Kevin Knudson: Welcome to My Favorite Theorem. I’m Kevin Knudson, professor of mathematics at the university of Florida, and this is your other host.
EL: Hi. I’m Evelyn Lamb. I’m a freelance math and science writer in Salt Lake City, Utah.
KK: How’s it going, Evelyn?
EL: How are you today?
KK: I’m okay. I’m a little sleepy. So before I came to Florida, I was at Mississippi State University, and I still have a lot of good friends and colleagues there, and that basketball game last night. I don’t know if you guys saw it, but that last minute shot, last second shot that Notre Dame hit to win was just a crusher. I’m feeling bad for my old friends. But other than that, everything’s great. Nice sunny day.
EL: Yeah, it’s gray here, so I’m a little, I always have trouble getting moving on gray mornings.
KK: But you’ve got that nice big cup of tea, so you’re in good shape.
KK: That’s right. So today we are pleased to welcome Mike Lawler. Mike, why don’t you introduce yourself and tell everyone about yourself?
1:24 ML: Hi. I’m Mike Lawler. I work in the reinsurance division for Berkshire Hathaway studying large reinsurance deals. And I also spend a lot of my spare time doing math activities for kids, actually mostly my own kids.
KK: Yours is one of my favorite sites on the internet, actually. I love watching how you explain really complicated stuff to your kids. How old are they now? They’re not terribly old.
ML: They’re in eighth grade and sixth grade.
KK: But you’ve been doing this for quite a while.
ML: We started. Boy, it could have been 2011, maybe before that.
KK: Wow, right.
ML: I think all three of us on the podcast today, and probably everybody listening, loves math.
KK: One hopes.
ML: And I think there’s a lot of really exciting math that kids are really interested in when they see. It’s fun finding things that are interesting to mathematicians and trying to figure out ways to share them with kids.
EL: Yeah. Well I like, you always make videos of the things, so listening to your kids talking through what they’re thinking is really fun. Recently I watched one of the old ones, and I was like, “Oh my goodness! They’re just little babies there.” They’re so much bigger now. I don’t have kids of my own, so I don’t have that firsthand look at kids growing up the same way. They’re sweet kids, though.
ML: I have to say, one of the first, it wasn’t actually the first one we did, but it’s called Family Math 1, where we do the famous “How many times can you fold a piece of paper?” And, you know, they’re probably 4 and 6 at the time, or maybe 5 and 7, and yeah, it’s always fun to go back and watch that one.
KK: I see videos of my son, he’s now 18, he’s off in college. When I see videos of him, he’s a musician, so when he was 10, figuring out how to play this little toy accordion we got him, I kind of get a little weepy. You know.
ML: It’s funny, I was picking him up somewhere the other day, and I confused him with a 20-year-old, my older son, and I just thought to myself: how did this happen?
KK: So, all right. Enough talking about kids, I guess. So, Mike, we asked you on to talk about your favorite theorem. So what is it?
ML: Well, it’s not quite a theorem, but it’s something that’s been very influential to me. Not in sharing math with kids, but in my own work. It comes from a paper from 1995 at a professor named Zvi Bodie at BU. And he was studying finance, and continues to study finance. And he published a paper showing that the cost of insurance for long holdings in the stock market actually increases with time. Specifically, if you want to buy insurance to guarantee your investments at least earn the risk-free rate, that cost of insurance goes up over time. And it just shocked me when I was just learning about finance, actually when I was just in grad school. And this paper has had a profound influence on me over the last 20 years. So that’s what I want to talk about today.
KK: Okay. I know hardly any of those words. I have my retirement accounts and all that, but like most good quantitatively-minded people, I just ignore them.
ML: Well, let’s take a simple example. Let’s just take actually the most simple example. Say you wanted to invest $100 in the stock market, and you thought, because you’ve read or you’ve heard that the stock market gives you good returns, you thought, “Well, in 10 years from now, I think I’ll probably have at least $150 in that account.” And you said, “Well, what I want to do is go out and buy some insurance that guarantees me that at least I’ll have that amount of money in the account. That’s the problem. That’s the math problem that Bodie studied.
KK: Right. So how does one price that insurance policy, I guess? So right, on the insurance side, how do they price that correctly, and on the consumer side, how do you know you’re getting a worthwhile insurance policy, I guess.
ML: Yeah, well this is kind of the fun of applied mathematics. So there’s a lot of theory behind this, and I think like a lot of good theories, it’s not named after the people who originally discovered that. So I think that’s important part of any theory. But then when you understand the theory, and you actually go into the financial markets, you have to start to ask yourself, “What parts of the theory apply here, and which ones don’t?” So the theory itself goes back to the early 1900s with a French mathematician and his Ph.D. thesis. His last name is Bachelier, and I’m probably butchering that. But then people began to study random processes, and Norbert Wiener studied those. And eventually all of that math came into economics, I think in the late 60s, early 1970s, and something called the Black-Scholes formula came to exist. The Black-Scholes formula is what people use to price this kind of insurance, sometimes called options. So that’s been around the financial markets since at least the early 1970s, so let’s call it 50 years now. And if you’re a consumer, I think you’d better be careful.
EL: Well I find, I don’t know a lot about financial math, but I’ve tried to read a few books about the financial crash, actually one of which you suggested to me, I think, All the Devils Are Here. And I find, even with my math background, it’s very confusing what they’re pricing and how they’re calculating these, how they’re batching all of these things. It just really seems like a black box that you’re just kind of hoping what’s in the box isn’t going to eat you.
ML: That’s a pretty good description. Yeah, Bethany MacLean’s book All the Devils Are Here is absolutely phenomenal, and Roger Lowenstein’s book, called When Genius Failed, is also an absolutely phenomenal book. You are absolutely right. The math is very heavy, and a lot of times, especially when you talk about the financial crisis, the math formulas get misused a little bit, and maybe are applied into situations where they might not necessarily apply.
KK: Really? Wall Street does that?
ML: So you really have to be careful. I think if you pull the original Black-Scholes paper, I think there are 7 or 8 assumptions that go into it. As long as these 7 or 8 things are true, then we can apply this theory. In theory we can apply the theory.
ML: So when you go into the financial markets, a lot of times if you have that checklist of 7 things with you, you’re going to find maybe not all 7 are true. In fact, a lot of times, maybe you’re going to find not a single one of those things is true. And that is I think a problem that a lot of mathematicians have when they come into the markets, and they just think the theory applies directly, if you will.
KK: Right, and we’ve all taught enough students to know they’re not very good at checking assumptions, right? So if you have to check off a list of 6 or 7 things, then after the first couple, you’re like, “Eh, I think it’s fine.”
ML: Right. Maybe that seventh one really matters.
ML: Or maybe you’re in a situation where the theory sort of applies 95% of the time, but now you’re in that 5% situation where it really doesn’t apply.
KK: So should I buy investment insurance? I mean, I’ve never directly done such a thing.
KK: I don’t know if it’s an option for me since I just have 401Ks, essentially.
ML: Well, it’s probably not a great idea to give investment advice over a podcast.
KK: Right, yeah, yeah.
ML: But from a mathematical point of view, the really interesting thing about Bodie’s paper is Black-Scholes is indeed a very complicated mathematical idea, but the the thing that Bodie found was a really natural question to ask about pricing this kind of insurance, ensuring that your portfolio would grow at the risk-free rate. In that situation, and you can see it in Bodie’s paper, the math simplifies tremendously. And I think that is a common theme across mathematics. When someone finds exactly the right way to look at a problem, all of a sudden the problem simplifies. And I’m sure you can probably give me 3 or 4 examples in your own fields where that is then the case.
KK: Sure. Well, I’m not going to, but yeah.
EL: So something when you told us that this was the theorem or quasi-theorem you were going to talk about, it got me wondering how much the financial world—I’ve been trying to think about how to phrase this question—but how much your natural tendencies as mathematicians actually carry over into finance. How much are you able to think about your work in finance and insurance as math questions and how much you really have to shift how you’re thinking about things to this more realistic point of view.
ML: I think it’s a great question because, you know, the assumptions and a lot of times the mathematical simplifications that allow you to solve these differential equations that stand behind the Black-Scholes theorem and generally stochastic processes, you know, you’re, that doesn’t translate perfectly to the real world. And you have to start asking questions like, “If this estimate is wrong, does it miss high? Does it miss low?” “In the 5% of the times it doesn’t work, do I lose all my money?
ML: And so those, I can tell you as an undergrad I was also a physics major, and I spent a lot of time in the physics lab, and there’s not one single person who was ever in lab with me who misses me. I was a mathematician in the labs. But doing some of these physics experiments really teaches you that applying the theory directly, even in a lab situation, is very difficult.
EL: Right. And your Ph.D. was in pure math, right?
ML: Right, it was sort of mathematical physics. In the late 90s, people were really excited about the Yang-Mills equations.
KK: Mirror symmetry.
ML: Work that Seiberg and Witten were doing. So I was interested in that.
EL: So your background is different from what you’re doing now.
ML: Oh, totally. You know, I, it’s kind of a hard story for me to tell, but I really loved math from the time I was in fifth grade all the way up through about my third year of graduate school.
EL: Yeah, I think that could be a painful story.
ML: I don’t know why, I really don’t know why, I just kind of lost interest in math then. I finished my Ph.D., and I even took an appointment at the University of Minnesota, but I just lost interest, and it was an odd feeling because from about fifth grade until—what grade is your third year of graduate school?
ML: Nineteenth grade. I really got out of bed every morning thinking about math, and I sort of drifted away from it. But my kids have brought me back into it, so I’m actually really happy about that.
KK: Well that’s great. So, what have you chosen to pair with your quasi-theorem, we’re calling it?
ML: Well, you know, so for me, this paper of Bodie’s goes back, and it sort of opened a new world for me, and for the last 20 years I’ve been studying more about it and learning more about it and all these different things, so I got to thinking about a journey. I have books on my table right now about this paper. So the journey I want to highlight is—and I think a lot of people can understand who are outside of math—is an athletic journey. I’m going to bring up a woman named Anna Nazarov, who represents the United States on the national ultimate frisbee team, which is a sport I’ve been around. And four years ago, she made it almost to being on the national team and got cut in the last minute and wrote this very powerful essay about her feelings about getting cut and then turned around and worked hard and improved and won three world and national championships in the last four years as a result of that work.
ML: Yeah, you know, it’s hard to compare world championships to just your plain old work. I think people in math understand that you kind of roll up your sleeves and over a long period of time you come to understand mathematics, or you come to understand in this case how certain mathematics applies, and so I want to pair this with that kind of athletic journey, which I think, to the general public, people understand a little bit better.
EL: Yeah, so I played ultimate very recreationally in grad school. There was a math department pickup ultimate game every week, and playing with other math grad students is my speed in ultimate. I really miss it. When you, I can tell, follow ultimate, and I often read the links you post about ultimate frisbee, I’m like, oh, I kind of miss doing that. But a few years ago, I did get to, I happened to be in Vancouver at the same time that they were doing the world ultimate championships there and got to see a couple games there, and it’s really fun, and it’s been fun to follow the much-higher-level-than-math-grad-student ultimate playing thing through the things you’ve posted.
ML: Yeah, it’s neat to follow an amateur sport, or not as well-known a sport because the players work so hard, and they spend so much of their own money to travel all over the world. You know, I think a lot of people do that with math. Despite the topic of today’s conversation, most people aren’t going into math because of the money.
KK: Well this has been great fun. Thanks for joining us, Mike. Is there anything, we always want to give our guest a chance to plug anything. We already kind of plugged your website.
EL: We’ll put links to your blog in the show notes there, and your Twitter. But yeah, if there’s anything else you want to plug here, this is the time for it.
ML: No, that’s fine. If you want to follow Mike’s Math Page, it’s a lot of fun sharing math with kids. And like I said, I sort of lost interest in math in grad school, but sharing math with kids now is what gets me out of bed in the mornings.
KK: All right. Well, thanks again, Mike.
ML: Thank you.