Transcript: Sandy Rattray



The transcript from this week’s, MiB: Sandy Rattray, CIO, Man Group, is below.

You can stream and download our full conversation, including the podcast extras on iTunes, Spotify, Stitcher, Google, Bloomberg, and Acast. All of our earlier podcasts on your favorite pod hosts can be found here.



RITHOLTZ: This week on the podcast I have an extra special guest.

What can I say about Sandy Rattray? He is the Chief Investment Officer of Man Group, which manages over $125 billion. He is the co-inventor of the VIX index. He has an incredible career, both in equity, research for derivatives, as well as systematic investing. He’s just a rock star. I don’t know what else to say about it. The — the track record that Man Group has amassed, as well as how they’ve pushed forward portfolio construction theory is really incredibly, incredibly influential. Not only was he the co-inventor of the VIX index, but he has written extensively about risk management and have designed portfolios and, you know, what to expect when you’re expecting a Black Swan, which you, by definition, can’t know what to expect and — and how to build strategies that give you some degree of protection against this. If you’re remotely interested in hedge funds, asset management, quantitative strategies, the VIX and managing risk, well, strap yourself in because this one is a good one.

With no further ado, my conversation with Sandy Rattray of Man Group.

VOICE-OVER: This is Masters in Business with Barry Ritholtz on Bloomberg Radio.

RITHOLTZ: My extra special guest this week is Sandy Rattray. He is the Chief Investment Officer of Man Group. He is also on the Executive Committee and the Responsible Investment Committee. He is perhaps most famously the co-inventor of the VIX index.

He has also run a number of different systematic strategies for Man and other organizations. Man Group’s assets under management are over $120 billion, and Sandy is the co-author of the book, “Strategic Risk Management: Designing Portfolios and Managing Risk.”

Sandy Rattray, welcome to Bloomberg.

RATTRAY: Great. Thank you very much, Barry. It’s good to be with you.

RITHOLTZ: So, you have a really interesting background. You’re deeply steeped in mathematics. How did you find your way into the investment business?

RATTRAY: So, it’s a — it’s a long story. I — as a — a teenager I thought I would become a theoretical physicist, and that was my ambition. I went to Cambridge University to study physics, and I really discovered a number of things at that time.

Number one, I was — I thought quite good at physics turned out that I surrounded myself with a whole bunch of other people who are also pretty good, and really standing out was hard. And second, I think, at the time, the amount of innovation that was taking place in physics seemed to have sort of dropped — dropped a little bit from the 1970’s, and — and it was a little slow period in the late 1980’s. And so, that made me think, well, maybe I could use these math skills for something else, and that really got me into thinking about finance.

So, I — some people duck out of physics having done PhDs or — or taught at universities, I ducked out a little bit earlier on. And that got me into then thinking, well, I should use these skills. I — I end up joining Goldman Sachs. And — and there, again I learned something, which was I thought the exciting bet would be the corporate finance areas or advising on major corporate transactions. And what I realized was that that didn’t really use the — the quant skills that I had. So, I did that for a couple of years and then I moved over to first fixed income research, then equity derivatives research, and — and then finally transitioned out of that into — into more proprietary trading and then into fund management.

RITHOLTZ: So, let’s build off of that. You — you did a lot of work on derivatives and fundamental strategy at Goldman. You then go to Man where you’re running things like systematic strategies and AHL. What — what was Man AHL focused on when you were managing that?

RATTRAY: So, when I arrived at AHL, I — which was end of 2012, was really a futures trend following business. It was CTA. And CTAs have been having a pretty difficult time really since the end of the financial crisis. They had a tremendous 2008 and then that really done nothing in the following years. So ’09, ’10, ’11, ’12 are all years, which essentially added up to nothing. So, it’s a fantastic crisis year, very few asset managers could say that 2008 was a great year, but AHL could definitely say that.

But then you had a long dry period, and people were starting to say momentum doesn’t work anymore, it’s broken. And I think what I really did when I write (inaudible) was to say, well, I’ve been involved in all sorts of different quant strategies in my golden years, and I can use a — a much broader perspective than maybe the future’s trend followers have and look to develop a much wider range of systematic strategies.

So, when I arrived, we had a handful of models. Today, we’ve got 300 to 400 models miles running at AHL, so we really expand the number of models we’re using. We expanded the number of markets that we’re trading, so we used to trade futures and F.X. markets. And Man Group had started trading OTC markets, but it was still quite small, and we really picked up and start trade a much wider variety of markets. Now we trade around 700 markets around the world using systematic models.

And then finally, we came up with different — you know, many different types of funds, so very short-term funds, funds which are more fundamentally-driven, funds which are — maybe trying to provide more protection characteristics or funds trying to maximize the sharp ratio. So — so we really try to grow quant into many different areas.

And I suppose my advantage coming into a place like AHL is that most people in those — in AHL and then the competitors had really grown up and have their whole careers in the — in the CTA or the futures trend following business. And I had had none of my career in the futures trend following, and I — I — but I had all these other influences that I could bring in. And so, that really was how I worked with the team now to significantly expand the — the business, which was having a very difficult time. And I arrived and had declined to less than $10 billion of assets in the …


RATTRAY: … AHL units. And — and today we’re, you know, many times larger than that.

RITHOLTZ: So, I want to focus on something you mentioned in passing, but it’s so relevant to what we’ve been seeing in the markets recently. You said that momentum as a factor seem to have been fading. We have seen other factor-based investing like value go long, long periods of underperforming. There’s so many different questions I — I can ask you about this. Let’s just start with, is that the nature of any factor or any specific trading edge that they only last so long before eventually everybody wises up to them and the alpha gets arbitraged away? And do you see this sort of edges disappearing more quickly these days than they used to in a, perhaps, kindlier, gentler era 20 or 30 years ago?

RATTRAY: So, I agree actually with everything you said, Barry, except for the lost bits about kindlier, gentler era. From my memory 20 or 30 years ago, it was probably less kind and less gentle than it is today. But let’s — let’s start with factors. So, I think one thing so it’s been interesting over my career is nobody really talked about factors apart from a very small sort of quant group 20, 30 years ago.

Today they’re in — you know, they’re — they’re sort of part of all our portfolio managers at Man Group, whether they’re quants or discretionary managers, everybody talks factors. And so, that’s been a big change. They’ve become sort of part of, you know, just sort of general dialog when people are talking about markets.

The — the second thing I’d say is that I — I don’t think that the — the core factors, which have been around a long time are going to disappear. And for me, you know, as a European, I was working in New York in the late 1990’s into the 2000’s, and I remember looking at front page of the Wall Street Journal one day, and on it said, “Value investing is for old people.”


And — and I — you know, the European, obviously — you know, Europeans want to live in the old houses. Actually, in the U.S., people mostly want to live in new houses, so there’s a big sort of didn’t quite understand the — the — the — the extent of the — the statement there. And it was a ridiculous thing to say as a young person be included in the front page of the Wall Street Journal right in the tail end of the tech bubble and just before huge out performance of — of — of value stocks.

So, these factors — and we should talk about, you know, which are the — which are the factors that are likely to persist and which are not. But factors like value, for example, I think generally don’t have particularly high sharp ratios, so their — their returns adjusted for risk are not particularly high. But the idea that buying cheap stocks will never work again, I — I have never thought that was a sensible …


RATTRAY: … thing to — to say or think. But every now and then, you know, that’s what this fellow on the front page of the journal said 20 odd years ago. So, I think factors — at least a core set of factors are very lightly to persist, but it won’t give particularly amazing risk-adjusted returns, but I think they are likely to give you positive risk-adjusted returns over in a relatively long cycle.

I would say though that one of the things I’ve seen in the last 10 years or so is as people thought they understood factors, some people start to find hundreds of these things …


RATTRAY: … and I don’t think there are hundreds of real factors. I think there’s a small handful of factors. And this explosion really is another fitting exercise as people finding patterns in the data that don’t really exist. And I think that’s something that people should be very wary of, you know, seen data providers and firms sell sort of libraries of factors with — with, you know, literally hundreds of these things. And — and I don’t think that’s going to be a source of returns.

The — the final thing I should say is that you mentioned momentum, and momentum is quite an interesting factor because there are two very different definitions of momentum. One is really used by equities people, and they will go long the positive momentum — price momentum stocks and short the negative price momentum stocks. They sometimes do it with earnings as well, but basically long the stocks which have been outperforming and short the stocks which have been underperforming.

But then there’s a very different definition of momentum, and that’s what the CTA is using. They don’t — they don’t look at the price move against anything, they just do it in absolute terms and they tend to do that in macro markets, so they’ll trade the S&P 500 or the — or the — the DAX or the — the euro or gold or something like that. And — and that’s a much different definition because it’s not — it’s not going long one set of markets and one set of stocks and short another set of stocks. It could be long everything or it could be short everything. And it gives you a very different type of return profile, but second type has a very nice feature, which is that it barely reliably will do well in bad periods in markets.

So, I talked about how, for example, AHL 2008 was an excellent year. Well, not many strategies could say 2008 was an excellent year, and that’s because that second definition of momentum, what I would call “time series momentum,” the — or univariate momentum, that definition of momentum has very good protection-like characteristics. It’ll pick up on a trend, especially a negative trend in markets and — and jump on that trend.

RITHOLTZ: So, it sounds like the price momentum seems to be relative while the time series has a persistence that gives it a very different characteristic or am I over simplifying that?

RATTRAY: No, no, I think that’s exactly right. So, I think, you know, the — the most investing strategies including price momentum in equities are — but most investing strategies have what people like me would call a “left tail,” going to make you money most of the time, and then every now and then they serve you up a non-pleasant surprise.


RATTRAY: Time series momentum, those are the opposite. Time series momentum, most of the time gives you pretty boring returns, but every now and then it will give you a very positive surprise. And — and that’s really rare in investing strategies. And — and from my perspective, that’s — you know, that’s a very attractive characteristic when you’re building portfolios to have a bit of something, which does the opposite of most other investing strategies.

RITHOLTZ: Let’s talk a little bit about the VIX index, which you were the co-inventor of. Tell us how does one go about inventing the VIX index.

RATTRAY: Well, you know, Barry, in short you get lucky. So …


… the — the story behind it is, as we talked about in our earlier segment, I was working in New York, I used to go and see clients. And every time you went to somebody’s office, the dead TV screen in the — in the fire — in the entrance area, and they would have prices of all sorts of things coming across that screen, you know, the sort of the price of crude oil, the — the treasury bond yield, the S&P 500 level, that sort of thing, and it would have the VIX on it, and so the world of VIX, but that was — the VIX was the only thing that seem to come across the screens that you couldn’t trade.

And so, the story really came because a colleague of mine at Golden Sachs came to me one evening and said, “You know, I had this call from a client who wants to do a trade on the VIX. Could we do that?” And my colleague Devesh Shah rab options trading, and I ran the derivatives research a bit of Goldman. And we got our I heads together, and I went and found the formula for the VIX as stood as — as preexisted and (inaudible) tell you that this wasn’t possible for us to do a trade on that. It wasn’t designed in a way that you could hedge a — a — a trade on the VIX.

So, we came out with a kind of crazy idea, which was, OK, well, this VIX thing, which is owned by the CBOE, but you couldn’t trade it and there’s a good reason why you couldn’t trade it because you couldn’t hedge it. So why don’t we change it? And so, we came up with a completely different formula. It turned out to give fairly similar levels to the old VIX, but — but it was a completely different formula, didn’t use Black-Scholes at all.

And we talked about, hey, this — this formula actually you could hedge a — a futures contract on or something like that. And so, what we then did is I was quite friendly with a fellow called Bill Speth at the CBOE who’s Head of Research there. And I called Bill and said, “You know, you have this VIX, but you make no money out of it because you just publish this thing and doesn’t give you any income. And we’ve got an idea how you could change it to make it something that could be traded and maybe could launch futures contracts on that, and so that might be interesting to you.

And then I launched into a long description of the math behind their formula. And — and Bill very wisely said, “You know, maybe you could send me a letter with that formula.” So — so I sent him a letter and — which was actually with the benefit of hindsight quite helpful because now I have a quite clear record of when we communicated this formula in 2003 to the CBOE.

And — and within six months we had a new VIX being calculated using this new formula. And another six months later the CBOE, which until that point was only an options exchange. I have launched futures contracts on it.

And so, there was a series of sort of, you know, lucky moments in there. A client came and asked the question. I happen to know Bill at the CBOE, so I — I knew somebody to call. They happen to be interested in — in launching futures contracts and our timing was — was spot-on. So those are a whole series of — of bits of luck along the way.

And — and what really happened after that is another good learning experience for me, which is I had a boss at the time who said, “Look, you should talk to all the sales people and find out if they’re going to bring in business on this new VIX thing that you’ve been working on.” So, I spoke to the sales people and we did little survey. And, you know, I was going to retire on the proceeds of this survey.


It was just amazing how much business we were going to do.

Day one comes along. I wait for the phone to ring.


And it doesn’t ring. Day two comes along, the phone still doesn’t ring. And by day three, you — you sort of get it, you know, it’s — nothing is happening. And amazingly, the first significant trades we got done were actually with investors outside of the U.S. And they were the people that have got the early stages of this new market in — in VIX going.

The other thing that happened was my boss said, “You should call, you know, some of the other banks and — and see if they’re going to support this thing.” So, I called nine other banks, and nine out of nine said they had no interest in supporting it. So, it wasn’t a particularly auspicious beginning, you know, the — and it — it took a little bit of persistence.

Now, today, it’s a huge market and — and it trades enormous volumes, but it’s a good feeder lesson in terms of how difficult it is to get something new going.

RITHOLTZ: So — so let’s talk a little bit about what’s the VIX index does and some of the misunderstandings around it. When you talk to people, especially traders on the equity side, they look at it as the fear index. It measures volatility. But — but to be more precise, it’s really measuring volatility expectations, right?

RATTRAY: Yes, but I think the — the word “fear gauge” or fear index is actually pretty accurate, but you — you’re also absolutely correct that what the VIX actually is is the market’s expectation of volatility over the next 30 calendar days, and so it is a — it’s a market price. And inevitably, because the volatility cannot mathematically go below zero, there’s no such thing as a volatility below zero, but it’s unlimited on the upside. You know, there’s no limit to how high volatility can be. Then if you go to the market and say, “Hey, give me a price for the next 30 days of volatility,” it’s generally going to overestimate because it’s going to have to protect itself a bit against …


RATTRAY: … the possibility of huge swings upwards and the fact that there’s a floor. It can’t go below zero. So, your description is absolutely correct. It’s the market’s expectation of realized volatility over the next 30 calendar days, but I have some features built into it. It’s always going to overestimate because you’re effectively selling insurance if you’re selling the VIX. And — and people don’t sell insurance cheap for the most part.

RITHOLTZ: That — that makes a whole lot of sense. I know that a lot of traders seem to conflate volatility with risk. How do you define the differences between the two?

RATTRAY: That’s a very good question. And I think, you know, it’s something I thought about a lot over the years. And there’s many different versions of this, I think. So, most models — most risk models do estimate volatility. They give you a VaR number, which is basically a — a manipulated volatility number or a — a risk in standard deviations or an expectation of loss or something like that.

And they’re useful numbers. But in the end, I’m pretty sure that both you and certainly I would never clue what the volatility of our personal portfolios was last year in 2020 in a very volatile year. But we have a pretty good idea of what the worst point is, you know, when — when we have the most losses or most pain in our — our portfolios. And that’s got nothing to do with volatility. That’s a drawdown.

So, in the end, actually, the risk that a lot of us really experienced and worry about is drawdowns, it’s not volatility, which is, you know, mathematical formula, which describes the shape of a — of a distribution. And that I think is something, which is difficult because estimating drawdowns is extremely hard. Estimating volatility is actually fairly straightforward, but the two don’t really connect.

And so, why do people estimate volatility? Because it’s useful, it gives you how wide the distribution will be. You can estimate it quite accurately. You can forecast it quite well as well. You can forecast volatility much better than you can forecast return. So, all of that is useful, but what’s not useful is that we don’t really worry rin the end about what our volatility was last year or what it’ll be next year. What we really worry about is how much we lost or how much we might lose, that sort of — that — that pain threshold, and volatility doesn’t really connect with that. So, unfortunately, the really useful statistic drawdown is very hard to estimate. Some people don’t really estimate it. The other statistic, volatility, is useful, but it’s, in my view, not the most useful estimate of — of — of risk because we actually experience it.

RITHOLTZ: That — that’s really kind of intriguing. So — so not only can you go long the VIX, but some people can go short the VIX, not — not exactly hedge if you have a long portfolio, but I guess if you short, maybe that — that’s useful. What do you think of — of how people have been using the VIX either as a risk management tool or as a way to get some non-correlated exposure to their — to their equity holdings?

RATTRAY: Well, I think there’s a few things in there. Firstly, the — the VIX and the price of futures on the VIX will nearly always disagree, and generally, the futures will be higher than the current level. So, you know, as we’re speaking now, the VIX is around 16, but our futures contract three months out who’s trading at almost 21, so five points higher. And that is a normal state of affairs. And as we talked about earlier on, volatility — because volatility can’t go below zero, then people — and it can go to an unlimited outside level than people generally the market will overestimate volatility to give a little bit of an insurance premium in there.

Now, in terms of trading and investing with the VIX, I think this thing is quite important to know. So, if you buy an ETF on the VIX, for example, then it is going to have to hedge itself with the futures contracts. And these futures contracts will trade a lot higher. I — I said, you know, 21 for September versus 16 now, so that’s almost a 30 percent higher.

And by September, one of two things have to happen. Either the VIX has to go up to 21 or the futures contract will go down to 16. More likely, the futures contract will go down to 16. So, I think people often don’t understand this when they’re buying a VIX ETFs that they’re not buying the level of the VIX they see on the — on the screen, on the television screens or on their Bloomberg terminals or wherever they see it. They’re — they’re buying effectively a future on the VIX, which generally is trading a much higher level. And so, they will have expected losses built in.

That is something which then some people on the other side have said, “Well, this is very exciting. You know, I can — I can sell the VIX at 21 in September, and I expect it’ll go to 16. I can make 30 percent in three months.” And they’re absolutely right, you can — and most likely will make 30 percent in three months, but — and the but is a big thing. If — if something bad happens between now and September then, you know, you can make very, very significant losses because the VIX can just, you know, very, very quickly go up to very high levels.

So people often do is they say that buying the VIX that gives me some protection against crises, if there’s a crisis and it’ll likely go up, and they’re right, but they do have to understand that it’s not the VIX going from the current 16 to say 18, it’s got to go above that 21 that’s priced in in September before you make any money, but it can be a — a protection strategy, an insurance strategy. And then you got people on the other side who say, look, I don’t expect something bad to happen and I can earn this very large insurance premium if I’m prepared to go short the VIX and you, of course, can do that through futures contracts, but you can also do it through ETF.

I think my real observation on this goes, you know, tried to give as clear an explanation as I can of how this is working, but it’s quite subtle. This is not a simple thing, and I think a lot of people that trade the VIX ETFs don’t really understand what’s going on underneath the surface of the ETF contracts, and there’s a lot going on underneath the surface.

RITHOLTZ: So — so let’s talk a little bit about people trading products that they didn’t really understand and — and who better to ask you, the co-inventor of the VIX. Back in 2018, we saw the notes that were based on the VIX, and Credit Suisse was one of the larger underwriters of these, just blow up and sent the VIX spiking. I kind of remember we kissed 50. I could — I could be wrong about that.

But that whole series of products, those short-term ETNs, XIV was one and SVXY was another, they — they just blew up spectacularly, as you’re watching this from your seat, what are you thinking about, gee, look — look, I lent the keys to the car — to the kids and they seem to have wrecked it.

RATTRAY: I think – firstly, I think your description there, Barry, is pretty fair. When we did the work — Devesh Shah and I did the work back in 2003-2004, the boss had asked me to do the various other things that we talked about, said, “You know, you should look at creating an ETF on this thing.” And so, we did and we got together with one of the very big ETF providers. And they said, “Well, look, maybe you could do some modeling of how this thing will behave.” And we did that and we concluded this is just not a good product. You know, people — it’s — it’s got some nasty characteristics, and so we decided along with that large firm that we should not sell ETFs on the VIX.

Now, other people took a different view, and so your analogy of kind of the kids getting the keys to the car is more or less accurate actually.

I think the — the — the — so I don’t like the ETF products mostly because they’re very complicated. They look simple on the outside, but underneath them they’re very complicated. And I don’t think people would understand all that complexity.

So, events that happened in February 2018 were the short VIX ETF, and the short VIX ETF kind of earned this insurance premium. So, lots of people — lots of Wall Streeter were happy owners of the short VIX ETFs. The problem with them is that what the ETF does then is that it issues units to people like you or I and then have to sell futures contracts against it.

If the price of the VIX does going up, they need to start buying those contracts back. And if it goes up a lot, it needs to buy a heck of a lot of them. And so, you have some volatility very late in the closing towards the end of the day, and I think it was February 5th if I remember rightly, 2018. And — and they need to buy heck of a lot of futures contracts in a very short period of time.

What did that do? It pushed the thing up even more, and so it kind of created its own volatility and its own noise in that period. So, I think that it’s a pretty good example of an unintended consequence from a financial product, and again, you know, it’s quite a complicated concept. A long VIX ETF is complicated. A short VIX ETF is very complicated.

And I — I think from that perspective, people probably had some surprising results that, you know, a lot of people lost a lot of money. Some of the issues of these short VIX ETFs made a lot of money at the same time. And it — it felt like a pretty bad state of affairs to me.

RITHOLTZ: Let’s talk a little bit about your book, which was written was Campbell Harvey who was a — a prior guest and — and just a — a delightful individual. What compelled you guys to write this book? This is a pretty in the weeds inside baseball sort of — sort of book.

RATTRAY: Yeah, you’re — you’re right, it’s absolutely in — in the weeds type of book. What have got us going on this was really a sense that for many portfolio managers, risk management is something, which comes afterwards. They build the portfolio and then the risk team do something later on and tell the mother it’s OK or not. And we thought that that’s actually a very bad way to run portfolios, and a much better way is to have the alpha side of building portfolios and the risk side to be equal partners. And that’s something that we’ve really tried to build as a culture of Man Group that risk is part of the investment team. It’s — as I sometimes put it, if risk is the police, if other people that come kind of knock on your door telling you’ve done something wrong, that’s — that’s not really a good way of running portfolios. What you really want is as you’re building the portfolios, the risk and the alphabets to — to come as — as equal partners.

And the reason for that is firstly huge amounts of damage tend to be done when there is bad risk management and stress periods. So, people unprepared for those stress periods, they make bad decisions and those stress periods lose a lot of money often crystallize losses, that sort of thing. So — so firstly, if you don’t have a proper risk approach to building portfolios when you enter choppier periods in markets, then you’re likely to make bad decisions.

The — the second, which I mentioned earlier on, is kind of surprisingly, it’s actually much easier to forecast risk than it is to forecast returns. And — and — and you can use that to give yourself more stable portfolios. And so, we were really trying to say that you can blend the alpha side of portfolio management with the risk side as equal partners, and you’ll build better, more stable portfolios, which will likely do better over the long run because you won’t end up making bad decisions during the — during the stress periods.

RITHOLTZ: So — so let’s talk about that last quote, it’s easy to forecast risk than returns. I’m going to play devil’s advocate and take the other side of that argument. Hey, we know over long periods of time what historical asset class returns are, and so we can reasonably forecast eight percent over 20 years for equities, but we can forecast the sort of black swans that show up every now and then that are just completely unexpected and are — are amongst the, quote, “unknown unknowns.” Tell me what’s wrong with that perspective that looks that extrapolating long-term returns versus, hey, we have no idea what the next random event is going to be.

RATTRAY: Yeah, I think what’s wrong with that is that you’ve tried to compare forecasting very long run returns and then said, but I need to forecast short-term risk. And so, let me sort of decompose that a little bit more.


RATTRAY: Many times people when they — when they forecast returns — and we’re all guilty of this — we — we end up being pretty influenced by what happened in the last month or two. And so, we say, you know, people — many people, for example, are pretty positive about equity market returns globally and — and maybe especially in the U.S.

And one of the reasons of that really is that we’ve had good returns, you know, really since March of — since April last year and people are extrapolating. They’re just stretching forward. But if you look at the data and if you look at the data over long periods of time, you find the correlation between past returns and next month’s returns is about zero. In almost all markets around the world — equity markets, bond markets, commodity markets — is just about zero. It has no — last month return’s have close to zero predictive ability telling you what next month’s returns are going to be.

If you not do that on risk and you can’t play the volatility of markets last month or the month before, the month before that, actually have very high predictive ability. So, people like me would call this the “serial correlation,” so the serial correlation of returns, in other words, from last month or two months ago or three months ago to this month’s return is — is — is close to zero. You might as well call it zero, so close to zero.

If you do the same thing in volatility and you can do this across equity markets in the U.S., but also across other parts of the world, bond markets, commodity markets, currency markets, that serial correlation is around 40 percent. That’s telling that last month’s volatility is actually telling you quite a lot about this month’s volatility.

And so, whilst you might be able to make a statement about, you know, 20-year expected return …


RATTRAY: … I suspect both of you and I will be — you know, at least 20 years older in that 20-year point, and whether anybody will really hold us to it or whether it’s useful observation will be, you know, tricky to — to — to really evaluate. But for most people, they need to have nearer term forecast in order to be able to make that decisions. And I think they make a mistake that they think they can forecast returns often by extrapolating from past month’s returns, and the evidence is that you shouldn’t extrapolate. There’s no extrapolation to be done was the risk you can.

RITHOLTZ: That — that is very parallel to what we were talking about earlier with price versus time series, so equities follow a random walk, but volatility and risk tends to be persistent and — and hence more likely to have some time series correlation. I think that’s what I’m hearing. Am I — am I saying that right?

RATTRAY: Yeah, absolutely, absolutely. The — the — there’s a very small — and what the CTA is trying to do or the futures trend followers is they — there’s — there’s a very small effect of being able to pick up some persistence in returns, but you have to do it across hundreds of markets and you have to do it consistently over time. And you’ll just manage to eke out a little bit of alpha by doing that. Volatility is much easier.

RITHOLTZ: So — so what should managers do proactively to prepare for not the known risk, but the unknown risk? And — and really just over the past 20 years, we had 9/11, we had the great financial crisis, we had the — the VIX meltdown, and — and more recently we had the COVID pandemic. How — how can a fund manager build protection against these black swans into their process?

RATTRAY: Well, so — so I think the first thing that a portfolio manager should do is realize that you cannot forecast these events. And I — you know, I speak a — I used at speaker conferences a lot when we’ve still had conferences. And, you know, people would ask me, well, what’s the black swan event that’s going to happen this year?


And I also – that was the most ridiculous question because, you know, clearly all of these events they’re unforecastable, and generally, the ones that you forecast will happen don’t end up being the thing that — that takes place. So, I think the first thing is to show a lot of humility about our ability to forecast what — what the bad events will be.

The only thing I can really feel confident about is that there will be more bad events in the future. You know, it seems that they just keep coming …


RATTRAY: … but they have different shapes and — and — and forms. And maybe as a side anecdote on that, we have an excellent risk management at Man Group and at the end of 2019 in a sort of planning exercise who’s giving you all the risks that could affect markets, you had about 20 of these things, and one of them was epidemic. And I looked at this at the end of 2019 and I said epidemic, well, I mean, like, you know, I don’t know much about epidemics, but I can’t say it’s impossible, but it doesn’t seem very likely, so we did exactly nothing about the risk of epidemic.

And if — if you got the word almost right, pandemic instead of epidemic but, you know, even if you have it on your list of things, which my risk manager did, it’s very hard to act on it. So, I think humility in terms of ability to forecast these things really important. If you think you can forecast, you’ll probably make a mistake by protecting yourself against the wrong thing.

The — the — once you’ve got over that and said, well, likely probably (inaudible) forecast the next bad thing, then I think what becomes much more important is, OK, now you need a strategy that is going to be relatively insensitive to the nature of the bad thing. In other words, whether it’s a tech bubble collapse or a credit crisis or, you know, something entirely different, a war or a pandemic or it could be any of these things, obviously, you need a strategy, which is going to be rebuff any of those things coming along.

And — and my own suggestion on this would be that it’s — it’s too expensive to buy put options. You — buying put options on the S&P 500, you can do every now and then, but you can’t do it all the time, it’s just — it just becomes too costly. And so, you’re going to have to have a strategy, which relies a little bit more on either assets in your portfolio, which you think are likely to do well in a stress period. That could be gold and my view is not terribly reliable, it could be gold. It could be U.S. treasury bonds or other government bonds around the world. Of course, if the problem emerges from the bond market, it’s not really going to help you.

And, you know, people, I think, forget that there have definitely been problems from the gold market. You just need to look back a little bit to the early 1990’s Oregon — or before then to see that they actually do plenty of problems that came from the bond market, or you could have some sort of trading strategy. And — and certainly for me, this time series momentum, which we touched on in our first segment, this idea that you — you can build a trading strategy like the CTAs have done, which relies on just a little bit of persistence in returns and — and looks for them everywhere, that can be a very good way of building a defense strategy.

So, in other words, if — if we describe a crisis — and I can’t tell you whether it comes from a war, a credit crisis, epidemic, something else, but typically in a crisis like that, you will tend to have equities going down. You will tend to have bonds going out. You’ll tend to have gold going up. It’s a bit harder to tell what might happen to energy prices.

But those moves tend to persist for a bit. They tend to, you know, equities fall and then they keep falling, and bonds might go up and they’ll keep rising. And gold is the same thing. As you can build a strategy, which encapsulates and tries to capture that effect, then you can build something, which is robust and is not depending on your ability to put your finger on what the next bad event might be.

RITHOLTZ: So — so in the book, you — you get into the nitty-gritty. You — you go over details of — of a new risk management approach to portfolio design. I want to ask how did those strategies do in back tests looking at ’08-’09, and how do they do in the real world in March 2020?

RATTRAY: Well, so for us, actually, I — I don’t think ’08 to ’09 really was back test because we were, you know, actually trading most of the strategies at that time, but — so I think we actually have a pretty good life experience.

And the — firstly, I should say March of 2020 was an extraordinary crisis, and all — all crises are extraordinary. But one of the things, which was most extraordinary about March 2020 was that it — markets fell very quickly. Well, we’ve seen that before, but then they reverted remarkably quickly and really the most similar crisis in terms of market action that you can put your finger on since the Second World War was the October ’87 crisis, so that — that very rapid fall you had, followed by an almost equally rapid recovery. So — so that might say, well, you know, if you fitted — if you sort of tested your crisis protection on all the slower crises, then maybe you wouldn’t do too well in this faster crisis. And that’s actually not what we found. So, we found that we had, you know, quite good strength of our strategies during the March-April period.

So, for example, futures trend following, something we talk about quite a lot did, you know, really rather well in March and April of — of last year, but we also talk about, for example, rebalancing and — and — and trying to stop rebalancing, which can — can have the nasty effect of — of buying the losers. And then if the losers carry on falling, then you (inaudible) that you just bought a whole bunch of losers in time for another month-fold.

And we found that if you — if you have strategies, which is trying to control your rebalancing, but they have to have relatively — they have to be quite fast strategies, and that would be my real point. So most of our protection strategies are quite fast. The signals are quite quick. These data that goes back are typically a few weeks, and they can be positioned around quite rapidly. And — and that worked pretty well in March and April last year. If you do much slower strategies, you would not have had the protection characteristics.

RITHOLTZ: Right. And — and — and to put some numbers on — on the speed of March 2020, we — we — S&P 500 fell 34 percent. That was the fastest 30 percent drop in history, and I — I believe it was just a day under a month, maybe a few days under a month. And then the recovery from the end of March, beginning of April, was back to breakeven by August. That — that’s a pretty astounding turnaround, arguably faster than the recovery from 1987, which was itself pretty quick, wasn’t it?

RATTRAY: Absolutely, so it was just totally extraordinary. And from that perspective, you know, the past didn’t give you a particularly good guide as to how — how that crisis would — would unfold. And then maybe that sort of reiterates my point a little bit that you can’t — you can’t build protection strategies, which are really trying to put your finger on exactly what’s going to happen. You have to — you have to be aware that your forecasting ability is poor, and you’re really going to have a — a strategic response, and that’s why we called the book, “Strategic Risk Management.”

It’s really effective strategies. It’s a plan, and you can’t make the plan up on the fly. You know, what you really — the worst thing you could have been doing last year is making up your protection strategy during March of 2020. I was too late by that point. You have to make up your — your protection strategy in the months and years before then, and then you had to be implementing it during March 2020.

RITHOLTZ: So, there was a quote of yours I really liked and I want to ask you about this, quote, “We are in a risk your environment than we have been in the past 20 years for the foreseeable future,” unquote. The past 20 years, really there were a lot of risky events that took place from 9/11 to the great financial crisis, to the pandemic. What makes this a riskier environment? And why do you see this as being a persistent risk for the — for the next foreseeable future?

RATTRAY: So, the reason that I think we’re in this highly — a much riskier environment that we’ve been in is because markets are much less diversified than at any point in my career. And so, you know, I started trading markets when I was in high school in the late 1980’s, and at that time, people got very worried that the Japanese market was found 50 percent of the MSCI world.

Well, today the U.S. market is two-thirds of the MSCI world, so it’s — and that’s the highest rate it’s ever been. So, it’s the highest rate that any one country has ever been in the global equity index. And then if you now dig in within the U.S. market — and this is a little tougher to do — but if you dig into the proportion that — of the U.S. equity market made up by technology — the reason is difficult as they change the classification system a couple of years ago — then you’ll see that tech is a bigger portion of the U.S. equity market than it has ever been, including in the late 1990’s in the tech bubble. So, you have an incredibly concentrated equity market, both globally into the U.S. and also by sector within the U.S.

And for me, that means that, you know, this is not sort of looking at the VIX today, tomorrow or yesterday, whatever. More strategically, the market feels much more likely to be able to produce unpleasant outcomes because the only free lunch you have in finance, the — the diversification, you — you have the least diversification I’ve ever seen.

RITHOLTZ: That’s kind of interesting, so we have concentrated non-diversified portfolios. And one of the things we’ve seen is domestically, the U.S. seems to be a higher proportion of global equity markets. And then within the U.S., the tech sector continues to increase its weighting with the S&P 500. What does that mean for the future of — of risk and managing it?

RATTRAY: Well, I — look, I think it means firstly that, you know, you need to be just aware of this that — that the market is so heavily concentrated. The — I think the — what can you do about it is probably the real question. And I think the — this is a pretty big challenge for people because, historically, the answer was, well, if I — — if I want to build a balanced portfolio then I’ll hold from equities and then I’ll hold some government bonds, often U.S. treasury bonds, as a sort of — as the ballast, as the thing which gives a bit of stability to my equity portfolio. But where we are today, I think, people are — are much less convinced that treasury bonds will be the ballast that they have been historically.

In particular, you know, if we continue to get high inflation numbers, then I think anybody couldn’t argue that high inflation is good for government bonds. It’s — it’s clearly bad for government bonds. And so, your challenge is that the way you build stable portfolios in the past is balancing equities and bonds is really much less suited to the current environment than it was to the — to the past environment. So, what can you do about it?

Well, I think what most people that I speak with at least, I think, doing about is saying, well, I need to own something other than treasury bonds to balance out my equity risk. And for some people, that’s private equity. For some people, that’s hedge funds or alternatives. For some people, it’s infrastructure or housing or other forms of real estate. But I think there’s a reason to be clear in my mind that you need to — you need to think about balancing your portfolio, and then you need to think pretty (inaudible) about whether bonds give you the same level of protection or balancing than they — than they would have done in the last 20, 30 years.

And from my own perspective, if I look back at the last 20 years, in particular, it’s a very dangerous period to look at when you look at equities and bonds. Over the last 20 years, when equities went down, bonds nearly always went up in price. And — and so we’ve got used to this idea of bonds being the protecting asset.

But if you look before then and you can look back for — in hundreds of years’ worth of data both in the U.S. and then also the U.K. where the bond market started earlier than the U.S. market, you see that for almost all of history except for the last 20 years when equities went down, bonds went down at the same time. And so, for me, I think it’s a very important question for investors, which is you need to balance the risk in your portfolio.

Our bond is the answer to it. In my view, they’re probably much less the answer than they were historically, so then you need to look at other asset classes and think more creatively about how you do that. And the fact that I think that equities — public equities are as risky as they’ve ever been from a strategic perspective means that question is actually as important as it’s ever been to think about.

RITHOLTZ: That’s — that’s really kind of intriguing. So — so sticking with the theme of — of risk, what does this concentration mean and this lack of diversification mean in — in terms of, you know, calibrating what we should be expecting? Should we be looking for larger moves in the future or, you know, how do you approach this philosophically when you’re thinking about what you want to do with your portfolios?

RATTRAY: Yeah, I — I think that, you know, right now we’re in a relatively sort of quiet summer period, and so markets are being relatively stable. But — but I say looking beyond just a short-term than this lack of diversification in markets definitely means that we should expect to see bigger moves in both directions just to be clear both upwards and downwards. It does not mean that markets couldn’t go up a whole bunch more from here, it just means that they’re likely to be more volatile than we’ve been used to in the last few years.

And so, I think it’s really having a plan of action and being prepared for how you respond to that because, in the end, for most of us the big up move — I mean, maybe we were underinvested, we have a bit of regret about it, but you don’t have much pain from the big up move. It’s the big down move that — that cause all the pain and cause the bad decisions to be made. So, I think it’s having a plan of action.

And I would argue that, you know, here we are sitting in a relatively comfortable moment in markets currently and, you know, if we’re fortunate then the summer will be enjoyable for all of us and — and not too — not too noisy. That’s a great time to be thinking about your plans for how you’d respond if there was a — if there was a negative volatility event.

RITHOLTZ: Really, really quite — quite interesting. So, let’s talk a little bit about some strategies. You mentioned alternatives like private equity and hedge funds. What can one do to hedge against the risk of increased volatility in the future?

RATTRAY: Well, I think, you know, you can do direct hedges, but they tend to be very expensive. So, you could go and buy futures contracts on the VIX or something like that, but they will turn out to be very costly a few over time as we’ve talked about in our earlier sections. So more lightly, what you need to do is to think about assets that will just behave differently to equity markets.

And as equity markets have become more concentrated, especially into tech, it’s — to be precise about that is tech and communication services are the two classifications that people use today. So as this become more concentrated into that — into those sectors, then you need, I think, to think about things, which will be not so affected by a negative price move in those.

And I think that private equity in the end, there has a lot of equity market exposure into it, but you tend to see the price action more slowly. But infrastructure, that’s — you know, could behave very differently. Hedge funds, if they’re good hedge funds, should have lots of protection strategies built in and lots of short holdings, as well as long holdings, and so should be less sensitive. We talked about CTAs a little bit, one of the few strategies, which has the right tail to it rather than the left tail. That could be part of your list of strategies as well.

I think the core things from my perspective would be recognize that you’re not going to build a forecast, the next difficult event, number one. Number two, if you can’t forecast it, then don’t pin all your diversification on a single thing. Have a range of protection strategies out there. And number three would be make sure those protection strategies are not too expensive to run. And that, of course, is the disadvantage of buying put options on the S&P or buying big futures …


RATTRAY: … that they’re very expensive to run, so you need something that you can actually put up with for a period of time.

I often see people that come buy those more expensive strategies strides, and they do it for six months or 12 months or 18 months, and then they give up. And oftentimes, they manage to give up just before the next bad event happen.


RATTRAY: And that’s a, you know, terrible outcome.

RITHOLTZ: Yeah. With — with earthquake insurance, it turns out that there’s always a spike right after an earthquake, which is the least likely time for there to be another earthquake. And by the time enough time elapses where risk has gone up dramatically, people have forgotten about it, and they — they let that — that risk laps.

RATTRAY: Exactly.

RITHOLTZ: I — I want to — I want to emphasize something you said and it comes back to that question someone asked you at the conference. You’re not really thinking about the specifics of the potential risk. It almost doesn’t matter if it’s a bond risk or an equity risk or some geopolitical risk, it’s, hey, we can expect these asset classes to go down, these asset classes to go up with a whole lot of increasing volatility. The — the black swan matters less than your preparation for some unforeseen event. Am I stating that correctly?

RATTRAY: Absolutely, yes. And — and we’ve talked a little bit about how — and people ask me at conferences forecast, the next black swan. I think it’s actually the question I get asked the most, and I’m a strong believer in this phrase that there’s no such thing as a bad question. But I think that one actually might be the bad question …


… because, by definition, you can’t forecast the black swan. That’s kind of where the black swan …


RATTRAY: … become forecastable.

RITHOLTZ: So — so let’s talk a little bit about the technology you guys use to create these models to — and to model out risk and — and other strategies. You build all that stuff in-house that you’re not really a big buyer of off-the-shelf risk management technology. Tell us a little bit about your approach, which seems to be pretty comprehensive to thinking about and planning for unforeseen risk.

RATTRAY: And so, I mean, the first thing I would say is that we’ve essentially build all of our own technology. We don’t really buy technology. We — we buy the hardware, of course, but — but we write all the software, all the code ourselves. And that’s because we think that the things you can buy off-the-shelf, well, everyone can buy it off-the-shelf and, therefore, it’s not really going to be a competitive advantage. It’s going to be — it’s going to be maybe a base standard.

I’m not trying to criticize the external products. I just think that if you really want to have an edge in building risk models or building short-term forecasters of risk or return or whatever, you need to write your own code, your own software. And — and you need to put a lot of effort into that. And you need to create an environment where you can hire the best software developers. And I often see people saying, well, you know, I hired a bunch of quants and I hired a bunch of developers as if, you know, that’s a sort of a generic thing, like buying a loaf of bread or something.

It’s just not. It’s, you know, the best developers are hundreds, maybe even thousands of times as productive as the average developers. So — so getting those best people into your organization, really important, and — and thinking about why they would want to work for you and not want to work for somebody else. That’s pretty important.

So, I think for us, we felt that we can have an edge by building better technology than you can buy off-the-shelf. And — and — and then in order to get that we’ve invested a huge amount in providing a good environment for quantitative researchers and technologists to operate in.

Just to give you a sort of a side example of that, we open source quite a lot of our code. So that means that, you know, we — we pay our developers to write code for us, and then we go and stick it on the website for other people to download it if they want. So why on earth — you know, what would possess you to do something like that? And the reason that we do it is that — that then provides advertising to people that we’re actually really serious software developers, and that we take our code really seriously. And if you’re a young software developer, you’ll probably see this stuff that we published and say, well, you know, actually, I wouldn’t mind working in a place like that because code and — and — and technology, and standards, and all those sorts of things are really high at — at — at this time.

So that’s how we think about investing in technology, investing in developers, creating a culture where developers and quant researchers really want to work. And the reason for that — and why would we carry on doing all this investment, it is really that you need — you know, it’s a very competitive business and you need to stay ahead all the time, and you need to carry on innovating all the time. And — and if you don’t, then somebody will eat your lunch.

So, from our perspective, we’re always building new models. We’re always coming out with new approaches to estimate risk. We’re always worrying about, you know, how can we find a new alpha source, what might go wrong, and how are markets changing in this structure, this, you know, big effective, more retail investment and retail investors in equity markets today? How should we respond to that? That’s really something, which is just a very ongoing and continuous form of a — a place for us to invest and where we try and get the benefits out of — out of that over the long-term.

RITHOLTZ: Really kind of interesting. Let’s talk a little bit about machine learning. You guys have been on the cutting edge of that, including a — a collaboration with the University of Oxford at the Oxford Man Institute. Tell us what you guys are doing with machine learning. And does any of this relate back to volatility?

RATTRAY: So, what we’re doing with machine learning is we’re really saying that financial markets have patents in them, which you can dig out and profit from if you — if you look hard enough. The problem in financial markets is that the patents are — are — are pretty weak. You know, they’re not — they’re not simple patents, they’re — people like me would say this — a low signal-to-noise ratio. There’s a lot of noise and not very much signal out there.

So what are we using machine learning for? We’re using it for a number of different things, but the — the — the underlying theme is that most models that people use in markets — and you could even think of it just as a value model, you know. You — P/E, for example, price over of earnings, that’s a linear model. It seems to sort of assume that price goes up in line with earnings. But we all know that when you look at markets, if there’s one thing they don’t ever do is move in a linear or straight-line fashion. They move in every shape you could imagine except for the straight line. And — and what machine learning is really trying to do is to say, can I find much more supple patent than the straight line, which is what most of finance actually ends up using for modeling.

And — and here are some examples. One that I’m particularly excited about is what we would call natural language processing, which is having machines read text. Now we all know that there’s far too much for us all to read. You know, nobody can read every analyst report, every company earnings statement, every annual report, attend every investor day. This is too much.

So wouldn’t it be wonderful if you could have a machines tool reading for you and tell you what to think at the end of it? And that might sound like science fiction. And at a certain level, I think it probably is science fiction today. But five years ago, if you said, well, machines will process images, will process pictures better than humans, then people would look at you a bit funny and say, you know, well, no, not really.

Now, you know, you have that on your phone. You just type a word into your phone, into your photos library and just watch it happen in action. And it’s just extraordinary how it will find all the pictures that reflect the words that you’ve — that you’ve typed in.

So, machines definitely do process images better than humans. It’s well-known, for example, processing x-ray images looking for cancers. It is much better done today by humans by — by machines and by humans.


RATTRAY: You might want human at the end, but you want the machine to do all the existing type work. And so, one example of machine learning is getting machines to understand text and tell you, you know, go ahead machine, read every analyst report on, you know, these 100 stocks and tell me, you know, not only the analyst reports, but all the newspapers in every language around the world, all the earnings calls, read all of it, and then tell me what to think. That is something, which today is science fiction, but I don’t think it will be in five years’ time.

RITHOLTZ: That — that’s really kind of intriguing. My last regular question I — I have to ask you is so you’ve spent most of your career developing quantitative strategies, what are some of the biggest changes you’ve noticed?

RATTRAY: I think the — firstly (inaudible) say a bit striking what hasn’t changed, so a lot of things haven’t changed. You know, the — many of the standard models today are basically the same as the standard models 20, 30 years ago. We still use Black-Scholes pricing options. We still use the Barra risk model for (inaudible) equity risk in portfolios. We still send data in very similar ways to the way that we sent it 20, 30 years ago for the most part in, you know, really terrible file formats, but nobody seems to come up with a better convention that everyone will accept.

So, there’s a lot of stuff that hasn’t changed. But I think there are some things, which have changed. The first is that people often like to sort of characterize well those the basic quants versus the discretionary people. So, the quants, you know, the model-driven people in some sort of battle would be discretionary people. And — and I say I don’t view it that way at all. I think that everyone is becoming much more quantitative in the way that they build and run their portfolios. The tools that we all have today on our Bloomberg terminals or websites or products that we can buy from third parties or build ourselves were, essentially, unimaginable five or 10 years ago, and everybody’s got them.

So, give you an example, you know, 15, 20 years ago I was building quite sophisticated screening tools that would search equity markets for opportunities. Today, you can basically do what I built on a Bloomberg terminal, so everybody’s got it or everybody who’s got a Bloomberg terminal has got it.

So, there’s been, you know, all investors not just the quants, but the discretionary minds as well, they’ve all become more quantitative. We’ve seen it with trading as well. You know, trading used to be people shouting at each other on a trading floor. Today, it’s — it’s all machines in — in almost every market around the world and very sophisticated machines, very sophisticated algorithms trading with each other.

So, what I — I think I’ve really seen is everything in markets has become more quantitative, but then there are some things, which have been kind of, you know, unattainable so far. Credit markets have remained stubbornly sort of immune to being taken over by more quantitative strategies so far. Private equity is the same. It’s — it’s really done in the same way if it was 20 or 30 years ago.

And I — and I think that will probably change over time. We’re certainly starting to see that in credit, for example, where the markets are starting to trade more like equity markets or futures markets, and it did start to be possible to build the same sorts of risk models and the same sorts of — of alpha models of — of return forecasting models in credit that you’ve had in equities for a long time. So — so I think my real thing is that everything has become more quantitative, and I think it is going to become a whole bunch more quantitative over the next 20, 30 years.

RITHOLTZ: All right. So, let’s jump to our favorite questions that we ask all our guests. Tell us what you’ve been streaming this past year or anything interesting that you’re watching on Netflix or Amazon Prime or — or whatever.

RATTRAY: I’m not a huge watcher of things on — of streaming services but, you know, I have been watching a — re-watching a series of films by a famous British actor called Bill Nighy, written by a playwright called David Hare. The first of them is called Page Eight. And there are quite sophisticated plays about an MI6 agent and his life struggles. So that’s what I’ve been streaming. And I — you can find it on — on — on Netflix. Page Eight is the — is the first of them.

RITHOLTZ: We’ll — we’ll definitely check that out. Tell me a — tell us a little bit about your mentors who helped to shape your career.

RATTRAY: So, I was very fortunate in the first 15 years of my career I was at Goldman Sachs. It was a outstanding place to work. The people that I particularly worked with over that period were really two or three folks, Manny Roman, who today is CEO of PIMCO. I worked with pretty much 25 years, both at Goldman Sachs, as well as at Man Group before he went off to PIMCO. I worked with a fellow called Girish Reddy who went on to run the fund-of-funds business called Prisma and a fellow called Mark Zurack went on to be a professor at Cornell.

And I think it was important to me to have a variety of different people to learn from and to sort of build different experiences. All three of them were extremely different people, but I really learned, I think, both how to manage people and how to get to the core of a problem. I think how to work out what was important and what was not important, and not to give a different path to sort of equal weight when you’re making decisions. And — and — and I learnt that differently from — from each of those three people who are really sort of my core mentors.

RITHOLTZ: Very interesting. Tell us about some of your favorite books, what — what are you reading right now and — and what are some of your old-time faves?

RATTRAY: Well, so I am — I am very interested in architecture, and so I tend to read relatively quirky and eclectic books. I am currently reading something about Nordic modernism, which I suspect will not be that popular with your audience. It’s a niche area. But I — I — I think architectural theory is something, which I’m very interested in. In another life I might have been an architect. So that’s sort of one area of interest for me.

I’m actually a keen piano player as well, so I know you asked about books, but I — I play a lot of music. And at the moment, I’m playing some early 20th century music by (inaudible), which drives my family nuts because it’s very hard to play. But if you play it well, it sounds good. I’m not sure I’ve mastered how to play it well yet. So that’s another sort of core part of my life as I — I try and play the piano for at least an hour every day, and that sort of straightens up my mind at the end of the day.

And in fiction, I am mid — I’m really a sort of enthusiast for — for mid-20th century writer, so Truman Capote or (inaudible), you know, sort of that — that group of — of writers were all my favorites.

RITHOLTZ: Very interesting. You know, there’s some really fascinating — I know you’re not a big video guy, but on YouTube there are some really fascinating shows about music like Song Exploder or Polyphonic or there’s just a run of things that take apart various genres of music from a musicologist or a historian’s perspective.

There — if you’re — if you’re a classical music fan and — and play the piano, you may find some of that stuff interesting because the parallel is back and forth between classical music and — and pop music. The pop audience is not familiar with it, but the classical fans clearly are. You might find some of that stuff interesting.

RATTRAY: And I see there are very strong parallels between music and architecture as well. Architecture is all about rhythms. People often don’t see it, but they there are.

RITHOLTZ: Well, you — I’m going to assume that someone like you read Godel Escher Bach 20 years ago. Am I …

RATTRAY: Of course, of course.

RITHOLTZ: So — so they’re the same parallels between pattern and repetition and — and how they — things morph over time, it’s — it’s really — and — and I — I never thought about architecture the way music and math show up and — and art show up. But I guess in a lot of ways specially with — with — with larger buildings, clearly, some of those fractal progressions are — are there. We’re really off on a — on a digression.

Let me — let me go to my next question. What sort of advice would you give to a recent college grad who is interested in a career in quantitative strategies or risk management and finance?

RATTRAY: So, my advice would be not to get too narrow too quickly and to try and build as broad a range of experience as you can. In my case, I did quite a few things in the early years of my career, and they really turned out to be different changes for me later on. So, I worked a bit in corporate finance. I worked hard, it wasn’t for me, but I learned a heck of a lot in my couple of years doing corporate finance.

I worked at fixed income, in equities, in credit. I worked on the sell-side, as well as the buy-side. And that was incredibly valuable to me. It gave me just different approaches to problems when I — I — I came across them. So, I think that was the first piece of advice.

The second piece of advice, I think, is that like most quants, I thought I was good at math and — and, you know, I probably wasn’t bad at it, but it turns out that actually there are a lot of people that are good at math. And I, from my perspective, learned that I had some skills, which maybe differentiated me a little bit from the core skill of all these other people that were good at math. And those, in my case, were — I was good at making decisions. I think I remained good at making decisions. I can see things. I don’t spend — have to spend a lot of time thinking about it. I can decide and move on, have much regret. And I learned that I was, I think, better than many quants at communicating at quantitative things in straightforward English, which most quants are not very good at.

And so, I really tried to work out what are my other strengths that — my differentiating strengths and — and — and — and tried to use those. And I would recommend any quant work out, if you’re just going to go straight for a math competition, you know, there’s some people pretty damn good at math out there, so you’re going to have to think about your extra strengths, the things which separate you from the crowd.

RITHOLTZ: It makes a lot of sense. And our final question, what do you know about the world of investing today you wish you knew 30 or so years ago when you were first getting started?

RATTRAY: So, I think 30 or so years ago, I think the thing that I most didn’t realize was how much more tech and quant-focused the world was going to become. And I slightly underemphasized my quant and tech skills at that time, so that’s the first thing I think. And I — and I shouldn’t. You know, well, today it all feels very obvious that tech has dominated our lives so much and behind most tech through a lot of algorithms, but 30 years ago it wasn’t so obvious. So that’s the — the first thing.

I think the second thing that I — I wish I’ve known 30 years ago was that it’s very easy to gravitate towards the glamorous businesses. So, when I was sitting on trading floors at Goldman Sachs, then the glamorous bid was — was trading what we called the “exotic derivatives,” so the more complicated derivatives contracts. But actually, that business almost doesn’t exist anymore. It does exist, but it’s really much smaller than it was 20 years ago. And — and that’s what everyone sort of wanted to do.

And then there were other things, which were, you know, apparently less interesting like understanding equity indices or — or building quant equity models or something like that, and those turned out to be much bigger things. So, I think the second thing which I’ve realized, which I wish I’d realized and understood 20 years ago is the glamorous stuff is not always the stuff to go for. Often, it’s the — the stuff that actually people sort of think maybe it’s a bit boring or something like that, but they’re very often the big opportunities lie and the stuff that people think is a bit boring.

RITHOLTZ: Really quite, quite interesting. Thank you, Sandy, for being so generous with your time.

We have been speaking with Sandy Rattray. He is the Chief Investment Officer of the $125 billion Man Group, as well as the co-inventor of the VIX index and the author of the book, “Strategic Risk Management.”

If you enjoyed this conversation, well, be sure and check out any of our previous 350 or so interviews that we’ve done over the past seven years. You can find those at iTunes, Spotify, Acast, wherever finer podcasts are sold.

We love your comments, feedback, and suggestions. Write to us at You can sign up for my daily reading list at Check out my weekly column on Follow me on Twitter @ritholtz.

I would be remiss if I did not thank the crack staff that helps put these conversations together each week. Charlie Vollmer is my Audio Engineer. Paris Wald is my Producer. Atika Valbrun is our Project Manager. Michael Batnick is our Head of Research.

I’m Barry Ritholtz. You’ve been listening to Masters in Business on Bloomberg Radio.




Print Friendly, PDF & Email

Posted Under