Governance and Risk Meeting: Ep. 40 (June 20 - 2019)¶
Video | Audio | Discussion
| References | Person | Text |
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| # / 00:00:00 | Richard Brown | Hello everyone. Welcome to the June 20th edition of the Scientific Governance and Risk Meeting with MakerDAO. My name is Richard Brown. I'm the head of the community development. I keep on forgetting that. I believe that's accurate. |
| # / 00:00:17 | Richard Brown | We're going to be tightening up the agenda slightly because we have a significant amount of science to crank through. Cyrus Younessi is going to introduce us to the wonderful world of collateral risk and everything that entails. I'm not going to describe any more than that because I'll probably use the wrong terminology, so I'll allow him to keep us informed. We'll hear from Vishesh about the state of the peg briefly for about 10 minutes. Cyrus, we're going to dig into his slideshow for the bulk of the call. |
| # / 00:00:50 | Richard Brown | I am going to restrict myself to five minutes of preamble today, so I'm going to talk real fast. If you have questions, comments, please do not feel shy. Jump right in. We have a chat. Type your questions in the chat if you don't have access to a microphone. If you do have access to a microphone, interrupt us whenever you need to and we can have the discussions as they arise. I think that's probably it for the boiler plates. I want to talk briefly about governance issues because we're seeing some interesting things happening again. |
| # / 00:01:26 | Richard Brown | Our polls this week up until the 11th hour was weighted towards a 15.5% stability fee, so the community has signaled for lowering it by 1%, and we might have seen the first example of an emergent behavior, which I'm happy about. We might've seen campaigning for the first time, which is great because this is something that we need to encourage as group and support whenever possible. |
| # / 00:01:55 | Richard Brown | People need to be involved with the system. They need to know that their involvement can affect people's opinions. It can affect the way that the system works. We had some people pop up in the chat yesterday saying, "OMG, why are people advocating for a lower stability fee?" There was a conversation there. People dug into the graphs and then somebody posted a thread in r/mkrgov saying essentially the same thing. Why are you all advocating for lowering the fee when it should be raised? |
| # / 00:02:31 | Richard Brown | People, there was a comment or two, but I don't know if this is coincidental or not, but the weight staked in that poll had moved since that post went up, and now it's advocating for a 1% increase. We'll leave it to Vishesh to present data about whether that seems to be the most logical option. |
| # / 00:02:54 | Richard Brown | What I'm far more interested in, though, is the fact that people determined that the system was moving in a way that they didn't like. They piped up. They had some chats, they made some posts, and then the system changed, and that's very encouraging to me. That's the sunshine aspect. Here's the contrarian view here. We're still in a situation where we're running into voter apathy, and this isn't a surprise. It's not something we weren't prepared for. This is the nature of the game, and we have some questions I think that we need to ask ourselves specifically related to the cadence of voting, the friction associated with voting, our expectation or requirements that the community needs to be engaged on a weekly basis, and they need to education themselves, stay up to date, and then move their keys and/or find their keys and then move their Maker every Friday. |
| # / 00:03:57 | Richard Brown | There's seems to be a different sentiment in the community about that's just the nature of the beast and that's what people need to do. I'm not sure that I'm convinced to do that, and one of the thought experiments that I do, and this is not a complicated one, I ask myself, "Rich, name five projects in the space that you'd be willing to do the same thing for," and the answer is none. I would not do that for any project in this space, so we need to determine whether that's a realistic expectation for asking people to interact with our system. |
| # / 00:04:28 | Richard Brown | I don't want to sound too prejudicial. I think that there's middle ground. There's other options that we can explore, and one of those things that I would like to refer everybody's attention to is a recap of these thoughts that I've posted in the r/mkrgov subreddit. Is somebody talking about Rich without a hat? Yeah, today is my baldy reminder day just so it's not a big surprise if I take my hat off six months from now. |
| # / 00:04:56 | Richard Brown | All right, so I'm posting a link in the chat. This recapped some of the questions that we'd asked previously, so they come from the community, come from me, come from these discussions. Are we seeing engagement fatigue? Is 1% increments too fine-grained? Are 10 plus polling options too confusing? Are people tempted to fiddle with the rate if we're moving things up and down by 1%? Are we asking people to vote on weekends? Well, we are. Is that a bad idea or does that not matter? The list of questions go on and on and on. I'm not going to read them all out because I promised I would only talk for five minutes and I've already broken that promise. |
| # / 00:05:36 | Richard Brown | The interesting thing about this is that it puts us into a situation where we have one signaling method available to us and that's the poll in voting portal. That poll is used every week to talk about the stability fees, so in order to change the cadence of the system, we need to figure out a signaling system that's outside of the system that we can use. |
| # / 00:06:01 | Richard Brown | My quick and dirty solution to that problem is a Reddit thread with contest mode turned on to comments. One is a risk parameter should be two weeks. One is a risk parameter should be one week. |
| # / 00:06:18 | Cyrus Younessi | What is contest mode? |
| # / 00:06:20 | Richard Brown | It's when it randomizes the order of the comments and it hides the replies under the assumption that people have a tendency to vote for whatever the first one or two things they read are. This is not scientific governance at all, but it is a signaling method that we can use to figure out whether there's enough interest to keep on pursuing this thing. |
| # / 00:06:44 | Richard Brown | I think the diminishing Venn diagram problem is happening here where we have serious people that are engaged in the system, people that are willing to hold an opinion about the system, people willing to do something about the system, and then that Venn diagram gets smaller and smaller when you get into people that are actually refreshing r/mkrgov on a daily basis around the weekends to figure out whether there's a contest mode thread, so that leads us to a situation where the comment for every week two weeks for a voting cadence has seven votes, and the comment for the voting cycle should remain at one week has five votes, so this is not an enormous turnout. |
| # / 00:07:26 | Richard Brown | I've decided to leave that thread up again and for the course of this week, and up until the next poll, I'm going to keep on collecting some signals, so if you have an opinion, please click on that link that posted on the side in the chat. Pick one of those options or add a comment. Yeah, I'll cut myself off here. |
| # / 00:07:46 | Richard Brown | One of the things I do want to add, though, is that there's an interesting suggestion in that thread, as well, from Long for Wisdom, who's become an increasingly engaged stakeholder of some cool ideas. He points out one of those things that every once in a while in retrospect seems obvious. Why didn't we do this from the very beginning? He points out that it might be smart to do rate stepping for the stability fees in exponential increases, so instead of 1, 2, 3, 4% plus or minus, we should perhaps consider steps of 0.5, 1, 2, 4, and 8, which allows us to do some fine-grained adjustments to the polls when required, but it also opens the door for us to do drastic changes to the stability and the poll, as well, which might be interesting if we see some dangerous market activity. |
| # / 00:08:48 | Richard Brown | I believe that is it for me. I think I've mostly cranked through the things that I wanted to talk about in my allotted time. I did. I just checked my notes, so Cyrus, I'm going to hand this off to you to pick if you want to start telling us about risk. |
| # / 00:09:04 | Cyrus Younessi | Sure. Well, I guess we'll start with monetary policy, right? [crosstalk 00:09:10] Vishesh. |
| # / 00:09:14 | Cyrus Younessi | I don't have the agenda in front of me. That's next, right? |
| # / 00:09:18 | Richard Brown | Yes. 10 minutes for Vishesh. Clock has started. |
| # / 00:09:23 | Vishesh Choudhry | Okay. All right, so if you can see my screen properly, I think the simple answer is things have by and large been going well. For DAI, the price has been broadly stable. There's been a little bit of drift down very slight. So hard to say whether it's a legitimate problem or not, and then we'll talk about supply a little bit. The price as we've seen over the past month, a lot of the past volatility has come down quite a bit, so that's good. |
| # / 00:10:02 | Vishesh Choudhry | Since the 16.5% stability fee, the price has drifted down a little bit. There was this June 15th spike, which I think is a bit of an outlier, something to exclude, and we can go into why, but if you take that data point, it has broadly drifted down a little, but again, very slight. |
| # / 00:10:27 | Vishesh Choudhry | What's interesting is the ETH price, although it has been fairly strong over the past month, has actually not changed significantly in magnitude, only from the 250 range to 268 more recently. The DAI price has held steady, as well. We haven't seen a strong drift in either direction, but we have seen more of this kind of positive correlation emerge at these higher ETH price levels, which as we've beat to death at this point, was a bit of a reversal from how things had worked in the past. |
| # / 00:11:11 | Vishesh Choudhry | That may start to resume again soon, which is something that I think will be interesting to dive into is under what conditions does DAI do well when ETH does well versus do poorly when ETH does well? The supply actually, and this was the blip that I was talking about, has ticked up quite a bit in the past week, or two weeks, I suppose. We've gone up from about 80 million to 85, which is not insignificant, and that coincided very well with the 17.5% decrease and then again to 16.5%. |
| # / 00:11:58 | Vishesh Choudhry | What's interesting is there is a large about of DAI minted on June 15th through, I think, it was two large draws, then again more DAI minted again on the 16th, but also a fair amount burned on that day, so those evened out a bit. |
| # / 00:12:18 | Vishesh Choudhry | The supply has ticked up. What I think there were were a few large positions that had come back to Maker from some of the secondary lending platforms, and that seemed to pretty clearly be a delayed effect from the 16.5% decrease. I don't know if people were maybe waiting to see if that fee would get increased back again or further decreased before they made their decision, but there was definitely some sort of reverse refinancing back to Maker. |
| # / 00:12:51 | Vishesh Choudhry | As far as the circulation of that, I think we saw pretty clearly that the moment the stability fee hit that 19.5% level, there was this precipitous drop in the average age of debt. That had really halted around the 16.5% decrease and has broadly sat at a flat level since then, so I think fewer people ... The rate of the amount of loans that are getting paid back has really stopped changing, so it's a bit of a steady state right now. |
| # / 00:13:30 | Vishesh Choudhry | As far as the new versus old CDPs, what we've seen is just a consistent decrease in the amount of debt that's being drawn out of new CDPs versus preexisting ones, and that's really been exaggerated since the 17.5 and 16.5% stability fee decreases. Now, that reason I harp on those is you could argue that it was some fundamental change at ETH price, but as we've seen, ETH price did not significantly change in that overall three- to four-week time span. |
| # / 00:14:10 | Vishesh Choudhry | There were some small movements in a two- to three-day time period, but overall, it was not a huge magnitude change, so they wouldn't really explain some of the month-long trends. |
| # / 00:14:24 | Vishesh Choudhry | The collateralization ratio, again, with that same June 15th-ish timeline had started to rise up a bit more, so as the stability fee was decreased to 17.5% and then again to 16.5%, we saw that collateralization ratio coming down and we saw ... I think that was a little bit of a delayed effect again from some of the de-leveraging behavior and moving debt onto other platforms. People commensurately reduced the amount of collateral. |
| # / 00:15:08 | Vishesh Choudhry | [inaudible 00:15:08] it also contributes, but what's interesting is as the rates became a little bit more attractive again, people refinanced back to Maker a little bit, the supply increased a bit, and the collateralization ratio started to come up again. Those are balancing effects. What's interesting is in the past, we've might've seen that happen and then we would see the collaterization ratio drop as well because were people were getting aggressive and they were really hyper-leveraging on ETH, so even though they may be moving their loans back to Maker, there doesn't seem to be as much of that risk-seeking behavior, so the collateralization ratio has maintained this elevated level. |
| # / 00:15:51 | Vishesh Choudhry | Unfortunately, Coinbase Pro decided to do a 45-minute maintenance update exactly during this call, so I have a screen grab of the DAI price breakdown here, and by the end of the call, it should be back up. What we'd seen was more in the past two weeks of this kind of spread where there's a significant amount of DAI trading below a dollar, but overall, the price had stayed fairly steady. |
| # / 00:16:21 | Vishesh Choudhry | Honestly, this looks like a fairly wide spread, but if you think about the magnitude of those values, between 0.98 and 1.02 is not a huge spread, and this is honestly ... DAI's in a much better shape than it was two to three months ago. It's just maybe a very slight drift down since the 16.5% decrease. I think that's something you can see in the stablecoin charts, as well. |
| # / 00:16:55 | Vishesh Choudhry | To just touch on the secondary lending in my last two minutes here, so what's interesting is the overall outstanding borrow and supply volumes on the secondary lending platform, in the longer time scale as we had talked about, exploded, but since then has actually held fairly steady, so even the supply overall has increased somewhat significantly, the amount of DAI that is being borrowed and supplied on these secondary lending platforms has been fairly steady, so that increase in supply is primarily attributed to Maker, which is interesting because I think what we'd seen in the past at the 19.5% level was a strong preference for going towards some of those secondary lending platforms which has been discussed about the relationship of secondary lending rates to the stability fee and the fact that that serves a similar function to what the DSR should eventually, suggest that perhaps 19.5% was a bit of an overshoot, but that somewhere in that 16.5, maybe 17% range, is somewhat of a steady state at least for the current conditions. |
| # / 00:18:16 | Vishesh Choudhry | That is about nine minutes, Rich. |
| # / 00:18:22 | Richard Brown | All right, I appreciate your attendance to the clock. Well, actually, I'm going to break the rules. I have a question. We generally look at secondary lending platforms as being actually led or potentially driving with the stability fee, equilibrium at MakerDAO. I'm curious, though, whether you think that the debt ceiling might have an impact on this function, as well, just one or two steps down the road. |
| # / 00:18:51 | Richard Brown | Obviously, there's only 100 million that's going to come out of the system. There is inventory levels that increase and decrease, and then that impacts the deviation from the peg, but is ultimately ... Yeah, maybe I'm wandering around a bit too much, but do you think that debt ceiling can have an impact on the usage on these secondary lending platforms and whether it's a completely separate metric altogether? |
| # / 00:19:20 | Vishesh Choudhry | I think the debt ceiling really comes into play as you start to get closer to it. There's still a bit of a buffer to that range, but I think the question of how should we think about these secondary lending platforms, what can we learn from that, and to what extent should we let it drive our decisions, ultimately I think the secondary lending platforms are serving this function of eating up inefficiency, so to the extent that the DAI supply significantly outpaces the demand for DAI, secondary lending platforms come in and ease that pain. |
| # / 00:19:55 | Vishesh Choudhry | That's effectively a similar function to what the DSR should be doing. You might see a significant portion of volume, if everything is properly calibrated, move to the DSR versus secondary lending platforms in the future because, again, it's ultimately economically the same effect. |
| # / 00:20:15 | Vishesh Choudhry | Now what that means is currently if we see not a lot of movement on secondary lending platforms, but we do see an increase in supply and a depression in the DAI price, then we may have undershot the stability fee and it's cheaper to draw DAI out of Maker, but given the collateral parameters and given the potential yields you can get on those secondary lending platforms, unfortunately rates are not perfectly transferrable across platforms. |
| # / 00:20:44 | Vishesh Choudhry | It may still mean that people would prefer to go to Maker and would prefer to draw DAI out of Maker, and those secondary lending rates may not necessarily move commensurately because they may be at somewhat of a steady state for those particular collateral parameters on those other platforms, because there's a lot of other interplaying factors that come into play in reality, so ultimately DSR is not going to kill the secondary lending platforms because there are a lot of factors in play in terms of I can use DAI as collateral to go short on some other asset on dYdX while at the same time getting a lending yield out of that DAI. |
| # / 00:21:24 | Vishesh Choudhry | It's a little bit more complex than that kind of simple relationship, so I think for a lot of reasons, we don't necessarily want to let the information about what's going on those secondary platforms drive what's going on in Maker, but at the same time, it is a useful data point for understanding to what extent oversupply exists. |
| # / 00:21:55 | David Utrobin | Rich, you're muted. |
| # / 00:21:56 | Vishesh Choudhry | Rich, you're on mute. |
| # / 00:21:58 | Richard Brown | All right. There's a question in the side chat from Patrick [O'Dee 00:22:02]. Do you have access to a mic, Patrick, or do you want us to read this out for you or have Vishesh read it? No mic, so Vishesh, can you see that or do you want me to read that to you? |
| # / 00:22:14 | Vishesh Choudhry | I can see it. It seems like I've moved from looking at price in terms of current price versus moving average versus outright price. I'm not sure if I got the difference between current versus outright price, but yeah. I can explain what I think the relative usefulness is in the moving average versus the current price. |
| # / 00:22:38 | Vishesh Choudhry | The current price, and again, I'm assuming you're referring to the spread and the bar chart, that's helpful for me at least to understand looking at not just what's the volume-weighted average price over time, but within that like the microstructures of what kinds of spreads are we seeing on different platforms, where does ETH to DAI tend to trade? Okay, well, it tends to be closer to a dollar, and then Uniswap has this wider spread. |
| # / 00:23:11 | Vishesh Choudhry | Understanding a little bit of the dynamics of where DAI is trading and what are some of the patterns of how it trades on those different platforms at least for me helps me understand as a dynamic function what DAI looks like. Okay, ETH price. Okay, so that's for DAI, and for ETH price, what I was looking at for the longer-running average before was these broader trends and the relationship between ETH in the long-term versus ETH in the short-term and how that impacts DAI, because in the past, we were just coming up to speed on this idea that the ETH price relative to the long-term price changes how attractive it is and how much people want to go long or short on it which then impacted DAI price. |
| # / 00:23:59 | Vishesh Choudhry | What's interesting now is I think that behavior probably still exists. It's probably a little bit muted now that ETH has come up in price a little bit, but I imagine that relationship still exists and it seems to just be impacting DAI a little bit of less, which is, I think, a positive marker for the resiliency of DAI to that leveraging behavior, because in the past, that leveraging behavior was much more effective at depressing the DAI price. |
| # / 00:24:29 | Richard Brown | All right, thanks, Vishesh. Trying to stay cognizant of the time. We're at half-past the hour, so Cyrus, do you want to unleash your slide deck on us? |
| # / 00:24:39 | Cyrus Younessi | Sure. One second. Okay, good? |
| # / 00:24:49 | Richard Brown | Yep, that's good. |
| # / 00:25:20 | Cyrus Younessi | Okay, cool. Today we're going to start talking a little bit about the quantitative side of things. Okay, so quick recap from last week. Last week, we mainly talked about the qualitative and fundamental side of collateral asset. We looked at a rough sketch on what we want to examine for a particular collateral asset. |
| # / 00:25:50 | Cyrus Younessi | I know we don't get into a ton of detail on it. I think it just makes more sense to run through the entire model, and then when we circle back to looking at specific collateral assets, we can get a little bit more detailed on examining an asset and talk about scoring frameworks, but essentially, the goal was to take everything we know about a particular collateral and turn it into some sort of risk rating. |
| # / 00:26:20 | Cyrus Younessi | We haven't exactly talked about how that risk rating comes in where it impacts the final risk parameters, but we will, and also obviously up to this point, we haven't used any information about the market's trading liquidity or anything of that. |
| # / 00:26:43 | Cyrus Younessi | Quick reminder, this was the overall outline process. We did skip actually the first step, the collateral onboarding process, which we will return to I think either next week or the following week. Waiting one some documentation to be released so that we can go over it. Last weeks due diligence and now we're on quantitative modeling. |
| # / 00:27:15 | Cyrus Younessi | Then today's outline, or I should say the outline for the next however many weeks it takes to get through this, certainly not a one-day thing. First, we're going to talk a little bit about the goals and strategy of what we're trying to achieve with the quant models, talk about inputs and outputs, [inaudible 00:27:37] background information, building blocks. |
| # / 00:27:41 | Cyrus Younessi | I think really these first three sections is what we're going to be able to get to today, but if we have time, we can start looking at single CDP credit risk model. Afterwards, liquidation ratio, putting a bunch of assets into a portfolio, and then looking at debt ceilings. |
| # / 00:28:04 | Cyrus Younessi | Okay, so first section, goals and strategy. What are we trying to do and how are we going to do it? First, a few philosophical goals. The MakerDAO mission, DAI becomes the first unbiased world currency, the tagline for this project. The risk side of things or the decentralized risk function should of course help support that mission, and the role of risk is to promote the stability and integrity of DAI. |
| # / 00:28:41 | Cyrus Younessi | Obviously, we want to grow the DAI supply, but we want to do it safely and responsibly, and we want to create sensible approaches to hard problems, and as we will see over the coming weeks, there's a few hard problems that we just got to get our hands around. How do we achieve these philosophical goals? I've said it a million times, but we have to patient and prudent. There's no other way around. If we rush through these models, I think we'll be setting ourselves up for not a fun time. |
| # / 00:29:26 | Cyrus Younessi | Operational goals. First step is just defining what these risk parameters represent. I think there is actually still, to this day, a lot of confusion about what the purpose of the different risk parameters are, what exactly are we looking for in the stability fee, and the debt ceiling, and even the liquidation ratio can sometimes be a little bit tricky to understand. |
| # / 00:29:53 | Cyrus Younessi | First, we just want to understand what these parameters do. We want to build the right models to calculate these parameters. We want to examine the weaknesses of these models so we know where are our weak points, where are we vulnerable, and then aspects of the models that we can't fix just [inaudible 00:30:23] manage at the social layer. We just have to be in constant communication and being monitoring the system. |
| # / 00:30:30 | Cyrus Younessi | At some point, we will tie in decentralized governance into this whole process and then also of course the monetary policy, as well. Everything has to tie together nicely and hopefully it will by the end. |
| # / 00:30:49 | Cyrus Younessi | Okay, so how do we go about actually getting this done? A few things that I want to emphasize, first is I think the goal should be to keep the model as modular as possible. We want to understand how everything works, but there is inevitably going to be a lot of differences in methodologies. For example, there really shouldn't be any disagreement from one risk team to another from one risk model to another about what the liquidation ratio represents. |
| # / 00:31:27 | Cyrus Younessi | There's a fairly static definition of what it's designed to do, but there are probably more than a handful of ways to go about actually calculating that parameter. Essentially, we want a risk team to come in and say, "The particular method that you guys have chosen is wrong," or, "There's a better way to do it," and hopefully from there we can improve our models and iterate. |
| # / 00:32:06 | Cyrus Younessi | Generally, nobody in the risk team has an ego about these things except for Rich, and Vishesh actually who, in my experience, both of them do not like to be told that the models are wrong even though it occasionally happens, but that's the point. I think we all want to get good discourse going and try to improve on our models. |
| # / 00:32:33 | Cyrus Younessi | Then secondly, I think at first, it's just instructive to start from an academic framework. A lot of intuition is much easier to understand from a theoretical ... If you could have all the data in the world and everything that you needed, how would you go about calculating these parameters? As I mentioned, a lot of these models are just intractable in practice and we absolutely have to find and discuss pragmatic solutions. |
| # / 00:33:07 | Cyrus Younessi | There will be simplifications to deal with these hard problems, but in turn, they will create other problems. There are just trade-offs no matter how you go about it. We just want to be clear on what these trade-offs are and come to rough consensus on what is acceptable for us and what is not acceptable. |
| # / 00:33:28 | Cyrus Younessi | Yeah, unfortunately, just a few problems are just unavoidable, so we just need best practices, and I think that's just what decentralized risk function is all about is finding a solution and coming to consensus on what's the best path forward. |
| # / 00:33:58 | Cyrus Younessi | Okay, so we're going to start off with a simple model with a lot of assumptions which we will then relax one by one. We're going to be conservative in a lot of our calculations because I think that's just the prudent way to do it. I think we're going to run our first, not think, we are going to run our first example on ETH. I think it's the only collateral that we can all agree on today that will be part of MCD. Also obviously has the most data. It's most applicable. There's obviously no counterparty risk to ETH, which is nice because I get questions every single day about counterparty risk with a lot of these other collateral types. It's something we can deal with a little bit later. |
| # / 00:34:59 | Cyrus Younessi | Of course, as we get more collateral type of certain aspects, we'll need to change. It doesn't need [inaudible 00:35:06]. We're going to try to keep things as general and modular as possible with the understanding that obviously specific collaterals will require changes to the model. |
| # / 00:35:18 | Cyrus Younessi | Okay, so at a high level, it would be great if this was all the work we had to do. Unfortunately, there's a lot of work ahead of us, and I think first, let's just define our inputs and outputs, figure out where we're starting, where we want to get to, and then of course we'll talk about the journey there. |
| # / 00:35:45 | Cyrus Younessi | Okay, so inputs. As I mentioned, first thing we're going to have is a collateral application which is just going to have some general information about the collateral asset organization, the team behind it, some data on the token itself, it being trading data, or token distribution. We'll get into that later. We're going to have a trading profile obviously collecting trade history. We're going to find a way to deal with wash trading. |
| # / 00:36:23 | Cyrus Younessi | For now, we're just going to focus on exchanges that we know don't use wash trading or don't allow it. There is a few services out there that do this curation for us. I think that's just going to be the way to go. It's obviously a pragmatic solution for now. I think also that's useful for determining oracles, as well. Going to calculate some metrics, daily returns, variance, all that stuff. |
| # / 00:36:56 | Cyrus Younessi | In time, we will collect order book data as well for more robust liquidity analysis, but that's another thing that I think will just have to be an improvement or iteration later on, or if someone wants to help out with that, reach out, obviously. We get to start with a lot of CDP data, which is great, so first is a historical CDP distribution data of collateralization ratios and then obviously our current CDP distribution, as well. |
| # / 00:37:33 | Cyrus Younessi | For the historical distribution, what I'm referring to is something like this, so basically per ... Does this work, this pointer? |
| # / 00:37:53 | Richard Brown | Yeah, I can see it. |
| # / 00:37:56 | Cyrus Younessi | Okay, cool. Per collateralization ratio bucket, we want to track the amount of debt relative to the other buckets over time. That becomes useful. These buckets are arbitrary. We definitely won't be going this granular, but we will be dividing it into several buckets. Source for this chart is Vishesh, of course. |
| # / 00:38:28 | Cyrus Younessi | Our outputs. Our outputs come in different categories just because there's obviously intermediate steps in the model, so some of the preliminary outputs, obviously our own qualitative framework that we submit and the risk rating that comes out of it, liquidity analysis. Liquidity analysis will essentially be a delta that says for a given amount of slippage or liquidity, whatever, that stability fee will need to be adjusted a certain amount up or down. |
| # / 00:39:10 | Cyrus Younessi | Then with this, you can essentially tinker with the liquidation ratio and the stability fee and say, "Well, I'm willing to allow up to X amount of slippage in the liquidation process and compensate for that with an additional adjustment to the stability fee." Our risk premium will come out of this, and then of course we go back and add the DSR adjustment to capture what is the final or total stability fee for a collateral asset. |
| # / 00:39:48 | Cyrus Younessi | Some more intermediate outputs. When we get into the more portfolio modeling side of things, we'll have to look at correlations. We'll have to look at stress tests, simulations, economic capital, and then the last stage in the process really is the debt ceiling and how much exposure MakerDAO can facilitate as a whole. |
| # / 00:40:15 | Cyrus Younessi | The two main items on this list in my mind are obviously the risk premium and the debt ceiling. Those are the two big goals that we're trying to get to. Any questions so far? |
| # / 00:40:34 | Richard Brown | Are we going to be circling back for a deeper definition of some of these terms like [crosstalk 00:40:38] capital? |
| # / 00:40:37 | Cyrus Younessi | Yeah. Yeah, yeah, yeah. As we go through calculating them, we will for sure. |
| # / 00:40:44 | Richard Brown | Okay. |
| # / 00:40:48 | Cyrus Younessi | Okay. We're going to talk a little bit about building blocks overview. This is going to be somewhat basic. I'm not sure we can avoid it, though, because I think it's important to lay the foundation for how CDPs and MakerDAO even works in the first place. A great contextual starting point, almost like a metaphor, is just traditional loans. CDPs are selfish, DAI-denominated loans, so I think it's extremely helpful to start by looking at how loans are evaluated from a risk perspective. |
| # / 00:41:33 | Cyrus Younessi | Also, MakerDAO loans are actually pretty niche in a lot of ways and it leads to a lot of confusion, especially with the collateral aspect of things, so I think it's easier just to do a quick background. Okay, so a few different examples, obviously hypothetical. You loaned $100 to a stranger on the street, you're not getting anything back. That's obvious. You loan some money to a roommate or somebody you trust, they might pay you back or maybe they're only able to get you back a certain amount of it, but alternatively, if you do lend to a stranger who leaves some collateral with you, then that's generally okay. |
| # / 00:42:12 | Cyrus Younessi | Obviously, this third one is the Maker model. We can immediately see that there's like a diverse set of scenarios here and distributions, and we want to be able to capture these different aspects in our models, and from just a simple example, the two areas to focus on are the actual default process and if they had any collateral with you in the first place. |
| # / 00:42:46 | Cyrus Younessi | Looking at default risk or credit risk, a good starting point is to think about loss distributions, which is essentially someone trying to figure out the different scenarios in which they get some amount of money back from their loan. In the example of the stranger, you probably get nothing back. If you lend to your friend, you might get some back, but you don't know how much it could be, $30. It could be $50. |
| # / 00:43:19 | Cyrus Younessi | Essentially there's a bunch of different outcomes that can happy, a bunch of different scenarios, and really the simplest first metric that you just want to look at is just the mean of this distribution. Just on average, what do you expect it to get back or alternatively expect to not get back? Which is the parlance for the field which is known as your expected loss. |
| # / 00:43:50 | Cyrus Younessi | This expected loss is just the mean of that distribution, and intuitively, without knowing what this distribution even looks like and could look a lot of different ways, you know that what you expect to lose depends on three things. One is how much you actually lent out in the first place just known as the exposure amount, the likelihood of not getting paid back or the probability that the borrow defaults on this loan, and then this conditional where, okay, if they have defaulted, are you able to claw any money back from them? |
| # / 00:44:32 | Cyrus Younessi | Is it the case that if they default, you've lost the entire amount of the loan or just part of it? This is a pretty general model that applies at a high level to all collateral types. Interestingly enough, this distribution also of course has a variance which describes the range of how bad things can get, and we'll circle back to that a little bit later, but that becomes important later. |
| # / 00:45:06 | Alexander Evans | Hey, Cyrus? |
| # / 00:45:07 | Cyrus Younessi | Yep. |
| # / 00:45:08 | Alexander Evans | Question for you. This might be a little bit philosophical. If you want to go back to the previous slide, although this slide can explain it well, too, how do you think about a default? Defining a default, you could define, let's say, a given liquidation that could be a default, but in that situation, you typically have a positive recovery, well, above-one recovery rate, right, so you can get 10% back? |
| # / 00:45:31 | Cyrus Younessi | Right. |
| # / 00:45:33 | Alexander Evans | Would it default then? There's two ways you can go about it, I guess. One, you could say a default is a liquidation that occurs at below 100% collateralization at which point there is some loss, or you could say it occurs whenever a [inaudible 00:45:49] collateralized and you can just assume that the recovery rate is above one which makes it a little bit more awkward. |
| # / 00:45:56 | Cyrus Younessi | Right, yeah, yeah. I know exactly what you mean. The best way to do it, and I think really the proper way, is that you define a default when the CDP gets liquidated and then the amount that you're able to recover from the collateral sale gets baked into that loss given default and essentially trying to find out the statistics behind what the auction looks like and how much you're able to recover. |
| # / 00:46:24 | Cyrus Younessi | If you're able to recover everything plus some, that's a collateral adjustment made to the loss given default, and in those scenarios, the LGD just becomes zero and you've just lost nothing. |
| # / 00:46:38 | Alexander Evans | Well, wait, wait, wait. Let me understand that. You're not losing negative amounts, in other words, gaining- |
| # / 00:46:48 | Cyrus Younessi | No, no. We cap it to ... right, because MakerDAO does not gain anything, even. They DAO returns the excess collateral back to the CDP user, so they actually can't have a negative LGD. |
| # / 00:47:06 | Alexander Evans | Yeah, I guess I'm referring to the fee and how you're dealing with that in that situation. |
| # / 00:47:10 | Cyrus Younessi | Oh, you mean the liquidation penalty? |
| # / 00:47:13 | Alexander Evans | Yeah. |
| # / 00:47:15 | Cyrus Younessi | Yeah. That's something to be factored in, but that's a specific- |
| # / 00:47:23 | Alexander Evans | Yeah, it is. I don't want to sidetrack. |
| # / 00:47:25 | Cyrus Younessi | Yeah. Yeah, we can factor that in for sure. |
| # / 00:47:31 | Alexander Evans | Thank you. |
| # / 00:47:31 | Cyrus Younessi | Cool. yep. Okay, so you can think of defaults or not-default as a two-state system, very simple, but very instructive. In this branch here, this is where there is no default, one minus the probability of default, and in this scenario, you get back everything or this is what you're owed. |
| # / 00:48:05 | Cyrus Younessi | Then in a scenario where they do default, you get back what you're owed times what you're actually able to recover from the loan. Your expected losses obviously, not obviously, but the expected loss is how much you're owed back minus what you expect to get back, and this expectation here is calculated through this branch here, and you do out the calculation and it simplifies nicely to your loss being the likelihood that you don't get your money back times the amount loaned out times the amount that you've lost. |
| # / 00:48:45 | Cyrus Younessi | This subscript, H, is just the horizon. It's not really that important. Are there any questions on this? There's got to be a question on this. Okay, cool. |
| # / 00:49:05 | Richard Brown | Well, Cyrus, there was a question in the side. I can read it out to you from Patrick again. Expected loss is capped at zero in traditional models. I think that's reasonable to use here, also, since Cyrus mentioned it's not like MakerDAO is keeping excess collateral proceeds, so I think that was a reference to Alex's question earlier. |
| # / 00:49:26 | Cyrus Younessi | Yeah. Yeah, but as Alex has pointed out, there is still a liquidation penalty which- |
| # / 00:49:33 | Richard Brown | [crosstalk 00:49:33] heads back into the buy and burn, though, right? |
| # / 00:49:37 | Cyrus Younessi | Right, but yeah. We'll come back to that. You lend out $100. You might get back 100. You might get back 30. Let's just assume it's a 50/50 chance. The loss given default is 70%. Exposure amount is 100. Your expected loss is $35, so as the lender, you're expecting to lose $35 on this loan, or 35%, and intuitively, a lender would require some compensation for this in the form of a risk premium. |
| # / 00:50:31 | Cyrus Younessi | In this case, the risk premium for this loan would come out to about 53%. It's just a break-even where over time if they were to repeat this loan a bunch of times, this is what would cause them to break even. The point here is we're trying to create a framework where you have an outstanding loan and you want to be able to quantify what is the expected amount that you will get back or what's the expected amount that you'll lose and then trying to derive the risk premium from that. |
| # / 00:51:25 | Cyrus Younessi | The big question is how do we even calculate those parameters in the first place? Because obviously the ones I chose were extremely arbitrary. Trying to figure out what is the likelihood that any loan such as a CDP or anything else will liquidate is quite difficult. Even more difficult is trying to estimate or forecast how much you're expected to lose if there is a default. |
| # / 00:51:52 | Cyrus Younessi | In the traditional world, something that helps derive that is reputation. That's what credit scores are for where they say, "Based on your credit history, we've assigned you this score," and generally people with this score have a 10% frequency of defaulting on their loans, and they can just do this through a lot of data mining and looking at historical data over the past hundreds of years of loans. |
| # / 00:52:28 | Cyrus Younessi | Typically that's the way to do it just looking at historical data. Of course, you could also look at non-historical or forward-looking metrics or a fundamental analysis and just evaluate somebody and offer them a rate based on what you perceive their reputation to behave like over time. |
| # / 00:52:57 | Cyrus Younessi | Of course, there are dis-incentives to default such as obviously your credit score penalty just similar to the CDP liquidation penalty. A key aspect here is that when defaults do happen, there are still additional repercussions that sometimes aren't talked about often enough and are actually important here, and these repercussions are, for example, debt collection and sometimes lenders try to come after your personal assets through the legal system. There's a whole bunch of stuff that happens. |
| # / 00:53:33 | Cyrus Younessi | It's not the case that once you default on standard loan, that's just the end of it, which is pretty much the case with Maker CDPs as of right now. Now, oftentimes for good reasons, lenders sometimes prefer collateral as part of the loan. It's not necessarily the case that people just go around getting loans with just nothing on the line. It happens in some cases, for example, student loans, but there are many cases where lenders will require collateral. |
| # / 00:54:18 | Cyrus Younessi | Intuitively is the more collateral they pledge, your expected loss is lower because now you have a much lower loss given default. If there's default, you, in many cases, just maybe lose nothing. It reduces the expected loss. Also, more importantly reduces the variance of your losses, which leads to some nice properties. As a very simple example, a secured loan is a mortgage where the collateral is the property, and in some cases, the collateral incentives repayment. Nobody wants to lose their home, but for a mortgages, there's two ways this loan can go bad. |
| # / 00:55:09 | Cyrus Younessi | The borrower can stop paying the mortgage payments or the collateral value falls. Oftentimes there's insurance purchased on the collateral value falling, so in a lot of ways, they're still focused on the likelihood of repayment, but additionally, house prices are typically stable and obviously we know that ETH is not, so we have to focus on the collateral of course. |
| # / 00:55:46 | Richard Brown | Cyrus, we're at the top of the hour. Do you want to continue on? |
| # / 00:55:51 | Cyrus Younessi | Yeah, I just have a couple more slides. |
| # / 00:55:53 | Richard Brown | Okay, cool. |
| # / 00:55:54 | Cyrus Younessi | Let me just finish up. Okay, so the three kinds of debt that we talked about, just a pure reputation-based loan unsecured, some sort of hybrid where there's both reputation and collateral involved, and then we have just pure collateral non-recourse debt, which is actually what CDPs are. This is why I was saying CDPs aren't necessarily a great place to start because it's just a niche type of loan. |
| # / 00:56:33 | Cyrus Younessi | Interestingly enough, CDPs can become into these other categories if there was some sort of identity system in place, decentralized or not. Right now it's just the permission-less ... actually, right now, it's more really the pseudonymous nature of CDPs that require this because there is no repercussions for ... No one's voluntarily going to be paying their CDP back. |
| # / 00:57:10 | Cyrus Younessi | This collateral-only model requires us to update our definitions a little bit. A CDP has no term, has no scheduled payments. There's really no such thing as nonpayment in a CDP. Default is now purely occurs when an asset hits some threshold. The loss given default is now what the expected liquidation value of the collateral is, and these become the two main parameters that we need to reason about as we continue our models, so this probability of default essentially becomes how can we reason about, what is the chance that ETH just tanks to, whatever, 150, 200, and how much can we get from the liquidation process? |
| # / 00:58:13 | Cyrus Younessi | There's also a little bit of work to be done with the exposure amount as well given that, let's say, there's a $250 million debt ceiling and only 100 million has been taken out. What is the rationale behind the likelihood that that additional 150 million can suddenly be drawn or not? |
| # / 00:58:42 | Cyrus Younessi | Okay, so yeah, that's actually it for today, then, because we're out of time, but next week, we can actually start digging into this stuff here, which is essentially we're going to use these to create some sort of loss distribution for the CDP and calculate the risk premium from there, and we'll explore a few different approaches on how to do that. As I said, a lot of this fairly academic and theoretical, and we'll see that in practice it doesn't work out as nicely as we'd hope, so we will explore some, not nonacademic, but non-theoretical models, as well. Okay. |
| # / 00:59:35 | Richard Brown | Okay, that was amazing. Thanks, Cyrus. We should probably try to figure out whether there's any questions. There was a lot of data there to go over. If anybody does have a question, pipe up now. Feel free to jump on the mic or type a question into the group chat. Cyrus, I'm wondering. Because the volume of data that we're going through in these calls, and we're going to go through, waiting for a finalized slide at the end of it might be a lot to review. Is there any way that we can get pieces of the slides we looked in the meeting just like a tiny little deck that we can post to the thread? |
| # / 01:00:12 | Cyrus Younessi | Yeah, absolutely. Just help me offline on [crosstalk 01:00:16]. |
| # / 01:00:16 | David Utrobin | I actually took a bunch of screenshots. I should be covered on those slides. I'll just post them in the summary. |
| # / 01:00:23 | Cyrus Younessi | I can share them for you guys. Just tell me what the best way to ... |
| # / 01:00:27 | Richard Brown | A summary would be good, too, because people are already heading there, so that might be a great option. |
| # / 01:00:30 | David Utrobin | Yeah, I'm just going to make it so that you could click a button and check out the screenshot of the relevant slide to the notes. |
| # / 01:00:40 | Richard Brown | All right, sounds good. Questions from the floor? All right, so maybe people are absorbing things. If we don't have questions related specifically to the risk presentation, we can revisit it in the thread after the summary has been posted. Give people some time to review. Matthew, I didn't ping you earlier to see whether you had a weekly recap for us this week. |
| # / 01:01:15 | Matthew rabinowitz | I have one, but I want to ask you do you want to go over the executive vote part first? We skipped over a little bit of where the polling was. |
| # / 01:01:24 | Richard Brown | I thought I addressed it. Did I not address it deeply enough? I talked a bit about how we saw this first example of campaigning arise in the system where previously the weight up until just the 11th hour was at 15. There was some discussion about how potentially it should be raised instead in the threads, and the Maker was moved into a 17 for the next [inaudible 01:01:54] next Friday. That's the 20th, that's right. Tomorrow we're looking at adding an executive for 17.5, which is a potential raise from the 16.5 we're at right now. |
| # / 01:02:09 | Richard Brown | Matthew, if you wanted to give us like a five- or 10-minute recap, that'd be awesome. We have time. |
| # / 01:02:14 | Matthew rabinowitz | Yeah, so basically, it was a continuation from the previous one outlining what I'm viewing like the greatest and the hardest challenges we're going to face. In addition to all the parts Cyrus was outlining about how we're going to to identify risk, it's also going to be how we can maintain the natural risk distribution of every type of collateral that'll be brought on to this system from something that is in theory riskless or as much of it as possible all the way to the stuff that's really risky. |
| # / 01:02:45 | Matthew rabinowitz | Some of this, as Cyrus was bringing it up, the difference in collateralization ratio, liquidation ratios, and debt ceilings, it's actually a question I have just in general. If the intent is to use those metrics and those three metrics only to identify and control the risk for a given, we'll call it, asset package that we're going to put out as collateral, the challenge, one of the, I guess, questions I have would be when we starting having the identical type of collateral behind it, say for example, ETH, and we have a different collateralization ratio or a different liquidation ratio, the risk is different. |
| # / 01:03:25 | Matthew rabinowitz | The question becomes as a community, how do you set forth a system where assets that are more risky stay priced more risky? Because there's a natural tendency to bring that risk, and the ability to vote on it brings that number down. That of course is one of the questions, and that's one of the points that I wrote about was how we can try to identify that and scenarios where asset classes, excuse me, asset packages basically become less risky, how they can be, in effect, refinanced, and when they become more risky, how you, in effect, drop the debt ceiling to zero and force new debt to be, in effect, priced at a higher rate. |
| # / 01:04:17 | Matthew rabinowitz | The bigger concern would be really how the debt, excuse me, the DAI savings rate is applied, because if we go down the fundamental theory that not all the assets are going to be placed, asset packages, excuse me, will be identically risked even with the collateralization liquidation ratios, and if they were all identically the same risk, then the DSR should be applied evenly for all of them, and it's somewhat a moot point. |
| # / 01:04:43 | Matthew rabinowitz | When they're not going to be equal, then the less-risky assets justifiably should be allocated more of the debts that the DAI savings rate allocation when we have to create more DAI, excuse me, when we have to absorb more DAI, the parties that are minting more because they have a risky asset should not be weighted as much. |
| # / 01:05:11 | Matthew rabinowitz | I guess the point really is to see how we're going to to ultimately compute the DAI savings right and to try to have it be as algorithmic as possible to ensure that the weighting average of a risky asset and more risky lease, excuse me, risk-free and a risky asset are not in parity in terms of how they're treated, because in doing so, we start to just inject risk into the system and we do it unintentionally. |
| # / 01:05:41 | Matthew rabinowitz | When we, for example, have a risky asset that mints a bunch of DAI, disproportionately having, as David said, a risk subsidy of the asset that are risk-free or much more lower risk, raising the DAI savings rates disproportionately injures them, per se, when, in fact, the party that was ultimately culpable was one that should just be adjusted with the ... What is it? We're going to call it the risk premium for that given asset. That's really the question is how we're going to to maintain that and how we can put it algorithmically where possible. That was it. |
| # / 01:06:29 | Richard Brown | Okay, well, I'm trying to sort that out in my mind. There was a lot of questions in there, so is there one question? Is there a summary question that we can probably try and bite off, I think? |
| # / 01:06:43 | Matthew rabinowitz | The number one question, let's start off. Let's imagine multi-collateral DAI launched tomorrow. Are we planning to vote on the risk premiums per asset package, or are we planning to vote on the risk premiums per asset package as well as voting on the DSR? |
| # / 01:07:08 | Cyrus Younessi | I think we're going to do it separately, the way that you're not a fan of, but I think that's just in the startup days. At least in my case, I'd like to see that kind of ... I don't know if I mentioned this before. I'd like to see that issue in action as opposed to just assuming it's going to happen necessarily. Even if we knew it was going to happen, it would be pretty much impossible to predict beforehand what any penalty would need to be for any particular collateral. You'd have to actually observe it first, no? |
| # / 01:07:50 | Matthew rabinowitz | It's not so much a penalty that I'm trying to say. It's a simultaneous equation. That's the point. It's similar to how circuit theory works with gigantic loops and circuits put together. It's simultaneously computed. That point is we don't want to calculate, excuse me, you want to calculate the DSR and you don't want to set it manually because of the fact that what we want to do is have the DSR be calculated and wait a week and realize that it didn't fix the problem, that we're not adjusting the risk premiums correctly, that DSR can't be the savior for a risky asset that mints a bunch of DAI. |
| # / 01:08:33 | Matthew rabinowitz | If you take a spectrum and just picture and you take three assets that we start off launching, one that's risk-free, one that's medium risk, and one that's very risky, the question becomes if the risk-free asset mints a bunch of DAI and the others too don't do anything, the DAI savings rate should fix that. |
| # / 01:08:52 | Matthew rabinowitz | Then if you take the exact opposite where the risk-free did nothing, the medium risk did nothing, but the extremely risky asset minted a bunch of DAI, what should the DAI savings rate do? The point is it shouldn't do anything. It should just stay there, and the risk premium, because it's a risky asset, is the one that should go up, not the DSR. |
| # / 01:09:19 | Matthew rabinowitz | Theoretically on three assets, it's easy to discuss. When you have 400 of them, it has to be computed because if we don't start using an algorithm to compute it, we will naturally have apathy to the fact we just can't tell the difference and we have excess DAI in the market, the supply and demand are out of whack, the price is 99 cents on the dollar, so what should we do? We should just increase the DSR by three basis points and that'll get rid of the problem, but it didn't. |
| # / 01:09:50 | Matthew rabinowitz | We just injected more risk to the system because an asset that minted that DAI that caused that 99 cents on the dollar somewhere in that risk spectrum is now misallocated. It is now not correctly priced for its risk premium and had a risk subsidy. The risk was subsidized by the risk-free assets or less risky assets because the DSR imperative. |
| # / 01:10:16 | Cyrus Younessi | A collateral's risk premium, its inherent risk to the MakerDAO holders or to MakerDAO, is not dependent on its impact on the DAI price, per se. It's dependent purely on itself. |
| # / 01:10:36 | Matthew rabinowitz | Totally. Agreed. |
| # / 01:10:38 | Cyrus Younessi | We can agree that at least, okay, there's definitely a risk premium that is solely calculated from the qualities of the asset, whatever, the liquidity and the fundamental properties, so we have that number. Let's call it a base risk premium for now. Now, for whatever reason this asset triggers, and let's just assume the DSR is zero, for some reason when DAI gets minted off of this collateral asset, DAI will be trading below a dollar not because of anything necessarily to do with the collateral itself, but rather there's just not enough demand from people holding DAI, and that's why the DSR comes in to ... |
| # / 01:11:41 | Matthew rabinowitz | Yeah, that, I think, is the assumption that I don't think we should use the DSR exclusively as a demand absorption tool across the board. It should be weighted, risk-adjusted in favor of assets that are less risky because the DSR by definition is risk-free. |
| # / 01:12:01 | Vishesh Choudhry | Can I ask a question? We've been dancing around this topic for a couple of weeks. It seems like there's two separate issues. One is how do you determine whether risk parameters have been properly calibrated versus do you need to change the universal nature of the function of the DSR and make it more targeted? My question is, okay, I understand that if there is oversupply, it is very simple to say the DSR should be calibrated to soak up that oversupply. |
| # / 01:12:40 | Vishesh Choudhry | Now, separately there's a question of that functionality could be taken advantage of by a given asset if that asset's risk parameters are not properly calibrated. Now, the question is why not attack the root issue and fix the risk parameters for a given asset if they are improperly calibrated? |
| # / 01:13:00 | Matthew rabinowitz | That's an excellent point. That's where I started off with. If we assume that all asset packages, and I call it asset packages because I just think of it as collateral could be ETH, but if we're changing the liquidation ratio from ETH as your collateral, imagine right now it is whatever it is, 66%, is that right, whatever the number is, and we change one from 50% and the other one to 95, one collateralization ratio now is at 150% and we make another one 104%, whatever, the numbers are different, even if the underlying asset is identical, the whole collateral package, they're diametrically different risk components. |
| # / 01:13:40 | Matthew rabinowitz | Even if they're priced correctly, even if the collateral package has an associated risk premium that's different, the two collateral packages are different, so how can the DSR be applied equally to both of them? [crosstalk 01:13:56]. |
| # / 01:13:56 | Cyrus Younessi | I think the issue here is I think your solution would actually in some ways unfairly penalize latecomers to the collateral pool. Imagine for a moment we only have a risky asset like ETH and let's say the DSR is 5% and everything is fine, then we add a completely risk-free asset that generates a ton of DAI and the supply outpaces and the DAI prices falls. Would you then penalize that risk-free asset for having impacted the DAI supply negatively? |
| # / 01:14:35 | Matthew rabinowitz | No, because- |
| # / 01:14:37 | Cyrus Younessi | No, because that would be unfair to the risk-free one because they just happened to be the latecomer, right? |
| # / 01:14:46 | Matthew rabinowitz | Well, picturing a pyramid, as you drop in new collateral types, they have to get recalibrated into the risk, call it the spectrum of the entire risk solution, and there are basically three scenarios every time you drop one asset in. It's not realistic to say, "We're going to recalibrate every single one of them every time we add any one asset," but we have to determine if an asset that was added or in fact all of them, if the risk profile as it compared to the system a whole, stayed the same, became better in terms of risk, or became worse. |
| # / 01:15:20 | Matthew rabinowitz | If they became worse, you have to increase and change their metrics, and if they became better, you basically let them be auto-refinanced down. |
| # / 01:15:29 | Vishesh Choudhry | Hang on [crosstalk 01:15:30]. |
| # / 01:15:30 | Cyrus Younessi | Sorry, go ahead, Vishesh. |
| # / 01:15:31 | Vishesh Choudhry | Yeah, I'm not sure it's the most well-intentioned design to say that, for one, if there's a problem, imagine you're talking about scales and it's almost like you have many different ... It's not a two-sided scale. It's many-sided, and if all of the scales are out of wack because one particular scale is over- or under-weighted, I don't think it's a great solution to try to solve all the relative weightings of those scales versus if there's one particular asset that is disproportionately drawing out supply because the risk parameters for that asset make it too attractive or too easy to do so, then ... |
| # / 01:16:18 | Vishesh Choudhry | For example, if donuts were a collateral and let's say there was no negative effects, there was no risk to Maker holders, etc., which presumably would supersede anything we're talking about here, because if an asset is causing a bunch of uncollateralized liquidations, that would presumably be the superseding issue, but let's say none of that is happening and it's just causing too much DAI to be drawn out. |
| # / 01:16:41 | Vishesh Choudhry | I could easily curtail tomorrow the amount of DAI that's being drawn out from CDPs for that asset by just increasing the amount of collateral that's required for that asset. |
| # / 01:16:54 | Matthew rabinowitz | Exactly, but [crosstalk 01:16:55]. |
| # / 01:16:55 | Vishesh Choudhry | What I don't understand is why collateral requirement- |
| # / 01:16:59 | Matthew rabinowitz | You can't, but this is the challenge, though. Yeah, but you can't change the collateral ratio or liquidation ratio after a given collateral package, but ignore the collateral packages out there. That's the equivalent of saying, "Hey, I'm going to give you a house mortgage. Your house is your collateral, and that's great. We're going to have an 80/20 deal, 20% equity," and then you start paying and I'd say, "Hey, wait a second. The risk profile just changed. Now it's a 40% equity deal," and you say, "But wait a second. That's not what the deal was when we started," but it triggered a liquidation. |
| # / 01:17:33 | Vishesh Choudhry | It's ultimately a distribution of different collateral requirements for a given asset, right? We've talked about this. There's going to be many different types of CDPs for a given collateral, so it's not necessarily about, for a given loan, changing the terms of that loan after it's been issued, but rather making loans that are in that range of types that we deem to be unfair, let's say, more expensive, so that people get priced out of those particular structures because those particular structures are improperly calibrated or unfair and that effectively would also push people towards those higher collateralization ratio CDPs because even though it's a higher collateral requirement, you can make it ultimately less expensive by changing what the premiums are. |
| # / 01:18:28 | Matthew rabinowitz | There are two fundamental problems here. How do you always, A, ensure that riskier assets stay continually priced as more risky, and the corollary, but one that I think is more dangerous, is how do you constantly ensure that the riskier assets, when the DSR is used, are disproportionately in favor of the less risky asset? Because if you we use it to sweep the problem underneath the rug because a risky asset is not correctly priced, we amplify the problem. |
| # / 01:19:02 | Vishesh Choudhry | I agree with that. My guess is going to be that it's going to be less tenable to try to disproportionately apply the DSR versus to adjust those particular premiums on a running basis or a more [crosstalk 01:19:20]. |
| # / 01:19:20 | Matthew rabinowitz | That's precisely why I want the DSR to be algorithmically computed such that when we try to apply it based on upon risky assets that are causing a problem or burning, it doesn't matter which direction it happens, where whatever the event happens and we try to adjust it, the DSR is only mathematically allowed to mint according to the risk price. |
| # / 01:19:43 | Cyrus Younessi | I don't see how you can say what particular asset is causing a problem even if it was the most recently added one. Again, let's say you have 50 million DAI from ETH generated and then add some super safe bonds, and then another 50 million DAI is minted, and let's assume that the risk parameters for both ETH and the bonds were properly calibrated, so you have ETH in there sitting in there for a year. DSR is 5%, no problems, nothing. Let's say 1%. You have no issues, and then a year later, bonds come in super safe, you have the right parameters, and because there's demand to leverage off of it, another 50 million DAI is minted and there just wasn't enough demand for DAI to keep up with this new 50 million batch of DAI. |
| # / 01:20:46 | Cyrus Younessi | Now, there's 100 million DAI out there and there isn't enough demand for it and now the DAI price has dipped a little bit. You can't say that, oh, it's the bond's fault that DAI is now lower just because then you're protecting [crosstalk 01:21:07]. No, no. That would even be worse. Then you're protecting ETH simply because it was first. |
| # / 01:21:14 | Matthew rabinowitz | No, no, no. That's fine. My concept is it has to be a simultaneous equation. We're going to know what collateral package is minting DAI or burning them accordingly. The real question is the other way around. It's not if you introduce a bond that's very riskless. JP Morgan issues a debt, we tokenize it, and you borrow a bunch of money against it. ETH is the other collateral in this spectrum. |
| # / 01:21:42 | Matthew rabinowitz | In that scenario, the DSR is going to absorb it because it is proportionally, on the risk spectrum, less risky than the other collaterals that would be off to the right. The real question is when you have a homogenous happy system that the amount of DAI outstanding is relatively static and you introduce ... The supermarket next door wants to borrow money against their future sales. We put it in a CDP, which is by definition very risky. Even if it's price more or less correctly, if it mints a whole bunch of DAI and it changes the price, do we use the DSR for that? |
| # / 01:22:22 | Cyrus Younessi | Why would it change the price any more or less than the JP Morgan debt would change the price? That's what I'm not understanding. |
| # / 01:22:27 | Matthew rabinowitz | They're totally segregated. It should change. If you have 50 million DAI that's printed from your left hand or from your right hand, that has nothing to do with the risk. It still degraded the price because it changed the equilibrium of supply and demand. The question is when you choose to try to fix that equilibrium, which one of those had more risk? Was it JP Morgan or the supermarket around this corner? If the supermarket- |
| # / 01:22:53 | Cyrus Younessi | It's not about debt. It's about just general DAI supply, like total DAI supply. The DSR should be harmonizing the total supply and demand. |
| # / 01:23:08 | Matthew rabinowitz | I'm not disputing that to an extent, and that's the point. Continue down that thinking, what you really should do is price the debts, excuse me, price the CDP that was causing this oversupply of minting of demand. You should increase the premium to the point where we need the amount of outstanding to go down. Using the DSR to absorb that would be systemically increasing the risk to the system. |
| # / 01:23:38 | Matthew rabinowitz | We went through this three months ago when we had too much DAI in the market right now. We increased the stability fee, the risk premium for ETH to the point where it started to contract the supply because people had minted too much DAI off of ETH. Same concept. |
| # / 01:23:55 | Vishesh Choudhry | Ultimately, you're, I think, in agreement where you're saying you shouldn't necessarily just use the DSR. Sorry, I want to be very clear. The primary function of the DSR should be to eat that oversupply, but the DSR should not be the only lever that is used to fix oversupply of DAI. That's ultimately what you're saying? |
| # / 01:24:23 | Matthew rabinowitz | Everything you said is correct. It should not be equally weighted across the risk spectrum. It needs to be weighted to the less risky assets because risky assets need to be priced correctly with a risk premium, and risky assets that have a higher risk premium, if the risk premium is too low, they will mint not-correct amounts of DAI which cause an oversupply which can degrade the price. |
| # / 01:24:52 | Matthew rabinowitz | To fix that as a lever using the DSR when it's a risky asset is not the correct action. We should increase the price. The question is how do we implement that both on the DSR side as well as correctly pricing the risk premiums. |
| # / 01:25:10 | Cyrus Younessi | Yeah, I think I may be coming around in some respects. I think I can see it in the case of if there was a miscalibration if the risk premium was set too low, then penalizing other collaterals to soak up the miscalibration is just probably not the right- |
| # / 01:25:34 | Matthew rabinowitz | The question is but how do you find that right price? This is where I'm going is that if we ... the only way we're going to find out what that "right price" is is to ensure that DSR can't be basically abused as it impacts everybody in this system. |
| # / 01:26:02 | Vishesh Choudhry | My one concern is ultimately going to be like whether you would actually operationally be able to discriminately apply the DSR. There's a process and there is a model for setting those risk premiums, and I think it would be more of a hot fix, less of a running process, to be able to fix those if they are improperly calibrated, but my concern is it would be operationally infeasible to discriminately apply the DSR. |
| # / 01:26:39 | Matthew rabinowitz | Yeah, I guess in summary, the greatest point I'm trying to bring up is if we both allow, maybe on a short-term basis we have to, but on a long-term basis, I just don't know how we as humans can vote on a risk premium as well as the DSR at the same time. Inherently that is absolutely ripe for conflict of not being able to compute it correctly. |
| # / 01:27:04 | Matthew rabinowitz | Ideally, we just vote on risk premiums across the board on every single collateral package, and the DSR is determined, and if it doesn't work, we will know that across that board the risk premiums somewhere in there were set incorrectly. Somebody was not paying the correct risk premium because it didn't have the desired effect. |
| # / 01:27:33 | Cyrus Younessi | I don't see how you could figure that out unless you were to add the assets one by one and wait weeks in between to see if it's affecting the DAI prices or not before moving on to the next asset I mean as a means of determining if the market thinks that the risk premium you set was accurate or not. |
| # / 01:27:55 | Matthew rabinowitz | Well, this goes back to when you were mentioning the credit score component, and I drew it on whatever, my fourth grade drawing presentation piece. I went through credit scores A through junk. It probably is more of the scenario that when you've correctly dialed in the collateralization ratio and liquidation ratios, probably everything is in the A and B range and maybe some stuff in the C. |
| # / 01:28:20 | Matthew rabinowitz | Realistically, if the risk side has done their job correctly with the liquidation ratio and collateralization, we shouldn't ever really have any defaults that should even allow there to be a problem, which means the risk premiums actually don't need to be that high, which means the DSR across the board is going to end up being a blunt tool. |
| # / 01:28:44 | Matthew rabinowitz | The only way to make this work in my mind's eyes is to do the simultaneous equation wherever ... It's three? Vishesh, correct me if I'm doing it wrong, but whatever, three equations and three variables. In this case, that would be for three collateral packages, and when we add 10 more, well, it's 13 equations and 13 variables, and somewhere in there is the DSR that bluntly impacts all of them on a weighted measure. |
| # / 01:29:10 | Matthew rabinowitz | The question really is when you put together your risk assessment ... We spoke earlier this week with a group that's putting together basically a factoring tool for payments via DSR, payments with DAI that are done on an irrevocable basis over a known time horizon. |
| # / 01:29:32 | Matthew rabinowitz | That is as risk-free of a future payment stream as we can get, and that is the asset that we could ever use that is truly risk-free as collateral in a CDP. How much should that cost? That's one of the questions. That is the risk-free asset for all of, basically would be for Maker, all the way to something that has more risk. You just have to be really delicate not to bluntly use the DSR for everything for all of our problems, because it will create them. |
| # / 01:30:10 | Matthew rabinowitz | All right, Rich. I'm done rambling |
| # / 01:30:14 | Richard Brown | No, that was good. You anticipated me attempting to cut people off. That was a good discussion, and I enjoy seeing Cyrus' will broken in real-time, so that was good for me. It feels like this is a one-pager where, Matthew, if you can summarize exactly what the argument is in a very targeted manner that people can absorb, and maybe we can continue this discussion in risk and governance chatroom. There's things to be addressed here. |
| # / 01:30:49 | Cyrus Younessi | But only if the summary is done in finger paint. |
| # / 01:30:54 | Richard Brown | Yeah, we want some more crayon diagrams I really enjoy. We're at 10:30. That's an hour and a half for a call. I think that we should probably stick a fork in this one. Sorry, continue the discussion, please, in the r/mkrgov sub-reddit. We have a thread designed for specifically this purpose. I'm posting another link. We'll have a summary in there soon of all the [inaudible 01:31:21] points that came out of this call. All right, let's continue the debate. |
| # / 01:31:24 | Richard Brown | All right, thanks everybody. Thanks, Cyrus. Thanks, Vishesh, for the great presentations. |
| # / 01:31:30 | Vishesh Choudhry | Indeed. Thank you, everybody. Take care. |
| # / 01:31:40 | Cyrus Younessi | Vishesh- |