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October 26, 2022

What Traders Need to Know About DEXs

with

Angie Malltezi, Chief of Staff at Shipyard Software.

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In this episode, we’re flipping the script–it’s Mark’s turn to share some insights! Shipyard’s Chief of Staff Angie Malltezi joins Mark to get his take on DEXs and how traders and liquidity providers (LPs) can get the most out of them. 

Why? Universal DEX volume is big–about $50B - $100B per month. That’s ~20% of the trading volume that occurs on centralized exchanges. What does this indicate? DEX trading is here to stay. But seeing through the vanity metrics to determine the best places to trade can be tough. In this conversation, Mark and Angie discuss DEX properties, different DEX models, and what to look for when choosing one. They cover everything from the inherent properties of DEXs and how the industry calculates yield to the most important factors for LPs when deciding where to allocate their capital. Mark also sheds light on why DEXs are so important for the DeFi ecosystem and where he believes DEX market structure is heading.

Angie is the Chief of Staff at Shipyard Software. Prior to Shipyard, Angie was a management consultant at Accenture Strategy, where she worked with C-suite executives of Fortune 500 companies to identify novel revenue streams, launch new products, and drive growth. Angie has served as a startup advisor to early-stage companies in the deep tech space and has a breadth of experience working with both public companies and early-stage startups. Angie holds a B.Sc in Neuroscience from the University of British Columbia.

Mark Lurie:

Welcome to WTF Crypto, where we peel back the layers of the onion of the crypto universe to understand what's really going on and how it affects you and your portfolio. I'm your host Mark Lurie, and as a caveat, nothing in this podcast is legal or investing advice. Today we're doing things a bit differently. Angie, Shipyard Software's Chief of Staff and I, will have a conversation about decentralized exchanges commonly referred to as DEXs for short. Together we're going to discuss DEX properties, features and what traders should care about. Most welcome, Angie. Thanks for joining us.

Angie:

So great to be here and test out this new style.

Mark Lurie:

So DEX volume is big. It's about 50 to 100 billion per month, even in this down market that's big, not just in absolute terms, but in relative terms, it's about 20% of trading volume that happens on centralized exchanges. So decentralized exchanges and trading in DeFi is here to stay and traders need to know about how to trade on DEXs because it's such a big part of where you get best execution and where trading flows are happening. But how do you know where to trade and how do you see through the vanity metrics to understand where is the best place for you to go? And so that's what we're going to talk about today. So I host this podcast, but I'm also the founder of, along with my partner Abe, of Shipyard Software. And we develop specialized decentralized exchanges. So we live and breathe decentralized exchanges every day.

And I think that alone makes us pretty good people to talk about this because you know what you do. I've also been in crypto for several years now, since 2017. This is my second crypto startup. And before that I spent a good amount of time in traditional finance, both in venture capital at Bessemer and I also spent a brief amount of time trading derivatives at a bank and also in research at Bridgewater, which is a large hedge fund. And so I kind of come at it from both a traditional finance and a technology and a builder perspective. And while that doesn't mean my opinions are necessarily right, I think it's a pretty good view on it and I'm excited to share those views today.

Angie:

I think it might be best to first discuss what is a DEX, what are the inherent properties of DEXs and why are they necessary in the ecosystem?

Mark Lurie:

So decentralized exchanges are structured very different from the way centralized markets are structured. And the reason this has come up is a few fold. So one, there's a really cool property of DEXs, which is that they are noncustodial. So when you use a decentralized exchange, you don't have to actually give your money to anyone until you're actually executing a trade. Whereas on a centralized exchange, you actually have to give your money to the exchange, they hold it in an account for you, and then they match it against other buyers and sellers. It's what we traditionally think of when we think of the New York Stock Exchange or another exchange, and that works mostly in the centralized markets because we have a lot of regulations around it. And if you want to access the New York Stock Exchange, you have to go through Schwab or some brokerage until it doesn't and there are issues in the market and it's tough to get your money or settlement becomes a problem, what have you.

And so it's actually a really nice property to be able to use an exchange where you don't have to give your money to the exchange, you just hold it yourself. And then when there's a trade that you want to make, you swap it for the other asset that you want. And that's just really cool. There's a second property of decentralized exchanges, which is that they are composable, because they run in the blockchain and because they don't run on one company's servers, you can use a decentralized exchange as a LEGO in another decentralized finance product. So you could create a structured instrument or you could have a game where in the game you swap one asset for another and that actually clears through the decentralized exchange underneath which anyone can access and is always on because it's on the blockchain, not on a private company's servers.

So that's an additional... Really it's called composability and it's a really interesting trait of decentralized exchanges. There's also one other aspect of being non-custodial, which is regulatory. So most of the regulations that have been written around centralized exchanges and finance assume that some financial intermediary has custody of user funds. And insofar is that's... The case, it prevents a lot of people from being able to access those exchanges, especially across different jurisdictions, the underbanked, et cetera. When you don't custody user funds, there's a lot less need for the kind of protections that regulations were created for in the first place. And that also means that it can serve people around the world in different jurisdictions and people who might even be underbanked because they don't need to be these kind of jurisdictional idiosyncrasies to make sure that the DEXs don't what run away with your money because they can't run away with user money. And so that means there's an access component and custody is really important. So those are a bunch of the reasons that decentralized exchanges exist and are actually better for a lot of people than centralized exchanges.

Angie:

So what might that mean for the user interacting or the liquidity provider? And how should we understand our mental model of the different types of DEX models out there?

Mark Lurie:

Typically when we think about an exchange, we think about a bunch of people putting orders into buy and a bunch of people putting orders into sell, and those being matched. That's the mental model for a centralized exchange. It's called an order book. That doesn't work on the blockchain. And the reason it doesn't work on the blockchain is a few full. One, the blockchain is kind of slow. It can take minutes to confirm a transaction. And it's also expensive. DEX can be dollars, tens of dollars or more for any given transaction. And submitting an order on the blockchain would then be slow and cost a lot of money. And so many orders are put in relative to the ones that clear that it's just impractical to have a centralized order book on the blockchain or to have an order book at all on the blockchain. Now, one way to solve this is to have the order book off chain and settlement on chain, but then that sacrifices composability, which we've discussed is a desirable trait.

So order books doesn't work. Now, one way that people solve this is faster blockchains, more scalable blockchains, layer twos. The issue is that centralized exchanges are some of the most high performance systems we have. I mean, there's high frequency traders, there are millions of orders put in for a second, taken out for a second. I mean, it's super high performance. There's no real way that a decentralized platform is going to be able to achieve that level of performance. And to the degree it tries to, the better it gets, the more trades will happen, which will congest the network and make it a victim of its own success. And so it's kind of inevitable that it's going to be really hard for a decentralized system, which is always going to be slower than centralized system because computations and storage has to be done redundantly across multiple computers instead of just one, is ever going to be able to achieve the level of performance that you really need for a good centralized order book.

And so the alternative is called an automated market maker. And that's what's emerged, that's a new paradigm. An automated market maker doesn't have an order book at all, instead it has a pool of liquidity. So smart contract, which is on the blockchain, it's like a safe that exists in code and into this, you can stick two assets or more, but let's just say two assets, Wrapped Bitcoin and Wrapped Ethereum. Now anyone can come to this pool and swap one of those assets for another. Of course there's a ratio and that's a price, and there's a math formula that defines that price based on the ratio of those assets. And that's basically the concept of an automated market maker. It doesn't require a lot of these orders flying back and forth and so it works in the blockchain. Now why do people put that money in that pool?

Well, every time someone makes a trade, they have to pay a fee, a trade fee, and that fee typically goes back to those providers of the capital of the pool, which are called liquidity providers. And so they put some capital in the pool and then they get trading fees every time there's a trade and that creates revenue for them, which is proportional to the amount of capital they put in. And so that's percentage yield and that's typically thought of as yield or APY, Annual Percentage Yield. And so that is how an automated market maker actually works. It's a different mental model and it's really cool. And that's where this kind of 20% of all volume is trading through.

Angie:

There's all these really interesting properties that you'd mention and I'd love to dissect them one by one. The first one that I feel like would be beneficial to talk about is prices. And I understand that there's different kinds of automated market makers, so perhaps we won't touch on that right now and maybe we'll come back to that towards the end of this. So let's talk about prices.

Mark Lurie:

So prices are surprisingly hard. Probably the first thing is what is a good price? Is it the lowest price or is it the closest to market? And if it's closest to market, who decides what the market price is? There's a lot of different exchanges. People are trading all over the place and there's some sort of average, I suppose, and that's the theoretical market price. But actually there's just the price at a bunch of different venues and we try to work backwards and okay, this is the fair price. And so that is a little bit hard because you want to trade at a place where it generally has the best prices, but at any one time it might not have the best prices. Perhaps there's an idiosyncrasy in one venue someplace where there's a price, but it's off market and it's fleeting. And so it's actually really tough to figure out where is the right place to trade usually because of this.

Angie:

What are some factors when it comes to pricing that determines price? We talk a lot about Oracles in this space, and then we also talk about... Within token assets that there are no existing Oracles. How does price gets established between two different assets that are brand new or two different tokens that are brand new?

Mark Lurie:

So price gets established in different ways in different types of decentralized exchanges. In a simple and first incarnation of automated market makers, it was called the CPMM, the Constant Product Market Maker. And this basically says if you have X of one asset and Y of another asset in the pool, you kind of have to multiply those units and they have to equal a constant. And that is a formula that you can use to determine the price. And in this one, there's like... Assuming every decentralized exchange in the world is this model, you can kind of proxy which is going to have the best price by, which has the most liquidity in it? Which DEX has the most TVL, Total Value Locked? If there's more, then probably prices are going to be better. But that is not always true for a couple reasons. One is price is both a function of the liquidity in the pool and also the fee that's charged.

And if you have more liquidity, then those liquidity providers have to earn enough money to make it worth their while. And so a larger fee might need to be charged and that might be more important than the amount of capital in the pool. And so that's one thing. The amount of capital pool affects price through this thing called slippage, which is like if you make a small trade, then you're going to have very little movement in the price. If you make a very large trade relative to the size of liquidity in the pool, then the price is going to move a lot and that's called slippage. And so depending on the trade you do, you're going to have more or less slippage based on how much capital is in this pool and you're going to have more or less fees, which is also based on how much capital is in the pool.

So people have looked to TVL to determine, okay, where am I going to get the best price? And the reality is that's not a great metric for small trades where slippage doesn't really matter, sometimes fees matter more. For large trades, that's a fine metric. But there are other models that have emerged for decentralized exchanges. One is the constant sum market maker where I won't get into the details of it, but it's like X plus Y equals K instead of X times Y equals K. The problem with that is that a liquidity pool can be fully drained of a certain asset, not a great property. But you can kind of meld these two functions and so you get what are called curves that are in the middle. And so you have things like the DEX Curve, which is better for stable coins, which don't move a lot relative to each other.

But there's also various other forms of DEXs. So one that incorporates off-chain Oracles instead of just relying on the ratio of assets in the pool. Another is RFQ, where a quote is generated by an off-chain server based on off-chain price fees and that enables you to trade with the pool. And that enables even faster updating of prices than through an Oracle. And as soon as you have different mental models for... Different models for how a decentralized change should work, the things that traders look at for what indicates where the best prices will be, starts breaking down. So it is not the case that more liquidity means better prices once you have these different decentralized exchange models. And so it becomes actually quite tough to figure out where you should trade. It's a hard problem.

Angie:

What I found really interesting within your explanation is that you articulated the different math behind each DEX model, which is really closely tied to the risk factors if you're a user who's contributing both liquidity and in terms of the prices that you're getting, it makes me think about the fluency of different traders and their ability to understand what they're actually getting into. And so for instance, it seems like there's this property of you have to dig in, look at the math and really understand this specific DEX is really good for stablecoin swaps, this one is really good for something else. What are other avenues for perhaps traders that aren't as fluent in doing kind of their own research? Would they perhaps use a DEX aggregator and rely on a DEX aggregator to make the decision of best prices for them?

Mark Lurie:

Yes, it's a good question because the reality is that individual traders and users should not be required to understand the nuances and idiosyncrasies and math behind every place they trade. That's just not a practical requirement. No one has time for that. And so it raises the question like, well, what do you do? And one way to solve that is to go to DEX aggregators. So these are places like 1Inch or Odos or 0x, and what these DEX aggregators do is, it's kind of like kayak.com, you put in the trade you want to make, and then they have an algorithm that goes out to all the different decentralized exchanges and tells you where you'd get the best price and then they kind of automatically route your trade for you. And sometimes a trade should be broken up into three or four trades that can be done at different venues, and that's how you get the best price.And so DEX aggregators will do that all for you, and that is actually a great place to... That is a great thing to do, especially if you're doing a larger trade, which should be broken up across multiple pools. The issue is that decentralized exchanges also don't always give you the best price. And the reason they don't give you the best price is because they have a pretty complex integration problem. It's hard to integrate all these different DEX models and when they're routing trades through various DEXs that often can incur costs. And by the way, Gas is not something that's really totally predictable up front. And so sometimes they're not including Gas in the right way.

So despite the promise of DEX aggregators, it's a good approach, but it's very hard to execute seamlessly in practice, there's a middle man. And that's okay, it's a useful middle man. But that middle man has to be paid and is never going to be perfect. So it's a good solution, but it's not a perfect solution. And the other problem with that is that it's a better solution the larger trade you make, but it kind of becomes a worse solution the smaller trades you make because you have less need to break this up over multiple pools. And so it's like, okay, well is it worth paying the extra gas and the extra prices for a DEX aggregator when you're really just doing one small trade? It's not always.

Angie:

Sounds like there's a lot to weigh in when you're a user and trying to make a trade. And so keeping up with that thread of understanding the trader's perspective, I'd love to talk more about yield and what does that mean for liquidity providers? You had mentioned the different types of DEX models and the math functions behind them. Could you please give an overview of what is yield? How does the industry calculate yield? Is that the right way of thinking about it? Are there alternative models? And really your perspective on how and the purpose of yield.

Mark Lurie:

Yield is an even tougher problem than trading. I feel like we're surfacing all these problems and few solutions here. So we'll-

Angie:

We'll get to the solutions, I think.

Mark Lurie:

Yeah. Well, hopefully we'll get to the solutions. Decentralized exchanges are a kind of a two-sided market, like all exchanges are, right? There's traders on one side and then there's the providers of liquidity on the other side, and those are the people who put capital in the pool. Okay, why do they do that? Well, they earn trading fees. And how do they decide where to put their capital? Well, where are they going to get yield for their capital? Where are they going to get the best returns? That's how people typically make capital allocation decisions. The problem here is that it's quite hard to measure and really know what yield you're getting and especially doing that in advance so you can make good capital allocation decisions. So let's talk about how the industry calculates yield today and then we can unpack some of the problems with that and then hopefully we can talk about the solutions which are actually relatively straightforward.

So one way to think about yield is, okay, let's just add up all the trading fees and that's the yield that we get. And that's quite easy. And in fact, that is what people do today. They have APY and APY is typically just the aggregate trading fees generated divided by the amount of capital in the pool. This creates the Field Fallacy and the Field Fallacy is that you can assess your returns based on the revenue without considering the costs. And that is just very obviously a bad idea. Trading pools have losses, they don't just have revenue. And so if you're just looking at revenue, then you're ignoring the fact that you could be losing a lot of your money.

Angie:

Can you speak a little bit more about the costs, so that we have a better understanding of where this revenue comes from and then what are the actual costs that are factors?

Mark Lurie:

You can think of an automated market maker as making... It makes a lot of trades and those trades are good or bad. They're good insofar as they get a little fee on each one, that helps every trade be good. But an automated market maker could make a really bad trade. It could sell for way above or below market and if it makes a lot of those trades, it's going to lose money over time. And so typically this manifests itself in something called impermanent loss. You could understand it in a bunch of ways, but one way you could understand it is like the loss you would get versus just holding the assets you put in initially. If you end up with less of each asset than you put in, then you kind of lost money. And there's this feature of the initial DEX designs, the Constant Product Market Maker, the CPMM, where the amount of money you lose is kind of based on how far prices have moved from when you deposited the money in the pool.

Now in theory, if the market comes back, if prices come back to where they were when you put money in the pool, you didn't lose anything. But if they departed all in either direction, you've lost money. And this is called impermanent loss. This is also a weird fallacy, the impermanent loss fallacy, because, A, it's not impermanent. Once markets move, they've moved. People mark things to market. It's like when I invest in the stock market and I choose stocks and I'm bad at picking stocks and they lose money, I don't say, "Oh, I didn't really lose that money because the stock could come back." I lost that money because the market is where the market is, it could go down further too. So that's one fallacy.

The other is that it's the only type of loss. There are other DEX designs, RFQs and Oracles where you have losses and it's actually a different type of loss than impermanent loss. But people only kind of think about the idea of impermanent loss and the kind of extra strange thing about impermanent loss is it's a little hard to track because it depends when you put your money in. And so it's different for each individual. And so conveniently, a lot of DEXs don't report impermanent loss perhaps because they don't want to... Why would you report your losses? You just really want to report your gains.

Angie:

You brought up a really interesting point that I want to dig into a bit further, which is the loss comparison and what has this been benchmark to. I know internally at Shipyard we discuss a lot if you weigh something against a crypto basis or a US dollar basis. And so if you're a DEX and you're looking at your yield from the perspective of just cryptocurrency that is very volatile, could you perhaps articulate the implications based off of how different people measure yield on what asset they're really looking at and what they're comparing to? So I really appreciated that you had mentioned all the different cost factors that people do not show in why the yield is down. And then there's also this idea of, Oh, in a year from now, this asset could be something like this, which is just a projection from one instant moment in time. So I'd love for you to dig in there around the different currencies that people use to measure yield and even impermanent loss.

Mark Lurie:

It is a really tough thing to measure. The problem with just looking at fee yield is that you're only looking at revenue, not losses, so you're going to make poor capital allocation decisions. The problem with only looking at impermanent loss is that you're kind of ignoring the data because it's hard to measure and you're ignoring other types of loss. So how do you solve this problem? And this isn't actually unique to DeFi. Measuring gains and losses is a problem that traditional finance has grappled with for many, many years. And there's actually a way to do it, which is called benchmarking, where you realize that every... All gains are relative to something else. And so the trick is choosing your benchmark. So for a lot of mutual fund managers, they're benchmarked to the S&P500, let's say, right? Or some other index of the market and they exceed that benchmark or they fall below that benchmark and that's how they're judged.

Now, why do they choose that benchmark? Well, in traditional finance we have this concept of alpha and beta where beta is just like your correlation in the market. If you are a fund manager and you buy a bunch of just S&P500 stocks and then you just sit there and do nothing, right? You're just going to have a hundred percent beta, you're just going to track the S&P500. Whereas if you have alpha, that's like the insight and skill and judgment you're putting in this better than market. And so there's this idea of alpha and beta and alpha can also be negative. You can have really bad judgment and do really bad work and then you do worse than market. Sometimes it's luck, but still it's negative alpha. Okay. So in crypto we need to think about what's the right benchmark? What are we judging returns against?

And we don't do a very good job of it. Probably the most common way to judge a benchmark is HODLing, which is just like if I held the assets myself and I never put them in the DEX, what would I... Do I have more or less than that? And that's not a great way to do it because you're mixing up alpha and beta, every DEX is going to lose some money and gain some money. And some of that's from markets and some of that's from the kind of alpha from that individual DEX and to kind of just like at HODLing in a different market conditions going forward, the DEXs might perform differently for liquidity providers, it might have a difference yield results. And so if you just look at verse HODLing, you'll make bad capital allocation decisions, respect to the future. And so the question is like, well, what do you benchmark against?

One way is, okay, benchmark it against just BTC, but if you're in a DEX, you have two assets and so it's kind of a pool. Probably the best way to do it is a hypothetical rebalancing portfolio, like a perfectly rebalancing portfolio, which is called the zero cost rebalancing portfolio, let's call it daily. And then you kind of benchmark returns against that and then you ignore this idea of impermanent loss, which just doesn't really make sense. And you ignore this idea of field API, doesn't really make sense. And then you're kind of like... You're able to separate alpha and beta and you're able to make better investment decisions. And every DEX could be tracked against that portfolio. But also the reality is that each investor or each, I don't want to say investor, but each liquidity provider is going to have their own benchmark because your benchmark is based on who's giving you capital. It's based on your alternatives and what they want.

If you're raising money from a pension fund, they might just tell you like, "Hey, I'm tracking you against Bitcoin," and then your benchmark's Bitcoin. And so you really have to know who you are and what benchmark you're measured against and measuring yourself against in order to make good asset allocation decisions. But if I were to choose one for the industry, it would probably be the hypothetical zero cost daily rebalancing portfolio for any given pool.

Angie:

I do have one question later on where we're going to discuss around where you feel like the market structure around DEXs will be going. But before we dig into that, I'd love it if you could summarize from an LPs perspective, what are some of the factors that they should consider for where they allocate their capital or even using DEXs?

Mark Lurie:

The factors they should consider, I think there's two types. There's ones who are, let's say professional and they can really do all this math and understand their benchmark and measure things themselves. And the other are people who have to take the metrics and reporting that are provided by various sites and third party services and make their decisions as best they can based on that. And that's a tough one because currently most of these sites suffer from the Field Fallacy and the Impermanent Loss Fallacy and so they actually don't report numbers in a way that's really ideal for asset allocation decisions. So then it's like, okay, if you're an everyday trader, how do you actually make the decision? It's a tough one. And I think the answer is to not overthink it too much. Well, the answer is probably twofold. One is think about what the DEX is saying their purpose is, because if you can't really measure that well then you should believe what DEXs say.And if DEXs say, "We're just trying to maximize TVL," then they're probably not going to end up with great results for you because that's not what you want. If a DEX says, "We're giving the best prices for retail traders, that's what we do," then they're probably going to, in the future, be better at giving those prices. And you should probably go there. If another DEX is saying, "We're trying to give you good yields but not crazy Ponzi yields," then you should probably believe them and you should put your capital there. And this isn't, you know, I'm saying you, but really it's like the purpose of the DEX because this is open source software, the purpose for which it was designed. So I think that's number one. And then the second thing is you can look at the actual kind of profits that a DEX is able to extract, the kind of excess yields.

The more that is, and the more they can actually do... That DEXs can do that, the more they're probably actually generating really good returns at the end of the day. And again, I'm using the royal they to refer to code. The last thing is like common sense. It's like if you're getting some sort of really high hundred percent yields, there's a reason, and if you know that reason, great. If you don't know that reason or that reason don't make sense to you, then it's made up and you should ignore it. And the final thing is like, look at the assets in the pool. If it's a decent APY, look at the assets in the pool. If they're weird volatile assets, then you know you're probably going to lose an especially big amount. If they're pretty good assets, BTC, ETH, et cetera, then you know you might not lose a crazy amount.

And finally, don't put money in pools that are the CPMM. The CPMM arguably does not ever make money, impermanent loss which suffer from is always negative. It's very, very rare for that to actually create positive yield at the end of the day. So any DEX that's like a Uniswap fork, a Uniswap V2 fork, you probably just should not be allocating liquidity to, you are probably losing more from impermanent loss than you are from yield. And so that cuts out a huge amount of the industry and I would think people should just stay away from that.

Angie:

Previously you and I have discussed how those incentive models impact yield. And so you brought up this point around if the yield quoted is really high APY, you should be distrustful. And I'd love to understand from your perspective that you run a company that builds custom DEXs, what are some incentive models that you've seen other companies use to attract money in the pool?

Mark Lurie:

The most common one is by giving away their native token. And now that we're in crypto winter, people often refer to this as Ponzi yields, but that's not necessarily the case. So to unpack that the one way, if you have a bunch of people providing liquidity and yields are not organically good for them, how can one solve that? Well, you just got to give them free money so they have higher yields and then they'll keep doing it. And how do you get free money? Well, you could raise a bunch of money like venture capital money and just give away US dollar Bitcoin, but that's pretty hard to do. That's what Uber did to get a bunch of people to drive for it or ride on it.

Another way you could do is issue your own token and all of a sudden this has a bunch of value because markets are what markets are and some people think perhaps that has future value and perhaps you have a lot of users or people who want to govern your platform and then you just give away some of that money to liquidity providers so they have higher yields. The problem is that there's a finite number of tokens and so you can't do that forever. And so it's like a shot of sugar, but it doesn't last forever. And if you are providing liquidity, you should be really concerned because you're being given a hot potato and it could kind of crash at any time and you're involved in something that's inherently unsustainable.

People talk about that being like, "Oh, it's a way to bootstrap liquidity, it's a short term thing, but like it generates market effects and then that's permanent." I'm would be really suspicious of that. That's a very convenient narrative to create a lot of growth, which is unsustainable and a lot of growth in an inherently unprofitable model. If you have an inherently unprofitable model and you create a ton of growth, it's very hard to turn profitable because it would mean losing a lot of those users or revenue. A lot of the people who came for one reason, would go away if you take away that unsustainable program. And so it creates this dilemma, which is how do you become profitable once you've created this growth engine that everyone's expecting and this thing that everyone's kind of wanting from you. So it's important to grow sustainably instead of grow unsustainably.

Angie:

You bring me to a question I love thinking about and so does a DEX company make money? If so, how?

Mark Lurie:

Well DEXs make money or in theory they make money. If a DEX is generating good returns for liquidity providers, then it should be able to capture some of those fees. Now there's some market cost of capital. Liquidity providers have a bunch of options where to put their money, they're going to put it where they're getting the best yields. And let's say the market cost of capital is 30%, right? In theory, if a DEX is generating more than 30%, well, it can take that premium for itself. Now sometimes that's in the form of a fee. Sometimes it's just fee share. There's a bunch of different ways to do it, but there's value there that can be captured by the DEX. Now it's up to every DEX, what to do with those funds.

Sometimes it's programmed in that it just keeps going to liquidity providers, sometimes it goes to a Dow and then that Dow decides where that money goes. Maybe it just sits there forever. Maybe it's used to build more open source software, maybe it's distributed to token holders. There's regulatory problems with that, right? That's not always okay. And so the Dow behind a DEX can certainly make money, and that's from generating excess yields at the end of the day, having a fundamentally sustainable model. And that is possible, but it's pretty rare. And I think if you see that, then you know that the model's probably actually making money for the people, everyone involved.

Angie:

Where do you see the market structure go around DEXs? Given how many companies have popped up in the last year and a half, how are you thinking about market competition or even the saturation point?

Mark Lurie:

I think it very much depends on crypto markets broadly. The more value is given to these long tail tokens, the longer unsustainable DEXs can artificially juice usage. At some point the kind of narratives wake up to that being a problem and they're starting to, narratives are starting to catch up. There's the idea of real yield. There's an increasing number of companies that are reporting metrics that are fundamentally better. Token terminal is one, but there's others that are grappling with these problems around, how do you measure returns? As that gets better, I think a lot of unsustainable DEXs, in particular like CPMM forks, will just fade away into oblivion. People will take their funds out, as they do that, prices will get worse, traders will use them even worse, it'll create this negative cycle and eventually market failure. And that can happen pretty fast.

Over time, I think DEX aggregators are always going to be a really important part of this ecosystem because it's always going to be hard for a user to know where the best place to trade is. But I also think that there's infinite number of decentralized exchange designs. And today they tend to be not very thoughtful or they're one size fits all, like Swap B3 or they're targeted specific types of traits. And over time I think you'll have DEXs which are really targeted at specific types of users and they tell that user, "Hey, we understand who you are, what you want, we're the place you should go to do your business." And users will become loyal to the DEX designs that do that for them, that are built for them.

And so I think there will be a lot of brands essentially, just like you have when people buy food or buy clothing, you go and buy because that brand, you identify with it and you know that brand has you in mind. And I think that's how traders should make their decisions on where to go, right? Because the truth is all this math and these DEX aggregators and everything, it doesn't always result in best execution. What really is going to, over in general result in best execution for a given user, is going to a place that's built for them and having faith. And that's actually a pretty good heuristic. So I think there'll be as many DEXs as there are users.

Angie:

So you brought up this ecosystem that different kind of companies will play, so we have DEXs aggregators, we have the companies that build the DEXs, we have DEXs themselves depending on how they're structured. Do you feel that regulation will ever come into the space or is there even a role for regulation to play here?

Mark Lurie:

Absolutely. The first thing is that regulation already applies, and there's a lot of people in crypto who think there's no regulation around this and that's just not true or that the regulation's unclear. There are parts of regulation that are unclear, but actually a lot of times there's very clear regulation and people just don't like it. So there is plenty of regulation that applies. The issue is that the regulation was designed for a different era and it doesn't always make sense. So first of all, is there a place for regulation? I think the answer is yes, in almost any aspect of human society, there's outcomes that we as a society think are good and think are bad. So an outcome we think is good is growth. An outcome we think is bad is uninformed investors losing their life savings. I think we can all agree that's a bad thing.

Also, child trafficking, money laundering, drug cartels, terrorist financing. I hope we can all agree those things are bad. And so regulation serves to mitigate and prevent those things that are bad. And so just any part of human society, crypto has those elements. And so regulation is good insofar as it's effective at preventing those things. Absolutely. The thing is it has to be smart about it and it has to balance growth and prevention. The issue with regulation in general is that it was all written that... Regulation is defined by regulators who have a mission and who are empowered based on legislation laws that are written. The laws and the missions of regulators are pretty good, like the SCC is to protect... It's something around protecting small investors or protecting investors in general. That seems like a good thing. The CFTC is around like, I think market stability, that seems like a good thing.

But the laws were all written assuming that there's always a financial intermediary that cust these funds, and that's just not the case here. And so a lot of the regulations just don't really make sense and are even less effective than other ways. For example, a lot of regulation is built around the idea that if someone has custody... If there's some financial intermediary that has to have custody of funds, then they should do KYC, know your customer and users, and then they should monitor suspicious transactions and report those to the government. Well, that works when financial intermediaries are custodying funds, but that doesn't really make sense if they're not. And it doesn't really make sense that transactions can just happen anonymously in code, right? But there's other ways to achieve the same mission, like know your transactions, you can just trace the actual money flow instead of the user and see where that money went and that's a great way to prevent that activity.

But the legislation hasn't really... Needs to be rewritten with that capability in mind. And so I think there's definitely a place for regulation and it just has to be... Has to catch up to the times. At the same time, there's stuff that's just obviously not bad and is already regulated. You cannot defraud people. You can't lie. There's no gray area around that. I think this is a really interesting space. I mean crypto and DeFi in general is super dynamic. I think people should get involved, try things, have faith that it'll work out well for them. Virtually anyone who is involved in Bitcoin in 2012 has done very well. And I think the same is true now. And the best advice is use common sense. And yes, do your own research, but also trust your intuition, going places where things make sense to you and not playing around in sandboxes that don't make sense to you because if they don't make sense to you, it's probably going to end poorly.

Angie:

There is one last thing that I'd like to do since I feel like I've been given the position of power to ask the questions. I would like to do a rapid fire exercise where I ask you three questions and to hear kind of what comes up in your mind. Is this something that you are interested in doing?

Mark Lurie:

Sure.

Angie:

Okay. We'll test it out. Okay. First question, what is the most impactful book or article that you've read to help shape your mental models as a serial entrepreneur?

Mark Lurie:

Probably The Hero with a Thousand Faces by Joseph Campbell. It's a little bit dense, but it talks about what a story is, why we think in stories and what the structure of those stories are. And we each individually think in stories and we communicate in stories and we receive information in stories. And that's almost every interaction. And to really understand what a story is, I think you have to read the book, Hero with a Thousand Faces, which looks at, what's the common structure in all stories and myths and religions over time? It's a really, really interesting book. And that story model has informed a lot of my mental models around where to take company, how to sell, how people are motivated, you name it. The other thing I'd recommend is The Struggle, it's a blog post by Ben Horowitz of Andreesen Horowitz, and it really encapsulates the emotional difficulty in building new things. And I think it's important to read because one very important mental model is that it's tough and it's tough for everyone. And it's good to know that it's not just tough for you.

Angie:

All right, thank you. So question number two, what is one piece of advice you can give entrepreneurs to cope in this market?

Mark Lurie:

Have faith in what you think makes sense to build. And I think you have to both ignore your own self-doubt and the narratives of the market and investors in particular along the way because those narratives come and go, they're just stories and they change every six months. And so you really have to have faith in your own conviction because every other thing to have faith in will steer you wrong.

Angie:

For the last question is, what is one type of technology or subject in this space that's really caught your attention lately that you're quite curious to learn more about?

Mark Lurie:

Access control and kind of account models in crypto. We did a podcast recently about access control and a lot of the usability issues in crypto come down to the idea that self custody requires holding this random thread of words and how impractical that is, for most people. And that the solution of that is around access control and account management. And that's something that's increasingly becoming a topic of conversation in where Ethereum goes and also in custody. And that to me is the number one thing that's going to help crypto reach the masses. And so I think that's something that I'm very interested in and need and want to learn more about.

Angie:

All right. Thank you. You've answered my rapid fire three question approach for this podcast. This has been really fun. Thanks again, Mark, for having me on here to be able to interview you about this topic.

Mark Lurie:

Thank you, Angie, for coming on and allowing me to opine and ramble. I really appreciate it. And as always, I encourage people to follow Shipyard Software, use Clipper and subscribe to the podcast and leave a review so that we know if you like what we're doing or not, because we can only get better if you tell us what you need.

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