WEBVTT - Allison Schrager: How Do We Master Risk?

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<v Speaker 1>I'm Bethany McLean. This is making a killing interviews with authors, journalists, filmmakers,

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<v Speaker 1>and economists, reframing the stories you've heard in the headlines,

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<v Speaker 1>and explaining why these stories and the lessons learned are

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<v Speaker 1>important for all of us to understand. There's this inversion

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<v Speaker 1>that I have always liked that's safe as risky, and

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<v Speaker 1>risky is safe. It's the idea of a swing and

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<v Speaker 1>a miss. You might be scared to try something new

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<v Speaker 1>and miss, but if you never swing at all, you're

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<v Speaker 1>guaranteed to miss one hundred percent of the time you

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<v Speaker 1>risk at all if you just sit safely on the sidelines.

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<v Speaker 1>This is good life advice to be sure risk brings

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<v Speaker 1>change into our lives. You won't get a raise if

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<v Speaker 1>you never change jobs. You'll never fall in love if

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<v Speaker 1>you don't go out on that first date. It's a

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<v Speaker 1>phenomenal skill to learn which risks are worth taking and

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<v Speaker 1>how to reduce the downside so you can figure out

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<v Speaker 1>how best to save her retirement, which degree is worth

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<v Speaker 1>the tuition, where to buy a house, and on and

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<v Speaker 1>on and on. But how can we also get smarter

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<v Speaker 1>at understanding risk and reward in business? At Fortune five

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<v Speaker 1>hundred companies on Wall Street in global markets. As technology

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<v Speaker 1>changes everything at an exponential rate, how do we run

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<v Speaker 1>risk reward analysis when the world around us is being

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<v Speaker 1>disrupted at this whispering pace. I'm excited that I get

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<v Speaker 1>to talk today with Alison Schrager, author of the new

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<v Speaker 1>book An Economist Walks into a Bravel, which has got

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<v Speaker 1>to be one of the best titles ever. She's a

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<v Speaker 1>retirement finance economist and has spent years talking to risk

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<v Speaker 1>takers in all kinds of businesses. But in a Hollywood

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<v Speaker 1>worthy twist, she's lately been studying risk in the unlikeliest

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<v Speaker 1>of places, talking to sex workers at the Bunny Ranch

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<v Speaker 1>brothel and Nevada. It turns out they are experts at

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<v Speaker 1>pricing and reducing risk. I say it all the time

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<v Speaker 1>in the world of business. Truth is always always stranger

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<v Speaker 1>than fiction. Anyway, Alison has learned that there's a science

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<v Speaker 1>to good risk taking. She says that no one reaches

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<v Speaker 1>the top of their field, be it sex work or

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<v Speaker 1>running a fortune five hundred company without mastering risk. They

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<v Speaker 1>don't jump in and just go with their gut. They

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<v Speaker 1>possess a deliberate, thoughtful strategy so they know what risks

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<v Speaker 1>to take, and how to reduce the downside if things

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<v Speaker 1>don't go their way. I've always loved the quote with

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<v Speaker 1>which Alison begins her book. It's from Peter Bernstein's Against

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<v Speaker 1>the Gods. The revolutionary idea that defines the boundary between

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<v Speaker 1>modern times in the past is the mastery of risk,

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<v Speaker 1>the notion that the future is more than a whim

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<v Speaker 1>of the gods, and that men and women are not

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<v Speaker 1>pass before nature. So how do we master risk? Okay,

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<v Speaker 1>so the Bunny Ranch, we obviously have to start there.

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<v Speaker 1>How did you find these guys? Well, so it's a

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<v Speaker 1>funny story. Oh, I was really struggling with my book proposal.

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<v Speaker 1>I felt like I needed a great risk taker, and

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<v Speaker 1>so I had a drink with a cousin who I

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<v Speaker 1>can't name, and I was like, I, really, do you you

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<v Speaker 1>know anyone who was broken the law? I could really

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<v Speaker 1>use a criminal. Maybe they'll help me because I was

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<v Speaker 1>having problems coming up with stories. I love that I

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<v Speaker 1>could really use a criminal. That's awesome. And he tells

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<v Speaker 1>me that his girlfriend runs an illegal brothel, and well,

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<v Speaker 1>you know, it was really way more information than I needed.

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<v Speaker 1>It was a very specific kind of brothel. And that

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<v Speaker 1>it was out of New York and they specialized in submissives,

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<v Speaker 1>so women who get tied up and then have sex

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<v Speaker 1>with their clients. And because this is a very high

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<v Speaker 1>risk thing, even more risky than normal sex work, what

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<v Speaker 1>she did is she got a thirty percent cut if

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<v Speaker 1>she did all the screening and made them safer. And

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<v Speaker 1>I was like, oh, that's an interesting risk story. So

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<v Speaker 1>I wrote a court story about this woman and met

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<v Speaker 1>her and she's lovely, and the bunny ranch saw it.

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<v Speaker 1>He called me, and they're right, Well, if your bunny

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<v Speaker 1>ranch called you fabulous, if you're gonna be writing this

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<v Speaker 1>is snobbery. I guess it's a hierarchy in every business.

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<v Speaker 1>If you're gonna be writing about brothels, you should be

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<v Speaker 1>writing about our brothel because we're the biggest and most

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<v Speaker 1>important one. I don't write about brothels, but it's an

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<v Speaker 1>interesting call. So I'm gonna take this. And they had

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<v Speaker 1>something they want me to write about. It didn't really

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<v Speaker 1>make sense for me, but then they said something quite interesting,

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<v Speaker 1>which was, well, so we don't upset prices, but what

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<v Speaker 1>the women come in and they negotiate every price and

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<v Speaker 1>every transaction individually and I was like, well, that's interesting.

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<v Speaker 1>You so telling me of women and who are about

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<v Speaker 1>twenty years old negotiating for tens of thousands of dollars

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<v Speaker 1>with men in their sixties. And I why, yes, yes,

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<v Speaker 1>And you know, no one's ever asked about that before.

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<v Speaker 1>You know, they come in not knowing their values. So

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<v Speaker 1>we have a negotiation training program. And you heard this

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<v Speaker 1>a brothel through the lens of an economist. Yeah, so

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<v Speaker 1>I'll say I need to see this. So I went

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<v Speaker 1>out there and met Dennis Hof and spent about a

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<v Speaker 1>week and a half going through their negotiation training program.

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<v Speaker 1>And that's where I developed a relationship to where they

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<v Speaker 1>were going to let me come back and collect pricing

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<v Speaker 1>data because I was struck by how much they charged.

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<v Speaker 1>I wouldn't have expected they could get away with it,

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<v Speaker 1>because I mean, this is not an easy place to

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<v Speaker 1>get to, and like, why just pay a lot less

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<v Speaker 1>and use someone like my cousin's girlfriends. And it's a

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<v Speaker 1>huge markup over the illiegal market, right three stunning and

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<v Speaker 1>you have to go to Nevada. But I discovered it's

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<v Speaker 1>like Dennis was just like, you come here and you

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<v Speaker 1>just don't have to worry about anything, And is that

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<v Speaker 1>the key lesson for you? What was the key lesson

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<v Speaker 1>for you out of this about risk? That you know,

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<v Speaker 1>every market puts a price on risk, and in any market,

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<v Speaker 1>you have to pay to reduce risk. So that's the

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<v Speaker 1>thing that three hundred percent is. So you know, you

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<v Speaker 1>don't have to worry about some sort of Robert Craft situation.

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<v Speaker 1>Come there, you're not going to get caught. You know,

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<v Speaker 1>they even have some innocuous thing you put on your

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<v Speaker 1>credit card, totally discreet, it's completely legal, and you don't

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<v Speaker 1>have to worry about anything. So you pay for that.

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<v Speaker 1>So it's aspect or risk premium that you're paying. But

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<v Speaker 1>the women pay it too, because anyway they're charging it

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<v Speaker 1>was a fourteen hundred dollars an hour on average, they

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<v Speaker 1>actually have to pay fifty percent of the brothel and

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<v Speaker 1>then taxes on top of that. Tell me a little

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<v Speaker 1>bit about Shelby Starr and why she was willing to

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<v Speaker 1>do things this way, Well, because she didn't. She's someone

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<v Speaker 1>who never really wanted to break the law. I mean,

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<v Speaker 1>I met women there who worked in the illegal market,

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<v Speaker 1>and they add bad experiences and that's why they're there.

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<v Speaker 1>But a lot of them just wanted to do this

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<v Speaker 1>job and didn't want to if you worry about dealing

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<v Speaker 1>with law enforcement. They didn't want to have to deal

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<v Speaker 1>with crazy. I mean, they said, my cousin's girlfriend has

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<v Speaker 1>to do this to protect people, because it's super dangerous

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<v Speaker 1>being a sex worker and meeting people online and doing

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<v Speaker 1>some illegal activity with them. So you don't know if

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<v Speaker 1>they're gonna be crazy, if they're going to kill you,

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<v Speaker 1>beat you up, or you're going to be arrested. So

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<v Speaker 1>they just don't want to deal with that. I mean,

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<v Speaker 1>Shelby definitely sees herself and they all do is people

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<v Speaker 1>who are in legitimate businesses and they don't want to

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<v Speaker 1>feel in any way that what they're doing is illegal.

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<v Speaker 1>So it teaches you about managing risk. But it also

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<v Speaker 1>teaches you about this other concept that we think of

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<v Speaker 1>as belonging to the world of finance, but really belongs

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<v Speaker 1>to the much broader world, which is hedging, right exactly.

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<v Speaker 1>So it's a hedge. So in finance, you paid to you,

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<v Speaker 1>you take some risk off the table, and that's a hedge.

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<v Speaker 1>So in finance, it would be like the simplest way

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<v Speaker 1>to think about it is if you were investing in

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<v Speaker 1>the stock market, like a stock index fund, and you

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<v Speaker 1>weren't totally comfortable with market risk, you would put a

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<v Speaker 1>little bit in a treasury bond and so that's a hedge.

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<v Speaker 1>You get a lower return, but you also have lower risk.

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<v Speaker 1>And that's effectively what they're doing. They're they're sharing their

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<v Speaker 1>risk with the brothel and an exchange they or they

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<v Speaker 1>are actually the brothel's taking getting rid of all their risk,

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<v Speaker 1>and an exchange they get at lower pay. It's one

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<v Speaker 1>of the fascinating things about your book that I found

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<v Speaker 1>so interesting is how relevant these topics that we think

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<v Speaker 1>of as financial topics are too ordinary life, right, Yeah,

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<v Speaker 1>And that was the goal, is that you know, the

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<v Speaker 1>risk concepts are everywhere. I mean, finance is the study

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<v Speaker 1>of risk and financial markets, and that's partially just because

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<v Speaker 1>there's tons of data, but they really apply everywhere. I

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<v Speaker 1>actually want to back up and talk a little bit

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<v Speaker 1>about you, because you have a very personal story about

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<v Speaker 1>risk that you tell in the book, but tell us

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<v Speaker 1>about it. Yeah, and I think a lot of us

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<v Speaker 1>have been there and that you know, we often think,

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<v Speaker 1>you know, if something's hard, or if we work hard

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<v Speaker 1>at something, it's not going to be risky. But This

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<v Speaker 1>speaks to why it's so important. And this is the

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<v Speaker 1>easiest risk management piece of advice I can give you.

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<v Speaker 1>We're not easy, but the most important for all the

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<v Speaker 1>fancy things you can do, if you have a very

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<v Speaker 1>clearly well defined goal of the risk you're taking, then

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<v Speaker 1>nothing else is going to do more to ensure that

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<v Speaker 1>a risk works out. And so I went to grad

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<v Speaker 1>school right out of undergrad and it was an economics PhD.

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<v Speaker 1>And you know, I love economics. I always like idolized

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<v Speaker 1>famous economists in a really weird, geeky way when I

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<v Speaker 1>was in high school. That's the line you're not going

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<v Speaker 1>to hear about from everybody. I always lied famous economists.

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<v Speaker 1>I love that. Yeah. No, I was such a nerd

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<v Speaker 1>about it. I was so excited to get into like

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<v Speaker 1>good PhD programs where I ought to work with them.

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<v Speaker 1>I wanted to be one of them, I thought. And

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<v Speaker 1>so I, you know, at twenty three, just jump into

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<v Speaker 1>a quantitative PhD program. Anyway, I hadn't even taken calculus,

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<v Speaker 1>I'd know math training, and it was just awful. I mean,

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<v Speaker 1>it's it's it's it's a tough PhD. All PhDs are tough,

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<v Speaker 1>but economists tend to be particularly unhappy, and I'm told

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<v Speaker 1>my program was particularly unhappy. They even tell me now

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<v Speaker 1>when I see people from my department, theyre always like,

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<v Speaker 1>we're so much nice sort of people than we were

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<v Speaker 1>to you. But it was just a tough experience, and

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<v Speaker 1>especially the first year I was struggling so much because

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<v Speaker 1>I didn't have the math training as a former math major.

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<v Speaker 1>My heart is going out to you. Yeah, Like I

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<v Speaker 1>learned about, you know, a master's worth of math on

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<v Speaker 1>my own at night and still failed every exam. It

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<v Speaker 1>was just never note I empathize. So I figured, well,

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<v Speaker 1>this is hard. So therefore if I just work hard

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<v Speaker 1>and then do not only that an insanely quantitative dissertation

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<v Speaker 1>way more than necessary, then somehow this is going to

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<v Speaker 1>bring me great success and this is all going to

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<v Speaker 1>pay off because it's this hard, then something great's going

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<v Speaker 1>to happen. And then I solve this ridiculously difficult math problem. Anyway,

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<v Speaker 1>I'm not really a math person, or didn't consider myself one.

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<v Speaker 1>And then I went on the job market and was

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<v Speaker 1>on all these interviews to be a professor, and I

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<v Speaker 1>was like, I have no interest in being here. I

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<v Speaker 1>have you know, it's a great job for some people.

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<v Speaker 1>But I realized, you know, this is not what I

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<v Speaker 1>ever wanted. So it's things I invested in this asset

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<v Speaker 1>that never really got me to my goal because I

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<v Speaker 1>wasn't sure what my goal was. But it definitely wasn't that.

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<v Speaker 1>I loved your chapter heading getting what you want requires

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<v Speaker 1>knowing what you want. Yeah, and it's so basic, I guess.

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<v Speaker 1>It's so like the secret but also for a finance

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<v Speaker 1>and you see this all the time in financial markets too,

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<v Speaker 1>is you know when you invest with an for something

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<v Speaker 1>as this in retirement, which is what my background's in,

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<v Speaker 1>is that people everyone's geared towards investing for this huge

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<v Speaker 1>pot of money on day one er retirement, Like you

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<v Speaker 1>often see like what's your number, which is this pile

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<v Speaker 1>of money number, like maybe a million dollars if you're

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<v Speaker 1>lucky to retire with. But that's not your goal. Your

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<v Speaker 1>goal is income and investing for a pot of money

0:11:14.520 --> 0:11:16.600
<v Speaker 1>and investing for income that lasts a lifetime or to

0:11:16.640 --> 0:11:20.559
<v Speaker 1>totally different financial goals and require two totally different strategies,

0:11:20.559 --> 0:11:22.240
<v Speaker 1>and if you invest for one, you're going to be

0:11:22.240 --> 0:11:24.800
<v Speaker 1>a lot riskier with the other. One makes a ton

0:11:24.840 --> 0:11:27.559
<v Speaker 1>of sense, getting what you want requires knowing what you want, right,

0:11:28.320 --> 0:11:30.840
<v Speaker 1>But let's go let's go to that your fascination with

0:11:30.920 --> 0:11:33.640
<v Speaker 1>retirement because okay, that word in and of itself for

0:11:33.760 --> 0:11:35.800
<v Speaker 1>most of us, unless it's some kind of mixture of

0:11:35.880 --> 0:11:39.200
<v Speaker 1>Durad's stultifying boredom, I don't know. But you've always been

0:11:39.200 --> 0:11:42.319
<v Speaker 1>fascinated by retirement. Yeah, I mean, I think one of

0:11:42.320 --> 0:11:44.720
<v Speaker 1>the reasons people are put off by it is it's

0:11:44.720 --> 0:11:46.520
<v Speaker 1>sort of the last thing you do before you die,

0:11:46.720 --> 0:11:48.920
<v Speaker 1>and it's when you sort of give up on being

0:11:48.920 --> 0:11:52.760
<v Speaker 1>that person who contributes. It courses you to confront mortality. Yeah,

0:11:52.800 --> 0:11:55.200
<v Speaker 1>and also that you're like done with your career and

0:11:55.360 --> 0:11:56.920
<v Speaker 1>now you're just sort of being put out to pasture.

0:11:56.960 --> 0:11:59.880
<v Speaker 1>Although retirement, modern retirement need to be that way, but

0:12:00.040 --> 0:12:03.040
<v Speaker 1>for me, it was always this fascinating problem because it

0:12:03.120 --> 0:12:05.600
<v Speaker 1>was this pure distillation of what I thought economics was,

0:12:06.000 --> 0:12:10.280
<v Speaker 1>which is allocation of scarce resources. But it's over your lifetime, right,

0:12:10.360 --> 0:12:12.880
<v Speaker 1>So you make a certain amount of money and you

0:12:12.920 --> 0:12:15.240
<v Speaker 1>have to spend a certain amount of money, and how

0:12:15.400 --> 0:12:18.800
<v Speaker 1>do you do that in the best way? And if

0:12:18.840 --> 0:12:21.840
<v Speaker 1>you take more risk, you have the expectation of more

0:12:22.240 --> 0:12:24.360
<v Speaker 1>So how do you manage that risk. So this is

0:12:24.480 --> 0:12:27.240
<v Speaker 1>very pure, beautiful problem, which honestly, most of the most

0:12:27.280 --> 0:12:31.720
<v Speaker 1>interesting things happen when you're young, because it's a lifetime problem.

0:12:32.520 --> 0:12:34.960
<v Speaker 1>And I think when I was in grad school and

0:12:35.000 --> 0:12:37.160
<v Speaker 1>thinking about the problems, the problem you want to solve

0:12:37.160 --> 0:12:38.840
<v Speaker 1>and what you want to dedicate your career too, it

0:12:38.920 --> 0:12:42.360
<v Speaker 1>just really interested me. And what's the key insight that

0:12:42.400 --> 0:12:44.960
<v Speaker 1>you had that enabled you to think about retirement in

0:12:44.960 --> 0:12:49.040
<v Speaker 1>a different way. Well, you know, it's evolved over the years.

0:12:49.040 --> 0:12:51.560
<v Speaker 1>Even in grad school, I was thinking about risk. My

0:12:51.640 --> 0:12:54.680
<v Speaker 1>dissertation was looking at the move from define benefit to

0:12:54.679 --> 0:12:58.199
<v Speaker 1>define contribution plans, and I wasn't totally sold that define

0:12:58.240 --> 0:13:00.559
<v Speaker 1>benefit plans were that great that I saw all these

0:13:00.640 --> 0:13:03.160
<v Speaker 1>risks they did pose to people, the risk that this

0:13:03.200 --> 0:13:04.920
<v Speaker 1>company is going to go to business and you're gonna

0:13:04.920 --> 0:13:06.320
<v Speaker 1>have to take a huge haircut. I mean this as

0:13:06.320 --> 0:13:08.800
<v Speaker 1>big as you right now in Chicago. Who I believe me,

0:13:08.960 --> 0:13:13.400
<v Speaker 1>I know, Chicago unheedgeable risk for the participants in the

0:13:13.480 --> 0:13:16.480
<v Speaker 1>retirement or even if you back in the day, you know,

0:13:16.520 --> 0:13:19.000
<v Speaker 1>if you change jobs, you would often give up your pension.

0:13:19.160 --> 0:13:20.800
<v Speaker 1>So I was interested in what was risk here to

0:13:20.800 --> 0:13:24.199
<v Speaker 1>find contribution to find benefit. But back then I was

0:13:24.240 --> 0:13:27.480
<v Speaker 1>a macroeconomist, so I was thinking about it in a

0:13:27.480 --> 0:13:30.520
<v Speaker 1>more of a policy way. Then after grad school, as

0:13:30.520 --> 0:13:32.080
<v Speaker 1>I said, after I had blow up my career when

0:13:32.120 --> 0:13:33.720
<v Speaker 1>I realized I didn't want to be a professor, and

0:13:33.960 --> 0:13:35.600
<v Speaker 1>when you're in grad school, that's all you're told you

0:13:35.600 --> 0:13:38.760
<v Speaker 1>could ever be. So I was kind of lost, and

0:13:38.840 --> 0:13:41.440
<v Speaker 1>so I made a really sot of questionable decision to

0:13:41.440 --> 0:13:43.760
<v Speaker 1>be a journalist. Oh that's not a question about decision.

0:13:43.760 --> 0:13:46.000
<v Speaker 1>Who would call that a question about decision company. It

0:13:46.040 --> 0:13:47.880
<v Speaker 1>was like, I mean, granted, every year they tell your

0:13:47.920 --> 0:13:50.040
<v Speaker 1>journalism is dead, but there's two thousand and six, and

0:13:50.480 --> 0:13:52.400
<v Speaker 1>it was actually a really good time to do this

0:13:52.440 --> 0:13:55.000
<v Speaker 1>because it was the very early days of web journalism

0:13:55.120 --> 0:13:57.040
<v Speaker 1>when everyone thought this was going to disrupt the market,

0:13:57.080 --> 0:14:00.559
<v Speaker 1>but also didn't take it seriously at all. So the anyway,

0:14:00.559 --> 0:14:02.600
<v Speaker 1>I had no idea how to write. We sort of

0:14:02.640 --> 0:14:04.200
<v Speaker 1>just let me come in and write for them for

0:14:04.280 --> 0:14:06.720
<v Speaker 1>free on the web because they just were like, well,

0:14:07.320 --> 0:14:09.200
<v Speaker 1>this's the web most of the time. If you decide

0:14:09.240 --> 0:14:10.439
<v Speaker 1>you want to life change, you want to write for

0:14:10.440 --> 0:14:12.600
<v Speaker 1>the economist. That does not work. They want people who

0:14:12.600 --> 0:14:14.400
<v Speaker 1>actually know how to write that's important to them. But

0:14:14.440 --> 0:14:16.320
<v Speaker 1>they let me do it because it was web days

0:14:16.360 --> 0:14:18.600
<v Speaker 1>and they were pretty open. So for all your calibration

0:14:18.679 --> 0:14:21.440
<v Speaker 1>of risk, what role do you think luck place? Because

0:14:21.480 --> 0:14:24.840
<v Speaker 1>to some extent that two thousand and six move, was

0:14:25.040 --> 0:14:28.040
<v Speaker 1>luck right with timing or would you think about it differently?

0:14:28.400 --> 0:14:31.120
<v Speaker 1>I was. It didn't feel like it at the time.

0:14:31.560 --> 0:14:34.000
<v Speaker 1>In retrospect, it was because I learned this amazing skill,

0:14:34.080 --> 0:14:37.720
<v Speaker 1>skills about storytelling, skills about how to communicate economics to

0:14:37.760 --> 0:14:40.600
<v Speaker 1>an audience, which you certainly don't learn at academia. But

0:14:40.720 --> 0:14:43.840
<v Speaker 1>I think everyone gets a certain amount of luck in life,

0:14:44.440 --> 0:14:46.760
<v Speaker 1>but it's about knowing how to capitalize on it and

0:14:46.840 --> 0:14:50.000
<v Speaker 1>knowing how to hedge or be prepared for bad luck too.

0:14:50.280 --> 0:14:52.160
<v Speaker 1>I mean, at the time it looked like bad luck.

0:14:52.200 --> 0:14:54.520
<v Speaker 1>I had no job, I was graduating from an economics

0:14:54.520 --> 0:14:56.760
<v Speaker 1>PhD with no job. I was writing for free for

0:14:56.800 --> 0:14:58.760
<v Speaker 1>the web. I mean, this did not seem like a

0:14:58.800 --> 0:15:02.200
<v Speaker 1>good move. So before we leave the topic of retirement alone,

0:15:02.320 --> 0:15:04.480
<v Speaker 1>I want to come back to it because one I

0:15:04.520 --> 0:15:07.400
<v Speaker 1>want to ask you how big an issue is this today?

0:15:07.640 --> 0:15:09.080
<v Speaker 1>I mean, it's a big issue. I think it's not

0:15:09.120 --> 0:15:12.000
<v Speaker 1>the issue people think it is. I think everyone's convinced

0:15:12.040 --> 0:15:14.880
<v Speaker 1>they just don't have enough money, and that's true for

0:15:14.960 --> 0:15:16.920
<v Speaker 1>a lot of people. I don't want to minimize that,

0:15:17.000 --> 0:15:19.680
<v Speaker 1>but I think that's not the primary issue. The primary

0:15:19.680 --> 0:15:21.160
<v Speaker 1>issue is that people don't and this is one of

0:15:21.160 --> 0:15:23.160
<v Speaker 1>the reasons I really want to do the book have

0:15:23.320 --> 0:15:26.480
<v Speaker 1>the tools to really manage They've been handed a huge

0:15:26.560 --> 0:15:29.400
<v Speaker 1>risk problem with the fine benefit plans. The employer took

0:15:29.440 --> 0:15:32.720
<v Speaker 1>all the risk. Now we've a fairly significant risk problem,

0:15:32.800 --> 0:15:36.040
<v Speaker 1>a problem I've dedicated my whole career too, and still

0:15:36.040 --> 0:15:39.960
<v Speaker 1>haven't found easy answers to on everyone. So people don't

0:15:39.960 --> 0:15:42.840
<v Speaker 1>really have the tools to manage this incredibly complicated risk problem.

0:15:42.960 --> 0:15:44.920
<v Speaker 1>And I think a lot of the personal finance literature

0:15:44.960 --> 0:15:47.560
<v Speaker 1>gets people, leads people stray or sets them up to

0:15:47.800 --> 0:15:50.160
<v Speaker 1>feel like they're failing because they's like, oh, it's easy,

0:15:50.240 --> 0:15:53.080
<v Speaker 1>just do this, but aren't really addressing all the risks

0:15:53.080 --> 0:15:56.400
<v Speaker 1>they're really facing. So we've dumped a problem on people

0:15:56.440 --> 0:15:59.400
<v Speaker 1>and not given them the tools to manage it. In essence, Yeah,

0:15:59.400 --> 0:16:01.240
<v Speaker 1>and it doesn't mean it's not workable. I mean, I

0:16:01.280 --> 0:16:05.280
<v Speaker 1>think the defined contribution for on K structure can really

0:16:05.320 --> 0:16:08.240
<v Speaker 1>work and give people secure retirement. But we have to

0:16:08.280 --> 0:16:10.640
<v Speaker 1>think more holistically about the tools and think of it

0:16:10.920 --> 0:16:14.320
<v Speaker 1>as this lifetime problem rather than well, I don't know,

0:16:14.400 --> 0:16:16.360
<v Speaker 1>you just save and invest and we'll see what happens,

0:16:16.360 --> 0:16:18.600
<v Speaker 1>and perhaps get people to think about it like you do,

0:16:18.760 --> 0:16:22.240
<v Speaker 1>as a beautiful, pure problem rather than it's some force

0:16:22.280 --> 0:16:24.880
<v Speaker 1>of existential dread hanging over all of our heads. Right.

0:16:25.840 --> 0:16:27.760
<v Speaker 1>I wanted to go back to this notion as well,

0:16:28.200 --> 0:16:30.680
<v Speaker 1>of the concept of risk free. I loved this quote

0:16:30.680 --> 0:16:33.440
<v Speaker 1>you use from Gerta. The dangers of life are infinite,

0:16:33.440 --> 0:16:36.120
<v Speaker 1>and among them is safety. Is there actually something as

0:16:36.120 --> 0:16:39.240
<v Speaker 1>simple as risk free? Well? There is. I don't think

0:16:39.280 --> 0:16:41.120
<v Speaker 1>a lot of people appreciate this, certainly not a lot

0:16:41.120 --> 0:16:43.120
<v Speaker 1>of people actually, who even work in finance, that the

0:16:43.160 --> 0:16:46.000
<v Speaker 1>foundation of all risk problems is the risk free asset.

0:16:46.040 --> 0:16:48.840
<v Speaker 1>If you look at any of these complicated formulas that

0:16:48.840 --> 0:16:50.960
<v Speaker 1>people do to price risk, there's always the risk free

0:16:51.040 --> 0:16:54.160
<v Speaker 1>rate in there. So it is in some ways it

0:16:54.200 --> 0:16:56.720
<v Speaker 1>calibrates how much risk you can take. Because if a

0:16:56.720 --> 0:17:01.160
<v Speaker 1>savings bond is going to pay you sent inflation adjusted

0:17:01.200 --> 0:17:03.600
<v Speaker 1>to return, why bother going into the stock market. So

0:17:03.960 --> 0:17:06.080
<v Speaker 1>it determines how much risk you take, and it determines

0:17:06.119 --> 0:17:08.879
<v Speaker 1>how much you put a price on risk. Obviously you

0:17:08.920 --> 0:17:11.920
<v Speaker 1>know there's problems with it and that people sometimes get

0:17:11.920 --> 0:17:14.640
<v Speaker 1>confused about, Like as I said, I assume more education

0:17:14.720 --> 0:17:17.080
<v Speaker 1>was a risk free asset. That's not always true. Or

0:17:17.160 --> 0:17:20.040
<v Speaker 1>people assume a bond can't default when it does, so

0:17:20.359 --> 0:17:23.280
<v Speaker 1>there can be this illusion of either you've defined risk

0:17:23.280 --> 0:17:25.360
<v Speaker 1>free wrong, or you think something's risk for you when

0:17:25.400 --> 0:17:28.639
<v Speaker 1>it's not and that can create other risks. Or I

0:17:28.760 --> 0:17:31.000
<v Speaker 1>just wrote a fun story which I was ripping off

0:17:31.000 --> 0:17:35.879
<v Speaker 1>of the book, which is sometimes I worry that you

0:17:35.920 --> 0:17:38.520
<v Speaker 1>know the risk free value of not leaving your home,

0:17:38.640 --> 0:17:40.439
<v Speaker 1>which is sort of the risk free choice, right, Like

0:17:40.480 --> 0:17:42.240
<v Speaker 1>I'm not gonna bother go home, I'm gonna do stay,

0:17:42.240 --> 0:17:44.679
<v Speaker 1>I'm gonna watch Netflix is supposed to Leaving your house

0:17:44.720 --> 0:17:46.160
<v Speaker 1>is always a risk. You don't know it's gonna happen.

0:17:46.160 --> 0:17:47.439
<v Speaker 1>You might have a bad time, you could get hit

0:17:47.440 --> 0:17:49.560
<v Speaker 1>by a car, or something great could happen. It's just

0:17:49.600 --> 0:17:52.879
<v Speaker 1>like stay at home. It's become so compelling, Like maybe

0:17:52.920 --> 0:17:56.440
<v Speaker 1>this is why millennials apparently aren't having sex anymore. Is

0:17:56.480 --> 0:17:58.720
<v Speaker 1>it's just like why go out on a Tinder date

0:17:58.760 --> 0:18:02.000
<v Speaker 1>when you can watch Game of throwing good questions? But

0:18:02.600 --> 0:18:04.840
<v Speaker 1>is staying at home truly risk free or is that

0:18:04.920 --> 0:18:07.200
<v Speaker 1>an illusion? It's an illusion or in the short run,

0:18:07.320 --> 0:18:09.159
<v Speaker 1>or maybe it is. I mean, maybe you feel like

0:18:09.520 --> 0:18:11.560
<v Speaker 1>I can have a very satisfying life never leaving the

0:18:11.560 --> 0:18:13.760
<v Speaker 1>house and playing video games and watching Game of Thrones.

0:18:13.800 --> 0:18:16.639
<v Speaker 1>But it's important to take risks. It's, you know, it's

0:18:16.680 --> 0:18:19.400
<v Speaker 1>how your life moves forward. It's how you actually will

0:18:19.440 --> 0:18:22.040
<v Speaker 1>meet people and have a career and do all these

0:18:22.080 --> 0:18:25.040
<v Speaker 1>important things that will ultimately make you happier. I mean,

0:18:25.080 --> 0:18:27.199
<v Speaker 1>maybe the fact that people are staying in more and

0:18:27.200 --> 0:18:30.360
<v Speaker 1>have become more attached to these sort of risk free

0:18:30.760 --> 0:18:32.920
<v Speaker 1>sources of stimulation is also why there's higher rates of

0:18:32.960 --> 0:18:35.680
<v Speaker 1>anxiety and depression. It goes back to that Gerta quote,

0:18:35.680 --> 0:18:37.840
<v Speaker 1>I think the dangerous of life are infinite, and among

0:18:37.880 --> 0:18:40.720
<v Speaker 1>them as safety. It's an incredibly compelling quote. So what

0:18:40.760 --> 0:18:44.040
<v Speaker 1>do you think people misunderstand most about risk? I think

0:18:44.080 --> 0:18:45.840
<v Speaker 1>they tend to think of it as this binary thing,

0:18:46.040 --> 0:18:48.639
<v Speaker 1>like either you're a risk taker or you're not, or

0:18:48.640 --> 0:18:50.720
<v Speaker 1>either you take a risk in you're someone who shakes

0:18:50.800 --> 0:18:53.080
<v Speaker 1>up things or you don't. But really risk has this

0:18:53.200 --> 0:18:57.280
<v Speaker 1>huge middle ground that you calibrate to whatever your preferences. Are,

0:18:57.359 --> 0:18:59.920
<v Speaker 1>or whatever your desires are, and once you take a risk,

0:19:00.160 --> 0:19:01.879
<v Speaker 1>you can manage it. I mean, I think people to

0:19:01.920 --> 0:19:03.960
<v Speaker 1>call this a calculated risk, although they don't really able

0:19:03.960 --> 0:19:05.800
<v Speaker 1>to say what that means, which is, you take a

0:19:05.920 --> 0:19:08.720
<v Speaker 1>risk where you're very clear about what it is you want,

0:19:08.760 --> 0:19:11.159
<v Speaker 1>and then you do things to manage the downside. Like

0:19:11.280 --> 0:19:13.760
<v Speaker 1>your sex workers, like Shelby Starr, she takes a risk

0:19:13.840 --> 0:19:16.359
<v Speaker 1>and then she figures out how to hedge against the

0:19:16.400 --> 0:19:18.800
<v Speaker 1>risk she's taking, exactly like becoming a sex workers a

0:19:18.840 --> 0:19:22.280
<v Speaker 1>fairly risky job, even if you're in the bunny ranch

0:19:22.359 --> 0:19:26.119
<v Speaker 1>where you have access to healthcare and they get tested

0:19:26.160 --> 0:19:28.000
<v Speaker 1>for diseases and they don't worry about breaking the law.

0:19:28.040 --> 0:19:30.200
<v Speaker 1>I mean, there's still a huge social stigma. So do

0:19:30.320 --> 0:19:33.600
<v Speaker 1>optimism and pessimism have anything to do with risk reward?

0:19:33.680 --> 0:19:36.320
<v Speaker 1>Whether people consider themselves a risk taker or not? In

0:19:36.320 --> 0:19:38.639
<v Speaker 1>other words, are optimists more inclined to take risk and

0:19:38.720 --> 0:19:41.120
<v Speaker 1>pessimists not? Or does it not break down that simply?

0:19:41.600 --> 0:19:43.560
<v Speaker 1>I don't know if it breaks down that simply. I mean,

0:19:43.800 --> 0:19:47.080
<v Speaker 1>certainly people decide whether or not to take a risk.

0:19:47.320 --> 0:19:49.640
<v Speaker 1>There's I mean, it might not happen as precisely as

0:19:49.640 --> 0:19:52.960
<v Speaker 1>financial economists do, but I think there's some calculation that

0:19:53.000 --> 0:19:54.720
<v Speaker 1>goes on on what the odds these are going to

0:19:54.760 --> 0:19:57.879
<v Speaker 1>work out for me? And if you think it's definitely

0:19:58.040 --> 0:19:59.800
<v Speaker 1>not going to be a problem and it's definitely going

0:19:59.880 --> 0:20:01.679
<v Speaker 1>to go your way, you're more inclined to do it.

0:20:01.880 --> 0:20:04.480
<v Speaker 1>On the other hand, if you only see downside, you're

0:20:04.560 --> 0:20:07.680
<v Speaker 1>less likely. But that might be partially driven by personality

0:20:07.680 --> 0:20:09.639
<v Speaker 1>and outlook, and it also might be driven by the

0:20:09.720 --> 0:20:14.119
<v Speaker 1>cues or personal experiences with risk of how comfortable we

0:20:14.160 --> 0:20:17.399
<v Speaker 1>feel taking on risk. So you mentioned the odds, and

0:20:17.480 --> 0:20:19.919
<v Speaker 1>something else I thought was fascinating about your book is

0:20:19.960 --> 0:20:23.000
<v Speaker 1>how bad we are probabilities. Why are we so bad

0:20:23.040 --> 0:20:27.280
<v Speaker 1>at understanding probabilities when they are so key to life? Well,

0:20:27.320 --> 0:20:30.600
<v Speaker 1>I think it's partially that probabilities are a relatively new invention.

0:20:30.760 --> 0:20:32.480
<v Speaker 1>We take them for granted. And I always say new,

0:20:32.520 --> 0:20:35.200
<v Speaker 1>I mean, like, you know, like late Renaissance, which seems

0:20:35.200 --> 0:20:36.919
<v Speaker 1>like a long time ago, but it seems like a

0:20:36.920 --> 0:20:39.840
<v Speaker 1>long time ago, and the granted scheme of human evolutions. Yes,

0:20:40.040 --> 0:20:44.280
<v Speaker 1>it's a relatively recent invention, so it's not shocking that

0:20:44.320 --> 0:20:47.200
<v Speaker 1>our brains don't conform to it, especially if you compare

0:20:47.240 --> 0:20:50.600
<v Speaker 1>it to say reading. Reading also isn't something we're more

0:20:50.760 --> 0:20:52.600
<v Speaker 1>knowing how to do. It's something we're trained to do

0:20:52.600 --> 0:20:54.280
<v Speaker 1>when we take it for granted. But yet we've been

0:20:54.280 --> 0:20:57.520
<v Speaker 1>trained for centuries exactly. It's opposed to we don't. We've

0:20:57.520 --> 0:20:59.840
<v Speaker 1>come up with probabilities, but we never really trained people

0:21:00.119 --> 0:21:01.920
<v Speaker 1>to think about them, how to make sense of them.

0:21:02.000 --> 0:21:04.120
<v Speaker 1>Yet we expect people to just to be born knowing

0:21:04.119 --> 0:21:06.200
<v Speaker 1>how to do it. But I mean, they're a modern

0:21:06.240 --> 0:21:08.520
<v Speaker 1>construct in the same way the written word is. I

0:21:08.640 --> 0:21:11.600
<v Speaker 1>came across the work of Gigerenzer, who believes that you

0:21:11.680 --> 0:21:14.440
<v Speaker 1>actually really can make sense of uncertainty and risk and

0:21:15.240 --> 0:21:17.960
<v Speaker 1>make conferences about probabilities that actually makes sense. It just

0:21:18.000 --> 0:21:20.400
<v Speaker 1>depends on how it's presented. It's like, if you think

0:21:20.440 --> 0:21:23.600
<v Speaker 1>in terms of frequencies instead of a raw probability, people

0:21:23.640 --> 0:21:26.000
<v Speaker 1>tend to make better choices. Give me the most compelling

0:21:26.080 --> 0:21:28.440
<v Speaker 1>example of how you can think, how you can think

0:21:28.480 --> 0:21:32.480
<v Speaker 1>smartly about probabilities. So when you hear a probability, you know,

0:21:32.640 --> 0:21:35.440
<v Speaker 1>rather than sink, okay, there's a point a one percent

0:21:35.520 --> 0:21:37.280
<v Speaker 1>chance of something happening. That doesn't really have a lot

0:21:37.320 --> 0:21:39.880
<v Speaker 1>of meaning now, but a one in one thousand does

0:21:40.480 --> 0:21:42.760
<v Speaker 1>I mean, you even see this with a lottery. Statistically,

0:21:42.800 --> 0:21:46.800
<v Speaker 1>it's very unlikely you're going to win the lottery. But

0:21:46.880 --> 0:21:49.359
<v Speaker 1>when you get that ticket or you see how the

0:21:49.520 --> 0:21:53.040
<v Speaker 1>lottery markets itself, they always plant in your head this

0:21:53.200 --> 0:21:56.679
<v Speaker 1>whole story. They make the frequency seem larger than it is.

0:21:57.000 --> 0:21:59.920
<v Speaker 1>They trot out the winner. They have that little song

0:22:00.320 --> 0:22:02.440
<v Speaker 1>when you are buying the lottery ticket says you can't

0:22:02.440 --> 0:22:04.919
<v Speaker 1>win if you don't play. So all of a sudden,

0:22:05.119 --> 0:22:08.760
<v Speaker 1>that infintestinal probability seems much larger it is. But you

0:22:08.800 --> 0:22:11.480
<v Speaker 1>could think about it in terms of frequency. They don't

0:22:11.480 --> 0:22:13.040
<v Speaker 1>do this is they could line up all the people

0:22:13.080 --> 0:22:15.800
<v Speaker 1>who played and didn't win. So you have to cut

0:22:15.800 --> 0:22:18.399
<v Speaker 1>through the hopes and fears and desires and get to

0:22:18.440 --> 0:22:20.919
<v Speaker 1>the numbers, and get to the numbers presented in a

0:22:20.960 --> 0:22:23.960
<v Speaker 1>way that makes sense to your brain exactly. Okay, So

0:22:24.000 --> 0:22:27.120
<v Speaker 1>let's think about risk as it's applied to various industries.

0:22:27.200 --> 0:22:29.520
<v Speaker 1>And I loved the story that you tell in the

0:22:29.560 --> 0:22:33.320
<v Speaker 1>book of Ryan Cavanaugh and Hollywood. What does that teach

0:22:33.400 --> 0:22:36.439
<v Speaker 1>us about risk? I think about why risk measurements so

0:22:36.520 --> 0:22:38.840
<v Speaker 1>hard because we make we come up with these probabilities.

0:22:38.840 --> 0:22:41.119
<v Speaker 1>They have to be based on something and they're usually

0:22:41.119 --> 0:22:43.439
<v Speaker 1>based on data because you know, what else do we

0:22:43.480 --> 0:22:46.240
<v Speaker 1>have to go on. Problem is data is always by

0:22:46.280 --> 0:22:49.760
<v Speaker 1>definition from the past, and you know the past changes.

0:22:50.080 --> 0:22:53.560
<v Speaker 1>So Ryan Cavanaugh was this whiz kid type who came

0:22:53.560 --> 0:22:56.480
<v Speaker 1>to Hollywood, and people in Hollywood are it's a big

0:22:56.520 --> 0:22:59.359
<v Speaker 1>financial risk to finance a movie is that you know

0:22:59.400 --> 0:23:01.760
<v Speaker 1>you don't pay starting for years. Most of the movies

0:23:01.840 --> 0:23:04.719
<v Speaker 1>lose money, and you know you have to put all

0:23:04.720 --> 0:23:07.800
<v Speaker 1>the money up up front. So he promised that he

0:23:08.000 --> 0:23:11.840
<v Speaker 1>had an algorithm that would predict movie success. And everyone

0:23:11.920 --> 0:23:14.159
<v Speaker 1>signed on to this because everyone wants to believe this

0:23:15.040 --> 0:23:18.080
<v Speaker 1>the magic algorithm. Yeah, and it was a good timing

0:23:18.160 --> 0:23:20.600
<v Speaker 1>for him, and that the studios were looking for new

0:23:20.680 --> 0:23:26.399
<v Speaker 1>sources of financing and hedge funds were looking for higher yields. Plus,

0:23:26.480 --> 0:23:28.919
<v Speaker 1>people from this finance world tend to like the glamor

0:23:28.960 --> 0:23:32.160
<v Speaker 1>of movies and tend to not make great choices when

0:23:32.200 --> 0:23:35.000
<v Speaker 1>they have that glamor presented to them. So he kind

0:23:35.000 --> 0:23:39.000
<v Speaker 1>of married these two groups by telling these hedge funders secret,

0:23:39.040 --> 0:23:41.080
<v Speaker 1>I can quantify risk the same way you like to

0:23:41.119 --> 0:23:45.000
<v Speaker 1>do it. And the movie students where he's like, I

0:23:45.040 --> 0:23:47.720
<v Speaker 1>can bring in money. So they gave him all their

0:23:47.720 --> 0:23:51.439
<v Speaker 1>best data, and he had this fancy model that he claimed,

0:23:51.520 --> 0:23:53.520
<v Speaker 1>I can put a number on a chance and movies

0:23:53.640 --> 0:23:57.639
<v Speaker 1>gonna make it or not. And he put together slights

0:23:57.640 --> 0:24:00.000
<v Speaker 1>of movies and it worked for a couple of years,

0:24:00.800 --> 0:24:04.840
<v Speaker 1>but then it didn't because the movie industry just keeps changing.

0:24:04.960 --> 0:24:08.160
<v Speaker 1>Data gets stale so fast. In the time I think

0:24:08.160 --> 0:24:10.480
<v Speaker 1>he was in business, DVD sales came from a significant

0:24:10.480 --> 0:24:13.600
<v Speaker 1>source of revenue to just completely disappearing. Or you get fads,

0:24:13.600 --> 0:24:15.920
<v Speaker 1>you have China coming into the market and all of

0:24:15.960 --> 0:24:18.800
<v Speaker 1>a sudden, comic book movies become more important, or you

0:24:18.840 --> 0:24:21.600
<v Speaker 1>have rotten tomatoes that totally undermine all the marketing plans.

0:24:21.960 --> 0:24:25.240
<v Speaker 1>So the data just becomes so stale and almost worthless.

0:24:25.280 --> 0:24:26.760
<v Speaker 1>And so if you're going to use a model like this,

0:24:26.840 --> 0:24:28.920
<v Speaker 1>you always have to stay on top of it. That's

0:24:28.960 --> 0:24:31.440
<v Speaker 1>interesting I was thinking as you were talking about how

0:24:31.480 --> 0:24:35.080
<v Speaker 1>it ties back to our previous discussion about the hopes

0:24:35.080 --> 0:24:37.800
<v Speaker 1>and dreams and fears clouding the numbers, because you can't

0:24:37.800 --> 0:24:40.000
<v Speaker 1>think of a better example than Hollywood, right where the

0:24:40.000 --> 0:24:44.159
<v Speaker 1>glamor of the movies clouds people's judgment about what the

0:24:44.240 --> 0:24:47.679
<v Speaker 1>numbers actually are. But it's also a fascinating industry given that,

0:24:47.720 --> 0:24:50.119
<v Speaker 1>as you note, there's more and more data, but the

0:24:50.200 --> 0:24:52.800
<v Speaker 1>limitations are also more and more imparent in the face

0:24:52.800 --> 0:24:55.480
<v Speaker 1>of all this rapid change, and how do you deal

0:24:55.520 --> 0:24:58.360
<v Speaker 1>with that from the standpoint of risk management, Because it's

0:24:58.400 --> 0:25:00.639
<v Speaker 1>a broader issue than Hollywood, right, it's a facet of

0:25:00.680 --> 0:25:04.000
<v Speaker 1>our world, more and more data and more and more change. Yeah,

0:25:04.040 --> 0:25:06.840
<v Speaker 1>so I think where we're maybe going wrong as thinking

0:25:06.920 --> 0:25:09.360
<v Speaker 1>data just speaks for itself, which is I think when

0:25:09.400 --> 0:25:12.000
<v Speaker 1>the lessons from this Ryan have an off parable. Data

0:25:12.080 --> 0:25:14.840
<v Speaker 1>is a great tool. I'm not saying we shouldn't use data,

0:25:14.920 --> 0:25:16.760
<v Speaker 1>but we have to be mindful of how we use it.

0:25:17.040 --> 0:25:18.920
<v Speaker 1>And right now with movies, we've got the best data

0:25:18.960 --> 0:25:22.119
<v Speaker 1>we've ever had, and that with Netflix and Amazon, they

0:25:22.200 --> 0:25:25.879
<v Speaker 1>have actual data on who very finally tune demographics of

0:25:25.920 --> 0:25:28.600
<v Speaker 1>who starts and stops movies and what do they attract

0:25:28.800 --> 0:25:31.120
<v Speaker 1>in a way we never had before. So the potential

0:25:31.200 --> 0:25:34.720
<v Speaker 1>is there to really do marketing a lot cheaper and

0:25:34.800 --> 0:25:38.000
<v Speaker 1>to really start tellering movies to more what's considered niche

0:25:38.040 --> 0:25:40.760
<v Speaker 1>audiences like women. But you have to be smart and

0:25:40.800 --> 0:25:42.320
<v Speaker 1>how you use your data, and you can't assume that

0:25:42.320 --> 0:25:43.840
<v Speaker 1>the data is just there. You have to be very

0:25:43.840 --> 0:25:46.520
<v Speaker 1>mindful of is this data relevant to what you're interested in.

0:25:46.680 --> 0:25:49.280
<v Speaker 1>I think I use the parallel to using pass trips

0:25:49.320 --> 0:25:52.200
<v Speaker 1>to the airport to calibrate the risk you're going to

0:25:52.240 --> 0:25:53.920
<v Speaker 1>be late to the airport if you go to the

0:25:53.960 --> 0:25:56.000
<v Speaker 1>airport and most of the time it's between twenty five

0:25:56.040 --> 0:25:58.000
<v Speaker 1>and thirty five minutes. You based your airport travel time

0:25:58.000 --> 0:26:00.719
<v Speaker 1>based on your past history. But like, what if they

0:26:00.720 --> 0:26:03.320
<v Speaker 1>build a new highway to the airport that just completely

0:26:03.400 --> 0:26:06.040
<v Speaker 1>changes your route, then all those pass trips aren't really

0:26:06.080 --> 0:26:08.800
<v Speaker 1>useful anymore, even though they're still implanted in your brain

0:26:08.960 --> 0:26:11.680
<v Speaker 1>somewhere as a mental as a mental roadmap. I think

0:26:11.720 --> 0:26:13.479
<v Speaker 1>you used the phrase in the book, which I've always

0:26:13.520 --> 0:26:18.040
<v Speaker 1>loved about models, garbage in, garbage out. Yeah, And that's

0:26:18.080 --> 0:26:21.320
<v Speaker 1>what they said about Ryan's model. I spoke to a

0:26:21.359 --> 0:26:24.080
<v Speaker 1>lot of banks that have their movie business, and they

0:26:24.080 --> 0:26:26.800
<v Speaker 1>were incredibly candid, one about people who go in and

0:26:26.800 --> 0:26:29.560
<v Speaker 1>invest naively in two about just who've been working on

0:26:29.640 --> 0:26:32.760
<v Speaker 1>financial models for years, about all the weaknesses in Kavano's model.

0:26:32.920 --> 0:26:35.080
<v Speaker 1>Speaking of weaknesses and models, that's something I've actually been

0:26:35.080 --> 0:26:37.080
<v Speaker 1>fascinated with for a while, and I was just reading

0:26:37.119 --> 0:26:40.520
<v Speaker 1>about a finance guy named Emmanuel Derman math Quondai who

0:26:40.600 --> 0:26:43.360
<v Speaker 1>started to question models in the wake of the financial crisis,

0:26:43.359 --> 0:26:46.040
<v Speaker 1>And he said this to confuse a model with the

0:26:46.040 --> 0:26:49.320
<v Speaker 1>world of humans as a form of idolatry and more dangerous.

0:26:49.720 --> 0:26:52.000
<v Speaker 1>And I started to think after the financial crisis that

0:26:52.040 --> 0:26:54.879
<v Speaker 1>the phrase risk management was actually an oxymoron, sort of

0:26:54.880 --> 0:26:58.359
<v Speaker 1>like jumbo shrimp, because the finance industry clearly didn't do

0:26:58.400 --> 0:27:00.320
<v Speaker 1>a very good job of managing risk in the run

0:27:00.400 --> 0:27:02.560
<v Speaker 1>up to the crisis. So what did they get wrong?

0:27:02.600 --> 0:27:04.720
<v Speaker 1>Where did their models go wrong? Well, a couple of

0:27:04.720 --> 0:27:07.960
<v Speaker 1>different ways. My mentor was Robert Merton, who was the

0:27:08.000 --> 0:27:09.880
<v Speaker 1>creator of a lot of these models and also known

0:27:10.000 --> 0:27:12.720
<v Speaker 1>for a hedge fund that didn't go well himself. That

0:27:12.800 --> 0:27:16.120
<v Speaker 1>was long term capital management, wasn't it, Yes, hedge fund.

0:27:17.000 --> 0:27:19.800
<v Speaker 1>He always says that when you're assessing the viability of

0:27:19.800 --> 0:27:22.639
<v Speaker 1>a model, there's two things you have to keep in mind.

0:27:22.920 --> 0:27:25.480
<v Speaker 1>One is the quality of the model. Sometimes it's just

0:27:25.520 --> 0:27:29.400
<v Speaker 1>a bad model. Two is the right model being used

0:27:29.440 --> 0:27:31.240
<v Speaker 1>for the right job. It's like, are you using a

0:27:31.280 --> 0:27:33.760
<v Speaker 1>screwdriver to do a job that a hammer should? And

0:27:33.880 --> 0:27:35.800
<v Speaker 1>three is the person using it know what they're doing,

0:27:36.560 --> 0:27:39.359
<v Speaker 1>and I think with a financial crisis you can see

0:27:39.720 --> 0:27:43.200
<v Speaker 1>a lot of all of those happening. Sometimes people use

0:27:43.200 --> 0:27:45.840
<v Speaker 1>models that just weren't great. Sometimes people use perfectly good

0:27:45.880 --> 0:27:48.320
<v Speaker 1>models but just in the wrong way. And sometimes they

0:27:48.359 --> 0:27:51.240
<v Speaker 1>just applied it to the wrong problem. And this is

0:27:51.280 --> 0:27:54.679
<v Speaker 1>why I think you need one more education about what

0:27:54.720 --> 0:27:57.320
<v Speaker 1>these models are and what they can do, and also

0:27:57.520 --> 0:28:00.720
<v Speaker 1>more awareness of what their natural limitation are. That doesn't

0:28:00.720 --> 0:28:02.720
<v Speaker 1>mean you shouldn't use them. I feel like a lot

0:28:02.760 --> 0:28:05.199
<v Speaker 1>of people who critique financial models, I'm not quite sure

0:28:05.280 --> 0:28:07.960
<v Speaker 1>what their point is is that should we just not

0:28:08.040 --> 0:28:10.520
<v Speaker 1>do anything, Should we just not bother to measure or

0:28:10.560 --> 0:28:13.919
<v Speaker 1>manage risk? Should we just guess? Yeah? Because I like

0:28:13.960 --> 0:28:16.840
<v Speaker 1>to think of risk models as like a roadmap if

0:28:16.880 --> 0:28:19.080
<v Speaker 1>you're taking a trip. I mean, it does not guarantee

0:28:19.119 --> 0:28:21.520
<v Speaker 1>a safe journey. You might still get into a car accident.

0:28:21.920 --> 0:28:24.640
<v Speaker 1>But what it does is it helps you understand how

0:28:24.680 --> 0:28:28.119
<v Speaker 1>different factors relate to each other, what makes what enhances

0:28:28.160 --> 0:28:30.919
<v Speaker 1>your risk, what things might get in your way. But

0:28:31.040 --> 0:28:33.240
<v Speaker 1>it doesn't have every tree in there. You know, you

0:28:33.280 --> 0:28:35.919
<v Speaker 1>have to make abstractions, you have to make choices, But

0:28:36.000 --> 0:28:37.879
<v Speaker 1>it can really help the odds that you're gonna have

0:28:37.880 --> 0:28:40.520
<v Speaker 1>a successful journey, but it doesn't really make any guarantees.

0:28:40.600 --> 0:28:42.800
<v Speaker 1>So I mean, and this is why you have to

0:28:42.800 --> 0:28:45.000
<v Speaker 1>be careful of its limitations and also make sure you're

0:28:45.080 --> 0:28:47.600
<v Speaker 1>using it right. Switching gears a little bit, what do

0:28:47.640 --> 0:28:51.440
<v Speaker 1>you think technology CEOs could stand to learn from sex workers.

0:28:51.960 --> 0:28:54.720
<v Speaker 1>I think it's about hedging, like you see them, and

0:28:54.960 --> 0:28:56.960
<v Speaker 1>I mean, maybe it's because they've been getting capital with

0:28:57.040 --> 0:28:59.760
<v Speaker 1>having to earn a profit that they just feel like

0:28:59.760 --> 0:29:02.640
<v Speaker 1>it seems like that they aren't really think being very

0:29:02.640 --> 0:29:05.120
<v Speaker 1>thoughtful about risk. I mean, you look at Facebook, and

0:29:05.200 --> 0:29:07.840
<v Speaker 1>you look at their early days, and they were so careful,

0:29:08.040 --> 0:29:11.720
<v Speaker 1>Like even the rollout was so slow and deliberate because

0:29:11.720 --> 0:29:14.520
<v Speaker 1>they were heating the lessons from friends stir that just

0:29:14.600 --> 0:29:17.440
<v Speaker 1>tried to meet their demands and overstretch themselves and had

0:29:17.440 --> 0:29:20.320
<v Speaker 1>a bad product. So Facebook would it only roll out

0:29:20.400 --> 0:29:22.720
<v Speaker 1>very slowly anyway, They weren't meeting the demand of all

0:29:22.760 --> 0:29:25.160
<v Speaker 1>their customers, which is kind of risky when you're trying

0:29:25.160 --> 0:29:26.960
<v Speaker 1>to build a social network and getting a core group

0:29:27.000 --> 0:29:29.920
<v Speaker 1>of users quickly is important. Right, It's a conundrum. Yeah,

0:29:29.920 --> 0:29:32.320
<v Speaker 1>but they hedged by being like, well, we'll give up

0:29:32.320 --> 0:29:35.080
<v Speaker 1>that upside and maybe not catching on so we can

0:29:35.120 --> 0:29:38.600
<v Speaker 1>make sure we have a stable, reliable product. Nothing about

0:29:38.600 --> 0:29:41.080
<v Speaker 1>that behavior seems true of the company today. I mean,

0:29:41.120 --> 0:29:43.960
<v Speaker 1>you think in the last five years they kept getting

0:29:43.960 --> 0:29:47.520
<v Speaker 1>caught sharing people's data and saw that regulators and individuals

0:29:47.520 --> 0:29:50.840
<v Speaker 1>were very uncomfortable with it, yet they still kept doing it.

0:29:50.920 --> 0:29:54.200
<v Speaker 1>So same CEO, What do you think changed? Why does

0:29:54.240 --> 0:29:57.040
<v Speaker 1>somebody who carefully calibrates risk at one moment of their

0:29:57.080 --> 0:30:01.200
<v Speaker 1>career becomes somebody who does not. Well, maybe if you

0:30:01.240 --> 0:30:03.160
<v Speaker 1>have success in the past, do you think it's gonna

0:30:03.160 --> 0:30:05.560
<v Speaker 1>be the future. I spoke to a lot of criminals

0:30:05.640 --> 0:30:07.880
<v Speaker 1>and they all said the same thing. They're all like, well,

0:30:07.880 --> 0:30:10.320
<v Speaker 1>you know, I started breaking law of super nervous, but

0:30:10.400 --> 0:30:12.880
<v Speaker 1>then I didn't get caught, So I thought that then

0:30:12.920 --> 0:30:16.360
<v Speaker 1>I wouldn't get caught in the future. So they just

0:30:16.480 --> 0:30:20.640
<v Speaker 1>kept taking more and more risk, and eventually, as they

0:30:20.640 --> 0:30:23.520
<v Speaker 1>took more risk, they also exposed themselves to a higher

0:30:23.520 --> 0:30:25.800
<v Speaker 1>likelihood of getting caught. And then they got caught and

0:30:25.840 --> 0:30:28.120
<v Speaker 1>they were all shocked. What about Elon Musk So I

0:30:28.160 --> 0:30:30.560
<v Speaker 1>think of him as a major risk taker, right, And

0:30:30.640 --> 0:30:32.800
<v Speaker 1>I was thinking of this ts Elliott quote that you

0:30:32.840 --> 0:30:34.760
<v Speaker 1>actually use in your book, which I love as well.

0:30:34.960 --> 0:30:37.680
<v Speaker 1>Only those who risk going too far can possibly find

0:30:37.680 --> 0:30:40.160
<v Speaker 1>out how far one can go, And that seems to

0:30:40.200 --> 0:30:43.360
<v Speaker 1>be musk. But in your view, how is he calibrating it?

0:30:43.480 --> 0:30:46.120
<v Speaker 1>Is he going too far or is he finding out

0:30:46.120 --> 0:30:48.720
<v Speaker 1>how far he can go? I don't think he's internalized

0:30:48.720 --> 0:30:51.560
<v Speaker 1>that he can go too far, you know, And I

0:30:52.960 --> 0:30:55.160
<v Speaker 1>suppose I would have to agree with that. I mean,

0:30:55.200 --> 0:30:57.240
<v Speaker 1>it's a problem I would like to have. But maybe

0:30:57.280 --> 0:31:01.760
<v Speaker 1>being that successful that early make you feel like somewhat invincible.

0:31:01.920 --> 0:31:04.120
<v Speaker 1>There's something else that people are talking about a lot

0:31:04.160 --> 0:31:06.560
<v Speaker 1>in the world of innovation that I think is really interesting,

0:31:06.600 --> 0:31:10.640
<v Speaker 1>which is this ongoing debate about core versus edge. How

0:31:10.640 --> 0:31:12.560
<v Speaker 1>do you decide when to focus on the core of

0:31:12.600 --> 0:31:16.040
<v Speaker 1>your business versus how you figure out about going out

0:31:16.120 --> 0:31:18.280
<v Speaker 1>on the edge? And if you leave the core unchanged,

0:31:18.600 --> 0:31:21.760
<v Speaker 1>then sometimes that can make you get taken over by

0:31:21.760 --> 0:31:24.200
<v Speaker 1>somebody else, right, But if you go too far out

0:31:24.200 --> 0:31:27.200
<v Speaker 1>on the edge, then that can mean you lose focus

0:31:27.280 --> 0:31:30.320
<v Speaker 1>on the core. Does anything in the way you think

0:31:30.400 --> 0:31:33.200
<v Speaker 1>about risk help answer that question? Well, yeah, I mean

0:31:33.240 --> 0:31:35.480
<v Speaker 1>you want to probably do a little bit of both,

0:31:35.760 --> 0:31:37.880
<v Speaker 1>because you know, if you focus too much on the core,

0:31:38.080 --> 0:31:41.640
<v Speaker 1>you risk losing your edge and becoming obsolete. I don't

0:31:41.640 --> 0:31:44.040
<v Speaker 1>know if this is good or bad, but it's just different.

0:31:44.080 --> 0:31:45.920
<v Speaker 1>I think what we're seeing a lot with companies now

0:31:46.240 --> 0:31:49.680
<v Speaker 1>is that they're outsourcing their edge. Oh what do you

0:31:49.680 --> 0:31:52.440
<v Speaker 1>mean by that? Well, if they're letting other smaller companies

0:31:52.440 --> 0:31:56.080
<v Speaker 1>do the innovation than they buy them. Ah, And do

0:31:56.120 --> 0:31:58.800
<v Speaker 1>you think that's ultimately a flawed way of going about things?

0:31:59.080 --> 0:32:02.040
<v Speaker 1>Imprissiple know, but I think in practice often it is

0:32:02.280 --> 0:32:04.800
<v Speaker 1>like anyone I know who's had an edgy startup, and

0:32:05.000 --> 0:32:06.960
<v Speaker 1>I've been part of that too, and then you're bought

0:32:06.960 --> 0:32:09.760
<v Speaker 1>by a big company. It's never off. It's a very

0:32:09.760 --> 0:32:13.719
<v Speaker 1>hard transition because you have a corporate culture that's become

0:32:13.880 --> 0:32:16.840
<v Speaker 1>very like, sort of adverse to innovation, and then you

0:32:16.920 --> 0:32:19.280
<v Speaker 1>bring this innovative product in and it's a hard miss

0:32:19.320 --> 0:32:23.560
<v Speaker 1>and the corporate culture smothers the edge exactly. Oh that's interesting.

0:32:23.600 --> 0:32:25.680
<v Speaker 1>I haven't thought about it that way before, but that

0:32:25.760 --> 0:32:28.200
<v Speaker 1>makes sense. So there's another quote in your book that

0:32:28.280 --> 0:32:30.080
<v Speaker 1>I love that goes to the heart of some of

0:32:30.120 --> 0:32:33.040
<v Speaker 1>what we're talking about. Our capacity for self delusion. And

0:32:33.080 --> 0:32:35.640
<v Speaker 1>you wrote, I am irrational and I know it, so

0:32:35.760 --> 0:32:38.200
<v Speaker 1>to talk about that and talk about the role that

0:32:38.280 --> 0:32:41.320
<v Speaker 1>self knowledge plays and how you manage risk, how you

0:32:41.320 --> 0:32:43.840
<v Speaker 1>think about risk. Well, I mean there's all this literature

0:32:43.840 --> 0:32:46.240
<v Speaker 1>about people have these behavioral biases and so they don't

0:32:46.280 --> 0:32:48.640
<v Speaker 1>manage as well. We talked before about how you tend

0:32:48.680 --> 0:32:52.000
<v Speaker 1>to be over or under confident and for probabilities accurately.

0:32:52.280 --> 0:32:54.520
<v Speaker 1>But there's also a loss of version, which is we

0:32:54.560 --> 0:32:57.080
<v Speaker 1>hate losing so much. When we're faced with loss, will

0:32:57.080 --> 0:33:00.200
<v Speaker 1>take way bigger risks and lose even more often, and

0:33:00.320 --> 0:33:03.160
<v Speaker 1>that's not good. And I think I wrote about this

0:33:03.520 --> 0:33:06.800
<v Speaker 1>poker player named Phil Helmuth who is a complete lunatic,

0:33:06.920 --> 0:33:09.160
<v Speaker 1>like I mean, really it sounds like a complete lunatic,

0:33:09.320 --> 0:33:12.320
<v Speaker 1>no self control, although he said he wasn't happy with

0:33:12.400 --> 0:33:15.080
<v Speaker 1>the way I portrayed him. Although I was, like, you

0:33:15.200 --> 0:33:21.080
<v Speaker 1>named your bio poker Brett talk about the limitations of

0:33:21.080 --> 0:33:24.200
<v Speaker 1>self knowledge. But he is actually very self aware in

0:33:24.240 --> 0:33:25.680
<v Speaker 1>a lot of ways, and this is why he's been

0:33:25.720 --> 0:33:29.400
<v Speaker 1>a successful poker player, is you know. Anyway, he's famous

0:33:29.400 --> 0:33:33.040
<v Speaker 1>for having these tantrums after he loses, or kind of

0:33:33.080 --> 0:33:35.760
<v Speaker 1>being this bully especially, I mean, he's not afraid to

0:33:35.760 --> 0:33:38.560
<v Speaker 1>brate amateur small poker players. Anyway, He's one of the

0:33:38.640 --> 0:33:43.040
<v Speaker 1>superstars in his industry. But when you're actually play poker,

0:33:43.320 --> 0:33:45.200
<v Speaker 1>if you let the emotions get the better of you

0:33:45.520 --> 0:33:47.360
<v Speaker 1>and get too aggressive when you're down, I mean, he

0:33:47.400 --> 0:33:49.200
<v Speaker 1>really hates to lose. You would think when he was

0:33:49.240 --> 0:33:52.320
<v Speaker 1>down he'd be desperate to get back up, but he's not.

0:33:52.400 --> 0:33:54.719
<v Speaker 1>He's a very consistent player and he's very patient. He

0:33:54.720 --> 0:33:57.200
<v Speaker 1>only pays twelve percent of his hands, which is much

0:33:57.200 --> 0:34:00.840
<v Speaker 1>lower than average. Wow, that juxtaps and does not seem

0:34:00.880 --> 0:34:03.720
<v Speaker 1>to go together you temper tantrums and the patients. But

0:34:03.840 --> 0:34:06.600
<v Speaker 1>he's trained himself, and he has all these tricks like

0:34:06.640 --> 0:34:09.080
<v Speaker 1>he knows he's irrational. He knows these are traps that

0:34:09.120 --> 0:34:11.600
<v Speaker 1>he falls into and everyone falls into. So it becomes

0:34:11.600 --> 0:34:14.480
<v Speaker 1>his edge and that he's a completely different person in

0:34:14.520 --> 0:34:17.480
<v Speaker 1>his style play. So that gets to another key question

0:34:17.520 --> 0:34:20.520
<v Speaker 1>I wanted to ask, by understanding your own approach to risk,

0:34:20.640 --> 0:34:24.280
<v Speaker 1>or by understanding risk more broadly, can you actually improve yourself?

0:34:24.320 --> 0:34:26.760
<v Speaker 1>And the answer in the case of Philhelmuth would appear

0:34:26.800 --> 0:34:30.160
<v Speaker 1>to be yes, Yes, I think anyone can. It's also

0:34:30.239 --> 0:34:32.600
<v Speaker 1>true people talk a lot about how humans are irrationally

0:34:32.600 --> 0:34:35.080
<v Speaker 1>of all these risk biases. But when people say that

0:34:35.440 --> 0:34:39.520
<v Speaker 1>it's not really entirely true, because we change as we

0:34:39.560 --> 0:34:42.719
<v Speaker 1>get older, As we learn more, older people tend to

0:34:42.920 --> 0:34:46.919
<v Speaker 1>behave more like classical economists expect people to. Or there's

0:34:46.960 --> 0:34:50.720
<v Speaker 1>research that people who take risks all the time tend

0:34:50.800 --> 0:34:54.080
<v Speaker 1>to be more rational. So learning and awareness make a

0:34:54.120 --> 0:34:57.040
<v Speaker 1>huge difference. What would you tell your kids about taking risks?

0:34:57.360 --> 0:34:59.279
<v Speaker 1>That they should take them, that they should feel good

0:34:59.280 --> 0:35:02.319
<v Speaker 1>about taking them. Yep, back to that girl to quote again, right,

0:35:02.560 --> 0:35:05.160
<v Speaker 1>the evolution of safety is sometimes the most dangerous think

0:35:05.280 --> 0:35:08.239
<v Speaker 1>or however, I'm mangling it. Yeah, especially because people say,

0:35:08.280 --> 0:35:09.719
<v Speaker 1>you know, I don't know this is true. I think

0:35:09.760 --> 0:35:11.480
<v Speaker 1>every generation is the same, more than people give them

0:35:11.520 --> 0:35:13.560
<v Speaker 1>credit for. But they keep saying that kids don't take

0:35:13.640 --> 0:35:16.480
<v Speaker 1>risks anymore. But I'm not sure if that's really true.

0:35:16.960 --> 0:35:19.279
<v Speaker 1>So I think that is an important message. Well, thank

0:35:19.320 --> 0:35:21.120
<v Speaker 1>you for coming in and chatting with me. Thanks for

0:35:21.160 --> 0:35:25.000
<v Speaker 1>having me. As Alison and I talked, I kept thinking

0:35:25.040 --> 0:35:28.000
<v Speaker 1>that in unexpected ways, finance does have a lot to

0:35:28.040 --> 0:35:30.640
<v Speaker 1>offer life. We could all learn to be smarter at

0:35:30.640 --> 0:35:33.880
<v Speaker 1>managing risk. But of course, some of the key questions

0:35:33.920 --> 0:35:37.040
<v Speaker 1>you need to answer in order to employ Alison's strategies

0:35:37.320 --> 0:35:40.960
<v Speaker 1>are pretty deep. Philosophical ones, what is it that you want?

0:35:41.520 --> 0:35:44.080
<v Speaker 1>And if there's danger in safety, is there really such

0:35:44.080 --> 0:35:46.279
<v Speaker 1>a thing in life as a risk free rate from

0:35:46.280 --> 0:35:49.720
<v Speaker 1>which you can benchmark? So maybe in the end, life,

0:35:49.760 --> 0:35:53.080
<v Speaker 1>with all its uncertainty and messy human dimensions, has more

0:35:53.080 --> 0:35:59.320
<v Speaker 1>to teach finance. Making a Killing is a co production

0:35:59.360 --> 0:36:02.920
<v Speaker 1>of Pushkin Industries and Chalk and Blade. It's produced by

0:36:03.000 --> 0:36:07.360
<v Speaker 1>Ruth Barnes and Rosie Stoffer. My executive producers are Alison

0:36:07.440 --> 0:36:11.719
<v Speaker 1>mcclein no relation in Making Casey. The executive producer at

0:36:11.719 --> 0:36:16.560
<v Speaker 1>Pushkin is Nea Loebell. Engineering is by Jason Gambrell. Our

0:36:16.640 --> 0:36:20.360
<v Speaker 1>music is by Jed Flood. Special thanks to Jacob Weisberg

0:36:20.360 --> 0:36:23.960
<v Speaker 1>at Pushkin and everyone on the show. I'm Bethany McLean.

0:36:24.160 --> 0:36:27.399
<v Speaker 1>Thanks so much for listening. Find me on Twitter at

0:36:27.400 --> 0:36:30.360
<v Speaker 1>Bethany mac twelve and let me know who you've enjoyed

0:36:30.400 --> 0:36:31.000
<v Speaker 1>hearing from.