The King of Chicago Trading Wants to Build a GPU Market Bigger Than Oil

Summary

Odd Lots Podcast Summary

Episode Title: The King of Chicago Trading Wants to Build a GPU Market Bigger Than Oil
Date: September 29, 2025
Host(s): Tracy Alloway & Jill Weisenthal
Guest: Don Wilson (Founder and CEO, DRW)
Format: Live from Chicago’s Untitled Supper Club

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Episode Overview

In this engaging Odd Lots episode, Joe Weisenthal and Tracy Alloway talk with Don Wilson, the founder and CEO of trading giant DRW and often dubbed the "smartest man in trading." The conversation focuses on Wilson’s ambitious plan to create a commodity market for GPUs (graphics processing units) that rivals—perhaps even surpasses—the scale of the global crude oil market. Beyond GPUs, the discussion ventures into the future of trading, standardization in financial instruments, pitfalls in tech-based futures markets, tokenized assets, prediction markets, and the industry’s evolving relationship between professional and retail traders. The tone is fast-paced, curious, and often irreverent, with technical depth and insider anecdotes.

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Key Discussion Points & Insights

1. Why a GPU Market? (02:12–02:53)

• Don Wilson’s vision:
  “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…you would kind of need a market for that.” (Don Wilson, 02:19)
• Reasoning: As AI grows, demand for GPUs to power model training and inference explodes—necessitating transparent, standardized pricing and tradable futures.

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2. Don Wilson’s Background & Street Cred (03:23–06:05)

• Trading origins: Wilson started on the Chicago Eurodollar option pit, combining pit trading with coding and model-building at home.
• Inventing "Psi":
  Wilson created a new Greek letter, psi, to quantify and manage linear skew risk in options.
  “We came up with kind of a measure of the linear skew between the calls and puts and decided to use the Greek letter psi to describe it…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.” (Don Wilson, 04:53)

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3. Building a Standardized GPU Market (06:05–09:02)

• Companies established:
  • Compute Exchange: Marketplace for matching compute demand and supply.
  • Silicon Data: Builds GPU price indices (e.g., H100, A100 indices, listed on Bloomberg).
• Standardization challenge:
  “All different types of chips, different types of memory, different latency…How do you go about addressing that?” (Tracy Alloway, 06:06)
• Solution: Indices and auctions define a product standard (by GPU type and performance benchmark) to enable transparent trading.

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4. Market Participants & Impact (07:31–10:36)

• Who benefits:
  • Niche cloud providers (“NEO clouds”) and AI companies can use Compute Exchange to source GPUs more efficiently.
  • AI firms gain flexibility by hedging future GPU needs (through futures contracts), potentially reducing cost of capital.
• Quote:
  "If you want to hedge the next three years, you sell 36 of them [monthly GPU futures] 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.” (Don Wilson, 09:12)

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5. How Will Cloud Market Structure Shift? (10:36–11:15)

• Prediction: Big clouds (AWS, GCP, etc.) remain but shrink as a fraction of a rapidly expanding GPU market. Proliferation of new players and NEO clouds is expected.

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6. Incumbent Resistance & Opaque Pricing (11:17–11:56)

• Incumbent advantage:
  “Hyperscalers benefit from opaque pricing and kind of bundled pricing. And of course they would prefer to have all the GPUs, but Nvidia, I…would also prefer to have all the GPUs...But I think Nvidia wants the GPUs to be widely distributed and they're really the ones that make the call.” (Don Wilson, 11:36–11:48)

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7. Why DRAM Futures Failed & GPU Price Volatility (12:20–13:14)

• Historic attempts failed: DRAM futures didn’t take off as their prices declined predictably, reducing hedging interest.
• GPUs are different: Cyclicality and multiple value streams (training, inference, gaming) should ensure more persistent demand shocks.

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8. Regulatory & Market Structure Issues (13:14–14:25)

• Political and regulatory support:
  “I don't think that this is a controversial thing...I don't think the CFTC would complain about the product.” (Don Wilson, 13:24)

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9. Cloud Trading Infrastructure – The Matching Engine Debate (16:39–19:08)

• CME's move to Google Cloud:
  Wilson is skeptical about moving critical parts, especially the matching engine, to the public cloud, due to risks to determinism and market fairness.
• “You want the matching engine to be as deterministic as possible...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. That is super disruptive for liquidity providers.” (Don Wilson, 17:09)

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10. AI Trading in Practice at DRW (19:08–21:11)

• Current state:
  • Using AI to interact with proprietary data and suggest trades.
  • Experimenting with agent-based AI models (multiple "analyst" agents, risk-taking agent).
• “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...we have some tools that do that now.” (Don Wilson, 19:58–20:20)

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11. State and Evolution of GPU Derivatives Market (21:13–23:33)

• Current activity: Five or six auctions conducted in the past month—market is nascent but building.
• Contract structure:
  Wilson expects straightforward cash-settled futures against GPU indices, with benchmarks ensuring cluster performance comparability.

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12. Commodity Market Risks & Failure Scenarios (23:33–25:16)

• Market failure risks:
  Asked if GPUs could go negative like oil, Wilson recounted trading negative-priced oil futures during COVID-19:
  “I bought oil futures for negative prices. 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 the oil. And he said, I will go to Cushing, Oklahoma and figure out how to do it.” (Don Wilson, 24:14–24:35)
• But for GPUs: Negative pricing unlikely—if demand crashes, you just turn GPUs off instead of inventing storage.

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13. GPU Pricing and Electricity Costs (25:16–25:44)

• Power is a modest share of total cost: “For an H100, it's less than 15%” (Don Wilson, 25:32)

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14. Tokenized Trading & On-Chain Finance (25:45–28:31)

• DRW’s history in crypto markets (Cumberland) and early interest in using public ledgers for traditional assets.
• Digital Asset Holdings & the Canton chain: Created for privacy and financial instrument tokenization.
• Bold prediction: “I think that everything will be on chain...” (Don Wilson, 28:19)
• Timeline: Next five years for mainstream adoption.

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15. Collaterals and 24/7 Markets (31:07–31:30)

• Tokenization enables instant collateral movement, key to making round-the-clock markets work.

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16. Prediction Markets (31:30–34:28)

• DRW’s historic and pragmatic use:
  “We use it as a reference price. Obviously during the election it was super helpful to use that as a gauge…” (Don Wilson, 32:18)
• Not currently providing liquidity but open-minded.
• Prediction market quirks:
  “If you’re trading a prediction market on…whether somebody will throw a rubber object onto a WNBA court…providing liquidity in that you would be at a disadvantage.” (Don Wilson, 33:21)

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17. CME, Regulation, and Natural Monopolies in Futures (34:28–36:13)

• Once a futures market is established, it gains a network effect and is hard to unseat—not mainly a regulatory issue.
• “Once you have a liquid market in something, it becomes a natural monopoly. It’s very hard to move that to a different venue.” (Don Wilson, 35:00)

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18. Blurring of Retail & Professional Trading and the Rise of “Tradable Everything” (36:13–38:58)

• Rise of retail traders, prediction markets, and convergence with traditional trading.
• “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.” (Jill Weisenthal, 37:24)
• Don Wilson voices legal skepticism: unclear if prediction markets and sports contracts truly fit the Commodity Exchange Act.

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Notable Quotes (with Attribution & Timestamps)

• “Within the next 10 years, the world will spend more per year on GPUs than it does on crude oil.”
  – Don Wilson, 02:19

• “We came up with...the Greek letter psi to describe [linear skew]. 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.”
  – Don Wilson, 04:53

• “Hyperscalers benefit from opaque pricing... Nvidia wants the GPUs to be widely distributed and they're really the ones that make the call.”
  – Don Wilson, 11:36

• “You want the matching engine to be as deterministic as possible...If you put stuff in the cloud, it's very hard to make that happen...That is super disruptive for liquidity providers.”
  – Don Wilson, 17:09

• “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.”
  – Don Wilson, 19:58

• “I think that everything will be on chain.”
  – Don Wilson, 28:19

• “Once you have a liquid market in something, it becomes a natural monopoly. It’s very hard to move that to a different venue.”
  – Don Wilson, 35:00

• “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.”
  – Jill Weisenthal, 37:24

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Timeline of Important Segments

• 02:12 – Don Wilson introduces the idea of a GPU market bigger than oil.
• 03:23 – Wilson’s trading background and invention of the “psi” risk measure.
• 06:05–09:02 – How DRW’s Compute Exchange and Silicon Data aim to standardize GPU trading.
• 10:36 – Predictions on changing cloud vendor landscape.
• 12:20 – Why DRAM futures failed vs. GPUs.
• 16:39–19:08 – Deep dive on determinism in cloud-based matching engines.
• 19:08 – Practical use of AI for trading at DRW.
• 21:19–23:33 – The current state and envisioned evolution of GPU derivatives markets.
• 24:14 – Wilson’s recounting of trading negative oil futures with his son.
• 25:32 – Discussion of power costs in GPU total ownership.
• 25:45–28:31 – Tokenization journey and prediction of all assets on chain.
• 31:07 – Role of tokenization in collateral management/24x7 markets.
• 31:46–33:54 – The state and challenges of prediction markets.
• 34:28–36:13 – Futures platforms, regulation, and natural monopolies.
• 36:13–38:58 – Rise of retail trading, prediction markets, and blurring with gambling.

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This episode delivers a rare, insider view into both the conceptual design and real-world challenges of building the next great commodity market, as well as candid perspectives on the future of finance from an industry legend.

Transcript

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[Tracy Alloway]

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[Tracy Alloway]

Hey there odd lots Listeners, you are about to get a conversation with Don Wilson, founder and CEO of drw, sometimes called the smartest man in trading. This was recorded live on stage 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.

[Don Wilson]

Great to be here.

[Tracy Alloway]

Truly the perfect guest to talk about what's next in trading. But just to begin with, why GPUs?

[Don Wilson]

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.

[Tracy Alloway]

A very modest call. Just the largest market in the world.

[Jill Weisenthal]

Yeah, it's funny because I associate oil often coming out of sandy desert, but now they're literally turning the sand and 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 32nd or the 45 second description of what you do or what DRW is?

[Don Wilson]

Yeah. So I started off standing in the trading pit in Chicago, in the Eurodollar option pit, yelling and screaming. And then I would go home and write code on my Macintosh computer and put build models. And essentially 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.

[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.

[Jill Weisenthal]

This is cool.

[Don Wilson]

Yeah. So here, I mean, you're confusing two stories. So 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 could talk about convexity bias. It goes even more in the weeds than a lot of your podcasts go into. So when 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.

[Jill Weisenthal]

What was the letter?

[Don Wilson]

So back to the letter. The letter was about after a really unpleasant period in the Eurodollar 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 kind of a measure of the linear skew between the calls and puts and decided to use the Greek letter psi to describe it. And so by Monday morning, we had put. 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.

[Jill Weisenthal]

Amazing.

[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, all different types of chips, different types of memory, different latency, I guess. How do you go about addressing that?

[Don Wilson]

That's a great question. What we've done is we set up two companies. One is called Compute Exchange. Not very creatively named. We have a tendency to do that.

[Tracy Alloway]

A DRW is your initials, right?

[Don Wilson]

That was my trading badge. And yes, also my initials, YE I. You know, I mean, we did better later on with Cumberland, our crypto trading arm. That was actually a reference to the Grateful Dead song about the Cumberland mines.

[Tracy Alloway]

Oh, I didn't know that.

[Jill Weisenthal]

I didn't know that either.

[Don Wilson]

Yeah, one of my partners who does the more creative naming came up with that one. 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, 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.

[Jill Weisenthal]

Amazing. I love hearing that. If we were in the studio, I would already be, we would be looking it up. 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 liquid market for compute?

[Don Wilson]

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 one of the things that you can do is you can specify if, let's say that you're an AI company and you know roughly what kind of cluster you want, 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 $0.20 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 kind of 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, but, but for inference it works great, or for smaller training runs it works really well.

[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.

[Don Wilson]

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 so what does that do? It enables the NEO clouds 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 NEO cloud 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. 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 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.

[Jill 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?

[Don Wilson]

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 space smaller percentage of the whole. Okay, that's my guess.

[Jill Weisenthal]

But how come?

[Don Wilson]

Because there's such proliferation of other companies buying GPUs and deploying them.

[Jill Weisenthal]

Okay, that's a good answer.

[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?

[Don Wilson]

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, I.

[Tracy Alloway]

Would also prefer to have all the GPUs.

[Don Wilson]

Yeah, 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.

[Jill 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?

[Don Wilson]

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. We've certainly gone through periods where GPU demand was super high and then we've gone through a period where there was kind of some excess supply.

[Jill Weisenthal]

There's not a consistent trajectory of pricing.

[Don Wilson]

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 a little bit more cyclicality and less predictability.

[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.

[Don Wilson]

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. Foreign.

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[Jill 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 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?

[Tracy Alloway]

We interviewed Terry earlier today and he was excited, for sure.

[Don Wilson]

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. 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. 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.

[Jill Weisenthal]

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.

[Don Wilson]

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.

[Jill 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?

[Don Wilson]

Well, when you have on prem computers, you can, it's all right there. You can control where the wires go.

[Jill Weisenthal]

Oh, I see.

[Don Wilson]

And so when it's in the cloud, it's a little bit more, well, nebulous, I guess it's just harder to do.

[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, excluding the.

[Jill Weisenthal]

Engineers, we know that they're. We know that they're generating.

[Tracy Alloway]

We know people are.

[Jill Weisenthal]

Yes, we know that they're using clog code or whatever. So besides the engineering.

[Don Wilson]

Yeah, yeah, yeah, you're right. That's kind of the boring answer.

[Jill Weisenthal]

Yeah, it's the boring. And then the other thing is then when we ask this question, people cite a bunch of machine learning things that have been here for a while. So let's talk about actual AI.

[Don Wilson]

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.

[Jill Weisenthal]

Are you doing that right now?

[Don Wilson]

Yeah, so we're starting to do that, but we have some tools that do that now. 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 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.

[Jill 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?

[Don Wilson]

I mean, as far as where the matching engines are.

[Jill Weisenthal]

No, no, no, no, sorry. On the, on the GPU trading. Oh, how do you visit right now? Like, like where is the state of the business?

[Don Wilson]

Oh, you know, I think last month we conducted five or six auctions. So it's early but, but it's happening.

[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 imagine for this?

[Don Wilson]

Not necessarily. I think that the simplest, I mean, 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 one of the things that you asked about was, well, how do you deal with the lack of standardized and so one thing is you go to a certain type of GPU 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. 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 there are a couple 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. And then people could have the option of either essentially just cash settling their derivative and walking away, or cash settling 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 future is cash settled to the index.

[Tracy Alloway]

What would a market failure look like in GPU trading? Because your analogy is the oil market and weird stuff happens in the oil market. Could we get negative GPU prices? Or if everyone, everyone wakes up one day and decides they want to use ChatGPT as their psychotherapist or whatever some people are doing, could you have a GPU shortage where maybe people can't deliver into the contract?

[Don Wilson]

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.

[Jill Weisenthal]

You were one of the. He made money. Amazing.

[Don Wilson]

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 the oil. And he said, I will go to Cushing, Oklahoma and figure out how to do it.

[Jill Weisenthal]

You've really raised son, daughter, son, son, you've really. He's been learning.

[Tracy Alloway]

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.

[Don Wilson]

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 can always just turn the GPUs off. So I don't think they trade negative.

[Jill Weisenthal]

How much of the volatility? When you anticipate market volatility in the price of GPUs, how much is that embedded electricity cost? So when you buy compute, right, you're buying the chip, but also the power. How much of that volatility will be the power?

[Don Wilson]

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%.

[Jill Weisenthal]

Less than 15, yeah.

[Tracy Alloway]

Okay, 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?

[Don Wilson]

So. 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, you were.

[Tracy Alloway]

Very early into it. 2012 was still pretty early.

[Don Wilson]

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, 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 we didn't call it drw because at the time everybody knew that anybody trading crypto was obviously a crook. So we wanted to kind of separate the brand a little bit. But the other thing was this idea that you could move value instantaneously in a trustless ecosystem was super interesting to me. 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. 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, they don't want to broadcast to the entire world when they are buying or selling something. I mean, obviously if it's above the reporting thresholds, you do. So that was kind of a fundamental characteristic of this chain. That'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.

[Jill 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?

[Don Wilson]

Yeah, I think that everything will be on chain.

[Jill Weisenthal]

Wow. By when? Give us a. Give us a year.

[Don Wilson]

No, I'm always way too early on this stuff. But, but I think in the next five years, really all of these instruments will be on chain.

[Jill Weisenthal]

Okay, that's a good. Primarily we will have a live episode in 2020.

[Tracy Alloway]

We'll come back to Chicago, we'll revisit that question.

[Jill Weisenthal]

Yeah.

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[Tracy Alloway]

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[Don Wilson]

Founder of Meaningful Beauty. Well, I don't know about you, but.

[Tracy Alloway]

Like I never liked being told, oh wow, you look so good for your age. Like, why even bother saying that? Why don't you just say you look great at any age, every age. That's what Meaningful Beauty is all about. We create products that make you feel confident in your skin at the age you are now. Meaningful Beauty, beautiful skin at every age.

[Don Wilson]

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[Jill Weisenthal]

Month for premium wireless.

[Don Wilson]

And if you haven't made the switch yet, here are 15 reasons why you should. One, it's $15 a month. Two, seriously, it's $15 a month. Three, no big contracts. Four, I use it.

[Jill Weisenthal]

Five, my mom uses it.

[Don Wilson]

Are you, are you playing me off? That's what's happening, right?

[Jill Weisenthal]

Okay, give it a try.

[Don Wilson]

@Mintmobile.Com Switch upfront payment of $45 for.

[Tracy Alloway]

Three month plan, $15 per month equivalent required. New customer offer first three months only, then full price plan options available, taxes and fees extra. See mintmobile.com, is the idea with tokenized assets also that you could use that for collateral management and use it as a way to move collateral 100%.

[Don Wilson]

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.

[Jill Weisenthal]

So speaking of very exciting sexy topics in trading, right after you, we're going to be speaking with Tarek Mansour of Kalshi. 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?

[Don Wilson]

So a million years ago we actually made markets and prediction markets, I think it was, I don't know, in trade or something. And it never went anywhere. Nobody cared. And I always thought prediction market 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. So it's taken a long time. So at this point we use it as a reference price. Obviously during the election it was super helpful to use that as a gauge of.

[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.

[Don Wilson]

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, it's up on Bloomberg now. And I was like, oh, that's awesome.

[Jill Weisenthal]

Shane, the Shane Copeland from Poly.

[Don Wilson]

Yeah, that's right. Yeah.

[Jill Weisenthal]

But currently, like, do you foresee, like, are you going to enter not either making markets on some of these exchanges and would you get into the sports contracts?

[Don Wilson]

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.

[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. To think about either in terms of pricing the trade or maybe risk management?

[Don Wilson]

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, 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.

[Tracy Alloway]

That was a very particular example, by the way. I was going to go with Taylor Swift getting married, but you went with that one.

[Jill Weisenthal]

Well, these are markets that people can directly intervene on, directly impact, as opposed to, for instance, their own antisocial behavior.

[Don Wilson]

That's right. 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 totally fits in with the risk that we already trade.

[Jill Weisenthal]

So we mentioned in the intro there's going to be this big meeting in D.C. 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? So I'm trying to ask questions that are going to create some tension around the table next week.

[Don Wilson]

Yeah. So here, I mean.

[Tracy Alloway]

Oh, yeah. You should hear what Terry said about Howard Lutnick.

[Don Wilson]

It'll be on the podcast, I'm sure. I could 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 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 Eurex, was able to move the entire Bund futures complex onto the computer on a different exchange. Now, 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 the natural state of affairs.

[Tracy Alloway]

Network effect, I guess.

[Don Wilson]

Yeah.

[Tracy Alloway]

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 Kalshi 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.

[Jill Weisenthal]

Maybe for US workers.

[Don Wilson]

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 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.

[Jill Weisenthal]

It feels to me like culturally, because you're talking about why have prediction markets taken off when they've been around for over 20 years? I think I first heard about them in 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, et cetera, is it, do we want this world?

[Don Wilson]

So I don't think 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 guess is perfectly here benefits from his ability to list these contracts. 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 do you want to stay on stage?

[Jill Weisenthal]

Yeah, you can ask the question anyway.

[Don Wilson]

Or maybe they've decided that actually these are economically important transactions that are consistent with the cea. It's unclear to me.

[Jill Weisenthal]

Amazing.

[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.

[Don Wilson]

Thank you for having me.

[Tracy Alloway]

That was our conversation with DRW founder and CEO Don Wilson, recorded live on stage in Chicago. I'm Tracy Alloway. You can follow me at Tracy Tracy Alloway.

[Jill Weisenthal]

And I'm Jill Weisenthal. You can follow me at the Stalwart Follow our producers Carmen Rodriguez at Carmenarmondasho, Bennett at Dashbot and Kale Brooks at Kalebrooks. For more Odd Lots content, go to bloomberg.comoddlots where the Daily newsletter and all of our episodes. You can chat about all of these topics 24. 7 in our Discord, Discord, GG, Oddlauts.

[Tracy Alloway]

And if you enjoy Odd Lots, if you like it when we do these live shows, then please subscribe. 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.

[Jill Weisenthal]

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[Don Wilson]

It's football season and now you can.

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