Tim Graf (TG): This is Street Signals, a weekly conversation about markets and macro brought to you by State Street Markets. I'm your host, Tim Graf, head of macro strategy for Europe. Each week, we talk about the latest insights from our award-winning research, as well as the current thinking from our strategists, traders, business leaders, clients, and other experts from financial markets. If you listen to us and like what you're hearing, please subscribe, leave us a good review, get in touch, it all helps us to improve what we offer. With that, here's what's on our minds this week.

David Dredge (DD): And so anybody whose entire perspective is around optimizing to the mean, is going to benefit by adding convexity. And you want to always want to think about adding convexity on both sides. It's not about betting on a blow up, a meltdown, a wildfire. It's about protecting against it and freeing up capital to go and take more participating risk. Being in those back-to-back-to-back 25 percent up years is being in thin-tailed opportunities, right? But to do that, you want to have good brakes. If you're going to go out and explore and test how to make a car go faster, make sure the brakes work first or you're going to run it into the wall at the end of the straightaway.

TG: One of the things I love about the work of this week's guest and how he talks about it is that once you get a glimpse of the point he's making, you never really unsee it. And in fact, you start to see its implications everywhere. And the race car analogy you just heard in that clip is one of those framings of risk taking and portfolio construction that has stuck with me ever since I first read and heard David Dredge express it. It'll probably stick with you now too.

Dave's CIO of Convex Strategies, a Singapore-based hedge fund who specialize in providing long volatility exposure to their clients as part of a broader focus on making asset owner portfolios more resilient to shocks and to better ensure that their compounding return streams stay on a convex upwards path. We go through so much, this is kind of a long episode for what we normally do. But I really encourage a commitment to take it all in because it can have the potential to completely change the way you think about risk, from the mightiest asset owner all the way down to the individual investor.

DD: Hello, Tim.

TG: Hey Dave, how are you?

DD: I'm good, I'm good.

TG: Excellent. Well, thanks so much, Dave. Appreciate you joining this week.

I always like to start with people who are outside my firm, who haven't been on before, just with a little bit of background information, who you are, where you've been, what you're doing.

DD: That's a long story, obviously, for a guy like me. But, you know, I was early to Asia. I came out originally with Bank of America in 1987. Just in time, I got here the first Monday of October 1987, just in time to catch the, what is commonly known as Black Monday in most of the world, the October ‘87 crash, which we call Blacker Tuesday out here. I had graduated from Business School at Berkeley and had taken a job with Bank of America in San Francisco because I didn't want to get further away from home, which is in Salt Lake City. I turned down New York jobs because I wanted to stay close to home. And three months later, they sent me to Singapore.

So, my ability to forecast the future was laid bare fairly early on. And then, you know, sort of that start with the chaos that was the October ‘87 crash.

I studied Financial Mathematics at Berkeley under Mark Rubenstein of the famed Cox-Rubenstein binomial model at the peak of his portfolio insurance business. So I got a good first-hand look at the implications of making assumptions about continuous liquidity that were not true. I studied Economics at Berkeley under Janet Yellen in my grad school days and learned over the years how mythological most of her beliefs were in her economic models and beliefs of the world. And that sort of just started me down this path of trying to figure out what risk was and did a lot of work for Bank of America around their emerging market businesses in the late 80s when they were getting deregulated and opening up.

I legged that into going to work for Banker's Trust and what we constructed is what we called a core risk business with this sort of premise because of the complexity of risk around these actively managed pegged currencies, onshore offshore markets, that any assumptions about historical volatility and correlation and continuous liquidity were pretty stupid. And so we sort of built the premise on the business on this premise of embedding positive convexity while we went out and figured out how to make markets and structure derivatives and underwrite risks and stuff.

And it turns out that was a pretty good idea and did that and then did it again for ABN AMRO later on and then retired to the buy side. And now we sit with our little business here, Convex Strategies, where we just really sit in the same food chain that my Bankers Trust guys and I were innovators of back in the early 90s of this structured product, volatility selling behemoth that now is really global, but for 35 years was an Asia dominated thing, probably still an Asia dominated thing, but increasingly big around the world.

And we work with the derivative structuring banks in that world and help them recycle the long volatility and convexity. And we carry these pools of really super asymmetric, negatively correlating, we call it long volatility, but really long convexity. It's really more sort of third and fourth moment type stuff, skew and vol of vol. And we just manage those throughout endless time horizons to the benefit of our investors, who then free up capital from tying it up in very inefficient traditional diversifying strategies, like bonds, for example, and go out and take more participating risk and get in the game more aggressively.

The analogy that I'm sure you've heard me use before, using the multi-lap Formula One race, very popular here in Singapore just a couple of weekends back. Now, the guy who wins that race is the guy with the best brakes. And he wins the race because, one, he doesn't crash and, two, he can drive faster. And that's our whole concept of convexity, building convexity into people's investment portfolios so that they can accelerate and decelerate and get away from the volatility drag of traditionally concave strategies or sort of sharp ratio optimized strategies where you're foregoing upside, you're just driving slowly as a means of risk managing. You're foregoing upside to probabilistically mitigate downside. Well, we say let's explicitly mitigate downside and go in more aggressively search for opportunities, explore that straight away. What can I get out of it? Where can I overtake the guy knowing I've got brakes and I can respond to unknown future paths of the racetrack?

And so I've been out here for off and on forever, and I've worked in Japan and Hong Kong and Korea. And then I've just been around a long time and love living here and we do this business and try to help as many people as we can improve their compounding path.

TG: So many questions to come out of that. We're going to talk a lot about the portfolio construction aspect of that or the kind of race car analogy you used. Because I think that's, for me, that was the aha moment of understanding your process, was putting it in that very simple analogy that we're going to come back to.

But thinking about your process and actually thinking about aha moments, was Black Monday kind of that moment for you? Or are there other periods in your career where you thought, right, this is the way you manage risk, or this is the way, rather, that you construct a portfolio to make it more resilient, to make it kind of shock-absorbing?

DD: Yeah, so I spent the early years with Bank of America, and no offense to them back then, but the whole system wasn't very sophisticated back then. And they were a big behemoth bank, and they really saw the world through the lens of their US markets activities and the trading business that I was a part of. And they sort of applied a book of standard operating procedures to the entire world, and that book had been written based upon US Treasury markets and US equity markets and Dollar Deutschmark, back in those days. And that book didn't apply very well to emerging markets. And so in the old days, I used to have this real perception that there were inefficient markets and efficient markets. And what I learned in school from Janet Yellen and others applied to efficient markets, it was just these emerging markets that I defined as some sort of impediment to the market determining the equilibrium price of risk. So the currency was pegged. So the market didn't get to decide the price, or there was limited access for participants or limited access to information.

Now, eventually I grew up and realized how naive I was and found out that all markets are that way, particularly once they get regulated. You know, I learned as I went, you could see, particularly in the emerging market activities of Bank of America and others, they were very much caught in this trap of making a little bit of money over a few years and losing a lot when something happened.

They had the massive Turkey at Thanksgiving problem going on and weren't really doing anything about it because they were applying the risk methodology and concept that they used in US Treasuries and US equities and supposedly efficient markets that had much thinner tails. And so because you're in this world that had really fat tails because of the impediment of free market pricing and the impediment of natural volatility, you end up with things that had very significant fat tails that were constantly on the wrong side of them. And so you just saw it over and over again. And then, I guess, my biggest sort of shock into, wait, there's a different way to look at it, was when I met and eventually went to work for the guys at Bankers Trust. And Bankers Trust then was an investment bank during the era of Glass-Steagall. So they were outside the regulatory construct. And even though I was tasked with building a franchise business, my performance objective was a capital allocation because the risk was our responsibility. It wasn't a regulatory accounting practice.

And so you got to see that so clearly. And all of a sudden in that world back in the good old days of Glass-Steagall and pre the investment banks going into BIS regulatory guidelines, there was tacit knowledge, you were accountable for the risk. Your job was to protect and grow capital, whatever your business activity was. And that became a very different mindset. And of course, Bankers Trust was a leader in what then was considered advanced risk methodology, value at risk and derivatives and option models and stuff. And so, there's a very different mindset. And then it was much easier for them to buy into this concept. Hey, let's create these pools of positive convexity and use those then to be much more aggressive in our willingness to go and enter into new markets and create new market, create interest rate swap curves because we've done the first callable note structures in Korean won and we're now long optionality on interest rates. So we're happy to go and start providing a bid offer spread in a swap market that had never existed before.

And so sort of that recognition that these markets were inefficient, that the big problem was, and we could talk about it as much as you want, still is a lack of skin in the game because I say all the time, I give presentations and I'm sure you're probably somewhat aware on risk management all the time. And I always end with the same slide, if I'm giving a risk management presentation, the key to risk management is accountability because you can't model risk, you can't know. The only thing that will make people behave appropriately is skin in the game. And so I just got to see it enough times, and you could see, and this is going back to another Nassim Taleb-ism, so Nassim also got at the start of his career at Bankers Trust, that it's not trying to estimate acts, it's not trying to forecast the market, it's managing your payout function to X. And that's really, I guess, the number one thing I learned in that sort of transition from how do we account for risk in a very regulated structure at Bank of America, to how do we actually manage risk, manage our payout function to risk in a place like Bankers Trust that was a standalone investment banking partnership type structure.

TG: Is there a particular, and I'm not speaking about current positions, of course, but just sort of a practical example of your process. And that kind of typifies that approach that you can give people to just sort of give them the mechanics of kind of how you look at the world and think about risk.

DD: What we're doing now, or, you know, I've done over various parts of my career, you want to own risk in thin-tailed opportunities, right? Where there's natural high volatility, where you're getting rewarded with the upside tail for the downside tail risk that you're taking, and you want to mitigate risk in fat-tailed opportunities.

You want to own optionality and convexity, where there's asymmetric returns in fat tails, which is where suppressed volatility exists. Now, if you think about what I just said, Tim, you know I've just literally said exactly the opposite of the entire regulatory construct of the financial industry, because it tells you that low volatility is low risk, and you can assign very little capital to it, and most importantly, you can lever it without counting the leverage as risk.

So you can say you're super senior tranches of subprime CDOs because they're AAA weighted and you've tranched them just like this, are a zero risk-weighted asset, so they're no risk, and then you can lever them infinitely. Turns out, what is the risk? It's the fat tail created by that leverage. So from an investment perspective, you want to use that as a hedging strategy and be on the protection side of that fat tail, and then you want to go out and participate in things that reward you with thin-tailed natural volatility. And so we advise all of our investors. So again, the strategy that we run is only defensive, but we work with our investors. Everything's working from our investors' perspective.

We're always advocating to them to go out and take a risk that participates in markets. Find those things that are growth, innovation, unbounded moonshot opportunities and participate in them. And then we'll work with you to manage things that are fat, left tail, attract excess leverage. Obviously, specifically what we do, we're volatility supply is creating imbalances in supply and demand dynamics, again, driven by this sort of food chain, generally of regulated entities, because the insurance company that's buying the callable note structure is being allowed to account for it to the call date, as though that's the risk and not account for the short optionality.

And the terminal duration date should interest rates go up.

And the banks, when they're bringing in those Bermudan swaptions, going out and hedging them, their risk is being based upon value at risk and option models and stress scenarios, that also doesn't necessarily account for tail exposures that they'll end up with.

And so if you have enough participants in the food chain that get to recognize the repackaged option premium or the carry or the basis risk involved in edging them as calendar year, compensation year, revenue, but don't have to capitalize significant risk in the tails, almost without failure, get supply and demanded balances. Every Korean pension fund will be doing endless numbers of Korean callable note structures until it drives the volatility of Korean interest rate swaptions to nothing.

And then what we hope is in our work with our counterparties, because we're talking to them every day across whatever volatility supply that they're working with, we're trying to help them recycle that. We're trying to help put it into our books and structures and forms that suit how we're trying to carry through this endless time horizon, the convexity, trying to help them recycle it. And then obviously if they need it back because something happens, then we're happy to work with them, giving it back to them. And we just go through that through time.

So we're very, I guess, the answer to your question. And that's a long-winded answer, sorry, Tim, but we're very bottom-up. So we have no views on underlying markets. We're not bullish, we're not bearish, we're not betting on anything.

We're simply bottom-up value investors in convexity. And we're trying to judge supply and demand dynamics in volatility markets around the world, any asset class anywhere, working with our counter-parties who are the absolute experts in this world and trying to absorb things in the book that have the right levels, the attractive levels of asymmetry. We're always trying to buy insurance that costs the least if we don't need it and pays off the most if we do need it. Pretty simple.

TG: Yeah. And actually, I want to come back to the ‘how’ of that. But before we do that, I wanted to get to something I mentioned a bit ago, which is the notes you write on your website, which is convex-strategies.com for people who are looking into Dave's work. You talk about the improved return streams you get from the addition of long volatility exposure such as what you've just described, kind of trying to get that fat tail exposure.

I'm wondering if as a starting point, you can walk through the broader approach to portfolio construction, kind of like where you guys fit in with the asset owner who is maybe investing with you. You've alluded to bits of it, but then explaining the benefits of that exposure relative to more traditional asset allocation frameworks or particularly things like risk parity.

DD: The fiduciary industry, rightly or wrongly, has adopted what I call Sharpe world financial economic methodology. These assumptions that are know-ably wrong, Benoit Mandelbrot proved them all wrong 50 years ago. Normal Gaussian distributions and linear regressions and arithmetic as opposed to geometric means and ergodic as opposed to non-ergodic path, ignoring time, looking ensemble averages instead of time averages. The simple solution to the flaws in those problems is convexity. So simplifying Sharpe world down to where its nickname comes from, the Sharpe ratio, as I mentioned earlier. The Sharpe ratio is defining risk as volatility, which is obviously nonsense, because it's treating as symmetrical upside volatility and downside volatility.

And so the fundamental risk methodology in the financial industry, so think the simple 60-40 balance portfolio, is to simply reduce the amount of risk you're taking. So you take 40 percent out of the engine and bet that driving at 60 percent speed, you probably won't crash based upon a lap and a half look back of historical curves within 95 percentile confidence levels. And then you'll kind of map to the average lap speed, given this sort of normal lap shape. And so you're always driving too slow in the good parts and barely hanging on, on every curve, hoping that it's not a two-percentile curve relative to what you've seen in a far too short historical path.

And then you take that to the next level, you know, sort of modern portfolio theory and the sort of pinnacle of Sharpe world nonsense, risk parity. And you say, well, let's lever this low correlation benefit across this multiple universe of assets and we'll lever up based on risk. So the lower volatility assets, we'll lever them more to match the risk level of the higher volatility asset, Equity, and then get more of the diversification benefit of low correlation.

But inevitably, what you're doing in all of that is you're creating something that is concave in its correlation relationship to your benchmark, to the market. So you end up, because you're explicitly forgoing upside, the bonds have no upside beyond the coupon. So it's not going to participate in a 30 percent up year in equity markets, but you're only probabilistically reducing downside. You're saying, well, on this historical look back, the correlation has generally been this, on average, has been this way. So what you end up with is something that's always low correlation in good markets, but increasingly higher correlation in bad markets. And that's the concavity. And that leads to what is commonly known as volatility drag.

And so in this compounding path, which is the other thing that everybody is ignoring, because the fiduciary is always working to a calendar year, even though they're managing 40-year liabilities for some poor retiree, and that geometric compounding path, that is absolutely killing you, where the big numbers have a much bigger impact than the numbers near the mean, and the negative numbers have a much bigger impact than the positive numbers. If you lose 50, you've got to make 100 to get back to break even. And so you're constantly rolling around this concave return dynamic, and you're decaying away from the desired compounding path. And the way you turn that around, the way you build convexity is you add highly positively convex, negatively correlating stuff. You free up all the capital that's been burned and tied up into traditional absolute return, sharp ratio, bonds, strategies, and you put more of your capital to work in the things that participate in good markets.

You own some NASDAQ instead of just S&P, you own tech stocks, you own growth, you own Bitcoin. And you go find those things that are thin tailed, and then you construct things that have very explicit negative correlation and really high asymmetry.

Now, we're lucky because the way the world works, everybody's happy to be short of all because the accounting and risk and regulatory methodology encourages it, which allows guys like us to constantly go in and actively participate from the long vol side, incredibly cost-efficiently for the benefit of our investors. And so, over time, it doesn't take a rocket scientist to understand if you had more participating risk in 2019, you had a really good year. And if you had something really efficient to cut off the drawdown in Q1 2020, you didn't lose that compounding path. And then you stayed in the market and participated in the next three quarters of 2020 and participated in 2021, and then had something that cut off the negative compounding in 2022. So you come into 2023, still fully risked up. You're not sitting there listening to the bearish siren song of, oh, there's going to be a recession, and they hiked rates.

You come in and you get that 54 percent up your NASDAQ in 2023. And you're still actively taking risk in 2024. And bada bing! S&P goes up 25 percent two years in a row, and the whole world's crying recession. There is the whole world's moaning and groaning about geopolitics and blah, blah, blah. And then boom, 2025, guess what happens? You know, it's another up year. Gold goes up 60 percent. Bang, you're in it.

And so it's just this constant mindset of stop listening to the bearish siren song. And here's the best way to explain it, Tim. Stop trying to predict the future unknown shape of the race course and manage what you can control, the resiliency of your car. Put good brakes on your car and go out and explore how to drive it faster. Can you get more aerodynamic? Can you get a bigger engine? Can you get better steering? Can you get better transmission? But all of those things as you're exploring that. First thing you want to make sure you have in place, is good brakes on the car.

TG: Yeah. And that's what I wanted to get to next, is your process in, I guess, finding the right brakes. I don't know how you want to put it, but I'll start with kind of what people ask me, because I'm starting to focus a little bit more on my previous- and actually, we met, I think, about 16 or 17 years ago when you were at Artradis, and I was a Vol strategist. And I've started to do that again for my sins. And people always ask me kind of, well, how does this look? What's the valuation of this? And my usual answer is, I don't know. Because you're just trying to find the right price, not necessarily whether something is rich or cheap. But I'm curious, like selfishly, like how you go about that process.

How do you assess, whether it's absolute value or relative value, what's your process in thinking about volatility or correlation and whether you want to take on exposures?

DD: Yeah, that's a very good question, Tim. And I think this is really important.

I mean, again, I'm going to talk about the way we do it or the way I think about it. You know, one, we're agnostic to underlying. We don't have a view. We're not trying, I think, too many people think that hedging or tail risk hedging, what we do is people ask me this all the time. They say, oh, you know, because everybody knows that, you know, if I was running back to Bankers’ Trust during the Asian crisis and I was doing this during the GFC. And, you know, Dave always knows what's going on.

But some people say, oh, so, Dave, you figure out where you think the big risks are and you go and buy options. I say exactly the opposite of that. We buy options because the price is right. And over time, that probably tells us some idea of where the risks are, because we can see where the leverage is built up in the system, where the left tails exist, where the uncapitalized risk that makes the system vulnerable is.

So, again, for us, it's very bottom up. It goes back to embedding ourselves in that practice. People say, Dave, how do you find all this stuff? And I say, we put a sign on the door in Asia that says, we buy vol. Every morning, there's a queue of people outside saying, how about equity vol? How about FX vol? How about interest rate vol? How about credit correlation?

How about, you know, bing, bing, bing, because they're printing all this stuff on the other side, creating yield to sort of offset the decades-long financial repression that are artificially suppressed interest rates and limited access to global capital markets in various countries around Asia. So everything's very bottom-up. We don't have a view. We're not trying to time anything. The right time to buy it is when it's cheap.

And that's all we do 24 hours a day, about roughly 24-6 at the moment. The way things are going, it looks like it's going to go 24-7. We're just going to trade, not going to tokenize everything and trade 24-7. And we have to make our evaluation working with our counterparties. We need to understand the nature of the flow.

Are they doing, again, callable interest rate structures that are embedding Bermudan Swaptions? How is the bank hedging that, whether going to the vanilla Swaption market? How are they making determinations about probability of call dates? How are they managing the Vega duration through those strips of Bermudan Swaptions through time? How is the vanna affecting where they want to target within the vol surface, the different parts of that?

How is their in-house stress testing affecting the basis risk they're able to take in how they're hedging it? Is it auto callable structures on equities? Is it TARFs and TARNs on FX? Is it worst of multi credit baskets, credit link note stuff that's getting done to try to accommodate credit appetite in countries that don't have significant borrowing demand, aka Japan? And then it's working on that stuff. And the common thing for us, Tim, we have examples, I don't know how much we'll talk about actual examples, but there's a particular example that we're very active in at the moment that we started really working on pretty constantly in January 2024 and printed our first ticket in August 2025. So it takes that long. It's that, you know, think of us as fundamental investors. We're working on the flows, the structuring, the hedging, how it's impacting the market, what the bank's willing to do from the basis risk they're taking, how is it building up exposures?

How is that tail getting more and more fat to the left side? How much leverage, you know, implicit leverage involves selling? And to a great extent, that's driven by what we want to own. We want to own something that's efficient, that's convex, that has as much duration as possible in it. We don't like short-term options because we really want to own the vol of vol and the vega, which is sort of a long-dated leverage factor, not delta and gamma. Delta and gamma are not asymmetric enough for what we're interested in. They take too much work too. And we have a whole slate of things that we're evaluating and working with the banks and updating on and how much flow are you seeing in this? What are other guys doing? How big is the market? We're meeting with private bankers around the region saying, what are your clients doing?

We obviously, given our background, by background, we're familiar with the rules and regulations and accounting practices of Taiwanese insurance companies and Korean pension funds and Japanese banks and how people utilize the rules, regulations of Sharpe World to try to optimize to their objective.
And now their objective, however you look at it, rarely is long-term geometric compounding for the capital that they're responsible for. Because generally they aren't responsible for the downside and they're getting paid on some sort of weird calendar year incentive structure around accounting numbers, not around actual returns.

TG: I think you kind of answered my next question, but I'll ask it anyway. I mean, is there anything you do in the interim to kind of manage the negative carry of a lot of these strategies? Because long vol ultimately means you're paying for it, right? And do you do anything to kind of risk manage that? When you have maybe... I know you don't have a view, but if you have a view, say that some of these things are going to decay, even if they are Vega products, which don't decay the way Gamma product does, do you risk manage that at all?

DD: No, no, we don't think... We're tasked by our investors to build and optimize and grow and manage through infinite time asymmetry. We're not tasked with taking a risk. So we only risk mitigate. Now, the best way to mitigate the cost is to buy things efficiently, in efficient price, in efficient structure, in efficient time horizon.

But in a sense, our job is to invest. So our job is to go out and invest. We think of the fund as a private equity vehicle, where every year we're drawing our spending budget, our investment budget. Some people think of it as a bleed, but given the multi-year duration of our book, it's not really...

And we're just stacking year after year of investments in, you know, 20, 30, 40, 50, 100X potential payoffs that all inevitably will be tied together through correlation, if and when there's a systemic market type event. Anybody who's... I would say, I don't want to be mean, because I know it's very relevant to a lot of people, but I'll always say if somebody's doing strategies to mitigate the bleed of providing the breaks, they're trying to manage their compensation, their performance, not trying to manage their clients. The client wants breaks. He wants a goalkeeper. It's on him to take advantage of that and drive faster or goal score more goals. He doesn't want his goalkeeper running up and trying to score goals because he thinks it's opportunistic. That's only trying to game the standard compensation structure in the industry, the incentive structure that you get paid based on goals scored per game. And nobody knows how to pay the goalkeeper. Nobody knows how to attribute the contribution of the brakes.

But we sort of take that out of play and just say, we're working for these guys. It's obviously very easy - I mean, you look at how markets have behaved in recent years, you know, for a de minimis part of your portfolio, allocated to tail risk, going out and freeing up what you've had, you know, the massive amounts of capital you've had tied up in bonds and traditional diversifying strategies and putting that into markets that are going up 25, 30, 40 percent a year, you're more than paying for it very easily, driving faster. And that's the way to pay for it. And you know, I'm always adamant that allocators shouldn't be paying hedge fund fees for positively correlated risk. They can get all the positively correlated risk they want for free in the form of ETFs or equities or gold or futures or whatever, decide how much risk you want and take it cost efficiently, and then hire people to play goalkeeper to be the brakes, because that's hard. It takes a lot of day in and day out work to manage the cost, the data, the lost sensitivity through time to ignore calendar years and manage.

You know, nobody in the real world, nobody wants their insurance to decay to zero, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1 months, and then start over again. You'd like your insurance to be constant through time and if not growing.

TG: What mistakes do you see people make when they try to pursue this exposure? And what's your own? I want to talk about the blind spots as well, but what are the common errors that people make in trying to pursue these types of strategies?

DD: Yeah, so a whole bunch of things. Again, when people, when allocators are looking for it, because people know, I mean, enough people read my notes, that they know that the correct answer is convexity, the correct answer is negative correlation.

But again, everyone's sort of driven by incentive structures. And because most of the allocators, whether you're working for a pension fund or a sovereign wealth fund or a wealth manager, you're getting paid and operating within a Sharpe world environment. You're getting paid in a short time horizon. Your incentive is very much around average lap speed, not around terminal standings after a multi-lap race.

So I always say the biggest flaw in the industry is that they're just flat, not a benchmark or an incentive structure around geometric compounding. It's that simple. If you could turn it around so that geometric paths non-ergodic geometric paths were what people were driving towards, everybody's behavior would flip. I say all the time, you imagine that 40-lap race. If you're compounding from the beginning, if you're optimizing from the beginning one lap at a time, modern portfolio theory, it's going to tell you to sell the straddle around the expected return, which is exactly what modern portfolio does. It's optimizing to expected return, a made up precise number. But if you were optimizing from the terminal 40 laps backwards, it will tell you to buy the straddle because it will say the only thing that matters is the fastest part and the most dangerous part. All the other stuff around the middle doesn't make any difference. That's the biggest mistake people make because they're always managing to a short-term incentive structure.

And so without fail, you'll see people say, well, we want to we want breaks. And then they go out and hire an RV manager because it suits their utility function. It has a numerator and nobody knows how to measure the denominator. So they all like returns. And then you end up with the silos that are the traditional sort of structural asset allocation where you say, well, I'm going to put this much in fixed income and this much in equities and this much in credit, and this much in commodities. And then those silos each get evaluated on an individual performance basis down to each individual trade, each individual allocation. Now, fortunately, that's breaking up.

And I'd like to take some credit for it because I've been pounding these guys for 35 years. And more and more people talking about the new catchphrase as though somehow it's this revolutionary innovation, this total portfolio approach, and that we should actually evaluate everything on its contribution to the overall portfolio, and that our objective should be the performance of the portfolio.

Now, to most people listening to this, they're going to say, surely, they've known that all along, right? But you know, and I know, they haven't. They haven't practiced it at all. And they're still, even the vocal advocates of it still really are struggling to practice it. Because a little bit of the problem is it necessitates cleaning up what they've got. And so, everybody's been following Sharpe World, modern portfolio theory, risk parity, dependence on stable correlations and assumptions of steady volatility and application of leverage. You need to clean all that up. You need to free that capital up to go and participate in the convexity and flip your portfolio from being targeted at the mean to being targeted at the divergences from the mean, which is what drives the compounding path. I showed this in my latest note that just came out this week, the annual returns of S&P going back to 1929, and the average return, as people talk about all the time, 7.9 percent. And the frequency at that average is three times. In 90, however long that is, 96 years, three times. The standard deviation is 18.8 percent. What's driving the returns? The mean or the variance? Obviously, the variance, massively.

And so people are trapped in their world. And one of the problems they really have, and this is the point of my just do it note that I wrote earlier this year, is you can't optimize to the unknown future path. It's very easy to optimize to what they call expected return, which is the average of historical return. It's a number. It's a number that's never actually realized because this happens to be the average of the divergences. And so it has absolutely no impact on your compounding path.

But when you explain to people, no, we're going to start optimizing to actual returns, to actual utility, not expected returns or expected utility. You know, they want to whip out their optimizer calculator and say, well, where do I put in the number? We don't know the number. But what we do know is that we'll have an improved compounding path.

They're like, but we have to have a number because if we don't have a number, what are we going to do with all these computers we bought that optimize to that number? And we're going to have to tell somebody what we've been doing all these years and we got PhDs in was wrong. And there's a huge reluctance to do that. So even the current vocal advocates of total portfolio approach are really just saying, well, we're going to add on some negatively correlating explicit loss mitigation. We're not actually going to go and clean up all the junk has been a drag on our performance for the last 30 years. And there's a huge reluctance to clean out the capital.

So one of the things I get asked all the time by that crowd is, well, you know, how should we fund the tail risk? Well, easy, get rid of all this. No, we can't do that.

That's going to be because the whole point is if you're if you're dragging the car down by just impeding the capacity of the engine, and you're not going to fix that, what's the point of the better brace? The point is, that's free the engine up.

The word I always use, I'm sure you've read it, explore. Go out and explore for opportunities. Don't forgo them because it's reducing your volatility and your Sharpe ratio equation. Go out and explore.

TG: Here's a tougher question.

What are your blind spots? What do you need to kind of correct for and be self-aware about?

DD: Yeah, one of our catch phrases here is, if it's cheap, buy it. Because unfortunately, all of us, but mostly me, have been around a long time. I've seen a lot of things. I know a lot of people because of my past and present. I still get to speak to central banks and reserve managers and stuff. And the mistake I make is think that I know something. And the only thing that I need to know is if it's cheap. If it's cheap, we should buy it. And I shouldn't apply, well, I like that central bank. I think what they're doing is right. I like that market or I don't like that market.

I shouldn't buy something that's not cheap because I don't like the market. And I shouldn't reject something that is cheap because I do like the market. All the information I need is in the price of convexity. And I just always have to constantly remind myself of that. I can't say, oh, but I just talked to the chief economist in the central bank there, and these guys actually do know what they're doing. It has nothing to do with anything. Our world has nothing to do with anything. Just agnostically evaluate the supply and demand of volatility. And is it cheap? Is the buildup of volatility creating a willingness within the system and the people that we do business with for them to deliver the convexity at a price and in the format that we like? If so, buy it.

TG: I mean, you're dealing with institutional investors. And again, a very selfish question. How do individual investors think about this? You know, you mentioned in your portfolio modeling, using things like long volatility hedge fund indices. But of course, those are tough to access. Appreciating that, you know, this is not investment advice in any way, shape or form.

But how do you suggest small investors get exposure to this if it otherwise is unavailable?

DD: Yeah, obviously, what we do is not available to a retail investor. It needs ISDAs and SEG margin accounts and OTC derivative reporting and regulators around the globe. But any investor can think about structuring the payout function of how they manage their investments. Most simply put, you can buy call options, again, without getting into too much detail of how we see the world. But certainly from sort of middle of last year, top side volatility in equity markets was incredibly cheap. We always say we're only buying what we rank as the cheapest in the world. So for a significant chunk of time, that was the cheapest thing in the world from about middle of last year.

And so anybody who has access to exchange traded products can repackage their desired risk taking in call option form, certainly index options and most of the relevant individual name option. And so you can rethink how you want to structure your participation in the market by utilizing call options and then holding the balance in cash and money market funds or whatever. Then if the market goes up, you're participating and if the market goes down, you're risk managed, right? And you can step aside and you know exactly what your downside is. So you've immediately created that convexity in your own payout function. And that's the easiest way to do it.

Now, you can have portfolios of stuff and you can go and buy puts on indices, but certainly those aren't necessarily where you're going to find the most cost-efficient vol. You're always going to end up with basis risk if the thing you're buying puts on has different risk dynamics to the things you own. We'll talk about it, I'm sure, as we go along. End of the day, the risk that matters to everybody is correlation. And that correlated risk will feed through things that are exposed to it regardless of perfect matches. The problem when you get into the world of buying puts or you're buying explicit protection is it becomes very actively managed because you're back into this time problem, feed a problem, your Delta exposure is changing whether your long calls or your long stocks and long puts. So it requires once you get into the business of hedging, it becomes more active because you've got to, stocks you could just sit on, they're perpetual, but options are all fixed date.

So you need to manage, maintain exposure, roll, think about where you are within the Delta appetite that you have. Do you want to release some cash and add some more calls because prices have fallen? So now you could take advantage of the fact that you're de-risking as prices come down. So it requires a certain amount of active management. Some people might have in the US, RIAs that in theory can help with that. I say in theory, there generously. There are increasingly in the US, and somewhat in Europe, in UCITs form, actively managed ETFs. They're still not allowing that here in Singapore yet, but we're working on it. But again, those will be very constrained in what they can do.

And generally inside them, they're more often defined as a one-off trade idea by equity puts or by VIX or by interest rate options or something, right? And so they're not really actively managed the way hedge fund will be. But you can review those that have enough track record, and some seem to be better than others, and companies like my friends at Simplify, who run some of these types of strategies and things. So there's means to do it. Read, understand, go to our website, read stuff, send me a question if you have it. People are always surprised that email finds its way to be the willingness I might have to answer about stuff. The theoretical stuff, go and read Nassim Taleb's books, go and read Benoit Mandelbrot's book.

But the simplest thing is to, what can you convert your exposure into call options? That's the easiest thing to do.

TG: Well, let's think we've got a few minutes left. But I wanted to talk a little bit about current markets. And we are in this, for me, it's a very weird spot where it's obviously very frothy. There's huge uncertainty or measured uncertainty. I'm not sure how much stock I put in some of these kind of quantifications of uncertainty that people try to put out there. But we also have vol very low, and we have these kind of weird dynamics where spot and vol correlations and things like stocks and gold have just gone kind of haywire, people grabbing for upside.

And so I’m wondering what your thinking is now on what are maybe some of the most underappreciated risks that are bubbling under in markets.

DD: Well, we always tell everybody, particularly in what we do, but anybody who's managing a diversified portfolio or running a bank or a pension fund, the risk that they're not measuring is the biggest risk and that's correlation. And so everybody has built into their risk methodology. So buy your risk at a bank and the market risk equivalent close up of that into risk-weighted assets and how pension funds are measuring their risk, whether they're running a risk-parity structure or a liability-driven investment type structure. Everybody's making assumptions about correlation.

So it's always that correlation and the concave relationship your portfolio has to it, that is sort of the ultimate risk in the system. And if you think about it, I guess really even more broadly, risk is leverage. And it so happens that assumptions around correlation are maybe the biggest leverage in the system, because everybody's running more risk because they quote have diversification.

But they're assuming a correlation benefit that may or may not be there. And so when correlation gets wacky, people have to reduce risk because their diversification isn't working. And that becomes reflexive and self-fulfilling. And so I can go back through all of history and remind those that are old enough that correlation got wacky several months before we unwound LTCM. And correlation got wacky way before the banks went out of business in 2008. The systematic funds all blew up in August 07. And correlation right now is pretty wacky, right? As you just mentioned, you know, gold and equity, dollar and real rate, you know, wait a minute.

So we always sort of jokingly, we have a great big whiteboard here in the office that we just note sort of central bank policy changes or political, you know, big events through the year. And as we sort of see what regime we're in, because we don't forecast anything, we sort of name the board. The previous board name, I think that went up in sort of middle of summer 23 was the steepening cycle.

And then in January this year, we changed the board name to, excuse my language, you know, correlation is going to be a... And so right now correlation is driving things. And I think some of that comes down to my whole point about this total portfolio approach. You know, the whole world is tied up around these correlation assumptions that have really destroyed compounding paths for the last 15 years, but certainly for the last six or seven years. And as people are transitioning away to the recognition that wait a minute, low diversification, low correlation is a dis-benefit. We need explicit negative correlation and more participation. We need convexity.

Well, that necessitates the cleansing of these correlation-dependent structures, which is keeping pressure on correlation in the system. Now, the obvious one to replace that, you know, obviously, I've been an enormous advocate of forever, and I'm sure everyone's kind of figured out. One of the obvious ones to replace bonds is gold. You've been way better off owning gold for the last 30-40 years than owning US Treasury bonds.

And then, of course, who owns, relatively speaking, who's the most overweight government bonds in the world? Well, FX Reserve Managers, right? They've been doing QE, but because of the size of their markets, their QE is building FX Reserves, is buying somebody else's bonds. China and Russia and India and Singapore. And so these guys own so many bonds, and you don't need to be sort of a scholar of history to figure out that the guy selling you the bonds is debasing them. And you've got too many and you're just going to get more because you're constantly in the currency war and the Asian central banks are the master of keeping their currencies relatively weak. And they just keep accumulating them. How many do you need? And so would these guys make the decision to start spreading some of their reserve accumulation a little more into gold? And they're obviously very sticky holders.

I wrote this month about some of the talk about the inelastic market hypothesis and my friend Mike Green's commentary about passive flows into equity markets. Well, imagine the world's biggest central bank reserve managers and a sort of passive flow dynamic into gold. Kind of imagine getting what we're getting and that would just kind of keep going.

And so this is really correlation in general is the risk. Leverage is what makes fragility in the system, creates the uncapitalized tails. We've known for years now that the big uncapitalized tail has been government debt, that banks and insurance companies and pension funds because of the regulatory construct could hold duration sovereign bonds without any capital, zero risk-weighted assets to the point that, you know, a top 20 US bank could go out of business because they owned US treasuries. That's how good regulations are in the world, shockingly bad, right?

And so you've got all these pockets. Vol selling is a form of leverage, which is the one we're focused on. So you've seen this massive explosion. I'm sure you saw it was just last week that, you know, they came out with 40 new names of auto-callable single name ETFs that are getting launched. And that's just a massive form of leverage of vol selling pouring into the single names. The Asia Structured Product Auto-Callable Machine, which dwarfs everything else in the world, shifted from indices to single name stuff beginning of last year. And that has just been building and building and building. And that's had this implication around the dispersion trade, has been what's really driven implied correlation and the indices so low as the system has to absorb all that single name vol and is hedging it selling equity vol, running the dispersion risk, building up a massive short correlation exposure. So all of that correlation, see everything I just talked about there has some sort of a correlation tweak to it. And that's really where the big problems are right now. And right now today, it's all under pressure again.

TG: As an aside, do you look at things, like we have a turbulence index that we use that Mark Kritzman has worked on for years. It's the Mahalanobis distance basically. And it looks at volatility unusualness and correlation unusualness most. That's kind of its secret sauce, right? Looking for these changes under the hood.

I mean, how robust are those in trying to think about vol regimes? You mentioned regimes, and I know we're not trying to necessarily predict a ball regime to come. But how useful are tools like that?

DD: I think they can be very useful. And we have some funky math that we play around with that we're looking at. We always, by my most recent note, is titled Initial Conditions. So we're always trying to understand where we are. How fragile is the sandpile? We're not forecasting, we're not making any predictions. We're just trying to measure fragility, so that you can imagine there's a lot of curvature in the math that we're doing to measure stuff.

Now, the problem is, while those might be quite useful, and I think they are, they're not as practical as price. And so we might recognize fragility somewhere, but if nobody will sell us insurance at an attractive price, it doesn't matter. And so from a practical perspective in our actual activity, our focus is price. Our focus is where is the supply and how is that impacting price? And how is that, you know, and the guys we're working with, with how are we able to acquire things cost efficiently?

Now if everything goes to plan, as you may have heard me say before, right? The secret to what we do, and I, you know, don't tell anybody...

TG: It's at the end. So nobody will be listening.

DD: …Is that the biggest risk, the biggest fragility, the biggest uncapitalized hells line up to where the price is the cheapest, where the insurance is the cheapest. Because it's that application of insurance, the application of all selling, that's creating the self-organized criticality of the building network of leverage that makes the system fragile.

So super senior tranches of subprime CDOs were the best hedging product at exactly when they were priced at zero yield over US Treasuries, because the leverage had driven them there. And so the price for us from a practical execution and run the business is the number one driver. Models around turbulence are fun and mathematical, and we're trying, as you might imagine, we're always playing with different time horizons, because maybe if we could create a long enough time horizon, it gives us time to go and find insurance. Lots of times we find those signals, the signals of fragility are too short term, and nobody will sell us what we want to buy by the time we say, shit, there's a lot of fire risk, right?

TG: I get it, I get it. Very good. Well, and at the end of the day, it's all just math.

DD: Yes, I say it's just math. Yeah, and the beauty is about adding convexity to your investment portfolio is even doing it poorly will have a fantastically positive impact. Even, you know, moderately adding something ineffectively is going to improve your outcome. Because again, the more you can become resilient to divergences, the better you're going to do.

And so anybody whose entire perspective is around optimizing to the mean is going to benefit by adding convexity on you know, and you want to always want to think about adding convexity on both sides. It's not about betting on a blow up a meltdown a wildfire. It's about protecting against it and freeing up capital to go and take more participating risk. Being in those back-to-back-to-back 25 percent up here is being in thin-tailed opportunities, right? But to do that, you want to have good breaks. If you're going to go out and explore and test how to make a car go faster, make sure the brakes work first or you're going to run it into the wall at the end of the straightaway.

TG: Very good. We finished the circular lap. I think we have taken it full circle.

Dave, this has been amazing. It's been great to meet you again and great to talk to you. Thank you so much for doing this.

DD: Absolute pleasure. So much fun. I love talking about it, as you can tell.

TG: Yeah. There's questions that I had, like 85 questions I didn't get to, but maybe next time.

DD: Send me a note. I'll answer them.

TG: Yeah, exactly. And actually, on that note, yeah, while you're still here, convex-strategies.com is the website for Convex Strategies, whose CIO is David Dredge, who has been our guest this week. Thank you so much again, Dave.

DD: Thanks, Tim.

TG: Thanks for listening to Street Signals. Clients can find this podcast and all of our research at our web portal, Insights. There, you'll be able to find all of our latest thinking on markets where we leverage our deep experience in research on investor behavior, inflation, media sentiment, and risk, all of which goes into building an award-winning strategy product. And again, if you like what you've heard, please subscribe wherever you get your podcasts and leave us a review. We'll see you next time.