#56 Patrick Kazley - The Systematic House of Cards: Overfitting, Convexity and Protecting Portfolios

The Nalu Finance Podcast

Would you ask your goalkeeper to start scoring goals? Next to a rising equity portfolio, a defensive allocation can look disappointing. The temptation is to make it earn more in quiet markets. But what happens to its protection once we change its job?

I put that question to Patrick Kazley, CEO of One River Asset Management. At AQR, he worked across quantitative strategies and helped sovereign wealth funds diagnose the gaps in their portfolios. The biggest gap he kept finding was not another source of return. It was the absence of anything explicitly built to pay off when markets fall.

Patrick argues that negative carry does not mean negative returns over time. His test is simple: does the whole portfolio perform better with the hedge? Judge a defensive strategy on its own, and you will tweak it until it carries the very risks it was meant to offset. In football terms, you fire your defenders and hire more strikers.

For me, this conversation is about what we ask protection to deliver and how we measure it. The hard part is building a defence we can stick with, without letting an attractive backtest or the last few crises dictate the design.

What’s Inside:

• When the brief asks too much. An allocator wanted reliable crisis protection and strong returns in calm markets. Patrick explains why One River declined even as five competing submissions reportedly met the brief.
  

• First responders and second responders. Long volatility and trend address different kinds of market stress. Where can an extra diversifier start to weaken the defence?
  

• A hedge has worked. Now what? Patrick describes the challenge of locking in gains while retaining exposure if a crisis deepens.
  

Why Listen:

Allocators and manager selectors will find a practical framework here: What is the hedge for? What is the evidence? And does the portfolio perform better with it? It also helps distinguish the normal cost of protection from a strategy that has quietly drifted away from its purpose.

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🎙️ Transcript: Patrick Kazley 00:00:11  If you're trying to evaluate how useful a goalie is and you ask them how many goals they scored, then you don't understand the game. In soccer, you would never say to a goalie, hey, listen, you haven't saved a goal in three games. Can you start practising taking shots on goal? It seems absurd, but in finance you see this all the time.

Stefan Wagner 00:01:23  Today, I'm joined by Patrick Kazley, CEO of One River Asset Management and an alternative investment manager specialising in systemic risk mitigation, volatility, convexity, and trend strategies. I am particularly excited to have Patrick on the podcast because he brings an independent perspective to an area that is becoming increasingly important. I see more and more investors using SHS and systematic risk mitigation strategies. But even today, when I receive a new strategy for due diligence and approval, it often feels as though I have to start from zero to really understand what is happening inside. Such a strategy. Where the returns come from and what the risks are. So I'm looking forward to learning from Patrick and hopefully making some of these strategies a little easier for me to understand. Patrick. Welcome to the new Finance podcast. It's great to have you here.

Patrick Kazley 00:02:13  Stefan. Thank you for having me. Appreciate it.

Stefan Wagner 00:02:15  Thank you. Patrick. Maybe we can start a little bit with you. And what was your path, how you ended up at One River, and what a quant manager built around risk mitigation actually does day to day.

Patrick Kazley 00:02:27  Great. Well, I would call myself a little bit of a recovering quant, in that, I'm still a quant at heart, but my day in, day out, involves less and less true quant work. so I began my career a little bit shy of 15 years ago. JP Morgan pretty quickly found myself at AQR because of my, quantitative kind of academic background. at AQR did everything, had the pleasure to sit across a number of different teams. Global stock selection, macro strategies like trend, etc.. very quickly found myself actually going out to Asia, had the opportunity to open up the Hong Kong office. So later on in the Japan office. But my primary role there was to be the, portfolio representation with the major sovereign wealth funds of the world.

Patrick Kazley 00:03:13  And we would often do these decompositions of their portfolios. basically, here's what you have. Here's what you could use. And ideally, AQR would fill in the holes. And that was kind of the business model. And it was a good one. But one of the number one outcomes from those, I'd say, systematic diagnoses of their portfolios was that there was a missing element of explicit defense, positive convexity. and that was just something that stuck with me through that experience. I came back for personal reasons, just to come to the US after, you know, five years or so in Asia. And, I really couldn't shake this idea of long convexity explicitly. defensive strategies. one river was just down the street. Eric Peters was running the firm and still is. and we we chatted for a while about life, but also about convexity, defending portfolios. our philosophies were, I'd say, more similar than they are different. Eric was kind of the poet to my quant. so we decided to to join forces, and it's been a great ride.

That was in 2021. So today, One River is really 100% focused on systemic risk mitigation. That includes explicit long ball trend and some, let's say, defensively oriented risk premia and dispersion strategies.

Stefan Wagner 00:04:33  I mean, the interesting part is, you recently wrote an article or published a paper, systemic house of cards. With great backtesting powers comes great responsibility. What is the house of cards and why has been built up so high?

Patrick Kazley 00:04:47  Yeah, the systematic house of cards, and across our papers we usually reach for some sort of metaphor song lyric, or we just try to keep it fun. Otherwise, you're writing about formulas and nobody reads it. So yeah, systematic House of cards is a reference to, I would say, the siren song within quant work of creating the best return stream in the past at the direct and necessary cost of future robustness and resilience. Right. And so the House of cards is a as we say in the paper, you can build a really magnificent, systematic house of cards that is poised to fall over due to the stiff winds, about a sample evaluation…. and the issue, in finance is that there's very little accountability, and it's very difficult to ascertain when something is propped up or a robust strategy. And it requires actually quite a bit of skill to tease out the former from the latter. You know, we outlined some techniques to do that. We talk about that in the paper. I'm sure we'll cover some of that today. but ultimately that that was the systematic house of cards. It's been built so high because ultimately strong returns sell. And that's, you know, that's one of the positives and negatives. There's mixed evidence on whether you should do the opposite.

Stefan Wagner 00:06:01  I mean, I've been sort of through one of some of my work exposed to some of these shows strategies. This particular comes from the bank providers or investment banks. And there's a lot there's probably 800 billion outstanding across 7000 strategies. But I've found they sort of quietly bury the ones that don't perform anymore. Suddenly, the track record was not published anymore on Bloomberg and everything else. What does the Grave are tell us about the survivors in the sense?

Patrick Kazley 00:06:28  Yeah, it's and this is true for a lot of, I'd say hedge fund indices as well. The HFR or pick any index provider. But you have to use returns that exist. and the ones that exist exclude the ones that don't. The question is when you have a return stream that suffers a catastrophic loss, do you keep it as part of the composite mix, or do you just quietly retire it? the difference, I'd say between you mentioned that she's, you know, a quant hedge fund that's oriented in a GP LP format. there's audited financial records and public records of those track records existing, it's very difficult to sidestep the accountability of having created something that didn't succeed out of sample. The same can't be said of a systematic model with maybe little to no capital behind it. when that fails, either on paper trading or with real client money, it's very easy, as you said, to retire it and pretend it never existed. And so there's a asymmetry. So if that's the setup, if that's the kind of accountability spectrum, it's it should be no surprise if there's 7000 strategies, maybe 7000 retired and 7000 existing.

Patrick Kazley 00:07:38  So 14,000, you know, that's those are realistic numbers. We've done some best efforts to try to breathe life back into the survivors and the the the the ones that didn't make the cut. and our tentative count is something around 12 to 14,000 strategies over the last eight years.

Stefan Wagner 00:07:57  Well, okay. you you sort of mentioned something over the call to the siren song of overfitting. So how do you actually identify it or overcome it? I mean, how do you avoid it? I mean, at one point adding more parameters and you know, suddenly you find this incredible performance. But yeah, it's very based on one parameter if you're unlucky.

Patrick Kazley 00:08:19  Yeah. The the easiest thing to do when we do this in the paper is, when you consider adding a new parameter to an investment strategy, you have to really question before testing it while you're doing it. and intuition can be one of the steps in that process into intuition is is useful if something's economically unintuitive, you have to ask yourself, why are you even looking at it? but the intuitive filter sometimes is there, sometimes is missing.

Patrick Kazley 00:08:46  Oftentimes, I'd say the most overfit strategies are pure data mining exercises. you know, there may be some relationship between the humidity in France and tech earnings in the US. I wouldn't expect that relationship to remain robust out-of-sample. So that's that's kind of filter one. and that can be solved in a due diligence meeting as to asking why this certain parameter exists. What's the economic thesis for it? but I'd say in terms of the, avoiding that, you really have to, as a, as a quant manager or as a quant, when you created a new strategy, you should take your given parameter and you should alter it in an economically inconsequential way. and the results largely shouldn't change, right? If you're using, a 30 day lookback for a certain signal and you change it to 31 days, you should get roughly the same result. If not, then it's very likely that you've created this house of cards. And, we even do that in the paper and the extreme way. We create three false signals that achieve objectives similar to our flagship fund.

Patrick Kazley 00:09:51  and then we wiggle them, you know, an inch to the left or an inch to the right, and the whole thing falls apart. Now, that is an extreme example, but those are why those signals didn't make it into our process, because they don't survive those robustness tests. the issue though, as, as we note, is that it takes a quant to kind of do that or a very knowledgeable due diligence officer to ask that question. And you may or may not get, an earnest response to that question. So there's an element of trust. Of course, there's an element of brand and reputational risk on the line, but ultimately, what separates an inadequate from a great quant is doing these things before you test an idea, and having that kind of long term mindset of knowing that, yes, you can make a sale today on a great hypothetical track record, but if it dies out of sample, you're not going to have a fantastic career.

Stefan Wagner 00:10:42  Yeah. And I mean, in your paper you use the term backtest Olympics. What does that process look like inside the industry, and how does it distort what ultimately gets presented to the investor?

Patrick Kazley 00:10:52  Yeah. And I give a story from early on in my quant career where we had some of the brightest minds, young minds in quant finance in a room. And, we had a practitioner of 20 years in quant finance give us a pretty simple task of generating, a market neutral return stream, given a universe of a couple dozen stocks and, with pretty strict parameters. And, everybody in the class created, you know, something north of a to Sharpe ratio strategy, which, if you're familiar, is kind of an insanely rare outcome that usually is. And, you know, then we took those models, froze them, and expanded the sample by two times. Its its time window. And, the number of two Sharpe ratios that flip negative was astonishing. You know, it wasn't just that it started producing random returns. It actually started producing robustly negative returns. So there was actually a negative predictor of success.

Patrick Kazley 00:11:50  And that was a very humbling lesson, by the way. I think that's part of the core curriculum for quants anywhere. Is that you? You do something like that so you can understand the dangers of overfitting. now the backtest Olympics is where you have an allocator who wants something to exist. and they pull a series of, you know, quantitative professionals to see if it does exist. Now, when you start a question that way, the backtest Olympics enthuses, the backtest Olympics is where everybody competes to create the best hypothetical track record. And what we say in the paper is that nobody wins except, the manager. And so, yeah, it's the way to sidestep the backtest Olympics is to opt out. So, you know, when River is a firm, when we see, for instance, allocators asking for one Sharpe ratio hedges or something of the sort, we politely inform them that that's just not a thing that financial markets offer.

Stefan Wagner 00:12:42  Which is sort of something. That leads me to my next question.  you mentioned your thing about the tail hatch request for proposal experience. maybe you can double click on that a little bit and tell everybody what happened there. I think that's quite an interesting story.

Patrick Kazley 00:12:58  Yeah. It was it was a large, and it's one of a dozen, by the way. But it's, it's a large, institutional client, wanting to achieve, reliable convexity, with very specific attachment points. The markets are down X Europe, Y, the markets are down, Z Europe, Europe X. And and those are already lofty. But then on top of it there was an absolute return objective that would have been impressive for any standalone hedge fund strategy. so they wanted explicit defense and kind of, let's call it top quartile hedge fund returns in benign periods. And we said, you know, this may be achievable at the total portfolio level if you achieve sufficient diversification. But if you're looking for just explicitly defensive exposures, the financial markets won't give you this. And the feedback we got from the prospective client was, well, we've already received five submissions that comfortably meet all the criteria.

Patrick Kazley 00:13:58  And that was one of those moments that actually led to the writing of that piece, which was, you know, one river and a lot of, I'd say liquid alternatives or quant hedge funds right now are at this crossroads where they have to choose to either opt in or opt out of the backtest Olympics. And by the way, you know, I don't want to be too negative on the banks. You know, the banks. There are a number of fantastic teams at banks who likewise opt out of the backtest Olympics. And I think long term that's going to be the right move. But in the short term there's extremely high pressure dynamics to produce really attractive hypothetical returns.

Stefan Wagner 00:14:35  Yeah I mean I can only mirror that. I mean it, I've seen it so many times. High sharp ratios only ever exists in practice. And then reality is guaranteed. Looks very different. I mean, when we look I mean, I see this so often now with, you know, managers who are trying to get some, you know, long volatility tail risk strategies into their portfolio in the hope that that would be and they you know, they and then they go through the pain of the drag and the paying.

Stefan Wagner 00:15:05  And if you know the strikes are not the right place when it actually happens, you don't have it at the right time and everything else, I think, I think they're particularly difficult because the event you're trying to model occurs or relative infrequent, and most investors are not patient enough to actually let it play pay out. So they ask, why are you paying for this? Why you're dragging, where's the drag on my performance? But how do you build systematic strategy when the historical sample is simply so too small? Or do you actually say, I don't want to be long volatility? I want to be something else. How do you go about this in your in your life.

Patrick Kazley 00:15:42  You know, it's it's there's nothing really to new in finance but things come and go. You know portable alpha come and go. And one of those things that's coming back and I welcome it with full arms because I never really stepped away, was total portfolio approach. The total portfolio approach to portfolio construction is, in my view, just objectively the correct way to think about things.

Patrick Kazley 00:16:02  And if I were to just summarize my interpretation of total portfolio approach, it's that every single time you add a return stream or a unique exposure, you're thinking about its contribution to total portfolio outcomes. in that context, long volatility takes on a completely different shape than it would as a standalone allocation. And so what you call bleed or a low frequency of return when paired with a thing it's protecting, is not low frequency at all. In other words, you could decompose every long volatility returns treatment to a negative market bet and some sort of residual. It just so happens that that residual robustly positive over time. So if you're a total portfolio approach minded individual and you already own public equity data, which roughly describes 99% of institutional investors, long volatility makes a lot of sense. And so, you know, quarter one reverse mission is the belief that you can get paid to protect yourself and that a portfolio that protects itself meaningfully out compounds one that doesn't.

Stefan Wagner 00:17:03  I think the way I see sometimes have seen the struggle was that, you know, they try to do it themselves, bought out of the money, put put space and then, yes, suddenly hedged maybe their mark to market.

Stefan Wagner 00:17:13  But then they were basically caught like a D in the headlights. Are we going to now take the profit on the mark to market or not? And I think that's why it's much better to give it somebody like you professionally. but the other thing is I sometimes I'm a little bit sort of a misconception, Maybe I think you agree with it. But, you know, sometimes some of these strategies are sold as they will make always money. Put the right combination of these three four strategies together and they will always make money. And I don't think that's really possible. And at one point, discretion and macro judgment has to come in. Can you a little bit talk about this.

Patrick Kazley 00:17:51  Yeah. The the most recent piece we wrote was called The Perfect Hedge with the longer form quote is outside of a Japanese garden, there's no such thing as perfect hedge. And that's, I think, a direct reference too, to what you're making there. you can find a strategy that will work really well in a chaotic decline and really impressively in a protracted decline, really well in Covid, really poorly in the 22.

And you can find strategies that exhibit the opposite characteristics. there can be a rolling three year period where simple rolling put spreads look really great and long VIX looks horrific. And then there's periods where the long VIX exposure pays for 25 years of disappointing performance in a week. This is why hedging is such a frustrating endeavor for the uninitiated. But it's also why, for those that I think have skill in systematic risk mitigation or risk mitigation broadly, know that a composite approach is best. that composite doesn't mean that you're over diversifying or diluting convexity. It just means that you're not relying on one engine to deliver that convexity. So I think that the mistake is and this goes back to this backtest Olympics idea is that you find something that's worked really well over, the rolling X period and it stops working well. And you think it's something nothing's changed in the market. That's how markets work, right? the metaphor we use is it's like driving an old car. The thing that just broke down is the least likely thing to break down next.

Like, if you just fixed your carburetor, it's the least likely thing to break down next, because you just fixed in 2009, the least likely thing to break down was going to be asset backed securities in housing. Right. in in 2022. That was at the end of 22. It was not a good time to buy rates fall. You know, these are the wrong times. The time to do it is when the sun is shining and people think, they miss assigned probabilities. So whether your systematic or discretionary, your research process needs to be driven, with a sense of, you know, what hasn't happened in a really long period of time that really could.

Stefan Wagner 00:19:50  You have seen strategies advertised sort of 4,000% crisis return? You know, I think there sort of is something wrong with the denominator, you know, and how should actually these long volatility returns be reported instead?

Patrick Kazley 00:20:06  Yes. you're referring to lifting the veil on tail piece. And indeed, you know, it's, when it comes to convexity generation, there's a lot of ways to, try to make it look more appealing to a board, to a CIO, to general populace.

 And I'd say, one of the ways that we've seen is denominator selection. In other words, when there's a positive return, the denominator becomes something like an outstanding premium at risk or a margin deployment, which for derivative based strategies is very low, right? A trend following portfolio might be running 7% margin of equity. But ten ball you know. So it's even more extreme for hedging strategies typically. So that's a very favorable denominator for return generation. Now if you have a 4,000% return or something of the like in a crisis, it is necessary that you also have -100% returns every now and then, because it means you lost all your premium in a given benign month, which, by the way, the cash on cash return can still be very impressive and useful. but the issue is that you've just removed the ability to evaluate that as a geometric return stream, because the geometric return of plus 5,000% in -100% is -100%. So you've removed all of the evaluation criteria that one can use for any other line item, and you've now created a more insurance like dynamic to that.

The issue is, once you take on that insurance metaphor so literally, you start getting treated like an insurance policy. In other words, people view you as a cost, not a return enhancer. And that's a that's a grave mistake in my view of convexity, which can convexity, you know, simply put should be a return enhancer, a variance reducer, a volatility reducer, but also a geometric return compounded. It should be actually a tailwind to compounded returns.

Stefan Wagner 00:21:58  The challenge I often see is that, you know, the investors who hold these portfolios, they often hold portfolios that have done quite well, performed well. How do you and you sort of convince them then they have to sell something, or how do they overlay that additional piece that you bring in a sense, for risk mitigation?

00:22:17  Yes. And you you recently had Corey Hoffman did a great job. And, you know, we speak from the same gospel here. Don't make room. Don't make room for convexity. Add it to what you have.

Stefan Wagner 00:22:28  You mean the return stacking approach?

Patrick Kazley 00:22:30  Return stacking. But even more so. a portable alpha, mindset where, you know, portable alpha at its core is taking a given return stream and using it to a desired beta. Well, it's beta one zero. well, if you look at a long volatility return, it's a negative beta. So you should actually be adding more equity risk and adding. So if you have a portfolio today that is a certain amount exposed to the equity market and you add convexity and you want to perform higher than you did before, you should also add more equity risk. So we build portfolios at one river that pursue right and left tail at the same time. That's the insight. So going back to the what we call the long vol premium, if there is a premium to, you know, basically decomposing a long volatility return stream into a negative beta and a positive alpha will then extract that positive alpha by effectively beta neutralizing the benign market. So if there's a you call it a bleed, you call whatever you want negative theta.

You can neutralize that through positive equity beta. And the good news is when a world falls apart and equities contract, you get more expansion from your convex things. And that's how you unlock outperformance. So don't make room for it. In fact, using the F1 car metaphor, if convexity is a systematic set of brakes, you should drive faster because you have better brakes.

Stefan Wagner 00:23:54  Okay, I'm a petrol head, so I have to think about this for a minute, but I think I know what you mean with that. Yes. Okay. One thing I think I would like to talk about a little bit with you is sort of the difference how you, as an organisation at one River versus what your responsibility or fiduciary responsibility is versus other people. Maybe just provide a rule based, Index for a better world, but then obviously potentially even make some money around it because they're trading at better levels and or than what was in the rulebook. sort of what fundamentally changes when the person designing the strategy also owes a fiduciary duty to the end investor?

Patrick Kazley 00:24:39  Yeah. I think there's multiple parts. That question like part one was the rule book that I think is worth pausing on.

Alpha cannot exist in a rulebook. As a matter of course. You know, you cannot extract Alpha from the market through a rulebook based approach, because if there's genuine alpha in the model construction, then that rulebook becomes a playbook for alpha extractors. The market is far too competitive to really publish down to the signal level what you're doing and expect to generate alpha. But that doesn't mean that you can't extract a risk premium like a risk premium are not alpha in the true sense. Alpha is genuine. underappreciated on, you know, exploitation of inefficiencies and commodities.

Stefan Wagner 00:25:22  It's very regular that you can do that. Yeah.

Patrick Kazley 00:25:25  So at risk premium you're getting paid to bear a risk that is in some way undesirable in certain environments. Right. So you extract a premium for that. You could have rules for that. That's fine. I mean, and going back to my alma mater, AQR, that's the crux of that business is, is you you take on smart risks in a diversified way. Those risks have known not failure points but but tough periods. But those tough periods occur at different times. And that's the nature of diversification, right. and you don't try to engineer out the tough periods. You accept that they must exist and you diversify away from bad portfolio level periods. so that that's at the core of, I think, what it means to be a quant. So when it comes to a shift engines and extracting risk premium, I think it's an extremely effective tool. and you can publish a rule book. You can run that at Hyams because there's somebody on the other side of that trade. More or less all the time. That's why it's a risk premium. now, the moment when that stops being true is when you try to step into something that's truly alpha oriented, where you're trying to extract an inefficiency that if the world knew about it, would go away. So what brings in this fiduciary non fiduciary lens is that if you are a fiduciary running a strategy for LPs in your own capital, you are overly incentivized to keep the type of IP that is true alpha to yourself.

 Whereas a bank or let's call it any non fiduciary organization where transparency may be the reason you receive the mandate, there's no such incentive. And so by definition, you're not going to generate real alpha through a rule book approach. And and real alpha and risk premia are can be equally useful to a portfolio over time. But I think allocators should diagnose when something is truly inefficient and alpha, and when something is, say, a tried and true extraction of a risk premium.

Stefan Wagner 00:27:28  Okay. and the trading revenues has come from management fees. if you would separate that versus the trading revenues, do you think that would fix part of that problem, the issue?

Patrick Kazley 00:27:40  The the of course, what you're referring to is that a lot of non fiduciary, organizations also have or the reason that they're offering asset management services is that they can monetize that in multiple ways. They can charge, a management fee that doesn't need to be as high as a quant hedge fund. but they can also extract meaningful trading revenues through bid offer and other kind of, let's say,

Stefan Wagner 00:28:03  Stock lending, anything.

Patrick Kazley 00:28:05  Yeah. Slightly more obfuscated means. and and so the total fee load may even be quite higher to the end allocator than it would be through, say, a fiduciary angle.

Stefan Wagner 00:28:15  I think you you had a really nice analogy here that you compare an explicit hedge. To a goalie.

Patrick Kazley 00:28:25  Sure. you know, if you're trying to evaluate how useful a goalie is. And you ask them how many goals they scored, then you don't understand the game. Right. Because it's not the objective of a goalie to score a goal with. The objective ability to stop goals being scored. and of course, it's also the defense's responsibility. So the issue in finance is that when you're fielding a soccer team, you have this visual obviousness of the usefulness of a defense and a goalie because they're standing at that part of the field and you don't want the ball to go into your own goal. In finance, it becomes a little bit less obvious over time, especially when you have periods of, let's say, three years in a row of 20% equity returns.

The defensive players on the field of your portfolio start to look pretty useless. relative to all of the gold generation going on the other side of the field.

Stefan Wagner 00:29:12  If the ball is always in the other side of the field and the goal is not really needed.

Patrick Kazley 00:29:16  Yes, of course, in soccer you would never say to a goalie, hey, listen, you haven't saved a goal in three games. Can you start practicing taking shots on goal? It seems absurd, but in finance you see this all the time where people will will take, let's say, trend following or a long volatility mandate and they'll try to make it more pro cyclical to compete with the offensive line items. Not offensive in terms of being offended, but offensive, like trying to score goals. and that ends up defeating. And then of course, what happens is the defense is needed and the line items have been corrupted, through some sort of importation of the problem into the solution, you know, and that's we see that time and time again, we call it hedging fatigue. Call it whatever you'd like. But, markets are very good at squeezing out investors out of basically firing their defense and hiring a bunch of strikers right at the time when the defenders are needed most. And then what happens is when you allow many more goals than you otherwise should or needed to.

Stefan Wagner 00:30:19  Yeah. I mean, I think that's sort of what comes to the point that I think you said, you know, negative carry does not mean negative long term compounding, but that sort of is like that's why investors do not why why are we investors so much fixated on the frequency of returns. And they often miss the magnitude. And how much skew is there actually. You know, they would they would fire the goalie and basically hire only strikers. But then you get kicked out of the competition because you lose the first three games because you took one in. Yeah. No.

Patrick Kazley 00:30:51  Negative carry negative return thing I think is, important to pause on because it's one of the, I'd say, the least understood aspects of risk mitigation.

 Negative theta or negative carry is just the observation that certain return streams will generate a negative returns if nothing happens, that doesn't mean that they lose money over time. It's a very distinct thing and you can use whatever metaphor you want. We could stick with the same one. You're going to be paying the salaries of defenders. Even if the ball was on the other side of the field the whole time. You did not waste ex-ante. You did not waste money on those defenders, quite obviously. And the same is true of your long volatility portfolio. If it helps you over the long run compound, the best evaluation criteria is the simplest. Does my portfolio perform better or worse without this thing in there? And that should be the evaluation criteria for everything you add.

Stefan Wagner 00:31:47  I've seen now in the market huge amount of overwriting funds. You know, these overwriting funds or now you see it also in the ETF market that bringing out these auto calls where they're all these funds selling the data. Has this brought down maybe the cost of insurance or insurance.

 But hedging things like has this helped in any formal shape for you guys, or changed the way how you approach things? Because I feel the flow is very much from that side is purely selling volatility. And obviously if the sell calls, I can put it to put called put parity or just, you know, all these banks who are buying all these, auto call labels or the dawn inside knock ins. For me, it feels like when I look at their panels these days when they're reporting, they're doing really well. So it seems to be worthwhile these days, maybe being long with that kind of risk.

Patrick Kazley 00:32:38  Yeah, it absolutely helps us. We as a firm did fantastically well in Q1 of 2018 because 2017 happened, 2017 was benign year, one of the most benign years in financial market history. Right? Mark was up every month. I implied volatilities for single digits. and realized vol was even below that. So, that created, a plethora of managers and exposures that wanted to continue monetizing that.

And then February 2018 happened and, there was so much levered exposure in short vol that it made long ball compensation way outsized. And so we made back, you know, 5 or 6 years of what you would call bleed in in a week. and that's, that's kind of it's not a necessary precondition for us for what we do to work. Right. There can just be an exogenous economic shock. but there are nice little bonuses along the journey of long ball, where market microstructure really just gets over invested in, in this idea of benign markets.

Stefan Wagner 00:33:38  You touched a little bit on something that you made back all your money basically in the in the weeks time. how do you sort of structure your business? Because it feels like you have to be faster and faster and actually capturing these returns before the market things again. That's benign. You know, if you look at how wall spikes now last, they become very short when implied volatility goes up. And you want to lock in that revenue that you might have made through this one.

Stefan Wagner 00:34:03  How do you approach this?

Patrick Kazley 00:34:07  Yeah, well, this is where a bit of the alpha comes in. a rolling put strategy may do really well and may do that really poorly. It may not may not monetize.

Stefan Wagner 00:34:15  It's very path dependent as well.

Patrick Kazley 00:34:18  Yeah. But there are meaningful ways to reduce that path dependency. And that's a big part of I think, what a skilled manager should do. we call it the Convexity Rebalancing Act, which is this notion of when you are owning something, an inventory of divergent or explicitly defensive exposures and they go up in value. What do you do now? you know, and, back to the old car metaphor. You know, the worst thing to do is look at the last three events and over index to that. So we've had three V shapes in a row. The US banking crisis that wasn't in March 23rd, the August 24th Yun Carey trade and and the April 10th tariff tantrum of 2025 and you could you could open index to that and just take money.

 The moment ball pops. I think that's actually a wonderful pre-condition for the opposite to happen, where you get this massive, reflexive follow through of uncertainty. and you get this massive wave of disappointment from your defense because you took profit way too early. So in Covid, you know, we managed to stay in that trade, but also in April, we managed to do quite well because one's a V shape and one was was very different in its orientation and speed. Doing well across both of those require some skill, but I would say high level without sharing secret sauce. Our approach is having a reflexive engine meaning something that leans into a crisis as it gets worse. But just like you hedge your portfolio, you should hedge the gains that you've accrued through other forms of non-linearity. And that's that's really where we can. On the morning of April 9th, we can be agnostic to a capitulation or that getting much worse, April 9th being the, the, the policy capitulation that sent the market 12% upside intraday reversal.

So you know there's mechanisms to do that right. You can be long gamma without necessarily being short in the market. and we do that as a firm. But ultimately that's that's that's the alpha. You know I'd say the the beta of long vol is just buying a put, you know, the alpha is going to be getting out before the crisis is over.

Stefan Wagner 00:36:18  Correct. Exactly. First responders and second responders diversifies. If I'm an allocator, how should I actually size the three sleeves? And when do diverse fires start to defeat the purpose? You know, when do I over diversify? You know, it was all singing and dancing. What do you call it? The jack of all trade. It's not going to happen.

Patrick Kazley 00:36:38  Right? and this goes back to earlier question about, the perfect hedge. So, generally speaking, what we call the first responder is something that I call the fast twitch muscle, the portfolio. It's something that can provide value as markets are breaking down in real time. So this is your long volatility your tail hedge type of exposure… the more reliable something is in the immediate time frame, the less reliable it becomes. If the nature of that decline is protracted. And that's where second responders come in. So this is your your multi-asset trend following type portfolios. The beautiful thing about trend is that the rules of that strategy make it such that you tend to be on the right side of protracted drawdowns. That's that's definitely true. but the downside of trend is that you can get caught with your skis uphill when the avalanche falls. and, and if your positioning is wrong, nothing else matters. so it may be unsurprising with that setup that first and second responders are really good complements, a long volatility and trend. That is the crux of our business. and of course, you can try to sweeten the pot further by adding in diverse fires. and this is where most people get into trouble. and if I get into trouble, I mean that, once you start adding in orthogonal, diverse fires, there's an overwhelming tendency to focus on negatively skewed high compensation, high Sharpe ratio strategies… and so I would say we tread carefully here. We do this as a firm. But when we do it, we do it in a way that is has an explicitly defensive tilt. Or if there is any sort of negative skew, it's capped. For instance, don't just go along dispersion, which is really a short correlation of trade cap, your short leg, which is the. So, you know, in a crisis you're mechanically long convexity. Because the worst thing that can happen to a hedging portfolio with diverse fires is that the diversification like that was designed to increase returns and smooth out the ride ends up working against convexity. What your portfolio needs is the goalie and the defenders, and all of these other accoutrement are there to make that journey more robust and better feeling. But if you add in, you know, I said, import the problem into the solution, then what happens is that the portfolio is actually no better off.

Stefan Wagner 00:38:51  No, I mean, had to smile when you said at this point your skis downhill when the avalanche come. Number one rule when you're off piste skiing. Point them in the direction of safety. I've been peppering you with questions. Do you have a question for me?

Patrick Kazley 00:39:06  Yeah. I guess. you obviously have a pretty busy day job. Why? Why spend so much time, effort and attention? interviewing people? What's the, I guess, what's the intellectual benefit? And, what's the what's I guess the number one thing. You walk away being better at your job because you do this.

Stefan Wagner 00:39:28  Yeah. I mean, there's two things. One is, for me, I believe constant education is very important. You know, I read quite a bit, but I have found that actually talking to people get stuck with me. I learn much more. and I always liked, giving, passing on that knowledge. It's just not for me in the sense if I can share that with somebody, then that's a great result. and historically, you know, I always liked the concept of radio. So that's why we ended up with podcasts.

And I've done this now for such a long time. If I can help a little bit, passing on some awesome knowledge by asking the questions, that makes me happy, I don't know. It gives me quite a bit of satisfaction as well, not only for myself learning something, but also passing some of that, sharing that knowledge. And that makes me smile, you know, puts the spring in my step basically.

Patrick Kazley 00:40:24  Great.

Stefan Wagner 00:40:25  A little bit back to you. I mean, you must get a lot of information that you need to digest every day. How do you sort of organize your information diet.

Patrick Kazley 00:40:33  That's a I, I use quite a bit as a quant. I use a lot of systematic filters. which should not be too surprising. but I'd say, most importantly, just like in finance, principles, how do you come into information consumption? What's your objective? And I always have very simple objectives. I'm either doing something that's going to make me better at what I want to be the best at, or it's immensely interesting to me.

 And if it meets neither of those criteria, I don't consume the information, you know. And that means that a lot of, say, qualitative macro commentary, I just don't end up reading. It may be interesting, but it's not immensely interesting to me. And it's I don't think it's gonna make me better at what I do. Conversely, there can be a lot of white papers on option extraction of certain inefficiencies on the ball surface that I spend a lot of time on. And so that helps me be disciplined. And I also, I've completely unsubscribed from the social media trap, which I think is a poison. Of course, the amount of time that that people spend, you know, doom scrolling or whatever. If you replace that with productive life activities, you know, even if you're just staring at the ocean or spending time with your family, it's way better way to live.

Stefan Wagner 00:41:42  Where I couldn't agree more. Is there a favorite finance book of yours and why?

Patrick Kazley 00:41:49  I have to go to the Intelligent Investor for my favorite finance book. People say it's antiquated, and I think that it's more relevant today than it's ever been in markets. but in terms of, I would say that I learned the most about finance through non-financial books like Marcus Aurelius Meditations. I read a lot of the antiquities. I grew up studying Latin, so I'm a big believer in the the timeless lessons that people wrote about 3000 years ago. There's a certain level of truth that amazingly rings true today.

Stefan Wagner 00:42:17  Now, if people have liked what they have heard today, what's the best way of getting in contact with you?

Patrick Kazley 00:42:22  We have a website. you can definitely reach out through there. There's a contact tab. I'm also on on LinkedIn, as I mentioned before. Ultimately, we serve as institutional investors primarily. And so, you know, I do these things for for educational purposes and, certainly not a retail or high net worth product.

Stefan Wagner 00:42:40  Fully understood. Patrick. Thank you. Thank you very much.

Patrick Kazley 00:42:43  Thank you. Appreciate it.