Speaker 1: Hello, and welcome to another episode of the Odd Lots Podcast.
Speaker 1: I'm Joe Wisenthal, Managing editor at Bloomberg Markets, and I'm
Speaker 1: Tracy Alloway, Executive editor at Bloomberg Markets. So, Tracy, you
Speaker 1: know what's something really fun about having a podcast? Okay,
Speaker 1: tell me what that I can read a book or
Speaker 1: read an article and then two days later say, hey,
Speaker 1: we should have the author of that in that article
Speaker 1: or book on to discuss that, and we can do that.
Speaker 1: I think that's a really cool thing. Is this podcast
Speaker 1: going to become like Joe's book Club? It's basically going
Speaker 1: to become Yeah, basically it's gonna be just here's what
Speaker 1: Joe read the week before and wants to talk more about.
Speaker 1: You know, but I, well, I can live. Yeah, it
Speaker 1: won't be that bad. I read good stuff. But uh so,
Speaker 1: I recently had the chance to read the book My
Speaker 1: Life as a quant by Emmanuel Derman, who was a
Speaker 1: physic assist theoretical physicist who eventually joined Wall Street during
Speaker 1: the quantitative revolution and sort of was at all you know,
Speaker 1: all these sort of there's so much talk about the
Speaker 1: equations and models that run finance these days, and he
Speaker 1: was at the ground floor of how that all got
Speaker 1: built up. Oh well, that's exciting. We've talked plenty about
Speaker 1: mathematical models and their role in finance on this podcast before,
Speaker 1: so exactly so, why not? Exactly so? Why not talked
Speaker 1: to one of the very original practitioners of it. And
Speaker 1: we have Emmanuel here in studio, So um, I say,
Speaker 1: let's get started. Let's do it. Emmanuel, thanks for joining us,
Speaker 1: my pleasure. I'm really glad to be here. So I
Speaker 1: want to start with something in your book. One of
Speaker 1: the things that really struck me was you pointed out
Speaker 1: how the explosion of exotic equity derivatives was very much
Speaker 1: tied to the globalization of fine nand after the Cold
Speaker 1: War ended. And there's really seemed like a poignant thing
Speaker 1: to read right now after the Brexit vote, when it
Speaker 1: feels like the world is arguably deglobalizing a little bit.
Speaker 1: Finance seems to be in retreat. But explain to us
Speaker 1: the connection there, because I thought that that was something
Speaker 1: that I had never thought of until I read your book. Yeah,
Speaker 1: that's very interesting. It's funny. Nobody's ever mentioned that to
Speaker 1: me about my book before I joined them. Equity derivatives
Speaker 1: at Goldman. I've been in fixed income. I joined Equit
Speaker 1: Derivatives in early and I was in charge of the
Speaker 1: quantitative Strategies group and we basically supported the options disc
Speaker 1: And there was this flowering of interest in exotic options
Speaker 1: because and it was because of globalization. Essentially, once the
Speaker 1: Berlin Wall came down, people wanted to invest in foreign
Speaker 1: in foreign stock markets. They didn't want to buy individual stocks,
Speaker 1: so they used options, which was much simpler. There were
Speaker 1: indicas developed all over the world, from the neck to
Speaker 1: the keck to the decks, and everybody went to the
Speaker 1: part of it. And there was also this fashion in
Speaker 1: finance forum. Well it's still going on for sort of
Speaker 1: not just buying your own country, not just buying the
Speaker 1: stock of your own company. Canadian actually, Canadian pension funds
Speaker 1: used to come to US because Canadian pension funds weren't
Speaker 1: allowed to buy more than a small amount of foreign stock,
Speaker 1: and so they would do their exposure through derivatives. Yes,
Speaker 1: so explain that a little bit more. I think people
Speaker 1: understand what essentially an option is, but explain, well, why
Speaker 1: are they called exotic options and why do they have
Speaker 1: an important role in giving people this international exposure Okay,
Speaker 1: I'm glad you're asking that. No nobody have asked it before.
Speaker 1: The Well, an option is the right, but not the obligation,
Speaker 1: to buy something for a certain price in the future. So,
Speaker 1: for example, you might have have the right to buy
Speaker 1: IBM a ar from today at a hundred dollars or
Speaker 1: whatever it is, and if IBM s trading above a
Speaker 1: hundred dollars at that point, you can buy it for
Speaker 1: a hundred dollars, sell it for a hundred and ten
Speaker 1: if it's trading on hundred and ten, and make ten bucks.
Speaker 1: And that's what people call vanilla standard call, And there's
Speaker 1: a put similarly, but with exotic options. They allowed you
Speaker 1: to get a much more fine tuned exposure to different things. So,
Speaker 1: for example, the first thing I worked on, which was
Speaker 1: kind of famous, not not me individally, but a Goldman,
Speaker 1: was something called the Nike U the Nike put options,
Speaker 1: where Goldman issued puts on the Nike and the nick
Speaker 1: was trading at I don't remember it was that it's
Speaker 1: all time high of like twenty nine thousand or something
Speaker 1: like that. And there are a lot of people who
Speaker 1: were skeptical about the future of Japan. Rightly as it
Speaker 1: turns out and Goldman sold puts on the Nike. But
Speaker 1: the reason they were exotic was people wanted a bet
Speaker 1: than the Nike going down, but they didn't want to
Speaker 1: face currency risk. And normally, if you bought to put
Speaker 1: on the Nike, the NICK might go down, but the
Speaker 1: end might strengthen, and so you wouldn't make any money
Speaker 1: even if the NICK went down. And what was exotic
Speaker 1: about these so called quanto options were that you locked
Speaker 1: in a guaranteed exchange rate. It didn't matter what the
Speaker 1: yen dollar did. When you exercise your option, you got
Speaker 1: paid in dollars the amount that the unique dropped in percent.
Speaker 1: It was a put am I making sense. So that
Speaker 1: was exotic because so in other words, it's not just
Speaker 1: a planet, it's not a plane embedded in it. Are
Speaker 1: more scenarios and more hedges, yes, or actually less in
Speaker 1: a sense. You if you bought an ordery put on
Speaker 1: the Nick, you would be exposed to both the yen
Speaker 1: dollar and to the Nike, and this way you remove
Speaker 1: the end dollar. So people would do this kind of stuff,
Speaker 1: or people would buy knockout options, which were very popular,
Speaker 1: which is an option that gives you money if it's
Speaker 1: called gives you money if the stock rises, but gets
Speaker 1: knocked out if the stock drops too low, if the
Speaker 1: stock drops too high. All of these ways were basically
Speaker 1: ways of making speculative bets. By putting up less money
Speaker 1: than you would for vanial option, you were betting on
Speaker 1: a smaller range of probabilities than just what was what
Speaker 1: was reflected in an ordinary option. And Emmanuel, one thing
Speaker 1: I always wonder about when it comes to these sorts
Speaker 1: of exotic options and instruments is you're allowing me in
Speaker 1: investor to sort of fine tune their risk. But how
Speaker 1: do the banks that are actually offering these kind of products,
Speaker 1: how did they manage their risk? Because things like knockout
Speaker 1: options can be you know, um kind of painful for
Speaker 1: the issuer, right, yes, So I mean that that was
Speaker 1: my job exactly. We we Golden for example, issued these
Speaker 1: exotic options, but if you sold them to somebody, you
Speaker 1: didn't want to suffer when they made money. So you
Speaker 1: had to head yourself. And you couldn't just buy an
Speaker 1: exotic option from one person and sell it to another,
Speaker 1: So you had to deconstructed and what black shoals and
Speaker 1: all the extensions of option pricing do is tell you
Speaker 1: essentially how to synthesize an option or an exotic option
Speaker 1: from the underlying which is the currency and the and
Speaker 1: the nique itself. Am I making sense? I'm not sure? No? Absolutely, Okay.
Speaker 1: So so the models we worked on, which I did
Speaker 1: for ten years, told you how to dynamically every day
Speaker 1: trade the end dollar and every day trade the nika
Speaker 1: in order to replicate what you were selling to somebody else.
Speaker 1: You were selling them a package and now you had
Speaker 1: created for yourself so that when they wont you wouldn't lose. Yeah.
Speaker 1: I love the way in your book you essentially described
Speaker 1: it as you're buying raw material, some combination of equity, cash,
Speaker 1: the end, and then you're repackaging it and basically selling
Speaker 1: it as a mark up like any other manufacturer done. Honestly,
Speaker 1: that's what it is. You're you're a middleman, you're a
Speaker 1: market maker, You're you're a wholesaler. You're buying complex stuff
Speaker 1: that people want to sell, and you're decomposing it into
Speaker 1: its constituents, or you're selling people complex stuff and making
Speaker 1: it out of out of simple constituents. So it's really
Speaker 1: I think, I say in my book, it's a bit
Speaker 1: like fruit salad. If you want to know what you
Speaker 1: should charge for fruit salad, you have to know the
Speaker 1: cost of canning, the price of pears, apples, peaches, etcetera.
Speaker 1: And then you you had a spread for your risk.
Speaker 1: Because the models are really a little bit shaky. So
Speaker 1: let's actually let's go back. Tell you you mentioned the
Speaker 1: black skulls method, but tell us about your beginning on
Speaker 1: Wall Street where quantitative finance was, and when you joined,
Speaker 1: and then what you worked on in your earlier years.
Speaker 1: You know, I came to Goldman, I've been a physicist
Speaker 1: before that, and then I worked for five years of
Speaker 1: the labs, where I already learned a lot of software engineering,
Speaker 1: which was very useful, and I joined Goldman in and
Speaker 1: the hot thing in those days interest rates were coming
Speaker 1: down from the high of seventy nine. We've lived through
Speaker 1: a massive bull market in bonds right now. And I
Speaker 1: worked on black shoals explained how to price options on stock.
Speaker 1: But now people were interested in buying options on bonds
Speaker 1: because as interest rates came down, people wanted to speculate
Speaker 1: on them going up again or going down again, and
Speaker 1: so there was a big market and options on treasury bonds,
Speaker 1: And the first thing I did was work with Fisher
Speaker 1: Black and a colleague of mine, Bill Toy, on trying
Speaker 1: to extend Black shoals into seeing yield curve things bonds
Speaker 1: and bonds that paid coupons rather than stocks. And bonds
Speaker 1: are very different from stocks because stocks have no termination date,
Speaker 1: but bonds have a finite life, and and you really
Speaker 1: need a totally different model, And I worked on something
Speaker 1: called b d T everybody called it Black Dermon Toy,
Speaker 1: which was one of the early models I did. That.
Speaker 1: The world's gotten much more complicated since then. People make
Speaker 1: much more elaborate models. So the way you describe the
Speaker 1: eighties and the sort of explosion in exotic options, it
Speaker 1: almost sounds like a sort of industrial revolution type thing
Speaker 1: for the financial industry. Suddenly you have this big evolution
Speaker 1: happening in products in ways to manage risk, and it
Speaker 1: kind of leads to, um, I guess, more revenue and
Speaker 1: growth of the financial industry as well. Yes, it was everybody.
Speaker 1: It was a globalization. Um, it was the ability to
Speaker 1: trade farm markets suddenly. Um it was Actually I wasn't
Speaker 1: academic before. It was actually very excite. Everybody was waking
Speaker 1: up every day to new products coming out and trying
Speaker 1: to or your bank wanted to issue new products, and
Speaker 1: you were trying to figure out how to value them
Speaker 1: and hedge them because they want to eliminate as much
Speaker 1: risk for themselves as possible. And so there was a
Speaker 1: there was a Yeah, there was a literal sort of
Speaker 1: efflorescence of papers on exotic options and how to hedge
Speaker 1: volatility and the invention I worked on variant swaps, which
Speaker 1: are ways of trading volatility rather than stocks. So how
Speaker 1: did you feel about actually leaving physics and academia and
Speaker 1: going to Wall Street because I imagine it must have
Speaker 1: been quite a different work environment, right, Yes, I was.
Speaker 1: I was very ashamed. You know, people who in physics,
Speaker 1: and even I have colleagues today who are in physics,
Speaker 1: they go into I wrote about this in my book.
Speaker 1: They're going into physics a little bit like um with
Speaker 1: a religious sort of fervor, thinking they're getting to discover
Speaker 1: something fundamental, or try to discover something fundamental, and Um,
Speaker 1: everybody looks down on you if you start to become practical,
Speaker 1: if you start to go out to make a living.
Speaker 1: We all despised people who did that, and eventually I
Speaker 1: did that too. Yeah. I think one of the little
Speaker 1: anecdotes in your book was about having some friend who
Speaker 1: who went to work on traffic patterns in the city
Speaker 1: and feeling sorry for him. Er. Yeah. Yeah. Even though
Speaker 1: it sounds like interesting stuff, it is. One of the
Speaker 1: lessons I've learned is that is that everything is interesting.
Speaker 1: It's sort of like to see the world in a
Speaker 1: grain of sand. If you look hard enough, then a
Speaker 1: lot of things become interesting. But physics felt a bit
Speaker 1: like a religion, and people look down on you when
Speaker 1: you sort of left the monastery, and I felt that
Speaker 1: for a while. I spent five years at Bell Labs,
Speaker 1: which was interesting, but but it was my first experience
Speaker 1: of working in a corporation and I sort of hated it.
Speaker 1: And then when I came to gold to Wall Street
Speaker 1: into Goldman, I actually loved it because they kind of
Speaker 1: took an academic interest in this stuff, and so you
Speaker 1: woke up every morning working on something interesting. But at
Speaker 1: the same time there were people who really wanted it. Yeah. Actually,
Speaker 1: I am one thing I still didn't quite understand. So
Speaker 1: while you were working for Goldman, you also published papers
Speaker 1: regularly and sort of publicized your findings how does that work?
Speaker 1: The tension of wanting to have a model that allows
Speaker 1: Goldman to profit while also wanting to do research that
Speaker 1: the public can know about and you can have your
Speaker 1: name attached to. Yeah, that's that's some I think that's
Speaker 1: pretty much vanished. People on Wall Street, especially with Sabain's
Speaker 1: Oxley passing ten or fifteen years ago, they they don't
Speaker 1: publish much research anymore. But I grew up in an
Speaker 1: era where people developed new things and unless somebody really
Speaker 1: insisted that they were incredibly proprietary, like now, for example,
Speaker 1: algorithmic trading, people people won't published papers on. But the
Speaker 1: options business was by and large a sales business. You know,
Speaker 1: you were making money not so much from speculating in volatility,
Speaker 1: but from providing people services and and the more you
Speaker 1: educated your clients, the better they understood what you were
Speaker 1: trying to do. So it was a bit of a struggle,
Speaker 1: but I worked for Fisher Black and I pushed quite hard.
Speaker 1: We had a culture where where unless somebody it's sort out,
Speaker 1: where you could never publish. And then it became for
Speaker 1: a few years like they had to say you can't publish,
Speaker 1: rather than you can publish. Did you ever get pushed
Speaker 1: back from your employers, Goldman or someone else about I
Speaker 1: guess the real world application of some of the stuff
Speaker 1: you're doing, or its ability to generate money. Like if
Speaker 1: you were working on a project and they couldn't exactly
Speaker 1: see the commercial interest in it, would they ask you
Speaker 1: to stop? Yeah, I mean, you know, I published a
Speaker 1: lot of papers and I like doing that, and I
Speaker 1: had a big group of people that did that, and
Speaker 1: and sometimes actually contact me, and they said they didn't
Speaker 1: realize what a rare environment it was, because most people
Speaker 1: weren't allowed to do that. But we did that. But
Speaker 1: at the same time, our real job was building risk
Speaker 1: management systems for the people that traded equity derivatives, and
Speaker 1: so I would say we sort of earned our keep
Speaker 1: by building software that embedded these models and that let
Speaker 1: them manage that positions. And at the same time we
Speaker 1: had to build new models, and they moral less agreed
Speaker 1: to let us publish, so they sometimes didn't like it.
Speaker 1: One of the things that I found that maybe everybody
Speaker 1: knew this before me, but that I did not know
Speaker 1: until I read it in your book, was that the
Speaker 1: seven stock market crash caused a permanent change to the
Speaker 1: financial market landscape in terms of how options before that
Speaker 1: crashed price in afterwards, and that had permanently changed the
Speaker 1: way people value things. Can you explain what happened? Yes,
Speaker 1: I can, um, and I'll make you writing a textbook.
Speaker 1: I've just finished the textbook on that right now. But
Speaker 1: but what happened in before seven? People pretty much used
Speaker 1: the Black Sholes model to price options. Is it too
Speaker 1: technical to talk about different strikes? Okay, with different strikes,
Speaker 1: and they still use the same model and the tribute
Speaker 1: to the same risk to the stock that lay underneath
Speaker 1: the option. But after seven, when the market dropped in October,
Speaker 1: in one day, all of a sudden, all hell broke loose,
Speaker 1: and from then on everybody being a bit anthropomorphic, but
Speaker 1: everybody understood that markets tend to crash down and glide up,
Speaker 1: which is kind of what's been happening here too. You
Speaker 1: get a big move down, but you get slow moves up.
Speaker 1: And so if the world is more likely to move
Speaker 1: down dramatically but go up slowly, you ought to charge
Speaker 1: more money for a put which will make money when
Speaker 1: the market drops. And everybody immediately did that, and it's
Speaker 1: been like that ever since. It amazes me that The
Speaker 1: idea that markets don't crash up and only crash down
Speaker 1: was something that wasn't reflected in the market until seven.
Speaker 1: I mean we had market we had stock market crashes
Speaker 1: before then. Yeah, I guess there was no options market
Speaker 1: in in nine. And the options market didn't really get
Speaker 1: big until Black Black Controls published their paper in seventy three.
Speaker 1: And yeah, there was a fourteen year period where where
Speaker 1: people didn't worry too much about the stuff. And it's
Speaker 1: been like that ever since. And in fact, the gold
Speaker 1: market changed in the late nineties because central central banks
Speaker 1: in some central in Switzerland did something other about gold,
Speaker 1: and ever since then, gold tends to crash up when
Speaker 1: the market goes down. Gold doesn't God, Gold tends to
Speaker 1: go down slowly and go up dramatically, and so you
Speaker 1: get an inverse sort of option behavior that's been there since.
Speaker 1: So all this talk about market crashes is kind of
Speaker 1: reminding me of what's going on right now. In the
Speaker 1: aftermath of the Brexit referendum in the UK. Um we
Speaker 1: obviously saw market sell off after that, but we saw
Speaker 1: a lot of people worrying about what systematic traders, uh,
Speaker 1: you know, like risk parity guys that sort of thing
Speaker 1: what they would do. And those guys have been likened
Speaker 1: before to sort of modern portfolio insurers in the sense
Speaker 1: that they could create this sort of feedback loop during
Speaker 1: a big sell off. I'd love to get your thoughts
Speaker 1: on that. I think that's true. I think anybody who
Speaker 1: behaves mechanically um um is behaving a bit like portfolio insurance,
Speaker 1: and and if people know it's coming, they start to
Speaker 1: try to dodge it. I mean, there's pretty people have
Speaker 1: actually done very well in the best few months because
Speaker 1: they like them they invest equally in in bonds, stocks
Speaker 1: and commodities, and all of those things have gone up
Speaker 1: so um. But yes, since they're behaving mechanically, there is
Speaker 1: a danger that they keep doing the same thing. And
Speaker 1: and you can only be clever if you're a small
Speaker 1: part of the of the ocean. But if you're the
Speaker 1: whole ocean, then then and everybody doing the same thing,
Speaker 1: then your models don't work because you're actually affecting affecting
Speaker 1: the thing you're trying to model. So yeah, I think
Speaker 1: that could happen. Uh. You mentioned that part of the
Speaker 1: reason you did the work earlier. Early on in your work,
Speaker 1: there was a lot of demand for it because there
Speaker 1: was a major shift in the direction of interest rates.
Speaker 1: Right now, interest rates are only going in one direction.
Speaker 1: Every day we wake up to new lower rates around
Speaker 1: the world. Presumably one day that will change. It could
Speaker 1: be next week, it could be years from now. When
Speaker 1: that does happen, will we see once again lots of
Speaker 1: models just being completely destroyed and types of portfolio is
Speaker 1: not working and a sort of really really looking at
Speaker 1: how to do all this stuff. That's I mean, I
Speaker 1: think that's already happening. That's a perceptive question. If you
Speaker 1: look at the thing I mentioned earlier, this Black Derman
Speaker 1: toy model, and essentially all the interest rate models that
Speaker 1: people built, they always assumed rates could never go negative.
Speaker 1: If you try buying software, they actually won't let you
Speaker 1: enter a negative rate. And so I don't really work
Speaker 1: on this stuff anymore, but I think a lot of
Speaker 1: people have been working for banks on how do you
Speaker 1: value options when when there's actually a negative interest rate
Speaker 1: which the previous model just didn't allow. And I mean,
Speaker 1: this stuff is very different from physics. I try to
Speaker 1: point out in my book because in physics, once you
Speaker 1: figure out the way the planets work, they say that
Speaker 1: way they don't really care what you say about them.
Speaker 1: But when you figure out a model for markets and
Speaker 1: everybody uses it, as Tracy was pointing out, it actually
Speaker 1: starts to affect the thing you're modeling, and so no
Speaker 1: model asks forever, you know, there's there's some It lives
Speaker 1: for a while, and then people get smarter when market
Speaker 1: which is what happened, and he said, when the market
Speaker 1: suddenly misbehaves and they adjust their model, and it's it's
Speaker 1: sort of an endless leap frog in a way. Well,
Speaker 1: I suppose that gets to the heart of one of
Speaker 1: the major criticisms leveled at quantitative finance and at models,
Speaker 1: which is that how useful are they really? We hear
Speaker 1: all the time about like ten sigma events in markets,
Speaker 1: things that are only supposed to happen every you know,
Speaker 1: one day in five million years, and things like that,
Speaker 1: and they seem to keep happening. So clearly the models
Speaker 1: are missing something, right, Yeah, you're right, I think. Yeah,
Speaker 1: I've written a lot about the section. I think models
Speaker 1: are only good as as long as the world stays
Speaker 1: in the sort of regime that you're currently in, and
Speaker 1: then they provide a good way of valuing things as
Speaker 1: long as things change a little bit, not too much.
Speaker 1: When you move to a new regime like negative interest
Speaker 1: rates or this old central bank um sort of the
Speaker 1: last seven years of risk on risk off, then your
Speaker 1: old models don't work. And yeah, A kind of like
Speaker 1: to say, it's idolatry to imagine that you can write
Speaker 1: down an equation that's going to accurately reflect the way
Speaker 1: people behave. Uh So let's sort of start or go
Speaker 1: back to where we talked about in the beginning, with
Speaker 1: the connection of globalization and exotic options. In the wake
Speaker 1: of the Brexit vote, arguably finite the world maybe deglobalizing somewhat.
Speaker 1: What is uh, what is your assessment of the financial
Speaker 1: industry these days? Every day we wake up to news
Speaker 1: about layoffs, retrenchments, large banks divesting their their foreign subsidiaries.
Speaker 1: Where do you see the industry going? You know, it
Speaker 1: goes in cycles. When I when I started out, it
Speaker 1: was very important to be able to program and to
Speaker 1: do quantitative work. Then at some point being able to
Speaker 1: program became a commodity that you could give to the
Speaker 1: I T people and you just did theoretical work, which
Speaker 1: I never really liked. And now now exotic options are
Speaker 1: sort of pretty much a small market. Nobody's interested in
Speaker 1: that anymore. Everything's done electronically and algorithmically, and so software
Speaker 1: skills for for financial companies and investment banks and for
Speaker 1: hedge funds have become much more important. And so I'm
Speaker 1: looking for the point of the job market students now.
Speaker 1: Students now have to be good programmers if they want
Speaker 1: to get a job, which didn't used to be the
Speaker 1: case ten or fifteen years ago. So I think everything
Speaker 1: is moving away from exoticism and towards vanilla products um
Speaker 1: algorithmic trading, high frequency trading by computer. That's what it's
Speaker 1: been like for the last five or six years, and
Speaker 1: I don't see that ending soon. Does that make you
Speaker 1: happy or sad? The idea that some of the exoticism
Speaker 1: of Wall Street might be going away now A little
Speaker 1: bit sad in the sense that I had a good time.
Speaker 1: What was nice about the years that I worked at
Speaker 1: Goldman was that Goldman functioned in a very informal and
Speaker 1: bureaucratic way, at least for the first and for the
Speaker 1: first ten years I was there, And if you worked
Speaker 1: with the trading desk, it was a bit like being
Speaker 1: in physics. There were a bunch of traders who are
Speaker 1: like the experimentalists, and a bunch of quantity with the theorists,
Speaker 1: and you all spoke every day and you work together,
Speaker 1: and it was kind of exciting. And I think what's
Speaker 1: said a little bit for me now is that most
Speaker 1: of the jobs for people are in bureaucracy and risk
Speaker 1: management and risk reporting, in basle regulations. And yeah, very
Speaker 1: very um very driven by regulation and reporting rather than
Speaker 1: actually trying to do new things. Is the regulation, while
Speaker 1: it may be boring and not exciting, is it at
Speaker 1: a good thing for society or do you think it
Speaker 1: could be a counterproductive I think it's good up to
Speaker 1: a point. But I'm a bit of a skeptic about
Speaker 1: I'm a bit of a skeptic about what's happened in
Speaker 1: the last ideas I think they should have. I think
Speaker 1: that I think that the way people learn a good
Speaker 1: lesson is when they go bankrupt, when they lost a
Speaker 1: lot of money by being stupid, or by being careless,
Speaker 1: or but just just by the fact that that's the
Speaker 1: way the world works. And I think nothing's nothing prevents
Speaker 1: people from doing bad things again except getting punished by
Speaker 1: the market for having done them. And I think forty
Speaker 1: page of regulation are are not an adequate substitute for
Speaker 1: just letting people go under when they do badly? Easy
Speaker 1: to say, I know, but but nevertheless, Uh so you
Speaker 1: mentioned that you're working on a textbook. Let's what is that?
Speaker 1: And also just what else are you interested in these days? Um,
Speaker 1: I'm working. I taught a course on the volatility smile
Speaker 1: on this thing that happens in seven for the last
Speaker 1: ten or fifteen years, mostly based on the work I
Speaker 1: did at Goldman, and so I've just finished a textbook
Speaker 1: on that, which is coming out in September, and it
Speaker 1: has a very pretty cover from I don't know even
Speaker 1: know who hockey side was. He was some Spanish woodcutter
Speaker 1: a picture of a big wave which looks like a
Speaker 1: volatility smile. So I'm finished that. Um. I wrote another
Speaker 1: book called Models Behaving Badly, which was more philosophical about
Speaker 1: the difference between models and physics. And I kind of like,
Speaker 1: I don't know, I've I've spent a lot of time
Speaker 1: doing quantitative stuff. I prefer doing qualitative stuff and writing. Now.
Speaker 1: Um there's actually I'm working a little bit with the
Speaker 1: guy who's a professor of anthropology. This is kind of
Speaker 1: interesting at at at the News School, and there are
Speaker 1: a whole bunch of them who are very interested in
Speaker 1: the anthropology of finance and the way traders behave. And
Speaker 1: it's kind of interesting because traders use models that they
Speaker 1: know are wrong, but nevertheless they keep using them in
Speaker 1: a more or less effective way. And we're interested in
Speaker 1: sort of looking at at at how this works. And
Speaker 1: plus he's got this idea, which I think is right.
Speaker 1: It's a little that that that volatility became an interesting
Speaker 1: thing in society in the last fifteen in the last
Speaker 1: thirty years. If you look at them, if you look
Speaker 1: at people writing surfboards are doing skateboarding, they're actually doing
Speaker 1: something very similar. When they go up and down, up
Speaker 1: and down, they're sort of hedging out there there. Maybe
Speaker 1: I'm getting to complicate this is okay. Well, when you
Speaker 1: value an option, you first hedge it, and so you
Speaker 1: get rid of the pure market risk and what you
Speaker 1: left with is a sort of convexity kind of shape
Speaker 1: that's just the residual part of the option. And it's
Speaker 1: very similar in a in a metaphorical way to what
Speaker 1: skateboarders or to what surfers do when they ride they
Speaker 1: ride a wave, and they're not interested in the horizontal motion.
Speaker 1: They're interested in moving up and down the curve of
Speaker 1: the wave as it as it curls. And um, this
Speaker 1: friend of mine is sort of interested in the whole
Speaker 1: idea of people in the world since the early seventies
Speaker 1: being interested in volatility as a as a as a quantity,
Speaker 1: the same way as people use options to trade volatility
Speaker 1: as an asset. So you know, people who wander through
Speaker 1: city streets and try to experience the excitement rather than
Speaker 1: trying to go somewhere. Is a is a sort of
Speaker 1: version of of optionality. Interesting. Well, it sounds like fascinating stuff,
Speaker 1: and I hope you are now. I really want to
Speaker 1: read more about this stuff, and I hope you write
Speaker 1: on it. Okay, Um, yeah, my textbook is going to
Speaker 1: be a technical book, although I'm very against if I
Speaker 1: can say one more thing, Um, finance and financial engineering
Speaker 1: has gotten very mathematical in the last fifteen or twenty years,
Speaker 1: and I kind of disapproved people teach it as though
Speaker 1: it's a branch of mathematics, but really it's a real
Speaker 1: world field and it shouldn't have theorems or axioms. It's
Speaker 1: about the way the world behaves. And I'm I'm trying
Speaker 1: to write my textbook in that way too, and a
Speaker 1: little bit of a of a counter counterpoint to the
Speaker 1: way that people people often teach finance. And now it's
Speaker 1: a branch of pure math, as though you write down
Speaker 1: axioms and you you know, like euclid, and you work
Speaker 1: out the results, and the world doesn't really work that way.
Speaker 1: And as you point out, all models are wrong. It's
Speaker 1: just yes, which which ones are less wrong? Yes? All right,
Speaker 1: Emmanuel German, author of My Life as a quant and
Speaker 1: models are behaving badly and a forthcoming textbook on the
Speaker 1: volatility smile. Thank you very much for joining us. Thanks
Speaker 1: someone's glad to be here. Well, Tracy, I I loved
Speaker 1: that discussion. I'm guessing you did too, me too, I
Speaker 1: I gradgically admit I I will join the Joe Wisenthal
Speaker 1: book Club in future. It's you know, one thing. I mean,
Speaker 1: there's a lot to unpack, obviously, but this, this topic
Speaker 1: seems like such a great way of looking at so
Speaker 1: much Wall Street history from it being strictly a sort
Speaker 1: of like personal driven business too. Then the rise of
Speaker 1: the mathematics too, then the software driven. It seems like
Speaker 1: by examining this we really get this sort of pretty
Speaker 1: big scope of how things have changed over the last
Speaker 1: several decades. Yeah, and I think one of the really
Speaker 1: interesting things that Emmanuel pointed out towards the end of
Speaker 1: the conversation was that even though we essentially just recorded
Speaker 1: a podcast that was sort of about physics and mathematical
Speaker 1: models and quantitative finance, so oh, much of it actually
Speaker 1: has to do with human behavior and how traders and
Speaker 1: investors and people on Wall Street choose to use those models.
Speaker 1: And uh, you know, we've seen in the past that
Speaker 1: sometimes it goes horribly wrong, and sometimes they do have
Speaker 1: a lot of practical use. So I find that fascinating.
Speaker 1: And sometimes people's emotions just make them cause them to
Speaker 1: make horrible decisions, even though everything that intellectually or their
Speaker 1: models would say, uh, would have advised against it exactly.
Speaker 1: And you know what, Joe, this was actually a really
Speaker 1: timely discussion to have, given the market fallout from Brexit
Speaker 1: and all the discussion we've seen once again about var
Speaker 1: shocks and things that aren't supposed to be happening mathematically
Speaker 1: happening once again, it was a really timely discussion. I
Speaker 1: liked it. Yeah, you've written so much about That's a
Speaker 1: recurring theme of your writing is how these things that
Speaker 1: are supposed to only happen once every million years seemed
Speaker 1: to happen a few times a year these days. Yeah, exactly.
Speaker 1: And unfortunately the models aren't really well suited to taking
Speaker 1: that into account, so we'll see what happens. All right, Well,
Speaker 1: this has been another edition of the Odd Lots Podcast.
Speaker 1: I'm Joe Wisnthal. You can follow me on Twitter at
Speaker 1: the Stalwart, and I'm Tracy Alloway. I'm on Twitter at
Speaker 1: Tracy Alloway. And you should follow Emmanuel Derman on Twitter
Speaker 1: at Emmanuel Derma. All Right, thanks for listening. We'll see
Speaker 1: you here next week.