Allison Schrager: How Do We Master Risk?

a miss. You might be scared to try something new and miss, but if you never swing at all, you're guaranteed to miss one hundred percent of the time you risk at all if you just sit safely on the sidelines. This is good life advice to be sure risk brings change into our lives. You won't get a raise if you never change jobs. You'll never fall in love if

you don't go out on that first date. It's a phenomenal skill to learn which risks are worth taking and how to reduce the downside so you can figure out how best to save her retirement, which degree is worth the tuition, where to buy a house, and on and on and on. But how can we also get smarter at understanding risk and reward in business? At Fortune five

hundred companies on Wall Street in global markets. As technology changes everything at an exponential rate, how do we run risk reward analysis when the world around us is being disrupted at this whispering pace. I'm excited that I get to talk today with Alison Schrager, author of the new book An Economist Walks into a Bravel, which has got to be one of the best titles ever. She's a retirement finance economist and has spent years talking to risk

takers in all kinds of businesses. But in a Hollywood worthy twist, she's lately been studying risk in the unlikeliest of places, talking to sex workers at the Bunny Ranch brothel and Nevada. It turns out they are experts at pricing and reducing risk. I say it all the time in the world of business. Truth is always always stranger than fiction. Anyway, Alison has learned that there's a science to good risk taking. She says that no one reaches the top of their field, be it sex work or

running a fortune five hundred company without mastering risk. They don't jump in and just go with their gut. They possess a deliberate, thoughtful strategy so they know what risks to take, and how to reduce the downside if things don't go their way. I've always loved the quote with which Alison begins her book. It's from Peter Bernstein's Against

the Gods. The revolutionary idea that defines the boundary between modern times in the past is the mastery of risk, the notion that the future is more than a whim of the gods, and that men and women are not pass before nature. So how do we master risk? Okay, so the Bunny Ranch, we obviously have to start there. How did you find these guys? Well, so it's a funny story. Oh, I was really struggling with my book proposal.

I felt like I needed a great risk taker, and so I had a drink with a cousin who I can't name, and I was like, I, really, do you you know anyone who was broken the law? I could really use a criminal. Maybe they'll help me because I was having problems coming up with stories. I love that I could really use a criminal. That's awesome. And he tells me that his girlfriend runs an illegal brothel, and well, you know, it was really way more information than I needed.

It was a very specific kind of brothel. And that it was out of New York and they specialized in submissives, so women who get tied up and then have sex with their clients. And because this is a very high risk thing, even more risky than normal sex work, what she did is she got a thirty percent cut if she did all the screening and made them safer. And

I was like, oh, that's an interesting risk story. So I wrote a court story about this woman and met her and she's lovely, and the bunny ranch saw it. He called me, and they're right, Well, if your bunny ranch called you fabulous, if you're gonna be writing this is snobbery. I guess it's a hierarchy in every business. If you're gonna be writing about brothels, you should be writing about our brothel because we're the biggest and most important one. I don't write about brothels, but it's an

interesting call. So I'm gonna take this. And they had something they want me to write about. It didn't really make sense for me, but then they said something quite interesting, which was, well, so we don't upset prices, but what the women come in and they negotiate every price and every transaction individually and I was like, well, that's interesting. You so telling me of women and who are about twenty years old negotiating for tens of thousands of dollars

with men in their sixties. And I why, yes, yes, And you know, no one's ever asked about that before. You know, they come in not knowing their values. So we have a negotiation training program. And you heard this a brothel through the lens of an economist. Yeah, so I'll say I need to see this. So I went out there and met Dennis Hof and spent about a week and a half going through their negotiation training program.

And that's where I developed a relationship to where they were going to let me come back and collect pricing data because I was struck by how much they charged. I wouldn't have expected they could get away with it, because I mean, this is not an easy place to get to, and like, why just pay a lot less and use someone like my cousin's girlfriends. And it's a huge markup over the illiegal market, right three stunning and

you have to go to Nevada. But I discovered it's like Dennis was just like, you come here and you just don't have to worry about anything, And is that the key lesson for you? What was the key lesson for you out of this about risk? That you know, every market puts a price on risk, and in any market, you have to pay to reduce risk. So that's the thing that three hundred percent is. So you know, you don't have to worry about some sort of Robert Craft situation.

Come there, you're not going to get caught. You know, they even have some innocuous thing you put on your credit card, totally discreet, it's completely legal, and you don't have to worry about anything. So you pay for that. So it's aspect or risk premium that you're paying. But the women pay it too, because anyway they're charging it was a fourteen hundred dollars an hour on average, they actually have to pay fifty percent of the brothel and

then taxes on top of that. Tell me a little bit about Shelby Starr and why she was willing to do things this way, Well, because she didn't. She's someone who never really wanted to break the law. I mean, I met women there who worked in the illegal market, and they add bad experiences and that's why they're there. But a lot of them just wanted to do this job and didn't want to if you worry about dealing with law enforcement. They didn't want to have to deal

with crazy. I mean, they said, my cousin's girlfriend has to do this to protect people, because it's super dangerous being a sex worker and meeting people online and doing some illegal activity with them. So you don't know if they're gonna be crazy, if they're going to kill you, beat you up, or you're going to be arrested. So

they just don't want to deal with that. I mean, Shelby definitely sees herself and they all do is people who are in legitimate businesses and they don't want to feel in any way that what they're doing is illegal. So it teaches you about managing risk. But it also teaches you about this other concept that we think of as belonging to the world of finance, but really belongs to the much broader world, which is hedging, right exactly.

So it's a hedge. So in finance, you paid to you, you take some risk off the table, and that's a hedge. So in finance, it would be like the simplest way to think about it is if you were investing in the stock market, like a stock index fund, and you weren't totally comfortable with market risk, you would put a little bit in a treasury bond and so that's a hedge. You get a lower return, but you also have lower risk.

And that's effectively what they're doing. They're they're sharing their risk with the brothel and an exchange they or they are actually the brothel's taking getting rid of all their risk, and an exchange they get at lower pay. It's one of the fascinating things about your book that I found so interesting is how relevant these topics that we think of as financial topics are too ordinary life, right, Yeah, And that was the goal, is that you know, the

risk concepts are everywhere. I mean, finance is the study of risk and financial markets, and that's partially just because there's tons of data, but they really apply everywhere. I actually want to back up and talk a little bit about you, because you have a very personal story about risk that you tell in the book, but tell us about it. Yeah, and I think a lot of us have been there and that you know, we often think, you know, if something's hard, or if we work hard

at something, it's not going to be risky. But This speaks to why it's so important. And this is the easiest risk management piece of advice I can give you. We're not easy, but the most important for all the fancy things you can do, if you have a very clearly well defined goal of the risk you're taking, then nothing else is going to do more to ensure that a risk works out. And so I went to grad school right out of undergrad and it was an economics PhD.

And you know, I love economics. I always like idolized famous economists in a really weird, geeky way when I was in high school. That's the line you're not going to hear about from everybody. I always lied famous economists. I love that. Yeah. No, I was such a nerd about it. I was so excited to get into like good PhD programs where I ought to work with them. I wanted to be one of them, I thought. And so I, you know, at twenty three, just jump into

a quantitative PhD program. Anyway, I hadn't even taken calculus, I'd know math training, and it was just awful. I mean, it's it's it's it's a tough PhD. All PhDs are tough, but economists tend to be particularly unhappy, and I'm told my program was particularly unhappy. They even tell me now when I see people from my department, theyre always like, we're so much nice sort of people than we were

to you. But it was just a tough experience, and especially the first year I was struggling so much because I didn't have the math training as a former math major. My heart is going out to you. Yeah, Like I learned about, you know, a master's worth of math on my own at night and still failed every exam. It was just never note I empathize. So I figured, well,

this is hard. So therefore if I just work hard and then do not only that an insanely quantitative dissertation way more than necessary, then somehow this is going to bring me great success and this is all going to pay off because it's this hard, then something great's going to happen. And then I solve this ridiculously difficult math problem. Anyway, I'm not really a math person, or didn't consider myself one.

And then I went on the job market and was on all these interviews to be a professor, and I was like, I have no interest in being here. I have you know, it's a great job for some people. But I realized, you know, this is not what I ever wanted. So it's things I invested in this asset that never really got me to my goal because I wasn't sure what my goal was. But it definitely wasn't that. I loved your chapter heading getting what you want requires

knowing what you want. Yeah, and it's so basic, I guess. It's so like the secret but also for a finance and you see this all the time in financial markets too, is you know when you invest with an for something as this in retirement, which is what my background's in, is that people everyone's geared towards investing for this huge pot of money on day one er retirement, Like you often see like what's your number, which is this pile of money number, like maybe a million dollars if you're

lucky to retire with. But that's not your goal. Your goal is income and investing for a pot of money and investing for income that lasts a lifetime or to totally different financial goals and require two totally different strategies, and if you invest for one, you're going to be

a lot riskier with the other. One makes a ton of sense, getting what you want requires knowing what you want, right, But let's go let's go to that your fascination with retirement because okay, that word in and of itself for most of us, unless it's some kind of mixture of Durad's stultifying boredom, I don't know. But you've always been

fascinated by retirement. Yeah, I mean, I think one of the reasons people are put off by it is it's sort of the last thing you do before you die, and it's when you sort of give up on being that person who contributes. It courses you to confront mortality. Yeah, and also that you're like done with your career and now you're just sort of being put out to pasture.

Although retirement, modern retirement need to be that way, but for me, it was always this fascinating problem because it was this pure distillation of what I thought economics was, which is allocation of scarce resources. But it's over your lifetime, right, So you make a certain amount of money and you have to spend a certain amount of money, and how do you do that in the best way? And if you take more risk, you have the expectation of more

So how do you manage that risk. So this is very pure, beautiful problem, which honestly, most of the most interesting things happen when you're young, because it's a lifetime problem. And I think when I was in grad school and thinking about the problems, the problem you want to solve and what you want to dedicate your career too, it just really interested me. And what's the key insight that you had that enabled you to think about retirement in

a different way. Well, you know, it's evolved over the years. Even in grad school, I was thinking about risk. My dissertation was looking at the move from define benefit to define contribution plans, and I wasn't totally sold that define benefit plans were that great that I saw all these risks they did pose to people, the risk that this company is going to go to business and you're gonna have to take a huge haircut. I mean this as

big as you right now in Chicago. Who I believe me, I know, Chicago unheedgeable risk for the participants in the retirement or even if you back in the day, you know, if you change jobs, you would often give up your pension. So I was interested in what was risk here to find contribution to find benefit. But back then I was a macroeconomist, so I was thinking about it in a

more of a policy way. Then after grad school, as I said, after I had blow up my career when I realized I didn't want to be a professor, and when you're in grad school, that's all you're told you could ever be. So I was kind of lost, and so I made a really sot of questionable decision to be a journalist. Oh that's not a question about decision.

Who would call that a question about decision company. It was like, I mean, granted, every year they tell your journalism is dead, but there's two thousand and six, and it was actually a really good time to do this because it was the very early days of web journalism when everyone thought this was going to disrupt the market, but also didn't take it seriously at all. So the anyway,

I had no idea how to write. We sort of just let me come in and write for them for free on the web because they just were like, well, this's the web most of the time. If you decide you want to life change, you want to write for the economist. That does not work. They want people who actually know how to write that's important to them. But they let me do it because it was web days and they were pretty open. So for all your calibration

of risk, what role do you think luck place? Because to some extent that two thousand and six move, was luck right with timing or would you think about it differently? I was. It didn't feel like it at the time. In retrospect, it was because I learned this amazing skill, skills about storytelling, skills about how to communicate economics to

an audience, which you certainly don't learn at academia. But I think everyone gets a certain amount of luck in life, but it's about knowing how to capitalize on it and knowing how to hedge or be prepared for bad luck too. I mean, at the time it looked like bad luck. I had no job, I was graduating from an economics PhD with no job. I was writing for free for the web. I mean, this did not seem like a

good move. So before we leave the topic of retirement alone, I want to come back to it because one I want to ask you how big an issue is this today? I mean, it's a big issue. I think it's not the issue people think it is. I think everyone's convinced they just don't have enough money, and that's true for a lot of people. I don't want to minimize that,

but I think that's not the primary issue. The primary issue is that people don't and this is one of the reasons I really want to do the book have the tools to really manage They've been handed a huge risk problem with the fine benefit plans. The employer took all the risk. Now we've a fairly significant risk problem, a problem I've dedicated my whole career too, and still

haven't found easy answers to on everyone. So people don't really have the tools to manage this incredibly complicated risk problem. And I think a lot of the personal finance literature gets people, leads people stray or sets them up to feel like they're failing because they's like, oh, it's easy, just do this, but aren't really addressing all the risks they're really facing. So we've dumped a problem on people and not given them the tools to manage it. In essence, Yeah,

and it doesn't mean it's not workable. I mean, I think the defined contribution for on K structure can really work and give people secure retirement. But we have to think more holistically about the tools and think of it as this lifetime problem rather than well, I don't know, you just save and invest and we'll see what happens, and perhaps get people to think about it like you do, as a beautiful, pure problem rather than it's some force of existential dread hanging over all of our heads. Right.

I wanted to go back to this notion as well, of the concept of risk free. I loved this quote you use from Gerta. The dangers of life are infinite, and among them is safety. Is there actually something as simple as risk free? Well? There is. I don't think a lot of people appreciate this, certainly not a lot of people actually, who even work in finance, that the foundation of all risk problems is the risk free asset.

If you look at any of these complicated formulas that people do to price risk, there's always the risk free rate in there. So it is in some ways it calibrates how much risk you can take. Because if a savings bond is going to pay you sent inflation adjusted to return, why bother going into the stock market. So it determines how much risk you take, and it determines

how much you put a price on risk. Obviously you know there's problems with it and that people sometimes get confused about, Like as I said, I assume more education was a risk free asset. That's not always true. Or people assume a bond can't default when it does, so there can be this illusion of either you've defined risk free wrong, or you think something's risk for you when

it's not and that can create other risks. Or I just wrote a fun story which I was ripping off of the book, which is sometimes I worry that you know the risk free value of not leaving your home, which is sort of the risk free choice, right, Like I'm not gonna bother go home, I'm gonna do stay, I'm gonna watch Netflix is supposed to Leaving your house is always a risk. You don't know it's gonna happen. You might have a bad time, you could get hit

by a car, or something great could happen. It's just like stay at home. It's become so compelling, Like maybe this is why millennials apparently aren't having sex anymore. Is it's just like why go out on a Tinder date when you can watch Game of throwing good questions? But is staying at home truly risk free or is that an illusion? It's an illusion or in the short run,

or maybe it is. I mean, maybe you feel like I can have a very satisfying life never leaving the house and playing video games and watching Game of Thrones. But it's important to take risks. It's, you know, it's how your life moves forward. It's how you actually will meet people and have a career and do all these

important things that will ultimately make you happier. I mean, maybe the fact that people are staying in more and have become more attached to these sort of risk free sources of stimulation is also why there's higher rates of anxiety and depression. It goes back to that Gerta quote, I think the dangerous of life are infinite, and among them as safety. It's an incredibly compelling quote. So what

do you think people misunderstand most about risk? I think they tend to think of it as this binary thing, like either you're a risk taker or you're not, or either you take a risk in you're someone who shakes up things or you don't. But really risk has this huge middle ground that you calibrate to whatever your preferences. Are, or whatever your desires are, and once you take a risk,

you can manage it. I mean, I think people to call this a calculated risk, although they don't really able to say what that means, which is, you take a risk where you're very clear about what it is you want,

and then you do things to manage the downside. Like your sex workers, like Shelby Starr, she takes a risk and then she figures out how to hedge against the risk she's taking, exactly like becoming a sex workers a fairly risky job, even if you're in the bunny ranch where you have access to healthcare and they get tested for diseases and they don't worry about breaking the law. I mean, there's still a huge social stigma. So do optimism and pessimism have anything to do with risk reward?

Whether people consider themselves a risk taker or not? In other words, are optimists more inclined to take risk and pessimists not? Or does it not break down that simply? I don't know if it breaks down that simply. I mean, certainly people decide whether or not to take a risk. There's I mean, it might not happen as precisely as financial economists do, but I think there's some calculation that goes on on what the odds these are going to

work out for me? And if you think it's definitely not going to be a problem and it's definitely going to go your way, you're more inclined to do it. On the other hand, if you only see downside, you're less likely. But that might be partially driven by personality and outlook, and it also might be driven by the cues or personal experiences with risk of how comfortable we feel taking on risk. So you mentioned the odds, and something else I thought was fascinating about your book is

how bad we are probabilities. Why are we so bad at understanding probabilities when they are so key to life? Well, I think it's partially that probabilities are a relatively new invention. We take them for granted. And I always say new, I mean, like, you know, like late Renaissance, which seems like a long time ago, but it seems like a

long time ago, and the granted scheme of human evolutions. Yes, it's a relatively recent invention, so it's not shocking that our brains don't conform to it, especially if you compare it to say reading. Reading also isn't something we're more knowing how to do. It's something we're trained to do when we take it for granted. But yet we've been

trained for centuries exactly. It's opposed to we don't. We've come up with probabilities, but we never really trained people to think about them, how to make sense of them. Yet we expect people to just to be born knowing how to do it. But I mean, they're a modern construct in the same way the written word is. I came across the work of Gigerenzer, who believes that you actually really can make sense of uncertainty and risk and

make conferences about probabilities that actually makes sense. It just depends on how it's presented. It's like, if you think in terms of frequencies instead of a raw probability, people tend to make better choices. Give me the most compelling example of how you can think, how you can think smartly about probabilities. So when you hear a probability, you know, rather than sink, okay, there's a point a one percent

chance of something happening. That doesn't really have a lot of meaning now, but a one in one thousand does I mean, you even see this with a lottery. Statistically, it's very unlikely you're going to win the lottery. But when you get that ticket or you see how the lottery markets itself, they always plant in your head this whole story. They make the frequency seem larger than it is. They trot out the winner. They have that little song when you are buying the lottery ticket says you can't

win if you don't play. So all of a sudden, that infintestinal probability seems much larger it is. But you could think about it in terms of frequency. They don't do this is they could line up all the people who played and didn't win. So you have to cut through the hopes and fears and desires and get to the numbers, and get to the numbers presented in a way that makes sense to your brain exactly. Okay, So let's think about risk as it's applied to various industries.

And I loved the story that you tell in the book of Ryan Cavanaugh and Hollywood. What does that teach us about risk? I think about why risk measurements so hard because we make we come up with these probabilities. They have to be based on something and they're usually based on data because you know, what else do we have to go on. Problem is data is always by definition from the past, and you know the past changes.

So Ryan Cavanaugh was this whiz kid type who came to Hollywood, and people in Hollywood are it's a big financial risk to finance a movie is that you know you don't pay starting for years. Most of the movies lose money, and you know you have to put all the money up up front. So he promised that he had an algorithm that would predict movie success. And everyone signed on to this because everyone wants to believe this

the magic algorithm. Yeah, and it was a good timing for him, and that the studios were looking for new sources of financing and hedge funds were looking for higher yields. Plus, people from this finance world tend to like the glamor of movies and tend to not make great choices when they have that glamor presented to them. So he kind of married these two groups by telling these hedge funders secret, I can quantify risk the same way you like to do it. And the movie students where he's like, I

can bring in money. So they gave him all their best data, and he had this fancy model that he claimed, I can put a number on a chance and movies gonna make it or not. And he put together slights of movies and it worked for a couple of years, but then it didn't because the movie industry just keeps changing. Data gets stale so fast. In the time I think he was in business, DVD sales came from a significant

source of revenue to just completely disappearing. Or you get fads, you have China coming into the market and all of a sudden, comic book movies become more important, or you have rotten tomatoes that totally undermine all the marketing plans. So the data just becomes so stale and almost worthless. And so if you're going to use a model like this,

you always have to stay on top of it. That's interesting I was thinking as you were talking about how it ties back to our previous discussion about the hopes and dreams and fears clouding the numbers, because you can't think of a better example than Hollywood, right where the glamor of the movies clouds people's judgment about what the

numbers actually are. But it's also a fascinating industry given that, as you note, there's more and more data, but the limitations are also more and more imparent in the face of all this rapid change, and how do you deal with that from the standpoint of risk management, Because it's a broader issue than Hollywood, right, it's a facet of

our world, more and more data and more and more change. Yeah, so I think where we're maybe going wrong as thinking data just speaks for itself, which is I think when the lessons from this Ryan have an off parable. Data is a great tool. I'm not saying we shouldn't use data, but we have to be mindful of how we use it.

And right now with movies, we've got the best data we've ever had, and that with Netflix and Amazon, they have actual data on who very finally tune demographics of who starts and stops movies and what do they attract in a way we never had before. So the potential is there to really do marketing a lot cheaper and to really start tellering movies to more what's considered niche audiences like women. But you have to be smart and how you use your data, and you can't assume that

the data is just there. You have to be very mindful of is this data relevant to what you're interested in. I think I use the parallel to using pass trips to the airport to calibrate the risk you're going to be late to the airport if you go to the airport and most of the time it's between twenty five and thirty five minutes. You based your airport travel time

based on your past history. But like, what if they build a new highway to the airport that just completely changes your route, then all those pass trips aren't really useful anymore, even though they're still implanted in your brain somewhere as a mental as a mental roadmap. I think you used the phrase in the book, which I've always loved about models, garbage in, garbage out. Yeah, And that's

what they said about Ryan's model. I spoke to a lot of banks that have their movie business, and they were incredibly candid, one about people who go in and invest naively in two about just who've been working on financial models for years, about all the weaknesses in Kavano's model.

Speaking of weaknesses and models, that's something I've actually been fascinated with for a while, and I was just reading about a finance guy named Emmanuel Derman math Quondai who started to question models in the wake of the financial crisis, And he said this to confuse a model with the world of humans as a form of idolatry and more dangerous.

And I started to think after the financial crisis that the phrase risk management was actually an oxymoron, sort of like jumbo shrimp, because the finance industry clearly didn't do a very good job of managing risk in the run up to the crisis. So what did they get wrong? Where did their models go wrong? Well, a couple of different ways. My mentor was Robert Merton, who was the creator of a lot of these models and also known

for a hedge fund that didn't go well himself. That was long term capital management, wasn't it, Yes, hedge fund. He always says that when you're assessing the viability of a model, there's two things you have to keep in mind. One is the quality of the model. Sometimes it's just a bad model. Two is the right model being used for the right job. It's like, are you using a

screwdriver to do a job that a hammer should? And three is the person using it know what they're doing, and I think with a financial crisis you can see a lot of all of those happening. Sometimes people use models that just weren't great. Sometimes people use perfectly good models but just in the wrong way. And sometimes they just applied it to the wrong problem. And this is why I think you need one more education about what these models are and what they can do, and also

more awareness of what their natural limitation are. That doesn't mean you shouldn't use them. I feel like a lot of people who critique financial models, I'm not quite sure what their point is is that should we just not do anything, Should we just not bother to measure or manage risk? Should we just guess? Yeah? Because I like to think of risk models as like a roadmap if you're taking a trip. I mean, it does not guarantee a safe journey. You might still get into a car accident.

But what it does is it helps you understand how different factors relate to each other, what makes what enhances your risk, what things might get in your way. But it doesn't have every tree in there. You know, you have to make abstractions, you have to make choices, But it can really help the odds that you're gonna have a successful journey, but it doesn't really make any guarantees. So I mean, and this is why you have to be careful of its limitations and also make sure you're

using it right. Switching gears a little bit, what do you think technology CEOs could stand to learn from sex workers. I think it's about hedging, like you see them, and I mean, maybe it's because they've been getting capital with having to earn a profit that they just feel like it seems like that they aren't really think being very

thoughtful about risk. I mean, you look at Facebook, and you look at their early days, and they were so careful, Like even the rollout was so slow and deliberate because they were heating the lessons from friends stir that just tried to meet their demands and overstretch themselves and had

a bad product. So Facebook would it only roll out very slowly anyway, They weren't meeting the demand of all their customers, which is kind of risky when you're trying to build a social network and getting a core group of users quickly is important. Right, It's a conundrum. Yeah, but they hedged by being like, well, we'll give up that upside and maybe not catching on so we can make sure we have a stable, reliable product. Nothing about

that behavior seems true of the company today. I mean, you think in the last five years they kept getting caught sharing people's data and saw that regulators and individuals were very uncomfortable with it, yet they still kept doing it. So same CEO, What do you think changed? Why does somebody who carefully calibrates risk at one moment of their career becomes somebody who does not. Well, maybe if you have success in the past, do you think it's gonna be the future. I spoke to a lot of criminals

and they all said the same thing. They're all like, well, you know, I started breaking law of super nervous, but then I didn't get caught, So I thought that then I wouldn't get caught in the future. So they just kept taking more and more risk, and eventually, as they took more risk, they also exposed themselves to a higher likelihood of getting caught. And then they got caught and

they were all shocked. What about Elon Musk So I think of him as a major risk taker, right, And I was thinking of this ts Elliott quote that you actually use in your book, which I love as well. Only those who risk going too far can possibly find out how far one can go, And that seems to be musk. But in your view, how is he calibrating it? Is he going too far or is he finding out how far he can go? I don't think he's internalized that he can go too far, you know, And I

suppose I would have to agree with that. I mean, it's a problem I would like to have. But maybe being that successful that early make you feel like somewhat invincible. There's something else that people are talking about a lot in the world of innovation that I think is really interesting, which is this ongoing debate about core versus edge. How do you decide when to focus on the core of your business versus how you figure out about going out

on the edge? And if you leave the core unchanged, then sometimes that can make you get taken over by somebody else, right, But if you go too far out on the edge, then that can mean you lose focus on the core. Does anything in the way you think about risk help answer that question? Well, yeah, I mean you want to probably do a little bit of both, because you know, if you focus too much on the core,

you risk losing your edge and becoming obsolete. I don't know if this is good or bad, but it's just different. I think what we're seeing a lot with companies now is that they're outsourcing their edge. Oh what do you mean by that? Well, if they're letting other smaller companies do the innovation than they buy them. Ah, And do you think that's ultimately a flawed way of going about things?

Imprissiple know, but I think in practice often it is like anyone I know who's had an edgy startup, and I've been part of that too, and then you're bought by a big company. It's never off. It's a very hard transition because you have a corporate culture that's become very like, sort of adverse to innovation, and then you bring this innovative product in and it's a hard miss and the corporate culture smothers the edge exactly. Oh that's interesting.

I haven't thought about it that way before, but that makes sense. So there's another quote in your book that I love that goes to the heart of some of what we're talking about. Our capacity for self delusion. And you wrote, I am irrational and I know it, so to talk about that and talk about the role that self knowledge plays and how you manage risk, how you think about risk. Well, I mean there's all this literature about people have these behavioral biases and so they don't

manage as well. We talked before about how you tend to be over or under confident and for probabilities accurately. But there's also a loss of version, which is we hate losing so much. When we're faced with loss, will take way bigger risks and lose even more often, and that's not good. And I think I wrote about this poker player named Phil Helmuth who is a complete lunatic, like I mean, really it sounds like a complete lunatic, no self control, although he said he wasn't happy with

the way I portrayed him. Although I was, like, you named your bio poker Brett talk about the limitations of self knowledge. But he is actually very self aware in a lot of ways, and this is why he's been a successful poker player, is you know. Anyway, he's famous for having these tantrums after he loses, or kind of being this bully especially, I mean, he's not afraid to brate amateur small poker players. Anyway, He's one of the

superstars in his industry. But when you're actually play poker, if you let the emotions get the better of you and get too aggressive when you're down, I mean, he really hates to lose. You would think when he was down he'd be desperate to get back up, but he's not. He's a very consistent player and he's very patient. He only pays twelve percent of his hands, which is much lower than average. Wow, that juxtaps and does not seem

to go together you temper tantrums and the patients. But he's trained himself, and he has all these tricks like he knows he's irrational. He knows these are traps that he falls into and everyone falls into. So it becomes his edge and that he's a completely different person in his style play. So that gets to another key question I wanted to ask, by understanding your own approach to risk, or by understanding risk more broadly, can you actually improve yourself?

And the answer in the case of Philhelmuth would appear to be yes, Yes, I think anyone can. It's also true people talk a lot about how humans are irrationally of all these risk biases. But when people say that it's not really entirely true, because we change as we get older, As we learn more, older people tend to behave more like classical economists expect people to. Or there's research that people who take risks all the time tend to be more rational. So learning and awareness make a

huge difference. What would you tell your kids about taking risks? That they should take them, that they should feel good about taking them. Yep, back to that girl to quote again, right, the evolution of safety is sometimes the most dangerous think or however, I'm mangling it. Yeah, especially because people say, you know, I don't know this is true. I think every generation is the same, more than people give them credit for. But they keep saying that kids don't take

risks anymore. But I'm not sure if that's really true. So I think that is an important message. Well, thank you for coming in and chatting with me. Thanks for having me. As Alison and I talked, I kept thinking that in unexpected ways, finance does have a lot to offer life. We could all learn to be smarter at managing risk. But of course, some of the key questions you need to answer in order to employ Alison's strategies are pretty deep. Philosophical ones, what is it that you want?

And if there's danger in safety, is there really such a thing in life as a risk free rate from which you can benchmark? So maybe in the end, life, with all its uncertainty and messy human dimensions, has more to teach finance. Making a Killing is a co production of Pushkin Industries and Chalk and Blade. It's produced by Ruth Barnes and Rosie Stoffer. My executive producers are Alison mcclein no relation in Making Casey. The executive producer at

Pushkin is Nea Loebell. Engineering is by Jason Gambrell. Our music is by Jed Flood. Special thanks to Jacob Weisberg at Pushkin and everyone on the show. I'm Bethany McLean. Thanks so much for listening. Find me on Twitter at Bethany mac twelve and let me know who you've enjoyed hearing from.