Jon Havice, Founder and CIO, DGV Solutions

[00:00:00] Events come out of nowhere, the pandemic, right? COVID sort of popped up in February of 2020 and you have a big market move in a very short period of time and that volatility risk premium can invert. The good thing is, is if you're good at risk managing short option portfolios, you stay in the game and you say, oh, yep, the hurricane hit. I took a hit today. But what always happens on the backside of the hurricane is premiums expand. And in our world, that means, you know, the VIX goes from trading at 15 to trading 80.

[00:00:28] And if you're there to rate premiums in the wake of the hurricane, you make that up over time. Hello, this is Dean Curnutt and welcome to the Alpha Exchange, where we explore topics in financial markets associated with managing risk, generating return, and the deployment of capital in the alternative investment industry.

[00:00:54] My guest today on the Alpha Exchange is Jon Havice. He is the founder and CIO of DGV Solutions, a firm managing money on behalf of institutional investors, many of which are endowments and foundations. Jon, it's a pleasure to welcome you back to the podcast. Dean, it's great to be back. Just check my notes here. You appeared in December of 2019. Wow.

[00:01:18] A lifetime ago in markets and the world. We've kept in touch plenty along the way. So it's going to be excellent to explore some of your current thinking and what DGV is doing in terms of managing risk on behalf of clients and seeking to generate uncorrelated returns. Tell us just a little bit about DGV. You founded it in 2014 after a long tenure in the derivative space. Just give us a little bit of background on the firm.

[00:01:46] Yeah. So I founded DGV in 2014. What I had done for the few years prior to that, I was the chief investment officer of a consulting firm that has now been rolled up into commercial or global consulting.

[00:01:59] And I think one of the learnings that I had there, having spent the first 10 years of my career on Wall Street, trading derivatives and currencies, commodities, short-term rates, and then 12 years running hedge funds, and then taking this role as a consultant where we advise healthcare systems, endowments, foundations, retirement plans, etc.

[00:02:23] Taking this more holistic view of how do you allocate capital, asset allocation, and some of the levers you have to pull on that. Most of these institutional portfolios are very sophisticated now. They use hedge funds and private capital programs, etc. And I thought there were some things that maybe the market wasn't serving as well as what maybe I could do.

[00:02:46] And so that was the founding of DGV is, you know, could we offer liquid, attractive investment exposures that maybe look like hedge funds? But if you implemented those systematically, you didn't need big teams of people. You didn't need 1,200 people to do them. In this business, if you have low headcount, you can offer your products at a very reasonable price. And we've been true to that mantra since day one.

[00:03:11] You spent a number of years at O'Connor, famous shop for impounding DNA in terms of derivatives into folks that were a part of that firm. And you spent time in the 90s in FX vol markets, which were wild relative to what they are now. You had the ERM, you had Thai bot, the tequila crisis in 94, just event after event. Just tell us a little bit about that period. It was great.

[00:03:39] A great firm to learn from. So many mentors at O'Connor that are some still in the market, some have retired. Some are at some of the highest seats on Wall Street today. And in the Endowment and Foundation universe as well. And so incredible learning platform. I started as a floor trader in Philadelphia, trading currency options. And then I moved to Chicago and traded on the Chicago Mercantile Exchange.

[00:04:06] In 1994, O'Connor was acquired by Swiss Bank Corporation. And it was sort of a reverse takeover of Swiss Bank's trading operations. The O'Connor people spread out all over the globe. I ended up going to London and trading currency derivatives there. And then over that time, the O'Connor people ultimately took over the precious metals book at Swiss Bank. I took over the commodities business. Swiss Bank and UBS merged in 1998. And in more recent years, Credit Suisse was folded into the mix.

[00:04:36] So we've gone from three giant Swiss banks 35 years ago to just one remaining. And it's UBS today. But yeah, in the currency markets, it's the ultimate macro trade. It's where interest rates, FX obviously collides, all global capital flows and comes through that. But it's the closest thing to a continuous market.

[00:04:59] That market opens up New York time at about 4 p.m. New York time when New Zealand opens up on Sunday evenings. And it doesn't close until 5 p.m. New York time on Fridays. And so none of this 9.30 a.m. opening bell, 4 p.m. closing bell. It just runs around the world. So a great continuous market. And for the most part, it's operated really well over time. I mean, there have been times when pegs got involved.

[00:05:28] The currency crisis, the ERM or the convergence of the euro and things, the British pound. And sometimes those break and you have sort of a, I don't want to say jump to default, but you have a nonlinear move in currencies. But for the most part, they're pretty orderly in the way they move. You can focus on derivative risks and Greek risks and less about, oh, there's going to be some corporate action. There's going to be a cash takeover and things like that. So, yeah, that's how I spent the first decade of my career. It was great fun.

[00:05:56] I had Ken Rogoff on the podcast a number of months ago, former chief economist at the IMF, and had written a book called Our Dollar, Your Problem. And he was running through a lot of his experience as a policymaker during some of these, call them crisis or asymmetric events in FX. And you really just don't see them all that often these days relative to your time in the markets in the 90s. I mean, maybe the last one feels like when the Swiss walked away from their euro peg.

[00:06:26] I want to say that's early 2015. That was a gigantic one-day move. But is there just something different these days? You know, currency vol is just generally very low across most crosses these days. What do you make of the structure of markets? Is it permanently less volatile? How do you see that? I'm always reluctant to say permanent, right? Yeah. Never say never, right? Because we always find a new way to screw things up.

[00:06:51] But the kind of the original crisis, maybe not the original, was in Asia in the late 90s, right? But you had a lot of these pegs. You had a lot of countries, Thailand, Malaysia, that didn't have a lot of FX reserves and burned through them very quickly. And a lot of that's changed. One, those economies have really liberalized. And they've built up great export programs. And so they have a lot of foreign currency to defend their currencies if necessary. And they've come into the global order along with China.

[00:07:19] They live in that sphere of influence and satellite states to China. So I think that's been one thing that's changed a lot. The euro coming in, you took, now you've added more, but, you know, 20-odd currencies. So some of the peripheral troublemakers over the years, the Italian lira, the Spanish peseta, those don't exist anymore. And the longer it stays together, you know, that came in Jan 1st of 1999. So here we are 27-odd years later.

[00:07:48] There's just room for trouble. There's no going back to the Italian lira. I don't think. I mean, could you move down that way? But I don't think it would be to anybody's benefit. So there's just fewer opportunities for real trouble. Now there's the Mexican peso, the Brazilian real, the Argentinian peso. They still have their issues. There's a lot of inflation in the South American economies and things. But in terms of the majors, yeah, they're pretty stable. Here's a fun fact.

[00:08:17] In January 1st of 1999, when the euro was incepted, it came in at about 118.50 was where the exchange rate was. And so here we are, as I look at my Bloomberg screen, 115.30 is the euro today. So you're about three cents different in 27 years. Now there's been some moves around that central rate, but it's pretty amazing. You know, if you look over a long period of time, how stable those two currency blocks have been.

[00:08:42] Well, we're going to talk a lot about your process and your products, one of which is FXRV. So we'll talk about some of those currency trades on a relative value sense. Before we do that, I want to just go back a little bit to DGV's client base. And we talked about managing money on behalf of institutions, some of which are endowments, foundations. These are a very particular set of asset allocators. They are trying to solve a problem.

[00:09:12] They have objectives that they need to meet, whether it's budgeting objectives, retirement objectives. I'd love for you to just take us inside that a little bit more in terms of how you think about delivering to the end client and the unique set of objectives that they are trying to solve for. This was something I learned a lot at the consulting firm. So the 12 years prior to taking on this role at the consulting firm, I was managing a 2-in-20 hedge fund vehicle.

[00:09:41] And you sort of live by the law of the jungle. And then you take all those learnings from the macro trading. I learned trading FX and precious metals and then kind of the bottoms-up work you do trading convertible bonds and equities and credit and things at the hedge fund. And then you move into this consulting world and you're trying to guide these institutions that have really strong societal missions. It's providing higher education in your community.

[00:10:10] It's providing health care in your community. In the foundation world, it's what is your philanthropic goal? And some of those are poverty or health care or climate or whatever it is. But they have really strong societal benefits. And so your hat changes. Your perspective changes a little bit. And you think about what is the perfect portfolio for them to achieve those goals.

[00:10:36] So the simple math is charitable foundations in this country, they have to spend 5% of their corporates every year. And you think, like, if I want to deliver on my mission in perpetuity, well, I got to make that 5%. But I also want to be inflation, CPI. And then, you know, usually there might be 50 basis points of running costs or administrative costs. So I don't know. If inflation is 2%, you're talking about 5 plus 2 plus 50 basis points. And you got to get the 7.5%.

[00:11:05] And while you're doing that, the stability preference. You might make a grant to an organization that's, I don't know, providing homeless shelters or something like that. And you say, we're going to support that organization for the next 5 years. We're going to give you $10 million a year for the next 5 years. The last thing you want to do is have this portfolio that lurches around where you say,

[00:11:29] oh, you know, one year we make hay and we're up 30% and the next year we lose 30% so that you have to go back to the homeless shelter and say, well, we kind of had a bad year in the portfolio. And therefore, that $10 million that you thought you were going to get, we got to trim that to eight. Those are conversations you don't want to have. So thinking about, again, that perpetuity goal and the stability preference of managing those portfolios. But they do have a return need.

[00:11:55] I mean, making high single digits with some consistency in a world where a lot of the last 20 years interest rates were zero was not an easy task. Actually, as you mentioned that. So go back again to the founding of DGV. You've got the 2-2-2 economy, 2% GDP, 2% rates, 2% inflation. And today's markets look or economic backdrop looks nothing like that.

[00:12:20] How does the investment philosophy change and adapt, given that the mission that you're trying to support for your clients, as you said, is really about stability? It's certainly trying to generate returns above CPI, but I certainly sense a real aversion to large drawdowns, really trying to protect those tails. How does the set of objectives for you change in an environment where inflation is less stable, it's much higher?

[00:12:50] It's just very different on the economic and macro backdrop. So the first thing that we did, the first strategy that we chose to offer was a collateralized put right on the S&P 500. And people will ask, like, what the heck is that? Not option denizens. And the S&P 500 has been this incredible benchmark for a long period of time. It's the 500 biggest, best-run companies in the world's biggest economy.

[00:13:18] It's done, call it 10% returns for the last 30, 40 years. So that's very attractive. One of the things you spend an inordinate amount of time doing in that consulting chair is portfolio optimization. And you're going to do some mean variance optimization or something like that. And you're saying the three inputs that go into that are, you know, what is the return estimate? What is the volatility estimate or your risk? And what is the correlation with the other things in your portfolio?

[00:13:47] If you take a list of 30 different potential investments and you say, what is the highest return? Well, like the S&P has been just a gorilla of a benchmark to beat. And I think we all understand why that is. But if you can say with a high degree of confidence, here's an investment that I can make S&P returns, but it comes with a third less risk.

[00:14:11] And that's kind of if there's a proxy that the SIBO, the options exchange in Chicago, came up with called the SIBO Put Right Index. And it goes back to 1986. And if you look from 1986 to 2016, the SIBO Put Right Index actually outperformed the S&P 500 on an outright annualized return basis. But it did it with about 35% less volatility.

[00:14:36] So, again, if you're sitting in that consultant chair and you say, the model will tell you to allocate capital to that because you've got a really high returning asset that's got a lower volatility than just passively allocating to the S&P 500. And so that was where we started. And the SIBO Index was a pretty rudimentary index. It traded once a month, 12 times a year. And if you're savvy with options, we figured we could beat that. And that's been the case.

[00:15:01] We guided investors that we could do zero to 4% over that index over time. And our returns have been in that. So that's really where we started. But the return profile of a Put Right is defensive. It runs at about a 0.65 beta. You can do it different ways, but the way we do it runs at about a 0.65 beta to the S&P 500. So when the S&P 500 is ramping like it's done here the past few years, you know, annualizing at 20 odd percent or something like that, we might trail.

[00:15:31] We might be up 17 or 18. But the reverse is also true. The premiums that you collect by selling those options, hopefully if the market's down 30%, you might be down 10 or 15 or something like that. And that's a tradeoff that most institutions are willing to make is say, hey, match that S&P 500 or add a little bit of value to the S&P 500. And if you do it with a third less risk, that's a good investment. Let's sort of step back and think about that.

[00:15:58] So you've got a methodology for accessing beta. So market beta, the S&P, as you say, it's a beast of a benchmark. So it's a great place to start. You're overlaying this vol risk premium, which is something that can be dangerous if not done properly. So maybe we can talk a little bit about that.

[00:16:17] But the market efficiency person in me says, how is it possible that something so transparent, you say the SIBO is publishing it, can consistently deliver a similar return as the S&P, but with consistently less risk? Why is that something folks haven't picked up on enough? Is it just the fear of the tail outcome and risk transfer, getting paid for risk transfer? How do you size that out performance up? Yeah.

[00:16:46] So I'll start high level and then maybe simplify, right? So there's what we call the volatility risk premium. It basically says people and investors will overpay for this asymmetric return or put it on the downside term, people will overpay for insurance. This is just kind of a feature of any insurance market that you go in. And so if you want to buy homeowners insurance and you say my house is, you know, the average American house is worth about $500,000.

[00:17:14] And you go to a state farm and you say, I want to insure against fire and wind and flood and all those things. And they do the actuarial work and they say, well, you know, there's probably a one in a hundred chance that your house suffers this catastrophic peril in any given year. And so you would say the actuarial would say, well, your insurance policy should cost $5,000 a year. Well, if they offer it to you at that price, they're going to break even over time and they're going to have to write checks once every hundred years.

[00:17:43] But they have a pool of houses that they and homeowners risk that they insure. So they're going to say, well, we can't offer it to you at $5,000 a year, but maybe we can offer it to you at $7,500 a year. And that premium is sort of that insurance risk premium where they have shareholders, voters to satisfy. They have claims to process. They have administrative costs and selling and administrative general costs and things like that. Same thing exists in the options market.

[00:18:08] Nobody wakes up in the morning and says, gosh, I really want to sell crash protection on the S&P 500. Nobody would do that. Just as you wouldn't wake up and say, I want to sell fire protection on somebody's home. Will, however, at the right price say, I will do that and I can diversify it and I can risk manage that. And that's the case in the S&P 500. So there's an incredible amount of academic literature that grounds this volatility risk premium. And it can ebb and flow over time.

[00:18:37] And there are times when events come out of nowhere. The pandemic, COVID sort of popped up in February of 2020 and you have a big market move in a very short period of time. And that volatility risk premium can invert. The good thing is, is if you're good at risk managing short option portfolios, you stay in the game and you say, oh, yep, the hurricane hit. I took a hit today. But what always happens on the backside of the hurricane is premiums expand.

[00:19:04] And in our world, that means the VIX goes from trading at 15 to trading 80. And if you're there to write premiums in the wake of the hurricane, you make that up over time. And so that's kind of our core business is that volatility risk premium. And I don't think it's secret anymore. There's all kinds of ETFs that have popped up, you know, YieldMax and things like this. They've got these sort of crazy names. The buy right is probably the most popular option strategy in the world.

[00:19:31] People buy a share of Apple and they sell an out of the money call against it and they collect premium for that. And that's probably the most rudimentary way to do it. But there's a lot of different ways and tricks of the trade in capturing that volatility risk premium. Well, you make the point to actual insurance markets like homeowners and maybe reinsurance. This idea of the post event pricing, the hard market and having an opportunity as the insurance seller to recapture premiums at a higher level.

[00:20:00] And of course, that's critical if you're in the short vol business. And to be able to get to that, you've got to size it right. We're definitely going to explore your process and sort of thinking about sizing. Maybe as part of that, and you and I talked yesterday about 2020, you guys made it through 2020. As a short vol market participant with a gain, again, I think a lot of that speaks to being able to sell at an 80 VIX and recapture stuff that was coming down just as fast as it went up.

[00:20:29] Walk us through 2017. So if you're in the business of collecting risk premium in 2017, boy, you've got to look really hard to find some option premium in a world where I think the VIX closed below 10, 52 times that year. How do you risk manage through such a quiet period, but one in which you're getting so little for bearing that one-sided risk? So 2017 was really interesting. Lowest volatility year in history.

[00:20:57] I think the VIX averaged 10 and a half in 2017. The amazing thing is, is realized volatility came in at like six and a half. Yeah. The spread was still about four vol points. VIX is not quite the right thing, but in terms of tends to trade at premium because the tails, it's like the VIX. What if you use that as a simple comparison and say, hey, the VIX tends to average 20 over time and realize volatility. And the S&P has been 16 over time. There's four vol points there.

[00:21:26] That was the same thing in 2017. Now, as a percentage of sort of the premium you were taking in, we'd say like, really, if 16 is realized and 20 is your implied at the start of that time period, you're like, okay, there's four vol points on a 20. That's 20%. And whereas you say, if we're starting at 10 is implied 20%, you said we should have realized eight. And really, we realized six. So the volatility risk premium was there.

[00:21:54] The options market is like this eye of Sauron that can somehow see into the future, call it the wisdom of crowds, whatever it is. And people will bet on that. And they say, I think there's an event coming up. There's a U.S. election. There's some geopolitical event. There's a payroll number that people are paying attention to.

[00:22:12] And those who think the market is going to have an outside move, they have the ability to go out past that date in the future and buy an option expires and say, I'm going to buy an implied volatility and realize it's going to be higher. That's my bet. And somebody is on the other side of that trade saying the opposite and will risk manage that through. So 2017, again, we're a systematic shop. We hang our hats that the volatility risk premium exists.

[00:22:39] And sometimes it exists when the VIX is at 10. And sometimes it exists when the VIX is at 30. But it's pretty consistent and pretty persistent for all those reasons we talked about. People are wired not to like to write asymmetric profiles. The opposite is true. People like to buy asymmetric profiles. So we all know that lottery tickets people love. So there's the call option side of things.

[00:23:08] A lottery ticket Powerball is, depending on the jackpot size, might theoretically be worth 60 cents. But people consistently pay $2 for the lottery ticket. And the human mind just doesn't wrap around asymmetric profiles very well. I hosted my Macrominds conference a couple months ago. I had Ross Stevens, who founded and run Stone Ridge there. He's a PhD from University of Chicago.

[00:23:32] And while he was there in the early 90s, he was studying the long shot premium in horse racing, which is well documented. But what he found I thought was fascinating, which was not only is there a premium for the long shot, it's overpriced. You pay up for the lottery ticket. He found that over time, you pay even more up for it. In other words, throughout the day. And then the very last race of the day, it goes up a tremendous amount. So it's sort of like the better is there. He's lost all day and it's his last chance.

[00:24:02] And he'll just really pay for the long shot to try to get even. I thought that was super, super interesting. Okay, so we're going to talk about implementation in options. In terms of the portfolio, you're starting with the S&P as a benchmark, but accessing the beta component through options, through the put writing program and monetizing the VRP, the vol risk premium in the process. And you've got a number of other products that sit alongside that.

[00:24:32] So just take us through the philosophy of how the portfolio is constructed. And we'll talk about the products as well. So over time, going back to 2014 founding, we started with this option, collateralized put right fund. And people would come to us and say, gosh, you're really good at this. You can identify which puts to sell that are maybe overvalued and capture that excess premium. It's like a tennis player. Like you can hit a good forehand. Can you hit a good backhand?

[00:25:00] And so they would come to us about tail risk hedging programs and things like that. And then over time, we got approached for other different risk premiums, value, carry, momentum, volatility and other asset classes and things like that. We developed this sort of suite of products in separate accounts or strategies in separate accounts and said, these are good. That volatility risk premium, again, lots of different ways to implement it and capture it.

[00:25:28] And we said, what are the things that investors really want? Investors need that return of the S&P 500 to meet their perpetuity goals of just making somewhere in the high single digits. It comes with less volatility. So it's a more optimal allocation for U.S. large caps where, frankly, adding excess returns is really, really, really hard. And then you say, if those excess returns are really hard and we've seen investors try a lot of different things, right?

[00:25:55] And there's a lot of really clever investment managers out there and strategy. So if you went back to the 80s, even the 90s, private equity was really a novel strategy. You could buy private businesses at five times EBITDA and do some financial engineering, maybe you'd improve management and everything. And some of the greatest firms on Earth, Blackstone, Apollo started in that, KKR started in that realm. Over time, that's changed, right? I mean, there's an incredible amount of capital there.

[00:26:25] And so areas where we think are a little more interesting or maybe a little less covered are squeezing money out of commodity relative value. And just like the volatility risk premium, there's different ways to do it. In 2020, there were people trying to collect the volatility risk premium. And if they structured that trade incorrectly, they no longer exist today or they suffered great losses. So how you capitalize those trades, how you manage them.

[00:26:54] Everybody likes cake. And you say, but the recipe for making that cake and the ingredients you put into that cake really matters in whether you have a good product at the end of the day. That's where we spend almost all our time is lots of people do trend following. Can they do it well? Can they capture that momentum factor in a consistent way? And that's where we are. And you can do those in the futures market, which are easy to capitalize.

[00:27:24] If you look at a gold future, you know, requires like 8% capital against it or crude oil has a higher margin percentage. But they're easy to capitalize and therefore you can use them to port on top of whatever beta exposure you want, even if it's an optimized beta exposure like our put right strategy. And so that's really what we want to do is can we put those together in a diversified sense where we think they work.

[00:27:51] For example, FX, certainly in the developed market FX, momentum doesn't really work. Like mentioned before, the euro is three cents from where it was 27 years ago, right? And we just haven't seen a strategy. And maybe there are people that can do it on shorter time frames that momentum works in FX. But what really works well is carry in FX is a powerful signal and value in FX is a powerful signal. So can we use those where they work and ignore momentum?

[00:28:20] Whereas in the commodity markets, value doesn't really make sense. It's a commodity after all. It's all about supply and demand. But momentum and carry work really well in commodity markets. So we'll focus our efforts there to try to squeeze out excess returns. So in FX, talk about that a little bit more. So carry and value. Give us a little bit of an example of where each of those has worked.

[00:28:46] And what, of course, is always another side as you think about it and understand, of course, there's always pitfalls in a trade. There's always risks. The types of things you're looking for that could potentially derail that construction. So let's start with carry. Tons of money in global fixed income markets, $100 trillion or more, right? And it will look for places where it believes it will be treated best. So U.S. rates are currently high.

[00:29:14] Japanese rates are the lowest in the developed world, you know, alongside with Switzerland. And so pretty rational. No different than, I guess, the Japanese authorities say we're going to hold $1.1 trillion of U.S. treasuries because our money is treated better in the U.S. than it is in Japan, where rates have been artificially suppressed for a long period of time. Makes perfect sense.

[00:29:36] And you just kind of squeeze that return out by holding U.S. dollars or being, you know, short Japanese yen. The challenge with the carry trade is they tend to build up over time. People get in them. They work. They feed the beast. They put more money into it or they leverage them. And lo and behold, something will happen in the world that will cause that leverage to get unwound and that money will flow back from the U.S. back to Japan.

[00:30:05] And therefore, being short yen, long dollars will reverse very suddenly and abruptly. And if you're over leveraged in that trade, you get crushed. This is where the value component really comes into play. So what does value mean in a currency context? The simplest way to think about it is probably the economist has this Big Mac index, right? And they say, what does a Big Mac cost in the U.S.? And compare that to Switzerland and compare that to Tokyo or different regions around the world.

[00:30:33] And today, you know, the yen has weakened dramatically. It's gone from as low as about 78 yen to the dollar to today. It's 158 to the dollar. The economist Big Mac index just came out last week. A Big Mac in the U.S. costs $6.20. In Japan, it costs $3. You would say, wow, Japan is really cheap. And anecdotally, you've probably had friends that have groused about the cost of ski lift tickets in the U.S.

[00:31:01] They say, oh, I wanted to take my kids and go to spring break in Colorado or something. And I've had multiple people tell me, you know, we actually looked and we can fly to Japan, stay in a beautiful hotel and ski in Japan where lift tickets are $30 a day instead of $250 a day. And so the currency is making this adjustment. And so Japan looks really cheap from a value perspective now. So the question is, do you want to take that on?

[00:31:27] And you have to make that judgment of, hey, I'm picking up the carry factor by being in U.S. Treasuries at 4.5% versus 10-year Japan at 2%, right? But the fair value purchasing power parity of dollar yen is really at 100 and it's trading at 158 today. And so that's what we really want to try to blend and say, which one of those signals is more powerful?

[00:31:55] And for us, that value overlay on currency carry is really designed to keep you out of trouble. So it's kind of like capture that carry as long as you can. But when it gets too far away from fair value, get out of it. You actually want to say, I'm going to overweight that value factor that's going to draw it back. And again, the yen is a great example, right? Because the U.S. Treasury joined the BOJ last week and intervened in dollar yen.

[00:32:23] It got up to about 163 and change. They knocked it down to about 156, 155 on Sunday night. And we'll see. I think there's some ulterior motives there. But we like the Japanese yen because the value factor is really overwhelming. In our analysis, the carry that you'd give up in staying in dollars. But you've got a systematic approach and you're also very macro aware.

[00:32:50] And those can be difficult in some ways to allow each of those to stay closely linked to a systematic approach, not get chopped up by every last macro headline. I'm going back to 2011. I think it's the Japanese nuclear accident. It's the onset, I think, in short order of Abenomics. It was almost the exact opposite of where we are now, right? The yen was, I think, 80, might have been 77. And the whole goal was reflation.

[00:33:19] It was to weaken the yen. And here we are at the other side of things. And policymakers will cry no mas. And in most cases, maybe not Iceland in 2008, they can overwhelm the market. Sometimes you just know they're going to lose like Iceland in 2008. But for the most part, especially if Scott Besson and Japan want the yen to move higher, it's going to work, at least for a period of time.

[00:33:44] How do you stay systematic but also be macro aware and just respect that policymakers can really impose themselves at different points in time? We really want to trust our models, right? We want to stay systematic 100% of the time. There are times when events come up that you can't model. President Carter dies and they decided to close the market one Friday.

[00:34:10] So as a vol seller, that works for you because there's going to be zero volatility on that day that with a week in advance, they decide to close the market for his funeral. And so we really want to stay true to that. But there are times when policymakers intervene and they say they're going to peg a currency like the Swiss franc did in the euro to prevent, you know, the Swiss franc from just becoming even more and more overvalued. And then that ultimately breaks.

[00:34:36] So there are times where you have to override your models and just say, we're just not going to play there. Or we're going to do an overlay to protect ourselves for something discontinuous. But again, I mean, I can in the last 11 years on one hand count the number of times where we've overridden our models. And usually it's I wouldn't even call it overriding. It's just there were things that were unmodelable, the markets closed or something like that. So let's move to commodities.

[00:35:04] And I think commodities are so interesting because they're not financial assets in the same way that stocks and bonds and even FX are linked. Tell us about sources of excess return there and how to put trades together that can generate uncorrelated excess return. So trend momentum works really well in commodity markets. We got a lot of different ways. Some people do short term trends, longer term trends. We're kind of intermediate term trend followers.

[00:35:34] But the basic idea is that things happen. There are droughts. There are floods. There are fires. There are wars, you know, that cause these commodities to trend over long periods of time. And then they can reverse. But that momentum factor is well studied. And then it's just a question of its application. So that's one of the things we like. It carries a really interesting factor in commodity markets.

[00:36:01] So it's very similar to the VIX curve. The VIX curve, the short end, the normal state of the VIX curve, if it was a commodity, we could call it contango, right? And you say, oh, well, spot VIX is at 16. Third month VIX is at 19. We expect it to mean revert over time to 20, right? And so some longer dated VIX contract might be closer to 20. If you're sitting there as somebody who wants to get long volatility and you say, oh, I'm going to buy that third month VIX contract at 19.

[00:36:31] And the status quo just prevails. It's going to go from 19 to 18 to 17 to 16 over the three months when it expires at VIX spot. And you can imagine three points on a $19 investment going the wrong way on you in three months time is really expensive. And so there's that sort of form of VIX carry. The same thing is at play in the commodity markets.

[00:36:56] So you get this normal contango where people say, hey, the price of gold or oil or whatever, generally speaking, is going to be higher in the future. Because if I buy spot, I have to hold it in storage. I've got to pay for insurance. I've got to do all those things. So I'm willing to go out in the future sometime and take delivery in six months or nine months. And there it's higher. So that's the normal contango.

[00:37:22] And if you go out and, again, the status quo prevails and you pay $85 for a barrel of oil six months in the future and it rolls down to 75 spot today, it's a little painful. And that's generally what happens. And then you get these periods of time where more recently here in the Iran war, the curve inverted. And you get this backwardated curve. And so if you buy that third month and it rolls up the curve, the status quo prevails. You've got a carry thing.

[00:37:49] And just over time, that carry program will work. You systematically extract out of it. And so, again, similar to what we do in FX, we don't rely on just that carry signal. We rely on carry plus value in commodities. We really like the carry signal as our most powerful factor, but then we overlay it with momentum. So the idea is, hey, that curve is backwardated in oil. Our models are saying we should be getting long, you know, second month crude and ride it up to the spot price.

[00:38:19] But if it starts to shift and the momentum signal flips, our models will also flip and say we're not going to be long oil anymore. In fact, the momentum might actually overwhelm it and have a short oil on the way down. So that's the basic way. And then we just systematically do that to extract those risk premiums out of the commodity market. So we do that across 37 different instruments. So if we just stay with oil because it's such an important asset just given the Iran conflict. So take us through that period.

[00:38:48] So it's early February. Oil vol is pretty low. I can imagine the curve is in at least a modest contango. It ramps up after we engage, I want to say late February into March. Walk us through what's happening there on a momentum factor in terms of positioning because we ramped up. And then, of course, we've reached an MOU and then oil craters back down to 75 from 110. It's been a pretty wild up and down.

[00:39:18] What does that do for the signal and kind of the positioning around a momentum? They flip around a bit. Now, again, our models tend to be medium term. You know, there are people out there that are doing intraday momentum strategies, which is kind of mind boggling. Right. But ours tend to be medium term. And everybody focuses on oil because it's the most actively traded commodity. But remember, there's gasoline, there's heating oil, there's Brent. So there's this whole energy complex out there. We're fortunate.

[00:39:46] Our models had us long in aggregate the energy complex. I think we were actually short oil, but we were long some of the distillates and things like that that actually perform better. And natural gas had a nice move, right, because you took Cutter offline as one of the biggest natural gas producers. So that whole energy complex, we were long. So we had probably outsized gains when the war kicked off in March. And then things got more volatile and our models are also volatility adjusted.

[00:40:14] So as the underlying components become more volatile, they will get downweighted to try to target volatility. So it was like, yep, we're long the energy complex. We get a nice move. But as we get to our reconstitution, rebalancing dates, it basically shrunk that exposure, even though it kept the long position where you're like, okay, we ride oil from call it $70 a barrel up to $100 a barrel.

[00:40:42] Again, I'm just using that as a proxy for the energy complex. But then you reduce your size by half and it runs back down to 85. Those are the things. And it's, again, it's very much about extracting modest edges out of the marketplace and just being very systematic and consistent about doing that.

[00:41:02] When we talk about the VRP, the vol risk premium, let's just say inequities, we talk about that demand for insurance, that inequality of loss versus gain. The loss hurts more than the gain. Maybe there's a behavioral component. If you were to look at maybe some of the structural drivers of excess return in something like commodities, whether it's a economic or behavioral explanation, what is typically offered there in terms of being able to extract that risk premium?

[00:41:31] In terms of the magnitude of the risk premium? The risk premium exists at all. In FX markets, it's really the interest rate component. You're relying on investors seeking that out and then just saying, hey, if it gets too stretched, it will bring it back into fair value. The yen gets 50% overvalued in time. You would say people will just move money. They'll do leverage buyouts in Japan or whatever.

[00:41:57] I think the same thing exists in commodity markets where that ebb and flow around fair value can be systematically extracted. The curves get too steep. They get too inverted. And you just want to consistently play that. The supply and demand kind of clears in the marketplace and allows for that excess risk premium to be captured. Well, you mentioned adjusting for volatility in crude. It's obviously been an asset that's had some massive moves.

[00:42:27] And sometimes just at the macro level, we have these episodes. We reference 2017 of extremely low vol and then 2020, extremely high vol. Talk to us just about 30,000 feet from a portfolio standpoint, thinking about sizing, thinking about daily value at risk on behalf of your clients. How do you adjust for a regime knowing that whether it's high vol or low vol, it's not going to last forever.

[00:42:55] But especially in the high vol, I can imagine you want to be responsive to these markets are just much different than we're used to. And so we have to trade more carefully through it from a sizing standpoint. Talk to us about that risk management overlay. Yeah. So learnings of 36 years in this business, the one cardinal sin is ever letting anybody take your positions away from you. If that's a margin clerk, if that's a prime broker, if it's your underlying investors, right?

[00:43:24] And you have to say, I have to live in this construct where I always have control of my positions. We saw this happen last week. Big hedge fund that was playing the AI theme got over levered. And his prime broker moved to foreclose on him and he ended up selling his portfolio to Citadel at a discount and suffering a big loss. Cardinal sin. It didn't wipe him out, but he reportedly took a 67% loss. And so what we always want to do, one, I have sort of a natural aversion to leverage.

[00:43:54] And if you don't have any leverage, nobody can take your positions away from you. I mean, your clients can ask to redeem their money, but you can quickly convert in the markets that we trade in. You can quickly convert your positions into cash and return investor money. But we never want a broker, if there's a change in margin or there's a change in regime volatility, we never want them to. So we don't use much leverage. So, for example, in our fund, if a client gives us $100, we put $100 in T-bills.

[00:44:22] We write $100 of notional on the S&P 500, which the margin clerks require about $7 to back those. So you're like, okay, we've got $93 of excess collateral to back those positions. The exchanges are pretty sharp in terms of knowing how much collateral to check. They do it to, what, four nines or something. They want to collateralize trades.

[00:44:44] And then all the overlay trades that we do, our commodity relative value, our FX relative value, our trend, our tail hedging bucket, all that requires about 3% or $3. So we're using, we have about $90 of unencumbered capital of the $100 that investor gave us. So only $10. So that gives you a sense of what the market thinks of our risk.

[00:45:10] But you also have to look at situations where your models are saying, hey, the market's trading down and your model is saying, get longer S&P futures. And the market trades down five days in a row and you're like, holy cow, like I'm longer S&P exposure than I really want to be. The model better be right. We better get some mean reversion relatively soon or it gets really uncomfortable.

[00:45:34] And so what we want to do is stress test historical scenarios and say like, can we stomach it where John is not going to take us out of this trade because this exposure got too big. And that's really what we want to do and just say, yep, we know you can run in this world. We have so much computing power that we can use with artificial intelligence and machine learning. And oftentimes those models will give you a false sense of security.

[00:46:02] It'll say, oh, if you do this, if you leave your maximum position size unconstrained and you look back over the last 20 years, you can add an extra 300 basis points of annualized return. And then you look through it and you're like, oh boy, but there was that one time on March 15th of 2020 where your long S&P exposure was 150% of your fund. I think anybody would look at that and go, well, that's crazy.

[00:46:26] Nobody wants to be 150% long in the middle of March in 2020, no matter what your models are saying. So you've got to say like, we're going to have risk limits here that constrain the exposure for any individual positions or any sector exposure and things like that. So we try to model that up front. And again, we're not particularly risk seeking and we are leverage averse. We use leverage, but it's pretty modest at the end of the day.

[00:46:55] And that's why somebody who has sold options for a living for 36 years, we're still here. And we've seen so many people that are no longer in the business that maybe just weren't as attuned to risk management the way we are.

[00:47:11] Yeah, there's a ton of very smart, sophisticated folks in this business that have wound up being stewards of large pools of capital and have found a way to basically just missize in a way that was catastrophic. I can name 10 of them off the top of my head, starting with LTCM, Howie Hubler, Morgan Stanley during the GFC. Victor Niederhofer just passed away. He's a famous put seller from the 90s, blew up a couple of times.

[00:47:41] What do you think from a stress testing standpoint, are there pitfalls that you would say there's commonality in some of these episodes where people are missing something from a stress testing standpoint? What do you think ties these episodes together? Most of the time it comes back to leverage. If you use your 2017 example, all-time low vol, I think the people piled into the low vol trades.

[00:48:06] XIV was probably one of the most appropriate expressions of that. And people got overexposed to it. And if you're short an instrument at 10, volatility or otherwise, and it goes to 20, you lose 100%. So it doesn't take much to figure that out. But people, I think, just they stick with trades at work. They add to trades at work and then they don't work. They lose it.

[00:48:35] And I think the same thing as put sellers. They say, oh, I want to buy NVIDIA at $200. And how about I just sell my normal position size is $100. So I'll sell $100 of puts at the 200 strike on NVIDIA. And if it trades down, I'll own it. And then they say, oh, boy, this has worked. Like NVIDIA is generally trending up. The times that I get a sign on those puts, it bounces back. And it's all funny when you're making money, right? And then they say, gosh, my normal position size is $100. And this has been working. What if I do $500?

[00:49:05] And then there will be an episode, like we saw in July, where some of these stocks, not NVIDIA, but SK Hynex has a 50% drawdown. And it's like, oh, I'm five times bigger in that trade than what my normal position sizing was. I've taken a bigger loss. I think there's that behavior element of it's like emotional momentum. Add to things that are working and risk limits be damned.

[00:49:31] Well, let's finish off with some of what you see in the here and now. So you've got a very systematic approach. You want to be disciplined and stay true to that systematic approach. But you're also very macro aware and paid to look around corners. What do you see right now? What are some of the areas where you're very focused on whether it's potential vulnerabilities, events that could lead to asymmetries? What does your list look like?

[00:50:00] I think big picture, this artificial intelligence is broadening the spectrum of potential outcomes for both markets and I think for society. Put goalposts on that. In the right tail, you have Elon Musk and Jensen Huang's view of the world. It's like we're going to colonize Mars and we're going to have universal high income and money's not going to matter anymore. It's going to be this utopia.

[00:50:26] And on the left side of it is we're going to have some dystopian unemployment problem. People aren't going to be able to work because machines are going to do all the work and AI is going to displace it. And the reality is probably somewhere in the middle. And I would say human beings over history have had a way of working things out. And so I probably lean towards the right side of the distribution. But it could be really disruptive.

[00:50:47] So I think when you think about how to invest and what will give you the most durable and robust outcomes, diversification is your friend. Not so much in the traditional diversification of like, hey, I'm going to have 60% in stocks and 40% in bonds. And maybe I throw some real assets in there. I think understanding what the underlying drivers of your returns are and then expressing those across different asset classes.

[00:51:15] So for us, we love having exposure to the 500 best run companies or 500 of the best run companies in the world. That S&P beta, that equity risk premium, if you will. And so in our fund, we'd say we've got some of that. We think risk adjusted, accessing that premium through a put right will give you another diversified exposure, the volatility risk premium.

[00:51:41] And those two things tend to be inversely correlated, meaning when stocks are grinding higher, you'll make more money on your beta and less money on your volatility risk premium because vols are low. And then if you get a correction, it's like, oh, I'm going to lose on my beta, but the VIX is going to go from 15 to 35 or 55 or something. And that volatility risk, I'm going to get more and more premium if I just systematically keep doing that. So we think that makes a nice trade off. So that's one allocation.

[00:52:10] And then we say, hey, in our diversifiers, we love this value, momentum, carry factors that we express across where they're most prevalent in FX and commodity markets. And then we love this multi-asset trend. And multi-asset trend, I'm going to circle back to it. But when you think about big risk events in the market or big market drawdowns, they always play out differently.

[00:52:39] In 1987, you have this one-day crash where the market goes down, whatever, 20% in a day. Not terribly different than the 2020 experience. And COVID hits where the S&P 500 went down, I think, 35% in 27 trading days. But very high magnitude, very high velocity.

[00:53:00] That's a very different experience than 2000 to 2002, where the S&P 500 went down 50%, but it took two and a half years to do it. So if your best hedge in the 87 event or your best hedge in the 2020 event was very short-dated, out-of-the-money puts on the S&P 500, they just crushed it, made many, many multiples of the premium you invested.

[00:53:26] If you had done that strategy from 2000 to 2002, most likely that your puts would have went out of the money, expired out of the money. The whole time, you would have lost 50% in your underlying portfolio and paid a bunch of insurance premium along the way that provided no protection for you. So what really works in that slow trending decline is trend following. Your models, hopefully within a month or so, reverse, they get short, and they just ride that trend all the way down.

[00:53:52] We'll add that on top of our put-right strategy, which should do S&P 500 returns. And then last, I think in this current environment, there's real fragility underlying the market. I think there's one at the root of it, I think, is the fact that the U.S. Treasury is short $39 trillion of debt.

[00:54:15] And every time in the past, when you think about 1998, the government didn't intervene off their balance sheet, but they orchestrated the long-term capital bailout, and it was like $5 billion, right? And you fast forward to 2008, and the TARP bailout was $700 billion. You go up a factor of 100 in 10 years. And then you fast forward 12 years to 2020. All the COVID relief programs were like $5 trillion.

[00:54:46] And you're like, holy cow, we just 8X'd the relief program. But the government was always there. The Fed, the rescue team always steps in. They lower rates to zero. They do quantitative easing. Sometimes the Congress steps in and requisitions $700 billion or $5 trillion. In that next 10 years, these crises always seem to come in roughly 10-year increments.

[00:55:09] In 2030, is the next crisis going to require not a $5 trillion bailout, but maybe a $20 trillion bailout? Is the market there when we already have $39 trillion of debt to do that? And I think that's going to be the mother of all. Oh, my God. The buyer of last resort has no clothes, and that's a real problem.

[00:55:38] And I don't think we're there yet. I think you're seeing this play out in the UK more today. But the fact that a G7 economy can be there, like every time they try to do anything like on a fiscal spend, guilt yields explode higher. They're just constrained. And so that puts them in forced austerity. And so that's the underlying thing. And I think there's some other mixes of the rise of passive investing. There's a lot less stock picking where somebody steps in and says, oh, I'm going to buy that thing. It's more student body left, student body right.

[00:56:07] It's like, hey, I own the S&P, sell the S&P. And there's no discrimination. So that's part of it. I think the growth of the pod shop multi-strategy funds where there's sort of this hair trigger risk management. It's like, hey, if your pod goes down 5%, we're cutting your capital in half. If it goes down 10%, sorry, here's a box. Take your things and leave for the day. And that's very sophisticated real-time risk management.

[00:56:33] But if something happens, you see this cascade through where it's like, hey, we're just unwinding these highly levered. Most of those funds are levered six or seven times on 50 to $100 billion of capital. And they say, we're hitting the exit very quickly. And I think that's one of the reasons why you've seen the VIX has become much more reactive. Sometimes you'll see these little events or little headlines.

[00:56:56] The S&P will be down 5% and you'll be like, oh my God, the VIX just went from 17 to 39 on a 5% move in the S&P 500. I think you're seeing these just-in-time risk management, hair trigger risk management, make the market more fragile. And so that's where we put in, we've got five we think of as sort of optimized tail programs that are designed to carry relatively efficiently, but should give us that really asymmetric return.

[00:57:26] So that's how we kind of wrap it all together. Say, okay, if my put right does S&P 500 returns with a third less volatility, I like that. If my diversifiers can add 900 basis points of alpha, and then I'm going to spend, let's just say, target 25 basis points a month in tail hedges.

[00:57:46] So you're like 300 basis points over the course of a year, you're like, okay, my diversifier overlays and my tail edge overlays will get me to sort of a mid single digit alpha production with a real left tail kicker. We think that makes a really robust portfolio that's relying on, again, that diversification benefit in a world where the range of outcomes just seems really wide to me.

[00:58:12] And frankly, I'm not smart enough to know whether we're going to dystopia or utopia or somewhere in between. And we might just careen between the two, you know, on a month to month basis, like we saw, you know, June, July. And, you know, August feels kind of utopian where July felt pretty difficult for risk. And can we just navigate that way, but had a lot of value with, again, in a very risk controlled sense.

[00:58:38] I think our fund runs that even with the overlays that we've put on a third less risk than the S&P 500 and hopefully over time. Well, you mentioned the 100 year storm every 10 years. So I count it as 11. So if you go 87 plus 11 is 98 LTCM. I'll add 11. So the low in the S&P was 2009. I'll add 11 to get to 2020. So instead of 2030, I got it marked at 2031. Yep.

[00:59:08] So that's the biggie. We've got five years to plan, make sure the portfolio is durable. But John, it's been a real pleasure to have you back on my little podcast here. I'm sure the guests are going to really appreciate the insights. And I'll just say, I think the mission driven approach of DGV, I've always just been a big fan of managing capital, protecting capital on behalf of institutions that are in the business of public service is a real fine mission. So congrats on 12 years and keep it going. Thanks, Dean. It's great to be with you.

[00:59:38] You've been listening to the Alpha Exchange. If you've enjoyed the show, please do tell a friend. And before we leave, I wanted to invite you to drop us some feedback. As we aim to utilize these conversations to contribute to the investment community's understanding of risk, your input is valuable and provides direction on where we should focus. Please email us at feedback at alpha exchange podcast.com. Thanks again and catch you next time.