The King of Chicago Trading Wants to Build a GPU Market Bigger Than Oil About this episode Don Wilson has built a career diving into some of trading’s thorniest problems, including figuring out ways to trade new and niche markets. Now, the founder and CEO of DRW has his sights set on the GPUs powering AI, which he thinks could end up being a bigger market than crude oil. In this episode, which was recorded live onstage at our show in Chicago, we talk about how such a market would work, including ways to ‘standardize’ the vast array of different types of semiconductors, and how this could change the capital stack of the industry. We also talk the evolution of trading over Don’s storied career and why he thinks most assets (and maybe even all of them) will be tokenized within the next five years. Read more:ASM International Cuts Outlook After Chip Demand DisappointsTaiwan Pauses South African Chip Export Curbs After Two Days Only Bloomberg - Business News, Stock Markets, Finance, Breaking & World News subscribers can get the Odd Lots newsletter in their inbox each week, plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlotsSee omnystudio.com/listener for privacy information.
Transcript Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.
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2:35 Speaker 01 Hey there, Odd Lots listeners. You are about to get a conversation with Don Wilson,
2:40 Tracy Alloway? founder and CEO of DRW, sometimes called the smartest man in trading. This was recorded live onstage at Chicago's Untitled Supper Club. We had a blast and we hope you'll enjoy the show. All right, Don. Well, thank you for being here. Really appreciate it.
2:56 Speaker 04 Great to be here.
2:57 Tracy Alloway? Truly the perfect guest to talk about what's next in trading. But just to begin with, why GPUs?
3:05 Speaker 04 Well, obviously, AI is becoming more and more useful. And as it becomes more useful, people use more of it, which means they need to use more GPUs to run inference or train new models. And I actually have this theory that within the next 10 years, the world will spend more per year on GPUs than it does on crude oil. And that would, of course, make GPUs compute the largest commodity in the world. So it seems like you would kind of need a market for that.
3:39 Tracy Alloway? A very modest call. Just the largest market in the world.
3:43 Speaker 04 Yeah.
3:44 Joe Weisenthal? It's funny, because I associate oil often coming out of sandy deserts. But now they're literally turning the sand via chips into the commodity itself, or like breathing life into the sand. Just to back up, I have a million questions about this. For those who don't know, why don't you give us the sort of, you know, the 30-second or the 45-second description of what you do or what DRW is?
4:09 Speaker 04 Yeah, so I started off standing in the trading pit in Chicago, in the Euro-dollar option pit, yelling and screaming. And then I would go home and write code on my Macintosh computer and build models. And essentially, you know, I don't stand in the pit and yell and scream anymore. Most of the pits are gone. But we kind of do the same thing now with computers.
4:30 Tracy Alloway? I heard a story that you were once on vacation with your family and you were in Italy, I think in Florence, and instead of, I don't know, eating gelato or something like that, you decided to invent a new Greek letter for derivatives trading.
4:43 Speaker 04 So, so.
4:44 Joe Weisenthal? This is cool.
4:45 Speaker 04 Yeah, so, so here, I, I, I mean, you're confusing two stories. So, so actually, actually, what happened was there was a new exchange that had launched an interest rate swap futures contract. It was called IDCG. And I looked at the contract and I figured out that actually they had not designed the contracts properly. And so although they were telling everybody that it was economically equivalent to a regular interest rate swap, it wasn't because it had this additional convexity bias in it, which is, we, we could talk about convexity bias. It goes even more in the weeds than a lot of your podcasts go into, but, but, so when
5:28 Speaker 04 I was in Florence, I had this idea of how you could create an interest rate swap futures contract without this convexity bias problem. And that is what I focused my time on there.
5:38 Joe Weisenthal? What was the letter?
5:39 Speaker 04 So, so back to the letter, the, the, the letter was about, uh, after a really unpleasant period in the euro-dollar option pit where all the market makers lost tons of money because the shape of the skew shifted dramatically as the Fed started hiking in a very predictable manner. And nobody had really developed a measure for linear skew. And so during the week, I said, well, this isn't that much fun. We're losing a lot of money every day. But the good news is that that means we have something to learn. And so I spent the weekend working with the quants and we came up with, you know, kind of a, a measure of
6:21 Speaker 04 the linear skew between the calls and puts and decided to use the Greek letter psi to describe it. And, you know, so by Monday morning, we had put it into the risk and onto the sheets. And before the open, I explained to the traders how to talk about it, how to use language around it. And before you know it, we had made the money back because we were able to trade, manage this risk better than anybody else because we had a whole language around it.
6:51 Joe Weisenthal? Amazing.
6:51 Tracy Alloway? So we've established your street cred when it comes to solving problems in contracts for financial instruments. If I think about a GPU future or something like that, the first problem that comes to my mind is standardization. Because of course, you know, all different types of chips, different types of memory, different latency, I guess. How do you go about addressing that?
7:14 Speaker 04 So that's a great question. And, and right now, so what we've done is we've set up two companies. One is called Compute Exchange, not very creatively named. We have a tendency to do that.
7:25 Tracy Alloway? DRW is your initials, right?
7:27 Speaker 04 That was my trading badge and yes, also my initials. Yeah, I, you know, I mean, we did better later on with Cumberland, our crypto trading arm. That was actually of reference to the Grateful Dead song about Cumberland Mines.
7:40 Tracy Alloway? I didn't know that.
7:41 Joe Weisenthal? I didn't know that either.
7:42 Speaker 04 Yeah. One of my partners who does the more creative naming came up with that one. He's a, he's a dead fan. Anyway, the other company is called Silicon Data. And Silicon Data's job is to create indices that will become tradable, you know, will be viable to have futures contracts listed on them. And right now, they've created a number of different ones, but one is the H100 Index, another one is the A100 Index. And believe it or not, those indices are both available on Bloomberg.
8:16 Joe Weisenthal? Oh, amazing. That's a, I love hearing that. If we were in the studio, I would already be
8:20 Tracy Alloway? We would be looking at it.
8:21 Joe Weisenthal? I would already be looking up the chart as you were talking about it. Who are the natural participants? Because when I think about AI or training, you know, imagine someone goes to one of the big cloud vendors and they sign a long-term contract or whatever. Who are the participants who would be better off in an environment where there was a, a liquid market for compute?
8:42 Speaker 04 So what we found, and DRW actually uses Compute Exchange Source Compute. And we find that because there are something like 70 different cloud providers that participate, you can often get better pricing. And, and one of the things that you can do is you can specify if, let's say that you're an AI company
9:04 Joe Weisenthal? Yeah.
9:04 Speaker 04 and you know roughly what kind of cluster you want.
9:09 Speaker 04 You can specify that. You can even say, you know what, I'm indifferent between locations. Or, you know, if it's in the Middle East, I'm still okay with it, but I want to pay 20 cents per GPU or less. Whatever it is, you can kind of express your preference curve. Compute Exchange can conduct an auction and then, you know, find the kind of best price compute that matches your needs. So that's, that's kind of the, the idea of how it works. And, you know, it probably doesn't work if you want a 10,000 cluster monster for doing a huge training run. Okay. But for inference, it works great, or for smaller training runs, it works really well.
9:48 Tracy Alloway? Is the broader impact the idea that once you establish a liquid market where people can, you know, presumably hedge their exposure, that that would bring down the cost of capital?
9:58 Speaker 04 So that's right. So, so once you have a liquid market, then you have much more confidence in the indices. And you can then list futures contracts. And, and so what does that do? It enables the NeoClouds that are going out, raising capital, buying a bunch of GPUs, putting them in data centers and kind of hoping that they can rent them out and not really knowing what they're going to be able to rent them out for six months from now, let alone two years from now. So a NeoCloud could buy the GPUs, sell a strip of futures contracts. And I envision that these will be traded kind of like electricity futures where there's one for every month.
10:40 Speaker 04 And, and if you want to hedge the next three years, you sell 36 of them. And now you've locked in your pricing, obviously their cost of capital is going to go down, which in turn should make GPUs more readily available. And then on the flip side, if you're running an AI company and you raise a finite amount of dollars and you kind of know how much training you're going to do, but you don't know exactly what configuration, you can go ahead, buy the compute in the derivatives market. And then, once you have a clear view on exactly what configuration you want, then you can swap those derivatives for actual compute.
11:21 Joe Weisenthal? Talk to us a little bit more about the sell side. So like, we have these like, big clouds, right? The ones that everybody knows. And then you mentioned the Neo Clouds. Do you see that changing? Like, what do you see as the future mix of cloud vendors in the future?
11:39 Speaker 04 So, that is a great question. I think that the whole space is going to grow, but that the AWS, GCPs of the world will make up a smaller percentage of the whole.
11:52 Joe Weisenthal? Okay.
11:52 Speaker 04 That's my guess, but...
11:54 Joe Weisenthal? How come?
11:54 Speaker 04 Because there is such proliferation of other companies buying GPUs and deploying them.
12:01 Joe Weisenthal? Okay. That's a good answer.
12:03 Tracy Alloway? You know, Joe asked you who would be the natural market participants for this. I'm going to ask you the opposite question. Who wouldn't want this? Because I think of some of the hyperscalers. They seem to like controlling the GPU supply and maybe squeezing some of their competitors. Would you expect resistance from them?
12:21 Speaker 04 Yeah, I mean, I think the hyperscalers benefit from opaque pricing and kind of bundled pricing. And of course, they would prefer to have all the GPUs. But Nvidia wants...
12:32 Tracy Alloway? I would also prefer to have all the GPUs.
12:33 Speaker 04 Yeah, that's always a good thing. But I think Nvidia wants the GPUs to be widely distributed, and they're really the ones that make the call.
12:42 Joe Weisenthal? This isn't the first time that there's been an attempt to create futures markets out of technology. I think there's been multiple efforts decades ago to like DRAM futures. It doesn't seem that fundamentally different, although maybe it is. Why did those fail? Like, when you think about like, what's going to be different at this time? What was the failure that caused? Like, why didn't DRAM futures take off?
13:05 Speaker 04 So, the thing about DRAM was that the price just kept on going down. So, in a very predictable way. And so, why would you want to buy a futures contract if you know the price in the future is going to be lower? Whereas GPUs, you know, we've certainly gone through periods where GPU demand was super high. And then we've gone through a period where, you know, there was kind of some excess supply.
13:28 Joe Weisenthal? So, there's not a consistent trajectory of pricing?
13:31 Speaker 04 I think that there will be a consistent trajectory lower in terms of, I don't know, however you want to measure it, dollars per flop or dollars per token. I think that that's going to continue to decline. But, you know, an H100 is going to be a useful GPU for a very long time. And over its life, I think there will be periods where there's more demand, less demand, and, you know, a little bit more cyclicality and less predictability.
13:59 Tracy Alloway? So I know that the Trump administration has said that they want this market to happen, right? So you seem to have some regulatory, I guess, tailwind behind you.
14:09 Speaker 04 Yeah, I mean, I don't think that this is a controversial thing. I think that it's pretty clear that once we figure out the right index construction and have kind of sufficient data, that I don't think the CFTC would complain about the product.
14:41 Speaker 00 What's next for virtual assets? I'm Jacob Greece, host of Economy Scale, a series exploring growth in key global sectors. And this episode, we're diving into the digital forces shaping finance. Sean McHugh from Dubai-based Virtual Assets Regulatory Authority has this to say.
14:56 Speaker 06 We're seeing a lot of institutional players come in, digital asset dedicated hedge funds, high frequency traders and that sort of thing, and folks who service institutional clients.
15:05 Speaker 00 As more capital enters the market, adaptive regulation is likely to become increasingly key. Reese Merrick of Ripple says.
15:13 Speaker 07 A lot of regulators globally would like to keep the industry at arm's length. That's the opposite here. I think also what you'll find is that regulation and frameworks can come out, but some of them are maybe a slight iteration on some 80-year-old policy and not actually in line with what the technology can do and offer. And again, that's very different in Dubai.
15:32 Speaker 00 Listen to the full episode wherever you get your podcasts. This series is brought to you by Bloomberg Media Studios and the Dubai Department of Economy and Tourism.
15:42 Speaker 01 This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Muster. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume, so writes Bloomberg Businessweek's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs, and hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw innate intelligence. A spokesperson for SpaceX didn't respond to a request for comment on its recruiting
16:24 Speaker 01 and hiring practices, but according to recruiters, advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company, and Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates "must be willing to work extended hours and weekends as needed." One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time. That's the Bloomberg Tech Minute brought to you by ChatGPT. Get started at ChatGPT.com.
17:05 Speaker 02 Quick question for you. How much of your day is spent typing? Email, Slack, notes, prompts to ChatGPT? Whisperflow is a voice-to-text app. Instead of typing, you talk and it types for you in any app on your Mac, Windows, iPhone, or Android. It takes out the ums, fixes the typos, and the result sounds like you wrote it. Four times faster than typing. So the email that used to take two minutes now takes 30 seconds. Whisperflow is free. Download it at whisperflow.ai. That's W-I-S-P-R-flow.ai.
17:36 Joe Weisenthal? This is a little bit of a sideways question from your attempt to build this market. But speaking of the cloud, in your main business at DRW, I assume you're sort of major customers or users of the CME. Are you excited about the CME's migration of its backend to Google Cloud? Because they tout it, they talk about their partnership with Google, et cetera. As a client or customer, are you enthusiastic about this move?
18:02 Tracy Alloway? We interviewed Terry earlier today, and he was excited, for sure.
18:06 Speaker 04 Yeah, so it depends on what you put into the cloud. And it's totally fine to put a lot of things into the cloud. But the thing that you don't want to put into the cloud is a matching engine. And the reason for that is you want the matching engine to be as deterministic as possible. So that means that if you send two orders into the matching engine, one, let's say, a couple of microseconds behind the other one, you want the one that gets there first to be filled every time.
18:40 Joe Weisenthal? Yeah.
18:40 Speaker 04 And if you put stuff into the cloud, it's very hard to make that happen. You wind up getting a wide distribution around which order will be filled first. And even as you kind of stretch those times out, you could have an order that comes in, maybe a couple milliseconds later, be filled first. That is super disruptive for liquidity providers. And it means that the liquidity in the market is going to suffer.
19:11 Joe Weisenthal? Huh. But this is, you say it's not ideal for them to have a matching engine in the cloud. But this is the direction it's going in.
19:18 Speaker 04 Yeah, and it's unclear exactly which part of the matching engine will be in the cloud. Is it some kind of a dual structure? I don't know. But that's what matters, is a deterministic matching engine. I mean, if Google can figure out how to make matching engine in the cloud deterministic, go for it. I'm very skeptical that that's even possible.
19:38 Joe Weisenthal? Can you just describe the sort of theoretical problem? What is it about cloud computing that makes this particular problem, the deterministic aspect, difficult as opposed to traditional infrastructure?
19:51 Speaker 04 Well, when you have on-prem computers, you can, it's all right there. You can control where the wires go.
19:59 Joe Weisenthal? Oh, I see.
19:59 Speaker 04 And so when it's in the cloud, it's a little bit more, well, nebulous, I guess. It's just harder to do.
20:05 Tracy Alloway? That's a good pun. I admire it. So you mentioned that you have this long and storied career in the trading industry, starting from old school trading and now we're here talking about GPU trading and what's in the cloud and what works and what doesn't. Tell us what your company, what DRW is actually doing when it comes to practical application of AI. This is a question we're asking everyone. We ask all companies to spill all their proprietary secrets about AI.
20:35 Joe Weisenthal? Excluding the engineers. We know that they're generating code.
20:37 Tracy Alloway? We know people are coding.
20:39 Joe Weisenthal? Yes, we know that they're using Clog code or whatever. So besides the engineers.
20:43 Speaker 04 Yeah, you're right. That's kind of the boring answer.
20:45 Joe Weisenthal? Yeah, it's boring. And then the other thing is then when we ask this question, people cite a bunch of machine learning things that has been around forever. So let's talk about actual AI.
20:55 Speaker 04 Yeah, so I think that the way that we make trading decisions is going to change dramatically and it already is. You can use AI to interact with your proprietary data, your proprietary models and suggest trades. That's pretty cool.
21:16 Joe Weisenthal? Are you doing that right now?
21:17 Speaker 04 Yeah, so we're starting to do that, but we have some tools that kind of do that now. And the other thing that's really interesting is to fiddle around with agents and have different agents interact. And so you could kind of think about, maybe you have a couple different analysts, AI analysts, that both work on some stock and then you have kind of a risk-taking agent or maybe a couple of different risk-taking agents that interact with those analysts and then come up with trades based on that. So, I mean, these are, you know, that's a little bit of a theoretical concept, but I don't think we're that far away from things like that.
21:55 Joe Weisenthal? Just on the cloud trading a little bit more, I am really interested in this topic. What is the current state today? Just so that we understand where you're at. Like, what is today's snapshot of usage of the platforms?
22:08 Speaker 04 I mean, as far as where the matching engines are?
22:10 Joe Weisenthal? No, no, no, oh, sorry. On the GPU trading.
22:13 Speaker 04 Oh, the GPU.
22:14 Joe Weisenthal? How active is it right now? Like, where is the state of the business?
22:18 Speaker 04 You know, I think last month, we conducted five or six auctions. So it's early, but it's happening.
22:26 Tracy Alloway? So when I think about how like futures contracts are born, it's usually bespoke options. And then you get the index, I guess, and then you get a forward and then a future. That's kind of how I think about it in my head. Is that the process that you imagined for this?
22:41 Speaker 04 Uh, not necessarily. I think that the simplest, I mean, I, yeah, I suppose you could do some privately negotiated compute swap or something, and maybe that will happen first. But no, I think the first thing is a futures contract that settles to an index. If the spot market becomes really liquid and you have very standardized auctions. And, you know, one of the things that you asked about was, well, how do you deal with the lack of standardized, you know? And so one thing is you go to a certain type of GPU, you know, H100, for instance. But even within that, you can configure them in different ways. You could use InfiniBand, you could use some other way of connecting them.
23:25 Speaker 04 And so what's important is you need to decide on some benchmark. And one of the things that Silicon Data has done is they've actually built some measurement tools that measure how fast a GPU cluster is. And so you can then say, okay, well, in order for this GPU to be kind of eligible to be in the index, it needs to meet a certain standard. And you can, there are a couple of different vectors you can measure by. So I think that that's kind of how you would do it. And then if you got very liquid auctions, you could actually have a futures contract that cash settles to the auction price.
24:07 Speaker 04 And then, you know, people could have the option of either essentially just cash settling their derivative and walking away, or cash selling their derivative and participating in the auction. And they would know that price would transfer from one thing to another. That might be a future state of the world, and the initial state is probably just a generic index and the futures cash settle to the index.
24:30 Tracy Alloway? What would a market failure look like in GPU trading? Because your analogy is the oil market and, you know, weird stuff happens in the oil market. Could we get negative GPU prices? Or if everyone wakes up one day and decides they want to use ChatGPT as their psychotherapist or whatever, which some people are doing, could you have a GPU shortage where maybe people can't deliver into the contract?
24:54 Speaker 04 There are lots of ways that markets can break and go wrong. And I remember to this day that when oil futures went negative, it was during COVID. I was sitting at home, I was trading oil futures and I bought oil futures for negative prices.
25:08 Joe Weisenthal? You were one of the ones that actually got us.
25:11 Tracy Alloway? Amazing.
25:11 Speaker 04 My then, what was that, 2021? So yeah, my then 14-year-old said to me, "Please, please, please, I want to buy negative-priced futures contracts." And I said, "Well, you have no way of taking delivery of the oil." And he said, "I will go to Cushing, Oklahoma and figure out how to do it."
25:32 Joe Weisenthal? You've really raised a son, daughter, son.
25:36 Speaker 04 Son.
25:36 Joe Weisenthal? You've really, he's been learning.
25:39 Tracy Alloway? We have, we have an episode about taking physical possession of oil. I do not recommend it. Turns out, if you keep it on your desk for long enough, it evaporates into the atmosphere and poisons your colleagues.
25:50 Speaker 04 Yeah, anyway, a little bit of a tangent. So I think on the upward trajectory, if there's tons of demand, you know, that's something that commodity markets are really good at dealing with. The price will go up and more supply will come in and I think that's all good. On the downward side, you know, you can always just turn the GPUs off. So I don't think they trade negative.
26:13 Joe Weisenthal? How much of the volatility that do you, when you anticipate market volatility in the price of GPUs, how much of that like embedded electricity cost? So when you buy compute, right, you're buying the chip but also the power. Like, how much of that volatility will be the power?
26:28 Speaker 04 So the industry lingo that's used is total cost of ownership and, you know, what percentage of the total cost of ownership is the power price? And for an H100, it's less than 15%.
26:41 Joe Weisenthal? Less than 15?
26:42 Speaker 04 Yeah.
26:42 Joe Weisenthal? Okay.
26:43 Tracy Alloway? So GPU trading, obviously one of the things you're working on, but you're a busy guy and you've got other stuff up your sleeve. What are you doing in the realms of tokenized trading?
26:54 Speaker 04 So that is an area that we're super excited about. And we've been thinking about this for a very long time. So in 2012, when we started talking about Bitcoin at DRW, and there were a number of traders at DRW that were very excited about Bitcoin.
27:10 Tracy Alloway? You were very early into it. 2012 was still pretty early.
27:13 Speaker 04 Very early, yeah. So we were having these discussions of, why is this interesting? Is it interesting? What about it is interesting? And we came away with the following thesis. There's some small chance that Bitcoin could be digital gold. I don't know. You know, call it 1%. It's kind of an interesting product, so we should probably make markets in it. So we set up Cumberland as the... And, you know, we didn't call it DRW because at the time, everybody knew that anybody trading crypto was obviously a crook. So, you know, we wanted to kind of separate the brand a little bit. But, you know, the other thing was this idea that you could move value instantaneously in a trustless ecosystem was super interesting to me.
27:55 Speaker 04 And I said, wow, if you could do that in traditional financial markets, that would make the market so much better, so much more resilient. And so we should really figure out how to do that. So we started a company called, again, not very creatively named, Digital Asset Holdings, which created the Canton blockchain. Initially, the Canton blockchain was a private permissioned chain, but last summer, it actually became a public chain. And that chain was designed specifically with tokenization of traditional financial instruments in mind. So it has a couple of characteristics. One is it has configurable privacy. And believe it or not, for people who are in the finance business,
28:38 Speaker 04 they don't want to broadcast to the entire world when they are buying or selling something.
28:43 Joe Weisenthal? Right.
28:43 Speaker 04 I mean, obviously, if it's above the reporting thresholds, you do. So that was kind of a fundamental characteristic of this chain. It's different than Ethereum or Solana or any of these other things, where if you tokenize something and put it on top, and you move it around, everybody sees it move around. So that's kind of... Something we've been working on for quite a while.
29:03 Joe Weisenthal? How big could this get? Like, could it swallow everything? Could you imagine a world in which, given any financial instrument, a stock, a bond, et cetera, that it all sort of ends up on-chain?
29:16 Speaker 04 Yeah, I think that everything will be on-chain.
29:18 Joe Weisenthal? Wow. By when? Give us a year.
29:21 Speaker 04 No, I'm always way too early on this stuff. But I think in the next five years,
29:25 Joe Weisenthal? Really?
29:26 Speaker 04 all of these instruments will be on-chain.
29:28 Joe Weisenthal? Okay, that's a good.
29:29 Speaker 04 Primarily on-chain.
29:30 Joe Weisenthal? Pretty soon. We will have a live episode at 2030. We'll come back to Chicago. We'll revisit that question, yeah.
29:52 Speaker 01 This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Muster. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Businessweek's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs and hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw innate intelligence. A spokesperson for SpaceX didn't respond to a request for comment on its recruiting and hiring practices, but according to recruiters,
30:36 Speaker 01 advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company, and Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates, quote, "must be willing to work extended hours and weekends as needed." One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time. That's the Bloomberg Tech Minute brought to you by ChatGPT. Get started at chatgpt.com.
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32:44 Tracy Alloway? Is the idea with tokenized assets also that you could use that for collateral management and use it as a way to move collateral?
32:52 Speaker 04 100%. And so, everybody's talking about moving to 24/5 or 24/7 markets. And if you want to do that, it's really important to be able to move collateral 24/5 or 24/7 and move variation margin 24/5 or 24/7. And so, yes, that is a very important use case.
33:15 Joe Weisenthal? So speaking of very exciting sexy topics in trading, right after you, we're going to be speaking with Tarek Mansour of Kelsi. And so prediction markets are super hot. Where are you at with them? Is DRW making markets in any of these, in any of the spaces right now?
33:32 Speaker 04 So a million years ago, we actually made markets in prediction markets. I think it was, I don't know, in trade or something.
33:40 Joe Weisenthal? Yeah.
33:40 Speaker 04 And it never went anywhere. Nobody cared. And I always thought, you know, prediction markets should be a thing. Everybody should care. But nobody did. And then Augur came out and I was like, oh, this is really cool. This is going to take off and nobody cared. And so it's, it's taken a long time. So at this point, we use it as a reference price. You know, obviously during the election, it was super helpful to use that as a gauge of.
34:03 Tracy Alloway? Oh, so you were actually using that because, you know, we hear stories about institutional investors maybe finding prediction markets useful perhaps. But you were looking at it.
34:12 Speaker 04 We were definitely looking at it. We were not using it as a hedge. And it was funny, Shane messaged me and said, hey, you know, it's, it's, uh, it's up on Bloomberg now. And I was like, oh, that's awesome, Shane.
34:24 Joe Weisenthal? Shane Copeland from Polly.
34:25 Speaker 04 Yeah, that's right. Yeah.
34:27 Joe Weisenthal? But currently, like, do you foresee, like, are you going to enter not either in making markets on some of these exchanges? And would you get into the, uh, the sports contracts?
34:37 Speaker 04 I mean, so we're not here. I think it's highly likely that we'll start trading some of the prediction markets. Some of our competitors already trade in the sports markets pretty actively. We don't. So it's not necessarily a natural fit, but I don't have like a religious opposition to it.
34:55 Tracy Alloway? Would there be different considerations for trading in a prediction market versus a traditional financial asset? Are there different things you have to think about, either in terms of like pricing the trade or maybe risk management?
35:07 Speaker 04 Well, I think it depends on what the prediction market is. I mean, if you're trading a prediction market on, I don't know, whether somebody will throw a rubber object onto a WNBA court.
35:22 Speaker 04 Then, I mean, that's something that people in the audience can control. And so it seems like providing liquidity in that, you would be at a disadvantage.
35:31 Tracy Alloway? That was a very particular example, by the way.
35:35 Tracy Alloway? I was gonna go with Taylor Swift getting married, but you went with that one.
35:39 Joe Weisenthal? Well, these are markets that people can directly intervene on.
35:43 Speaker 04 Directly impact, right?
35:45 Tracy Alloway? This is true.
35:46 Speaker 04 As opposed to, for instance...
35:47 Joe Weisenthal? Inside trade their own antisocial behavior.
35:49 Speaker 04 That's right. And as opposed to, will the Fed cut 25 or 50 or stay on hold? I mean, you can trade that in SOFR, you can trade that in the Fed Funds Futures. There are some binaries you can trade. And so the prediction market version of that is totally fits in with the risk that we already trade.
36:13 Joe Weisenthal? So we mentioned in the intro, there's gonna be this big meeting in DC next week. And we just happened to sort of catch a bunch of the participants. When you look at the landscape for these new futures platforms, because that's what they are, right? The CME, has regulation been part of their dominance? Has regulation made it harder for other entrants to cut into CME margins or volumes?
36:40 Speaker 04 So...
36:42 Joe Weisenthal? I'm trying to ask questions that are gonna create some tension around the table next week.
36:46 Speaker 04 Yeah, still here. I mean...
36:48 Tracy Alloway? Oh yeah, you should hear what Terry said about Howard Lutnick.
36:51 Speaker 04 I...
36:52 Joe Weisenthal? It'll be on the podcast.
36:52 Speaker 04 I'm sure. I can probably repeat it without having heard it. So, once you have a liquid market in something, it becomes a natural monopoly. It's very hard to move that to a different venue. It's happened before. I was living in London in the mid 90s. And the Bund Futures were...
37:16 Speaker 04 On the floor of the life, it was this huge trading pit with a bunch of guys pushing and shoving. And over the course of 12 months, the DTB, now called the URX, was able to move the entire Bund futures complex onto the computer on a different exchange. Now, I mean, they gave hefty incentives to people. I think they went to all the German banks and they said, don't you dare trade on life anymore. So it's possible, but I think that these things are generally, I don't think that it's really a regulatory issue that causes them to be sticky. I think it's more just kind of a natural state of affairs.
37:56 Tracy Alloway? Network effect, I guess. So our theme for this evening is obviously the future of trading. And one of the things that seems to be happening is the sort of intermingling of professional and retail trading. And we, again, talked about that with Terry. I'm sure we're about to talk about it with the Calci CEO. But from your perspective, and again, you started this career back when, I don't think there were any retail traders doing day trading, really. How has that changed the way you think about trading? And can you envision a future where, I don't know, AI fires all of us and we're all going to be just day trading from home as an insurance policy? Robinhood is really a full employment program. Maybe. For US workers.
38:39 Speaker 04 Yeah, so, I mean, that is a thesis that I have heard is that what's happening is a bunch of relatively successful people are losing their jobs and they're retiring. But in their retirement, they decide to just manage their portfolios on Robinhood. And so there's this surge in trading activity that, you know, wouldn't have happened 10 years ago. And it's only going to grow from here. And I don't know, maybe that's right.
39:10 Joe Weisenthal? It feels to me like culturally, because you're talking about, right? Why have prediction markets taken off when they've been around for over 20 years? I think I first heard about them in like 2002 or 2003. They've suddenly taken off. There was never a bright line between what's gambling and what's sort of hedging or what's trading. But there's clearly, whatever line that is, just feels like it's completely collapsing. Is this good? Do you have an opinion like should should we is there is and I don't know if any of our opinions matter on the question because it feels like culturally we're entering this world where everything will be tradable on any app and there's you know you're going to see a price for gold futures right next to one day the line on a football match etc. Is it do we want this world?
39:53 Speaker 04 So I don't think that there's anything particularly wrong with it, but I am a little bit confused about whether prediction markets and sports are actually consistent with what the commodity exchange act says is permissible. And so I know that your next your next guess is
40:17 Joe Weisenthal? You're setting us up perfectly here.
40:19 Speaker 04 Is benefits from his ability to list these contracts and and I don't know if you know the CFTC is just kind of asleep and I know they're kind of understaffed now or
40:29 Joe Weisenthal? You want to stay on stage.
40:31 Tracy Alloway? Yeah, you can ask questions.
40:33 Speaker 04 Or or maybe they've decided that actually these are economically important transactions that are consistent with the CEA. It's unclear to me.
40:43 Joe Weisenthal? Amazing.
40:44 Tracy Alloway? All right, well, we're going to have to leave it there, but Don Wilson, founder and CEO of DRW, thank you so much for being here. Really appreciate it.
40:52 Speaker 04 Thank you for having me.
40:53 Tracy Alloway? That was our conversation with DRW founder and CEO Don Wilson, recorded live onstage in Chicago. I'm Tracy Alocke. You can follow me at Tracy Alocke.
41:17 Joe Weisenthal? And I'm Jill Weisenthal. You can follow me at the Stalwart. Follow our producers, Carmen Rodriguez at Carmen Armin, Dashell Bennett at Dashbot, and Cale Brooks at CaleBrooks. For more Odd Lots content, go to Bloomberg.com/oddlots, where the daily newsletter and all of our episodes. You can chat about all of these topics 24/7 in our Discord, discord.gg/oddlots.
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