This is an edited transcript of our podcast episode with David Dredge, first published on 17 September 2021. David has over 30 years’ experience of managing risk across global markets. David is the CIO of Singapore-based Convex strategies – which focuses on risk management including protecting against dislocations in asset markets. In this podcast we discuss the confusion between measuring risk and managing risk, the problem with value-at-risk and defining risk, the growing fragility in the financial system, and much more. While we have tried to make the transcript as accurate as possible, if you do notice any errors, let me know by email.
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This is an edited transcript of our podcast episode with David Dredge, first published on 17 September 2021. David has over 30 years’ experience of managing risk across global markets. David is the CIO of Singapore-based Convex strategies – which focuses on risk management including protecting against dislocations in asset markets. In this podcast we discuss the confusion between measuring risk and managing risk, the problem with value-at-risk and defining risk, the growing fragility in the financial system, and much more. While we have tried to make the transcript as accurate as possible, if you do notice any errors, let me know by email.
Bilal Hafeez (00:00:00):
Welcome to Macro Hive Conversations with Bilal Hafeez. We aim to bring you the best macro to help you successfully invest in markets.
This week, we got the latest US inflation numbers, and they were weaker than expected. This fits into the views we’ve been pushing on the Macro Hive site. And you can read Dominique’s latest take on these numbers and why she expects these numbers to continue to be weak. I also put out a piece looking at what both consensus and markets are expecting for the biggest moves in FX markets in 2022. And there’s a few surprises there. Our latest summary of new academic papers looks at how and when momentum models will be profitable. And we also feature a piece by this episode’s guest, David Dredge, on how to use convexity in your investment portfolios. You can get access to all of this and more, including our member slack room where the Macro Hive team and members discuss markets all hours of the day. It’s refreshingly different from Twitter. When you sign up, the first month is free and then it’s only the cost of a few weekly cappuccinos. It’s well worth it and many core Macro Hive, the hidden gem for investors. Once again, sign up to become a member at macrohive.com. And if you’re interested in our more high-octane research product for professional and institutional investors, drop me an email on email@example.com.
Now, onto this episode’s guest, David Dredge. David has over 30s experience of managing risk across global markets. He’s currently the CIO of Convex Strategies, which focuses on risk management, especially around protecting against major dislocations in markets. Before launching Convex Strategies, David served as MD and portfolio manager at our Artradis Fund Management in Singapore. And before that David built and ran Asian and Global EM trading businesses for RBS, Bankers Trust and Bank of America. David holds an MBA from the University of California, and he also sits on the Monetary Authority of Singapore Markets Committee.
Now, onto our conversation. So welcome David to our podcast show. I’ve been looking forward to our conversation.
David Dredge (00:02:05):
It’s great to be with you. Thanks for inviting me. It’s good to be back in touch on a more regular basis again.
Bilal Hafeez (00:02:09):
Absolutely. Now one thing I always do with all of my guests is I like to find people’s origin stories. And so it’ll be good to hear from you what you studied at university, was it inevitable you’d go to finance and then what’s been your career to date and how did you end up where you are now?
David Dredge (00:02:26):
It’s actually a very relevant story and I find myself to be one of the few guys that I feel like it’s inevitable that I ended up where I am. I’m from Utah. I’m a Salt Lake City, Utah boy. I’m an outdoorsy fly fisherman, hunter, play golf guy. I graduated from the University of Utah, master’s degree in finance and took the GMAT and got accepted. And I got tired of it being cold in the winter time. And so I decided I wanted to go to California. And I went and got an MBA at the University of California, Berkeley. And at Berkeley, and this is like I say, it seems like it was destiny. At Berkeley, my focus was economics and my professor was Janet Yellen and financial derivatives. And my professor was a guy named Mark Rubinstein of the Cox Rubinstein binomial model and of the Cox Rubinstein portfolio insurance business. And I graduated from Berkeley in spring of 1987 at the peak of Mr. Rubin. So I literally, I had Mark Rubinstein’s portfolio insurance, financial math binomial model class in the first half of 1987 when he was at the peak of his stardom and presence in developing the first real ever portfolio insurance business.
I graduated and I literally joined Bank of America who then was very much headquartered and run out of San Francisco because I didn’t want to go to New York because it was too far away from home, from Salt Lake and I didn’t want to move that far away and turned to down jobs in New York. Took the job in San Francisco and three months later they sent me to Singapore. So, I learned early on that my ability to forecast the future was pretty poor and I better figured it out something else to do for a living than just trying to forecast what was going to happen. And I literally arrived here in Singapore and I, probably one of the few guys that even you know, that I was in Asia for the October ’87 crash. So I got here the first Monday of October ’87 and two weeks later I got to see a trading business and senior guys that I was supposedly supposed to be learning from drop a decent amount of money in a blink of an eye. And literally, and I’m not making it up, it dawned on me that it was possible that these guys in the bank I worked for didn’t actually know what risk was because the size of their loss on that day in ’87 was much, much larger than their stop loss limits and their risk limits would’ve said was allowed. And I’m still working on that, trying to solve that problem.
So as you know because you know me for a while, I don’t consider myself a trader or an investor. I’m a risk manager. And off the back is my years of developing how I think about risk as we’ll talk about the importance of convexity and et cetera, I ended up pitching my idea around risk and emerging markets to these crazy guys at Bankers Trust and I started here in Asia, in essence what would be their emerging markets business back in the early in 1991. And on this premise of building a pool of positively convex risk that allowed you to engage in what I then defined as uniquely risky emerging markets. And they were uniquely risk because the market didn’t determine the equilibrium price of risk.
There was some market impediment, most obviously being pegged currencies or something where a central banker government constrained the free market mechanism of determining the price for risk, which obviously meant that using historical volatility and correlation was not a good tool for predictive risk in the future because any change in that dynamic meant that all historical terms were useless. And so really, we started this business at Bankers Trust, and me and a bunch of young guys and smart guys and Bankers Trust had this derivative capability. And we started embedding optionality in yield enhancing structured products and stripping out the optionality and using that as a pool of long convexity, that then allowed us to go and engage in liquidity foregoing franchise business activities, market making, and underwriting and derivative structuring. And all the traditional franchise businesses that we’ve both seen banks over the years. And obviously, I was well familiar having worked around all the Bank of America’s emerging market offices in Asia, as they all deregulated from 1988 onwards and opened up, banks coming and going in that business because they earn a little bit during the good times and then lose a lot in the bad times because they don’t manage the liquidity and correlation risk that’s inherent in their franchise business. And so we built that business at Bankers Trust and it was a fairly successful business and certainly the concept of positive convexity and innovation and a different mindset around risk management, the exact inverse of the risk management that’s implied by value at risk.
So that proved to be a very good mindset as you went through the Asian crisis and allowed us to have a very prominent role in that. And then of course that business became Deutsche Bank’s emerging market, Asia trading and sales business. And I took some time off and then I came back again and built that type of business within ABN AMRO. And then it went through the same thing with RBS and we had another successful business. And then I retired again from banking and moved to the buy-side and joined some old friends that had had a very successful fund called Artradis that ran a long volatility strategy that were so successful that the two founders set up their own family offices and closed down the business. And then we launched our business, first in partnership with Fortress and then they sold us, if you will, to a place called City Financial. And then we bought it out from them a couple of years ago and Convex Strategies is the Singapore licensed investment management business that manages our various convex-related activities. And in a sense, I’m still doing the same thing that we started way back at Bankers Trust, I’m only just doing the convexity side. So we just help risk manage people by creating long convexity. You can think of it as tail-risk type structures for people allowing them to more efficiently bend their convexity and their portfolios. And so I’ve been out here in Asia, and I guess you know this, as long as anybody. And that’s why I said I can tell anecdotes about every, going back to the October 1987 crash and every event in-between because I was in the midst of it. I was in the room with the LTCM guys and I was in the room with the regulators when we unwound the Malaysian ringgit. And I was in the room when messages were sent regarding detachments of actual market rates from LIBOR fixings. And I was there and can tell you stories about it, but most people don’t want to hear those stories anymore.
The problem with value-at-risk and defining risk
Bilal Hafeez (00:09:32):
I’m sure we’ll hear some of the stories as our conversation evolves. It really does sound like there’s a thread that runs through your career around risk and understanding almost unexpected moves or trying to look out for those sorts of things. Now, we know in markets and most risk management systems, the way risk is defined is usually based on some historic volatility of markets. And then you apply some metrics using, in essence, historic volatility. So essentially what we’re saying is some measure of recent volatility, whether it’s three months, six months, five years is your best estimate of the types of outsized moves you’re likely to get in the next period of time for your investments of holding. And even though we constantly hear about 10 standard deviation moves, this VaR or this historic volatilities approach continues to be used everywhere. So one question I have for you is why is that? I mean, why has it been so embedded in the system, even though we keep getting these extreme shocks?
David Dredge (00:10:36):
Yeah, that’s a dangerous question because most people don’t want to know the answer. So again, Bankers Trust was very early and depending on who you’re talking to, at Bankers Trust will take credit for inventing value at risk. Now, some J.P Morgan guys will claim the same. I’ll argue that they made the leap to risk weighted assets, but it was actually Bankers Trust who came up with the value at risk concept. And we came up with it as a risk reporting tool. It was a way to get a group of people around a table with senior management and talk as though you were talking apples and apples, as opposed to talking about equity, notionals and interest rate DVO1s and option Vegas. And you could say, “Well, this has a value at risk of this.” And I tell the story when… So I was the guy who went around Asia. So when the Fed gave Bankers Trust permission to report using their model, using value at risk, they were the first bank that reported using an internal model back in the early ’90s. I had to go and tell the Asian central banks, most prominently MAS here that we’re going to start reporting this way, because the Feds said we can and that’s way we’re going to do it. And they said, “Well, this is interesting. This is so innovative. So sophisticated. Is this how you manage risk?” And I said, “No, this is how we report risk. There’s a totally different system that we used to manage risk.” And that was a Monte Carlo based. You can go in and manipulate the covariance matrix and you can create any scenario you want. And the premise of that, again, is very much what we do now. That was looking at what could hurt you. Understanding what hurts. And I say this all the time, I’m sure it’s on our website, if you go to our website, a catchphrase, risk isn’t what you think is going to happen, risk is what hurts if it happens.
Bilal Hafeez (00:12:19):
Okay. Yeah. I was actually going to ask you how you define risk and actually just defined it for me.
David Dredge (00:12:24):
Correct. And so the value at risk, which is using historical volatility or historical data series, historical volatility and correlation, and then extrapolating that into a normal distribution, which is wrong in and of itself, and then applying standard deviation and percentiles to that as a probabilistic expected outcome of the underlying, which again, I talk all the time and this is maybe a Nassim Talebism. It’s focused on x, not f(x). So it’s focused on the probabilistic outcomes of the underlying, not the payout function of your exposure to the underlying. And that’s where you get things most famously. And this is what we talk about day in and day out, what we would call uncapitalised tales because you have the fiduciary financial industry, banks most famously, who are using this flawed risk methodology and saying, “Well, because 95% how within two standard deviations, we think this will be the outcome.” And so then it’s okay to run 99.9 times leverage and super senior tranches of subprime CDOs. And all of the risk outside of that is uncapitalised. And if you’d run a, again, what Nassim would call, we would call it a risk heuristic and run a true stress analysis on banks, in 2006, 2007, said, “What will because the bank to lose the most money? What would’ve been a change in the correlation assumption of housing prices embedded in mortgage securities that had been CDOed and tranched up into AAA tranches that were zero-risk weight assets?” And then if you change that correlation assumption, it wipes out all of the capital and the banking system. And so that’s what risk is. So risk is where are their uncovered losses? Where is there not capital in the system? That’s why you call it systemic. It’s systemic because the system has to absorb the loss because the guy making the decision doesn’t have enough capital to absorb the loss. And that’s where the word systemic risk comes from.
I like your idea of x versus f(x) because as a market strategist, what I find is that strategists or analysts spend a lot of time trying to forecast, say economic fundamentals. So they say, “Okay, the Fed’s going to do this so growth is going to be this, or inflation’s going to be that.” And then they assume some kind of linear mapping to what that means for markets. But half the time, if not more than half the time, the relationship between those economic fundamentals and markets is so unstable and so uncertain that you actually don’t know how it’s going to map from one to the other.
In FX, there’s a famous paper by Meese and Rogoff in the early 1980s where they ran all these models on FX forecasting to say that if you knew with perfect foresight, next year’s economic fundamentals, could you forecast currencies? And the answer was no because the relationship was so unstable. So I do like your idea of x and f(x). And it seems to be that’s big part of your, I’ve heard you speak about this often and use this idea in your writing. So can you just elaborate a bit more about the importance of this?
David Dredge (00:15:38):
Yeah, yeah. Risk is about payout, is about your payout function relative to what happens. And so it always drives me nuts to be involved in, obviously I spend a lot of time speaking, probably more time speaking to risk managers and chief risk officers than I do speaking to CIOs and PMs, and nothing drives me more crazy than a risk management professional saying that he thinks that’s an okay position because he agrees with the view. What in the world does your forecast of x have to do with anything? “Oh, I think that the market will go that direction.” So it’s okay to sell puts? That’s just dumb. That’s just mind numbingly dumb. And so f(x) is simply the payout exposure. And in the end, that’s what risk management is. And I’ll argue, that’s what portfolio management is. If you get your payout right, then your view doesn’t matter. And that’s sort of the whole premise. And any forecast, the trade is in essence a zero sum game. So you’re forecasting the currency’s going up and the guy on the other side of the trade’s forecasting it’s going down. And what you’ll find is there’s virtually no impact to returns in virtually all of the outcomes of that underlying.
David Dredge (00:16:58):
The only impact in returns is the outcomes that are in the two percentile wings. And the two percentile wings are driven by the guy who had the risk right, not anybody who had the view right because nobody would’ve predicted the two percentile wing, but the guy who had positively convex risk, where he was protected on the downside and participative on the upside performs very, very well in the wings and the guy who didn’t have his risk, right because he had structured the trade to lever carry and he participates in the downside and doesn’t participate in the upside, doesn’t perform well. And so over the longevity of time, and this, I think we’ve talked about this before, the fundamental flaw in the fiduciary world, which is what dominates the financial industry is the simple mathematics around returns that everybody is optimizing to a solution function of arithmetic average returns, not to a solution function targeting geometric compounded returns through time.
What is convexity?
Bilal Hafeez (00:17:56):
Yeah. That’s a very good point about the compounding versus arithmetic. And then also before we go into that bit more, it’ll be useful for you to define convexity. I mean, you did just then, but obviously the name of your fund and strategy and everything is convexity. So it’s pretty central to what you do. How do you define convexity?
David Dredge (00:18:14):
Accelerating gains and decelerating losses. So when things are going good for you, they’re going good at an increasing pace. And when things are going bad for you, they’re going bad at a decreasing pace. And so in my old math classes something that’s convex holds water and something that’s concave spills water. Is what we used to say in math class. And essentially, you could convexity as non-recourse leverage. I get all the upside and somebody else gets the downside. If you think about buying an option, all of the positive benefits of that accrue to me, any negative benefits is whoever sold me the options problem. I talk all the time, people, one of the things that I’m constantly trying to get people to see despite what they get from academia and the traditional industry, you’ll see over and over again people showing academic studies that put selling strategies make money. And I always show people that the exact same put buying strategy makes more money. And they’re like, “Wait, how can that be?” But the point being a put selling strategy makes money like depositing money at really low yields at a bank makes money. The bank who’s borrowing that money at really low yields and paying the depositor makes a lot more money than using that money to go and invest in higher returning strategies.
So a put buying strategy where you’re owning the underlying, S&P obviously the best example, and somebody’s selling you the non-recourse leverage of selling you the puts, makes a lot more money than just being short the puts. Just like running a bank is a lot more profitable than to depositing money in a bank. I find it stunning that banks have figured out that when they look at their income statement and it has interest earnings and interest cost, they don’t say, “Well, let’s get rid of the cost part and shut down the deposit business.” They understand that there’s a relationship there that the two need to be looked at together. Whereas in the investment industry, if you say to, and talk to anybody about hedging or buying optionality or buying protection, they say, “Oh, that costs money.”
Why buying options is not ‘expensive’
Bilal Hafeez (00:20:13):
Yeah. And on the costing money, the argument in the investment industry or the norm of that is that the options are expensive, implied trades over realised. So you’re overpaying for this optionality. So do the opposite and just sell and you clip the coupons so to speak like a carry trade. What do you say about the whole options are expensive?
David Dredge (00:20:36):
Well, again, that’s like saying it’s expensive for banks to borrow money at their deposit rate. If you simply look at the deposits on a standalone basis, I’d say, “Yeah.” So the guy placing the retail depositor depositing in today’s world at 10 basis points is making 10 basis points and the bank is losing 10 basis points. The bank’s obviously not losing 10 basis points. He’s taking on in effect, non-recourse leverage. He can take that money and go and lend it to somebody who pays him 5%. And if the guy doesn’t pay him back, he doesn’t pay back the depositor, yet he keeps all 490 basis points of upside. Well, the same thing is exactly true with buying puts. Which is why, if you look at the CBOE PutWriting Index, yes, it has a positive compounding line, but if you look at the Put Protect Index, which has the exact same systematic rule buying the puts and owning the S&P, it has a much higher return line. And because you wouldn’t measure the cost of deposits without measuring the benefit of the lending side.
Bilal Hafeez (00:21:39):
Yeah, yeah. I guess what we’re looking at, it’s a partial view of the system and not the whole system.
David Dredge (00:21:45):
Correct. And so logically, in my example of the Put Protect versus the PutWrite, the Put Protect guy has taken on non-recourse leverage. He gets all of the S&P upside and the guy who wrote him the put gets all of the downside. And overtime, particularly over a compounding period, geometric that compounding is driven much more by the performance in the big numbers than in the small numbers, particularly the big down number, which has a multiple impact because of the non-ergodic nature of compounding return. And it’s that simple. I’d much rather be the guy with the non-recourse leverage than the guy who’s lent the money and gets none of the upside. And that’s what put selling is, and that’s what vol selling is.
Importance of compound returns over arithmetic returns
Bilal Hafeez (00:22:25):
And mentioned, you’ve come back to this point about arithmetic versus geometrical compound gains. And you said the financial industry seems to optimise arithmetic. Can you just elaborate a bit more by what you mean about that?
David Dredge (00:22:38):
Yeah. I mean, as you’re well aware, there’s in the banking side and the investment side, the fiduciary has managed to structure the industry standard as an annual return cycle. And then of course the fiduciary who participates, whether it’s through bonuses or performance fees or it’s just simply a salary and a promotion, in the upside, doesn’t participate in the negative compound effect event on the downside. And so they tend to talk about expected return. They’re doing ensemble averages as though we live in ergodic space, as though 200 people place go and gamble in the casino and place one bet and on average, they make this much money, but the average of what a whole bunch of people do in one bet isn’t relevant to the investment track of one individual’s capital. Because if you’re the guy who loses all your money, well, you’re done. Doesn’t matter what the average is. And of course the average will always be vastly distorted because the actual distribution of wealth and returns is not a normal distribution. It’s a massively fat tail distribution. And so for the fiduciary, again, he’s happy to participate in that as long as he’s getting a cut of whatever the average is. The fact that only two out of 1000 guys is getting rich and everyone else is going bankrupt, as long as one of the clients is Jeff Bezos, he’s overjoyed. But in reality, each individual person it comes to a compounding thing. And in the compounding thing, the negative compound, we all know the simple math that if you lose 50%, you’ve got to make 100% to get back to break even. So the negative compound costs more than the positive compound make. And so risk management becomes more important than market forecasting in terms of the… There’s only really two things that matter in compounding, time and downside. And there’s a direct relationship to those because if you get the downside wrong, you won’t get the time.
Bilal Hafeez (00:24:34):
Yeah, no, that’s a good point. And actually, people like Warren Buffet constantly talk about compounding. And as it happens, he’s not constrained by the typical fiduciary requirements of the asset management industry. He basically says, “I’m going to just compound. I don’t care about quarterly annual returns and the snowball effect and cause all of these sorts of things.” So the legendary investor keeps talking about this yet, despite that. And actually he criticises the financial industry all the time as well. So it’s probably, it’s not inconsistent that we’ve seen that kind of outcome.
How to think about ergodicity
Bilal Hafeez (00:25:05):
And you mentioned this term ergodic, or ergodicity, it’s quite a fancy term. I mean, perhaps you can just explain that a bit more. I mean, you talked about ensemble averages versus time average. Perhaps you can just explain a bit more behind this idea?
David Dredge (00:25:20):
Yeah. I implore all of your listeners and followers to go and Google ergodicity and fine people, obviously, Nassim Taleb talks about it and writes about it a lot. And it’s a math concept that is well known. It’s just not taught in the financial industry, despite it being probably the most relevant concept for finance, for investment. It’s the math terminology for the difference between, in a sense between arithmetic returns and geometric compounded returns. And one is a path dependent through time unique to each individual path, that’s non-ergodic. And one is a ensemble average of multiple participants in one period. And that’s the way the financial system functions when at things like expected returns and et cetera, and assigns probability waitings to outcomes. And they’re saying, well, I get asked this all the time when we talk to people about risk and tail risk and asymmetry, and they say, “Oh, but what’s the probability of that happening?” And I say, “Well, 100%.” They say, “100%? Well, it can’t be.” And I say, “Well, what’s your time horizon?” Because their time horizon generally is whatever’s remaining in their compensation period. So that starts at a maximum of 12 months and then decays every month down to 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1 and then starts over again.
But in a time horizon that is the life cycle, there will be recessions, there will be depressions, there will be default cycles, there will be losses. And so applying the compounded return function of systematic selling the puts, because there’s a high probability that it works this month is really poor risk management. Just very, very poor risk management. And it’s a fiduciary mindset that allows that to function, it allows banks to function the way they… It allows banks, let’s say hypothetically to do swaps with family offices where they’re literally making millions and losing billions.
Bilal Hafeez (00:27:17):
Yeah. And we’ve seen some cases of that already this year of course.
David Dredge (00:27:21):
It’s a bad f(x). It’s a very bad f(x).
Why allocation to bonds don’t provide the right downside protection
Bilal Hafeez (00:27:24):
And this goes on to another broader topic of alpha and beta and the 60/40 portfolios. So there’s this general movement in finance at the moment to say, “Okay, the 60/40 portfolio has done really well, or some bounce funds has done really well over time, but bonds are probably too expensive. So you should just come up with factor-based investing or add private equity.” There are all these different ways to kind of juice up your returns. And so that’s where the differentiation seems to be in terms of the fund management industry of like, “Okay, how can we build the better mouse trap?” What’s your thought on that?
David Dredge (00:28:01):
This is what I talk about all day, every day, as I said earlier on, protect and participate. And so it comes down to convexity. So the 60/40 model is the real-world application of the problem with non-ergodic compounding and losses. So if you bet everything, you put 100% in and you’re on the losing end of it, you may not be able to compound back out. So the Kelly criterion, another thing your viewers can go and Google if they’re not familiar with it. The Kelly criterion basically says the solution to that problem is to de-lever your exposure. And so the practical implementation of that in the financial industry has been to reduce your participation in the higher risk growth asset by holding out a portion, the 40 or whatever fixed income to keep you from going bankrupt, from hitting the insolvency barrier. Now, a far better answer to that problem is insurance. If you can insure against the losses for a reasonable cost lost and put more money in participating, it inevitably forces you into the winning branch of the binomial decision tree in this game. And so that’s the, again, sort of a mathematical game theory concept of it. But the simple premise is, and I talk about my football analogy, hire a good goalkeeper and put more goal scores on the pitch. And just like in the financial markets where the key to compounding is how you perform in the two percentile tails, the 10 worst months in a 40-year S&P period and the 10 best months out of 480 months contribute almost all of the compounding that are long-term compounded returns. Just like in a football match, what happens in the two percentile of time in the two goal boxes is what drives the outcomes, not what happens in the middle of the pitch. And yet we focus on those other months and all the 96 percentile of outcomes because that’s what we see most of the time. And we tend to see investment strategies that actually destroy compounding in the wings. You miss up the big wins and you participate in the big losses and that’s destroying the compounding.
So the 60/40 model and its derivatives, risk parity, et cetera, have come through the greatest period imaginable for that strategy. You’ve had nothing but bull markets in equities and bonds for a 30-year period and you’ve had the central bank imposed reaction function of the portfolio benefit of negative correlation between bonds and equities. So it’s a reduced volatility, both legs have had maximum return over that period. And you still would’ve been way better off owning long volatility protection and more equities. Because the opportunity cost of owning the fixed income, particularly in the last 10 years, relative to what you would’ve earned having more of that capital at work in growth assets has been a far bigger cost, again, back to our example about non-recourse leverage, of owning vol and owning more equities.
So having something that has an explicit risk mitigating asymmetry that allows you to put more money in the game has paid off far, far bigger even when your traditional 60/40 portfolio has performed the best it could possibly perform. Now, looking forward, how well is that 60/40 or risk parity going to perform? It’s performed as well as it could from seven and a half percent on bonds to one, how well is it going to perform from one? How much leverage do you have to put into risk parity now to replicate the benefit you got from that leverage on the way down in rates?
How much reliance do you have to have in the ongoing central bank reaction function to generate the negative correlation that didn’t exist prior to Allen Greenspan. That negative correlation never existed prior to a change in central bank policy. Bonds and stocks used to be positively correlated in market selloffs. And you could argue in March 2020, when it really mattered that they were positively correlated, thus driving the Fed and the central banks to step in and buy every asset they can get their hands on and stop that unwind of uncapitalised tail risk and leverage in the fixed income markets. Now, the G30 paper and the Fed’s announcement of standing repo facilities as a part of a sustained effort to protect the unwind of the leverage inherent in the fixed income markets.
Bilal Hafeez (00:32:49):
Yeah. Now, that’s all really good points. So in essence, people who have had some version of the 60/40 or risk parity portfolio, have benefited from central banks shifting the correlation in their favour and this incredible bull run that we’ve had in both asset classes in both bonds and equities. But you are arguing that one is, we can’t be assured of that protection from the central bank. Plus also, it’s in some ways inefficient to allocate to bonds as your downside protection because that’s a very crude way of doing this because of correlation and evaluations and whatnot.
Getting your defense right, insurance and long vol strategies
Bilal Hafeez (00:33:28):
So can you give an example of this long vol strategy that you’re talking about as a better way to limit your downside? I mean, what are we talking about here? Buying a series of puts across multiple asset classes and you just constantly have this portfolio and then that allows you to allocate more risk to the higher risk assets like equities. But how does a long vol side of the equation work?
David Dredge (00:33:53):
Yeah. And that’s a very interesting and challenging topic. So if you think about, again, using my football example, the industry who has defined as its standing objective short-term returns. So in football terminology, goal scored per game. Where the end capital holder who are the fans of the football club, what they really want is terminal capital value or standings at the end of the season, but they’ve somehow allowed the coach to negotiate a goal scored per game performance metric. And so, again, using the 60/40 model, the coach has said, “Well, I just want people to score goals. And the only way I measure people is by goal-scoring metric.”
When you think about the investment industry, there’s only a return metric for measuring anything. So he doesn’t want a goalkeeper because the guy doesn’t get him paid because he doesn’t score goals, but he also doesn’t want to lose his job. So he puts some goal scores on his 60, let’s call it, and then his 40 are his defensive midfielders, guys that he hires to diversify, that play defense. But he still incentivises them to score goals. He still chooses them by their return dynamics. And then makes an assumption that somehow they’ll be on the right side of the pitch when it’s time to play defense, even though he is paying them to score goals. And that tends not to be the case.
So you end up with guys that are mediocre goal scores. They underperform good markets, fixed income. Don’t go up 30% in 2019 like equities do and levered carry or carry strategies embedded in hedge funds or whatever don’t participate in this 30% equity upside in 2019, but then do participate in the downside in March 2020 because they’re not playing defense. They inevitably end up being positively correlated at the wrong time. So the premise is get a goalkeeper, get rid of the defensive midfielders, get rid of as many of them as you possibly can, hire a goalkeeper, put more goal scores on the pitch because all that matters is cutting off the downside and participating in the upside. Now, the challenge is in the industry and the way it works, to your question, what’s a good goalkeeper? And how do you measure a goalkeeper if you’re only metric is goal scored?
Bilal Hafeez (00:35:55):
Actually, that’s a good point. There’s actually a more fundamental question of measurement here that we’re so ingrained to think about everything in terms of returns that we’d hire a goalkeeper that can score goals.
David Dredge (00:36:06):
So if you think about, and so there’s only a, really a handful of guys that do what we do that are full-time goalkeeping only. I am definitively not an absolute return strategy. I’m not running absolute return strategy. I’m only playing goalie. I’m only playing goalie so that my clients in whatever form were working with them can put more goal scores on the pitch. They’re not paying me for goal score that’s their job. I’m only playing goalie. And so you can think about it like insurance. Would you evaluate and compare insurance by how much it costs? You wouldn’t, right? You’d probably ask, “Well, how much insurance coverage is there? What am I covered for?” You wouldn’t just say, “Well, that insurance costs $1000 a month and that one costs 1500.” I’d like the 1000 one better. It doesn’t mean anything. So the challenge for goalkeeping is very different and it’s a very different mindset to investing. So your contra investing is very different to investing. Investing is modelling the denominator and targeting the numerator. So you use something like value at risk, some flow risk measure or how much risk I’m taking and then you go out and target the return you want. And then you evaluate strategies and then you make your investment decisions and then time is your friend. You accrue interest in coupons or capital gains. And you just go on to look at the next investment opportunity. Goal keeping is very different, or hedging or contra risk because you’re modelling the numerator, how much potential coverage might there be and you’re targeting the denominator. This is what it will cost. And then time is your enemy because if I’m committing to a client that for whatever their needs are, I’m going to go out and purchase volatility, purchase convexity that will provide this level of sensitivity, well tomorrow because of the nature of time decay and the securities that we buy, which are all, they’re not perpetual securities like equities, they’re fixed date securities or options predominantly and similar time products, I lose sensitivity every day. And so if oddly enough, this is where my football analogy breaks down, goalkeeping is a far more active strategy than goal scoring in the real investment world. Because you have to deal with the foregone sensitivity every day. Whereas that foregone sensitivity in your investment strategies is a benefit. You’re accruing the earnings every day hoping nothing happen.
Bilal Hafeez (00:38:40):
Yeah. No, that’s actually a very good point because in some ways, I guess in the investment industry and on a personal investment basis, we almost do wrong way around where we spend so much time trying to gain the returns. We don’t even think about the downside. When you could simply just buy an index, S&P 500 or some MSCI World or something. And that’s probably enough to capture a lot of the upside and need to focus a lot more on the downside. So rather than spending all your time trying to capture those 0.5% gains every day and just having a rolling stop as your best risk management system and just, to forgetting about that. We’ve ended up in this suboptimal situation.
David Dredge (00:39:19):
Yeah. And I say this all the time to allocators. So you can imagine I speak to pension funds and sovereign wealth funds and endowments and stuff every day. But their willingness to focus attention and costs and pay fees and hire managers to take on correlated investment risk, and then their resistance to do anything about protection, when in a sense, as you say, and I joke with some of my friends that have been in the sovereign wealth fund business for a long time around the world, that all they really need to do is just hire a bunch of a handful of execution traders to buy the one of every equity in the world until they run out of money and then built convexity to manage the correlation risk. That’s it. And the only part that you should be actively working on is that negatively correlating part, the protection part, the other stuff is sort of takes care of itself. The beautiful thing is you can in a sense, create convexity to the upside through owning equities because equities are a call. It’s a call option. It’s got limited downside. The most you can go down to is zero and you can participate on the upside infinitely. And so just own that and own that upside potential and convexity and then go and figure out how to protect the downside and how to deal with the correlation risk. That is ultimately the risk that pretty much any major global investment portfolio has. And I’ll argue pretty much anybody has, is really correlation risk. When it hurts, it’s correlation that is hurting.
Bilal Hafeez (00:40:47):
Yeah, yeah. And so in terms of the practical side of this very active way of protecting your portfolio, what does that entail?
David Dredge (00:40:59):
Yeah. So like I said, there’s a handful of people that are in that business and people do it different ways. And just like you would advise an investor to diversify their investments, we advise investors every day to diversify their hedging strategies. So there’s plenty of guys that are doing systematic VIX type trading strategies. So you go to Man and invest in one of their algorithmic VIX strategies that is trying to create that negatively correlating downside asymmetry that way. There’s Nassim Taleb’s affiliated business, Mark Spitznagel, and how they do it using the S&P puts and stuff. There’s a number of different ways to do it, but the gist of it is something that is actively investing in long volatility, convexity strategies, that’s finding efficient ways to create asymmetry and then dealing with the time problem around the sensitivities that they own. And so we talk all the time about the importance of how we advise people in layering convexity, in building out long-term strategies, in building out efficient, it’s about efficiency. What’s your bang for the buck? Where can you create the most efficient thing? There’s all kinds of different ways people do that.
We’re very agnostic about underlying. We simply care about the supply and demand dynamics and volatility market and are just looking for imbalances on capitalised tails as I keep saying. We’re the people who are the suppliers of the volatility for accounting regulatory reasons don’t have to capitalise the tail risks that they’re taking. So I could subprime CDO, super senior tranches of subprime CDOs had a lot more risk in them than the banks were capitalising. And so that and the nature of how risk works in the financial industry, and particularly the banking industry, but in general, is that because of the way it measures risk, that imbalance those uncapitalised tails will tend to align with where the price of the insurance is the cheapest, because it’s the application of that leverage to super senior tranches of subprime CDOs that compresses their return to one basis point over US Treasuries, because they’re getting treated as an equivalent risk-weighted asset by guys who have access to unlimited leverage at exactly the time the risk is the biggest. So this comes down to the concept of self-organised criticality. Think of it as the forest fire risk mentality. The system’s measuring risk as the probability using historical data that they’re extrapolating into a normal distribution of the next lightning strike. When in reality, the risk is the amount of accumulated dry brush and trees on the ground. And that gets bigger and bigger and bigger the longer you go without a lightning strike.
Bilal Hafeez (00:43:51):
Yeah. So in some ways, actually, there’s ironically, the hedging costs actually become cheaper the bigger the risk is in some ways.
David Dredge (00:43:58):
Correct. Which is fantastic, Which back to your question about 60/40 and how do you replace the foregone portfolio benefit of the, now far less efficient 40? Well, just as the 40, so fixed income is that it’s all time highest valuation, lowest return, less efficient portfolio benefit, vol is at its cheapest. Risk in the system, I mean, again, risk, I’m defining risk is fragility let’s say. So the forest is at its most fragile when it’s got the biggest buildup of interconnected brush and trees. Well, risk in the system, the system is at its most fragile when it’s got its biggest buildup of interconnected leverage and credit and lack of capital supporting all those risks. Well, you can look at whatever measures you want to of, you can use, again, using Warren Buffet, your financial assets to GDP are at all time extremes. So that’s global debt is at all time extreme so the fragility is high, or conveniently when the fragility is high, the cost of insurance is low.
Bilal Hafeez (00:45:00):
Yeah. And just a question on implementation, obviously, it sounds like you end up using lots of derivatives of different sorts, all those sorts of things. Do you feel like markets are liquid enough and you get access to enough puts on different asset classes for you to be able to do this in reasonable size to manage the downside? And how’s that evolved over time? You talked about being baptised by the ’87 sort of crash onwards and that’s evolved over time. I mean, how do you find the implementation side of implementing convex strategies?
David Dredge (00:45:37):
Yeah. So people ask me all the time, one of the questions I get asked all the time from my friends around the world is, “How do you guys find all this stuff?” And the simple answer to that is we put a sign on the door that says, “We buy it all.” And all day long, the system comes to us trying to redistribute the imbalance of volatility supply that’s inherent in the system. Now, the bulk of what we tap into and where we’re looking for these imbalances is driven by famed Asian yield enhancing structured product business that we innovated back in the early ’90s at Bankers Trust. And so you think about all this stuff that volatility is embedded in, now increasing around the world is financial repression moves from not just Asia, but to Europe and the US as interest rates everywhere went to zero, not just Japan. And this plethora of stuff from simple here in Singapore, virtually every deposit in the local retail banking system is a dual currency deposit. So every one of those deposits, every single retail deposit are in Singapore is selling an FX option every time they place a deposit.
You think of every bond that’s been distributed in the last five years is a callable note structure. It’s a 10-year, two-year no-call. Well, that’s just a strip of Bermudan swaptions. You think of all the accumulator structures on equities in Hong Kong, the autocallable structures coming out of Korea, the Pivot, TARN, TARF, KIKOs that all the corporate treasuries are doing on Euro and dollar China, and then the mother of them, the PRD, power reverse dual-currency structures in Japan. And all of these things are just yield enhanced products that are embedding short volatility, that then the derivative structuring players. And that’s not just the big bank, that’s a gazillion people through private banking accounts, pension fund accounts, insurance accounts, corporate treasuries, retail depositors. That volatility then gets recycled into the system. And because the participants, the food chain of that, as a general rule is not accounting for or capitalising the terrorists.
So you think about the guy selling that vol embedded in a structure. Now, whether he knows that’s what he’s doing or not, they’re all accounting for the enhanced revenue of that short option premium that they’re collecting in some form, but not accounting for the risk of the tail that they’re exposed to. On the other side, the buyer of the option in the end, me, let’s say, if I took flows through the system is accounting for the cost of it, but generally not getting any sort of capital relief from the risk mitigation inherent in it. So inevitably what you end up with has supply and demand imbalance. And that creates opportunities and inefficiencies in the system that smart people can go out if they have the diligence and are willing to do the hard work and construct incredibly efficient, positively convex, negatively correlating long volatility hedges for correlation and volatility job.
Bilal Hafeez (00:48:34):
Yeah. When you go through all of those structures, that became really clear to me actually, there’s not a problem buying vol. That the world is selling vol. And so if you’re a buyer of vol, it’s a buyers kind of markets, especially if you view it in the way that you’re viewing it in terms of the potential benefit of doing that, rather than just as a cost.
David Dredge (00:48:57):
As I tell people every day, I spend most of my day trying to avoid getting waterboarded with volatility. Because everybody’s got it and everybody’s trying to get rid of it. And then of course the beauty of it, and don’t tell anybody because this is the big secret. The cheaper it gets, the more aggressively they want to sell it because their risk methodology is telling them it’s less risky. Again, at the time that it’s the most risk behind is the time that they’re willing to give it away at the lowest price, super senior tranches of subprime CDOs. They were at their all-time tightest when the buildup of leveraged supporting it and the lack of capital supporting that risk was at its greatest. And so banks with their value at risk methodology, thinks that their risk management, when they press F9 wouldn’t allow them to do when volatility was high, will allow them to do endlessly when volatility is low. But that’s my secret so don’t tell anybody about that.
The role of central banks in shifting equity-bond correlations
Bilal Hafeez (00:49:53):
Okay. No, I won’t tell anyone, just our small audience of podcasters. The thousands of people that listen to the podcast will hear this. Now we’ve kind of touched on this through our conversation, but we can’t ignore the macro context of the world that we’re in now. And in many ways, it’s the behaviour or the actions of central banks that has really introduced some of these imbalances in the system. I mean, what’s your thoughts? I mean, you talked about how Greenspan set up this era of switching the correlation between bonds and equities. Then obviously, since the global financial crisis, things have gone to a whole new level of intervention by central banks, not just by the Fed, but by every central bank in the world. What are some of your thoughts around this?
David Dredge (00:50:36):
Exactly that. So you can take everything we’ve been talking about, about portfolio risk or investment risk and just apply the same concept to economic risk, cycle risk. The central bank is the guy trying to put out every fire, all the while creating more fire risks by not allowing it to cleanse. And they’re endless incessant expansion of moral hazard is exactly what’s leading to the fiduciary system taking a whole bunch of uncapitalised tail risk and running too much leverage and doing stupid things based upon probabilistic expectation of x and completely allowed to ignore highly destructive f(x)s. And all the while assigning those uncapitalised tail bad f(x) payout to somebody else’s capital ,to taxpayers, and to the real nasty and the endless road to serfdom of imposing hidden inflation on the masses. The constant… And when I say inflation, I’m talking about the creation of money and credit that creates the wealth segregation as it inflates asset prices to the benefit of the few who own it and the disbenefit of the many. And recommended reading, go read Road to Serfdom. It’s not like anything you got taught in school, but it sure sounds a lot like the reality. And so this game goes on and on and on and they’re creating the fragility. They’re making the forest more risky all the time every day. And every time they bail out the system, buy assets out of the system, come up with standing repo facilities, they’re just expanding that moral hazard and making the system more fragile, more dangerous down the road.
Bilal Hafeez (00:52:20):
Yeah. And I guess we saw a taste of that in March 2020 when COVID first erupted and the volatility on treasuries and tips exploded to levels that you just wouldn’t imagine, a supposedly safe-haven assets. So what are some of your reflections of things we’ve seen since the advent of COVID in terms of the financial system? And obviously at the same time, we’ve seen more intervention on the fiscal side as well. So not just the central bank.
David Dredge (00:52:45):
Yeah. As you said, it’s reaching epic scale. And after a prolonged cycle of zero interest rates and expanded central bank balance sheets and risk-taking, you had a near cleanse out in March 2020, which was immediately cut off. And then all of that down again at a far greater scale and then a acceleration of inflation debt creation in the form of fiscal, even above and beyond what we had already seen buildup. And now finally, you’re starting to see the various measures of very narrow, not surprisingly central banks choose very narrow measures of price stability starting to show inflation and you start hearing about it, but the inflation has been there all along. It’s just been in things that they choose not to measure. And so the system is highly fragile, that doesn’t… You knew me, I’m not perishable or shy, I’m just about risk. And so the mistake most people have made in this cycle is they’ve not participated enough in the upside. And the reason they haven’t participated enough in the upside is they have inefficient or non-existent protection. So had they had better protection, they would have participated more. And that, whether you’d started that at the beginning of the cycle in March 2009 or you’d started that before March 2020, it’s still the same answer, participate and protect.
So we don’t believe in timing at all, we just believe in good prudent risk all the time. And what’s not good prudent risk is defensive midfielders that neither participate nor protect and a whole bunch of dead capital tied up in that. And so the system is very fragile. And like we said, at the very beginning risk isn’t what you think is going to happen risk is what hurts if it happens. Well, I think to the world, what hurts is a loss of control of price stability that becomes socially destabilising and either leads to a continued breakdown of socio-political stability or leads to a change in the central bank reaction function where they decide they have to shift their bias to doing something about it. You don’t have to be a complete rocket scientist to see that the system would have a significant problem if central banks lost control of rates to the upside.
Bilal Hafeez (00:54:59):
Yeah, absolutely. Yeah. And then I guess the follow-up to all of this is the system is fragile. It’s unsustainable, but it’s a mistake to think you can time the crash, so to speak. And so the mistake many people do is to say, “Okay, the system is fragile. There’s too much debt. There’s too much inflation. So I’m going to sell equities.” And then they then enjoy a massive drawdown because they’re shorting and the market going up. Instead, you should create these convex strategies to balance your long risk structure. So the mistake people make is they might have the right view systems fragile too much debt, but the implementation is all wrong because they try to be clever and time it and do a short equities, which is an extremely crude way. And in fact, this way, in some ways of trying to play that view.
David Dredge (00:55:45):
That the core of our conversation, they’re focused on x when what they should be focusing on is f(x). I say, again, all the time, don’t manage or construct your portfolio for what you think is going to happen, structure it for what you don’t know. Don’t structure it for what you think you know, structure it for what you don’t know. And as long as you’ve appropriately managed the risks of what you don’t know, you’re fine. And so whatever you’re assigning short-term probabilities and thinking that, “Oh, I know.” So in this window of opportunity, earning carry by selling options or levering high yield credit is a good idea for this window. “Okay, what don’t you know?” You don’t know a whole bunch? You don’t know that, “Geez, if equities went up 30%, I’ve missed the whole opportunity.” You also don’t know that if equities went down 30%, your levered to high yield carry is going to go down 50, and yet you only had a fraction of the potential upside and you had more than the potential downside. So what you don’t know, you can solve by owning a positively convex participating asset and highly convex protecting. And so in a sense in the longer term in this geometric compounding world, being long the straddle always wins. Being short the straddle only win sometimes.
The growing fragility in the financial system
Bilal Hafeez (00:57:01):
Yeah. No, that’s absolutely true. And just to kind of wrap up our conversation on this whole big picture thing, I mean, do you think today we’re in a more fragile situation than say 2007 before GFC, or say ’95, ’96 before the Asia crisis and before LTCM? Do you think today the system is more fragile than those other instances?
David Dredge (00:57:28):
Yeah. I always say they’re always the same, but they’re always different. Each of your previous examples, the key pockets of fire risk were specific. And I might argue that the fire risk is much more broad now. Every country is at their all time largest fiscal debt to GDP. Every corporate sector is at all time highs of debt. Now, what everyone will argue and the central banks will tell you is better this time is that the major banks are better capitalised, but they’re better capitalised on the exact same wrong measure of risk that they didn’t have… They had 8% Tier 1 capital last time on a completely focused measure of RWA risk. Now they have 10% on a completely bogus. As it turned out, when we closed out the CDS on Lehman, they would’ve needed 90.5% capital for the RWA. That’s how-
Bilal Hafeez (00:58:27):
They’re slightly more than their 10% target today.
David Dredge (00:58:31):
Yeah. So that’s how far off the RWA measure was for what the actual risk was. So I think the, again, I don’t have views. I think correlation risk is unprecedented right now. And I think the central bank unprecedented active management of interest rates everywhere in the world in a very coordinated main pain parody fashion has created a level of correlation risk across all asset classes. There’s nothing more important arguably to the value of assets than the discount rate. And now you have a globally coordinated manipulation of the discount rate and a obvious unprecedented potential of the dollar failing as the most recent experience in a fiat reserve currency. And that creates a instability and a fragility in the system that I think is very unique. And I don’t think you’ve ever seen an environment before in such a global perspective where sensitivity to volatility in discount rates is so high.
Bilal Hafeez (00:59:36):
Okay. Now, I just wanted to wrap up our conversation with a couple of personal questions that I ask all my guests. So one was, what’s the best investment advice you’ve ever received?
David Dredge (00:59:47):
Focus on the downside. Again, when I started at Bankers Trust, this was back in the good old days of Glass–Steagall where we were not inside the moral hazard regulatory protection of the banking system. So if you think of Glass–Steagall, Glass–Steagall was actually a deregulation back in The Great Depression. It said, if you’re a bank and you get deposit insurance, this is all that you’re allowed to do and you’re protected. You’re a narrow bank. If you’re an investment bank, you can do anything you want, but there’s no protection. So you’re on your own. So if you want people to do business with you, you need to be able to justify the riskiness that you are.
So when I was at Bankers Trust in the early days, my performance objective was a capital allocation. Even though I ran a franchise business, my performance was based upon the preservation of growth of capital. Once Glass-Steagall went away and we went inside Basel I along with all the other investment banks and we came inside the moral hazard, risk ceased to be my responsibility and became the regulators responsibility. And so now my performance objective was maximize revenue following this BIS regulatory capital guidelines. So it became a very different optimisation function. And over time, as we saw in 2008, that definitively involved to an optimization around maximizing short-term compensation around a formulaic process of accounting revenue. And the risk was somebody else’s problem. And so guys like myself and Nassim Taleb who also started his career at Bankers trust and people who came up in that world and the early people of hedge funds, Paul Tudor Jones or George Soros, et cetera this mindset that it was all about capital preservation and then figuring out ways to participate in the upside.
It wasn’t about systematic vol selling programs. It wasn’t about levered carry, it wasn’t about things that I would call other people’s money traits. It was about capital preservation. And so protect and participate, protect and participate, protect and participate, it really is all there is to it. And I’m lucky because I have a natural interest in a protection business and protection strategy. So the system doesn’t make it easy for the retail investor to protect. It’s very easy to forego liquidity. It’s hard to store liquidity. It’s easy to buy an asset. It’s easy to buy a stock. It’s easy to buy a bond. It’s hard to issue a stock. It’s hard to issue a bond. It’s hard to create liabilities. It’s much easier to create assets for the common man.
Bilal Hafeez (01:02:15):
Yeah. No, no, that sounds great. And then the other question I had was, how do you manage your information and research flow, or overflow, I should say? It’s easy to be overwhelmed. So I mean, how do you do it? I mean, you’re very thorough. I know. So you must have a system or maybe you don’t have a system, I don’t know.
David Dredge (01:02:31):
So one thing that we have to be careful with, because we’ve been in markets our whole lives and we fancy ourselves semi-engage people, you can get overwhelmed with macro stuff and economic stuff, which isn’t really relevant to our job. We don’t really care about that stuff, although we’re curious and we’re interested and et cetera. Where it matters for us is the research around the supply and demand dynamics of the volatility markets that we’re engaged in. And we’re lucky in that sense because they want to sell it to us. And so we are only a handful of us and we’re involved in volatility markets in every asset class around the world. If somebody calls us and says, “Hey, we want to sell you this.” And we say, “Well, explain it to us. Where does it come from? What is the product that’s driving it? What are the risk metrics around how you guys treat it, how the end client treats it? How much is there going on in the market? In what format is it getting done?” So really what we’re focused on from a research perspective is the dynamics around volatility, supply and demand. And we can narrow that down to things we’re interested in. And the things we’re interested in is because someone’s trying to sell it to us. Because they’re trying to sell it to us, they’re usually pretty cooperative in telling us what we need to know. And so the trick for us is really focusing and not getting distracted. It’s another Nassim Taleb comment if you ever hear Nassim speak. People ask Nassim about the importance of data and you need more data and all this, you need AI and algorithm and data and data and data and data and data. And he points out from a risk management perspective, if your task is crossing the road, you don’t need to know the color of somebody’s shirt in the window on the other side. All you need to know is there something of this size moving at this speed coming down the road. And that’s a little bit us. We don’t need all the noise and distraction and et cetera, we just want to know very specifically, is this activity creating uncapitalised tails in the system that we can structure solutions on behalf of our clients that create negatively correlating asymmetric goalkeeping dynamics? And so it’s about focus for us. And most of the stuff that we’re looking for isn’t getting spun off on Bloomberg or et cetera. It involves a conversation. It involves knowledge and talking to people who know the Basel III accounting rules and how that works and understands how value at risk gets calculated and then how people are using 18-month or 12-month data series and the difference that makes. And they know something about how people are modelling volatility and using the interest rate space, using Sabre models and tweaking the models for volatility or volatility assumptions and say the alpha-beta row and understanding those dynamics. And again, I’m somewhat overly familiar with some of those things because a lot of those things were invented back in our Bankers Trust days, where we were creating rules of thumb for how you priced and managed risk that eventually then people were developing local volatility and stochastic volatility in Sabre models to back out market prices into volatility surfaces. To the thing that a lot of people don’t realise about those models, those models aren’t determining the price, the price is determining the model.
Bilal Hafeez (01:05:45):
Yeah, that’s interesting. That’s a good point.
David Dredge (01:05:48):
And then what ends up happening is the imbalances of supply and demand create pricing anomalies that then get interpreted into models of surfaces that then if you read them right tell you things. Tell you where the imbalances exist.
Books that influenced David
Bilal Hafeez (01:06:04):
Yeah. And then there’s opportunity for you to get something of good value then. Last question is on books. And I love reading. So I always ask this. So which books have influenced you the most, either in the work context or even at a personal level?
David Dredge (01:06:18):
Well, so again, given what we do, we’re very book-driven in the work world. So I think the most important book for risk management is How Nature Works, which is Per Bak, a guy named Per Bak who’s a physicist. Book on how nature works. And so that’s the core book on what is known as self-organised criticality or the sand pile theory, forest fires and earthquakes and the build out of self-organised criticality and how the avalanche is caused by the last drop of sand. And it’s the connectivity of the buildup of the sand pile, the interconnectedness and the instability and fragility within it that is the risk. And that’s really how nature works and how I’ll argue markets work and economies work and any complex adaptive system works. And so that’s a critical book for people to understand risk. The mathematics of a lot of what we do in markets is a Benoit Mandelbrot’s The Misbehaviour of Markets, which of course is the mathematical premise behind much of Nassim Taleb’s writings in his fantastic book. So Nassim’s Incerto series is an absolute must read for any professional financial manager, but also for any personal financial manager. It’s the best anti-fragility and skin in the game and black swan, et cetera, are all just building on this premise of self-organized criticality and endogenous risk and et cetera. And then I think from the societal impact of bad fire management, I think The Road to Serfdom by Friedrich Hayek tells the truth better than any other economic tax I’ve never read.
Bilal Hafeez (01:07:57):
Yeah, yeah, yeah. Yeah, no, it’s a very powerful book. I think I agree. And these are great, great book actually. And we’ve recently taken on one or two graduates our team. So I’m actually formulating a reading list. So these are great additions. Some of them I had already, but How Nature Works, I didn’t have. I think I have actually read that book. It’s good you’ve mentioned this.
David Dredge (01:08:16):
So Per Bak is a physicist and a group of guys developed what’s known as self-organised criticality, which they then computerized and studied through the sand pile methodology, dropping a grain of sand, dropping a grain of sand and number of, obviously, that’s then expanded into a number of things. There’s a good book by a guy named Buchanan, Mark Buchanan called Ubiquity that’s more of a layman’s version of that that’s come out recently. And even Mervyn King’s recent book basically is on the same premise.
Bilal Hafeez (01:08:44):
Oh yeah. Yeah. Yep. I actually had him on the podcast last year and we talked about the book. And it was a good book. No, that’s all great. And if people wanted to follow your thinking, what’s the best way for people to do that?
David Dredge (01:08:57):
Yeah. We have a simple little website, convex-strategies.com. And I write a monthly blog letter that goes out to our investors and goes up on the website mid-month, each month and it’s open to the public. You just have to click the disclaimer button when you go there. And there’s some other information, et cetera, about our little Singapore company on there and some other interviews and stuff I’ve done over the years. But the blog there is a generally pretty interesting reading.
Bilal Hafeez (01:09:22):
Yeah. I really enjoy it actually, since you pointed it to me. It’s a great read. It’s refreshingly different from a lot of other type of investor blog that you get out there where most are the ones that are just recycling the same debates, but you always have, you talk about the macro, but then the way you then talk about ergodicity, convexity, you give examples of portfolios where your long vol. I mean, it’s fantastic. It’s real eye-opening stuff. So I’ll include a link on our show notes so that people can click on it very easily.
Bilal Hafeez (01:09:54):
So with that, I just wanted to give you, so my big thank you. It’s been a great conversation. I’ve certainly learned a lot and stimulus of ideas of how I can talk about investment and improve. How we talk about investments to the broader world as well. And hopefully, I get educated, or we’ll get educated, and everyone tries to look at this in a more sophisticated way.
David Dredge (01:10:14):
That’s what we always say we’re… People say, “Why are you doing this? This goal keeping thing is so hard work and so thankless work in a world that basically only rewards for goal scoring.” And we just say, “We’re just trying to help one person’s retirement at a time. If we can change the terminal capital outcomes for people, make a big difference in people’s lives.” I jokingly say all the time, “Fix your convexity, fix your life.”
Bilal Hafeez (01:10:39):
Yeah, I like that. That’s a good note to end on. So a big thank you and good luck with everything for the rest of the year and we’ll obviously stay in conversation as well.
David Dredge (01:10:48):
Great. Thanks, Bilal. I really appreciate it. Good fun.
Bilal Hafeez (01:10:50):
Thanks for listening to this episode, please subscribe to the podcast show on Apple, Spotify, or wherever you listen to podcasts. Leave a five-star rating and a nice comment and let other people know about the show. We’d really be grateful. Also, sign up to become a member of Macro Hive at macrohive.com. We’ll be back soon. So tune in then.
Bilal Hafeez is the CEO and Editor of Macro Hive. He spent over twenty years doing research at big banks – JPMorgan, Deutsche Bank, and Nomura, where he had various “Global Head” roles and did FX, rates and cross-markets research.
(The commentary contained in the above article does not constitute an offer or a solicitation, or a recommendation to implement or liquidate an investment or to carry out any other transaction. It should not be used as a basis for any investment decision or other decision. Any investment decision should be based on appropriate professional advice specific to your needs.)
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