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