SPEAKER_1: Welcome to StarTalk, your place in the universe where science and pop culture collide.
SPEAKER_1: StarTalk begins right now.
SPEAKER_1: Welcome to StarTalk Radio.
SPEAKER_1: I'm your host, Neil deGrasse Tyson, astrophysicist and director of New York City's Hayden Planetarium.
SPEAKER_1: Joining me this week is comedian Eugene Merman.
SPEAKER_1: Eugene, welcome back.
SPEAKER_2: Hi, it's great to be here.
SPEAKER_1: You crossed the East River moat.
SPEAKER_2: I did.
SPEAKER_1: Around Manhattan, coming in from Brooklyn.
SPEAKER_1: Thanks for making that big trip.
SPEAKER_2: Sure, sure.
SPEAKER_2: It took about a day and a half.
SPEAKER_2: I had a sherpa.
SPEAKER_1: That's what you need.
SPEAKER_1: This week, we're talking about personal finance and the science of money management.
SPEAKER_1: And I needed more than you for this show to pull this off.
SPEAKER_2: Even though I tempted fidelity about 10 years ago, you needed more than me.
SPEAKER_1: Indeed, I did.
SPEAKER_2: Weird.
SPEAKER_1: So we only got the best for this one.
SPEAKER_1: We didn't find him walking the streets.
SPEAKER_1: We found him deep in the labs of MIT.
SPEAKER_1: Andrew Lowe, Professor of Finance at MIT Sloan School of Management.
SPEAKER_1: And he's also Director of their Laboratory for Financial Engineering.
SPEAKER_1: Andrew, welcome to StarTalk Radio.
SPEAKER_3: Thanks very much.
SPEAKER_3: Delighted to be here.
SPEAKER_1: And Laboratory for Financial Engineering, like there are engineers everywhere, it seems.
SPEAKER_3: Absolutely.
SPEAKER_1: Are you an engineer?
SPEAKER_3: I am.
SPEAKER_1: Do the engineers you manage call you an engineer?
SPEAKER_3: Well, you'd have to ask them.
SPEAKER_1: That's because engineers are particular about who they credit to their tribe.
SPEAKER_1: And so presumably, you're an expert on finance, but however expert you are, you are not as influential as our featured interview for this episode of StarTalk Radio.
SPEAKER_1: That would be Suze Orman.
SPEAKER_1: She's got her own TV show.
SPEAKER_1: Do you have your own TV show?
SPEAKER_3: Not yet.
SPEAKER_1: She's got best-selling books.
SPEAKER_1: Number one on the best side.
SPEAKER_1: Do you have your best-selling books?
SPEAKER_3: Not yet.
SPEAKER_1: But you have books though.
SPEAKER_3: Absolutely.
SPEAKER_1: But they're so not best-sellers, are they?
SPEAKER_3: I'm afraid so.
SPEAKER_2: Is this how we're going to start it, by insulting everyone who's a guest and then playing someone on television?
SPEAKER_3: No.
SPEAKER_1: I think he can take it.
SPEAKER_1: He's a tough guy.
SPEAKER_2: He does seem pretty tough.
SPEAKER_1: So this is all about personal finance and in my interview with Suze Orman, she came to my office and we just chatted about this.
SPEAKER_1: I wanted to know from her point of view because she advises households, American households, what to do with their money.
SPEAKER_1: Especially those people who didn't have a clue.
SPEAKER_1: She's their first introduction on how to think rationally about what to do with their money.
SPEAKER_1: And so I asked her whether being good at math is a necessary sort of prerequisite to invest wisely and this was her reply.
SPEAKER_4: Here we are at the Planetarium and you look up at the stars.
SPEAKER_4: Do you need to know the calculations of how far that star is from the sun or how fast this is?
SPEAKER_4: Do you need to know all those calculations to really just look at it and appreciate what's happening and to have a slight understanding of it?
SPEAKER_1: You don't need all the calculations.
SPEAKER_1: I mean, there are levels where you can enter and still appreciate what's going on.
SPEAKER_4: And the same is true for the stock market.
SPEAKER_4: All you have to know is I started with X.
SPEAKER_4: Do I have more than X or do I have less than X?
SPEAKER_1: That'd be like investment 101.
SPEAKER_4: And that's about all you need to know when it comes to math.
SPEAKER_4: If you're using math as an excuse as to why you don't want to invest in the stock market because you're saying, I'm not good at math, therefore I can't invest, that's equivalent to me saying, I don't understand science, so I don't want to look at the stars.
SPEAKER_1: Or I don't want to bask in the sunset because it's beautiful whether or not you understand what the sun is doing inside.
SPEAKER_4: And all you need to know when you're investing is what are you investing in?
SPEAKER_4: Does it make sense to you?
SPEAKER_4: And how much money have you put in?
SPEAKER_4: And you need to watch it every month, that's all.
SPEAKER_1: She says watch it every month.
SPEAKER_1: I will kind of watch it every minute because I worry about what's going on on the stock market.
SPEAKER_1: It's pretty scary stuff.
SPEAKER_1: Andrew, does it scare you?
SPEAKER_3: Well it can.
SPEAKER_3: And I think that the stock market is pretty alien to most of us.
SPEAKER_3: In fact, I think Americans spend more time thinking about astronomy.
SPEAKER_1: I'm an astrophysicist.
SPEAKER_1: When you say alien, I think the rest of the universe.
SPEAKER_1: But you got another word there?
SPEAKER_3: Well, in fact, I think that Americans spend more time thinking about astronomy than they do about finance.
SPEAKER_3: Because, you know, every night you look at the stars, and once a month you see the moon.
SPEAKER_3: How often do you look at your 401k plan?
SPEAKER_1: Never.
SPEAKER_3: Exactly.
SPEAKER_1: Yeah, I have to remind myself that I even have one.
SPEAKER_1: Yeah.
SPEAKER_1: And so, okay, so there's an exposure factor here.
SPEAKER_1: So Andrew, do you– so Eugene, do you have a 401k?
SPEAKER_2: This is a great answer.
SPEAKER_2: I don't think so.
SPEAKER_2: Meaning, I probably don't, but I'm also in, like, acting unions that I think maybe have started one, but I don't really know.
SPEAKER_2: No.
SPEAKER_2: The answer is probably not.
SPEAKER_2: I am not the best finance person to ask.
SPEAKER_2: I'm like, I know I have a savings account, but I know there's nothing there.
SPEAKER_1: So this question about how much math you need, you're up there at MIT.
SPEAKER_1: That's like geek central there.
SPEAKER_1: Guilty.
SPEAKER_1: Plus, you're a graduate of my alma mater.
SPEAKER_1: I get to say that because I graduated before you, the Bronx High School of Science.
SPEAKER_1: And then you go on and get all these fancy finance degrees.
SPEAKER_1: And so it sounds like you need some high education to know what you're doing, given what your background is.
SPEAKER_3: Well, you know, I have to agree with Ms.
SPEAKER_3: Orman that while more math can actually help you, the fact is that you don't need a lot of background to get some basics about what your finance is all about.
SPEAKER_3: And I think that a lot of people are scared to look.
SPEAKER_3: But once they do, they find that it's actually a lot of fun.
SPEAKER_3: And certainly it's really important.
SPEAKER_2: Like gambling.
SPEAKER_2: A lot of fun like gambling and addictive.
SPEAKER_1: Exactly.
SPEAKER_2: Yeah.
SPEAKER_1: I mean, so let me ask you, because I got Eugene's answer.
SPEAKER_1: Andrew, is the stock market gambling?
SPEAKER_3: Well, I don't think so.
SPEAKER_3: I mean, certainly there are some gamblers.
SPEAKER_1: Andrew, that's a yes or no question, please.
SPEAKER_3: No.
SPEAKER_2: I believe what you mean to say is it's slow, not as dangerous gambling.
SPEAKER_3: Well, you know, it depends on who's playing.
SPEAKER_3: I think that, you know, for most investors, they're trying to hold on to their assets for the long run.
SPEAKER_3: But that's not to say that you get some high frequency traders that do want to make money on a very, very high frequency basis.
SPEAKER_1: So high frequency means they're trading constantly, and they're not buy and wait.
SPEAKER_3: These are day traders that have attention deficit disorder, right?
SPEAKER_2: So day traders are gamblers, regular people who put their money in mutual funds, or just a family that one day wants to retire.
SPEAKER_3: Exactly.
SPEAKER_1: Okay.
SPEAKER_1: So you've distinguished these two cases.
SPEAKER_1: So now, how about picking stocks?
SPEAKER_1: I've always been curious about whether my dart against the wall would do better than any kind of perceived intelligent analysis.
SPEAKER_1: Do you guys pick stocks up there at MIT?
SPEAKER_3: Well, you know, we certainly…
SPEAKER_1: You have a stock club?
SPEAKER_3: We don't have a stock club, but we do have an investment club.
SPEAKER_1: That's what I meant.
SPEAKER_1: I'm sorry.
SPEAKER_1: Yeah.
SPEAKER_3: You know, stock picking is one of these things where if you spend a lot of time and effort and resources, you might actually be able to do better than random.
SPEAKER_3: But for most typical investors, they don't have those kind of resources.
SPEAKER_3: So for them, stock picking would be a disaster.
SPEAKER_1: Oh, so it's better to not engage at all with partial information than to put your money in thinking you know everything you need.
SPEAKER_3: Exactly.
SPEAKER_3: Just like the show Jackass says, don't try this at home.
SPEAKER_1: Don't try this.
SPEAKER_1: Well, Suze Orman had comments on whether computers can or should pick winners or not.
SPEAKER_1: And let's see what she tells us.
SPEAKER_4: Most of the people who say they can pick a good stock, they are using some computer method to determine the stock that they should pick.
SPEAKER_1: You know, they don't say that.
SPEAKER_1: I look at them and it's like, oh, I'm just brilliant and intuitive.
SPEAKER_4: No, they're either using some type of analysis, whether it's charting or whatever it may be.
SPEAKER_4: But there's usually now stock programs where they go back and they do this and they do that on it.
SPEAKER_4: So it's actually a very scientific way that they will pick their stocks.
SPEAKER_4: But then there is the other theory that if you had a little dart and you threw it and you hit something, it would probably perform just as well as somebody who used technical analysis.
SPEAKER_1: So which of those is right?
SPEAKER_1: The dart or the analysis?
SPEAKER_4: Depends at which time you're looking at it.
SPEAKER_1: Well, okay.
SPEAKER_1: So then the secret is knowing when to use one and not the other.
SPEAKER_4: Here's the problem when you're looking at returns of an investment.
SPEAKER_4: They usually look back 10 years and they'll say this mutual fund or the stock returned X over these 10 years.
SPEAKER_1: So that's an acceptable baseline because we all know it's not a forever amount of time, but it's certainly long enough you think if they're good at it, it should reveal itself.
SPEAKER_4: Yes, but let's say they're dating it from September of 2000 to, let's say, September 2010.
SPEAKER_4: Each year, a month or so drops off.
SPEAKER_4: And what happens...
SPEAKER_1: So it's a running sequence.
SPEAKER_4: It's a running sequence.
SPEAKER_4: And depending what happened, was it September 11, 2001?
SPEAKER_4: Was it this?
SPEAKER_4: Was it that?
SPEAKER_4: So it can really skew the results.
SPEAKER_4: So you have to know, and this is where science relates, by the way, what is the evidence behind it?
SPEAKER_4: What is the time frame?
SPEAKER_4: What happened besides just what the stock did?
SPEAKER_1: Science is all about evidence.
SPEAKER_1: Otherwise, you're just making stuff up.
SPEAKER_1: You might as well just read a horoscope chart.
SPEAKER_4: And the problem with using that for picking a stock or a mutual fund is that it's based on human behavior.
SPEAKER_4: And human behavior cannot be predicted.
SPEAKER_1: Humans always mess everything up.
SPEAKER_4: Always do.
SPEAKER_1: So human behavior, there is a great variable.
SPEAKER_2: We should have horses invest our money.
SPEAKER_2: They would make no mistakes.
SPEAKER_1: Well, there are the intelligent horses in Gulliver's Travels, the Hoinehams.
SPEAKER_2: Did you remember them?
SPEAKER_2: That's exactly who I meant.
SPEAKER_2: I meant we should get magic horses to invest our money.
SPEAKER_2: And that's a good solution.
SPEAKER_1: So Andrew, the human element, you're a professor in an institution where the behavior of humans is considered bad, right?
SPEAKER_1: In the sense that MIT is known for its technologies, its science, and anytime human behavior comes in the picture, it just messes everything up.
SPEAKER_1: And that's what happens every day in finance.
SPEAKER_3: Well, it certainly makes it more complicated.
SPEAKER_3: And one of the things we're doing at MIT is trying to understand how to put some kind of bounds on human behavior.
SPEAKER_3: And I think that there are times when you can predict what humans are going to be able to do.
SPEAKER_1: And from our earlier discussions, that's one of your research specialties, is right, figuring out how people behave under different conditions.
SPEAKER_2: What kind of conditions?
SPEAKER_2: Like falling or?
SPEAKER_3: Well, something like that.
SPEAKER_3: I mean, you know, it's very hard for me to predict what you're going to be doing tomorrow, Eugene, since I don't know you and I don't know what your schedule is going to be.
SPEAKER_1: Even if you did know him, you wouldn't be able to predict that.
SPEAKER_2: I'm very erratic.
SPEAKER_2: I feel like I'm always being followed.
SPEAKER_3: But on the other hand, if it turns out that there's a fire here in the studio, I have a pretty good prediction of what you're going to do.
SPEAKER_3: I suspect you're going to leave the studio as quickly as possible.
SPEAKER_1: Yeah, but why do I need an MIT professor to tell me that?
SPEAKER_3: Well, yeah.
SPEAKER_2: I see that you don't understand that I'm actually fire-retarded.
SPEAKER_3: Well, for one thing, you need to know when the fires are burning and when they're not.
SPEAKER_3: And I think that from the economic perspective, there are all sorts of different kinds of fires that occur all the time in financial markets.
SPEAKER_1: And there's also risk to being subjected to a fire, I guess, as well.
SPEAKER_3: That's right.
SPEAKER_3: And it's really that risk that people react to.
SPEAKER_3: And sometimes they don't react as much as they should.
SPEAKER_1: So is the act of investing an art or a science?
SPEAKER_2: So are you saying that if people were on fire but didn't pull out of the stock market, it would be fine?
SPEAKER_1: That's exactly what he's saying, Eugene.
SPEAKER_1: You're following right along with us.
SPEAKER_2: Just making sure.
SPEAKER_1: So is it an art or a science?
SPEAKER_3: Well, one of my colleagues is fond of saying that all good science is an art.
SPEAKER_2: You know, I'll back him up on that.
SPEAKER_1: So, that's like saying, you take something and raise it to an art or you bring it down to a science.
SPEAKER_3: Well, I think it's a bit of both.
SPEAKER_1: A little bit of both.
SPEAKER_1: Well, I kept talking to Suze about how do you sustain success if you're going to be successful on the stock market.
SPEAKER_1: Let's see what she tells us.
SPEAKER_1: I remember Louis Rukeyser where he said, you are selling a stock because you think it's going to drop to someone who's buying it, who thinks it's going to rise.
SPEAKER_1: And at that moment, I said, there is no hope.
SPEAKER_1: Everyone can't win in that scenario.
SPEAKER_4: Yes, everybody can win in that scenario.
SPEAKER_1: How?
SPEAKER_4: And I'll tell you how.
SPEAKER_4: You bought a stock of 10 and it goes to 20 and you feel like you've made enough money.
SPEAKER_4: You've doubled your money and that's fine and you sell.
SPEAKER_4: Somebody else is buying it from you at 20 and it now goes to 30.
SPEAKER_4: Now they made money as well.
SPEAKER_4: That doesn't mean that the first person lost money.
SPEAKER_4: So it is possible that everybody can win.
SPEAKER_1: So if we're in a booming economy, everybody's winning.
SPEAKER_4: If we're in a booming economy or if that stock isn't popular at that time, is manufacturing or in some type of area that's popular, even if the economy is not booming, you can win.
SPEAKER_1: And these are the important secret areas of economic...
SPEAKER_4: But here's the thing.
SPEAKER_4: You can give a scientific approach to how one invests.
SPEAKER_4: Since if your premise is true, that we don't know everything is random, there's chaos, do you win, do you lose, there's how you can be a winner all the time, if you ask me, in the stock market, no matter what happens.
SPEAKER_4: And that's through, rather than investing everything you have all at once, to take a certain amount of money and buy the same thing over and over and over again every single month, known as dollar cost averaging.
SPEAKER_4: When it goes up, so your money buys less shares.
SPEAKER_4: When it goes down, your money buys more shares.
SPEAKER_4: But over time, you will always come out a winner.
SPEAKER_4: And that is for people who don't know what they're doing in the stock market is the only way they should be invested.
SPEAKER_1: Well, that's some advice for you right there.
SPEAKER_1: When we come back, we're going to investigate the impact of the 2008 recession.
SPEAKER_1: This is StarTalk Radio.
SPEAKER_1: Thank Welcome back to StarTalk Radio.
SPEAKER_1: Our subject today is household finance, and how much science is there to investing if there's any science to it at all?
SPEAKER_1: I've got my guest, Andrew Lowe, Professor of Finance at MIT, and one of our favorite co-host comedians, Eugene Mermin.
SPEAKER_1: Eugene, you're tweeting at Eugene Mermin, aren't you?
SPEAKER_2: I am, I am, I'm just tweeting at my own name.
SPEAKER_2: I'm not hiding from America, but I'm out there.
SPEAKER_1: So Eugene, before the break, you had a comment.
SPEAKER_1: We had clipped from Suze Orman.
SPEAKER_1: She's, I interviewed her for this.
SPEAKER_2: No one's saying she's not on television, but I will say that the idea of...
SPEAKER_1: When we, before we went to break, she commented on dollar cost averaging, which is...
SPEAKER_2: Sounds very sciency.
SPEAKER_1: Sounds very sciency.
SPEAKER_1: You put the same amount of money in a stock.
SPEAKER_1: If it goes up, it buys a little less.
SPEAKER_1: It goes down, it buys a little more.
SPEAKER_1: And what she said is if you didn't know anything about investing, that's sort of investing one-on-one.
SPEAKER_1: You just go in and try that.
SPEAKER_2: Is that true though?
SPEAKER_2: I mean, if you have a stock that's slowly going down and you invest in it every month, it just sounds terrible.
SPEAKER_2: But I can't understand if I'm missing something, like if I don't know enough math, or if it's just a terrible idea to slowly every month invest in something that's plummeting, as opposed to divide your eggs in lots of baskets.
SPEAKER_1: Okay, so Eugene, we have an expert in the studio for just that purpose.
SPEAKER_2: Andrew.
SPEAKER_1: Andrew Lowe, yes.
SPEAKER_3: So, you know, as a geeky headed academic, what can I tell you?
SPEAKER_3: I've got to disagree to some degree.
SPEAKER_3: Like with any popular advice, there are some elements that are useful.
SPEAKER_1: That advice is useful in some occasions.
SPEAKER_3: That's right.
SPEAKER_1: So you're not disagreeing with the advice.
SPEAKER_1: What you're saying is that's not as widely usable as she's implying.
SPEAKER_3: Well, yeah, let me give you an example.
SPEAKER_3: For example, when stocks go up and down and up and down, when they cycle around, then dollar cost averaging can actually be useful because what goes up must come down, what goes down must come up, and by dollar cost averaging, you're smoothing over those bumps.
SPEAKER_3: But, you know, as Eugene pointed out, if you've got a sinking ship, it's probably not a good idea to keep investing more money in that sinking ship.
SPEAKER_2: It's hard to tell if something's sinking, too.
SPEAKER_1: Exactly.
SPEAKER_1: How do you know if a ship is sinking rather than just going through a lull?
SPEAKER_3: That's right, you don't.
SPEAKER_1: Well, then, what's so...
SPEAKER_2: See?
SPEAKER_2: I can't believe I don't give more financial advice to people with my massive observation skills.
SPEAKER_1: Let's get back to Suze Orman.
SPEAKER_1: I asked her about the 2008 meltdown just to see what insights she might have had to that meltdown that basically sunk America into a recession.
SPEAKER_4: The meltdown in 2008 could have been avoided, but not by the everyday person understanding whether it was a variable rate mortgage or a fixed rate mortgage.
SPEAKER_4: It could have been avoided if the banks, the financial services companies, and on an administration, the whole thing, decided to care more about people than they did about money.
SPEAKER_4: There was no securitization on these loans.
SPEAKER_1: What does that mean, securitization?
SPEAKER_4: It means you come to me and I'm the bank, and you want to borrow money to buy a house.
SPEAKER_4: I lend you the money to buy the house.
SPEAKER_4: Now, I care about you because you're paying me back, so I'm going to make sure that you are in good...
SPEAKER_4: Because we're together, we're borrowing, yep.
SPEAKER_1: We're in a bind together there.
SPEAKER_4: However, I don't care about you if I know as soon as I lend you the money, I'm going to turn around and sell your loan or your security to another bank.
SPEAKER_4: Then I don't care whether you're going to pay me back or not.
SPEAKER_1: And you're on to your next deal.
SPEAKER_4: And that's what made everything go down.
SPEAKER_1: So gone is the era of your personal banker who's caring for you, your present and your future.
SPEAKER_4: Was there ever such a thing?
SPEAKER_1: Well, that's what we tell ourselves.
SPEAKER_4: Yeah, they cared about their own future.
SPEAKER_1: Is...
SPEAKER_1: Andrew.
SPEAKER_1: So she's saying it's all about people.
SPEAKER_1: Now, that certainly would have been the case if your banker really cared about you.
SPEAKER_1: I don't know whoever feels that about their banker ever anymore, but she's got a point.
SPEAKER_1: If they cared about you, they would help you get through what might be a financial stress.
SPEAKER_2: They wouldn't sell your loan to someone else and leave the country.
SPEAKER_1: And leave the country.
SPEAKER_1: Or they wouldn't sell you, they wouldn't give you a loan that they didn't think you could pay back even if the computer model says you could.
SPEAKER_2: Right.
SPEAKER_1: Or would.
SPEAKER_1: Andrew, right?
SPEAKER_3: Yeah, but you got to remember that there's a good reason why we had securitization.
SPEAKER_3: This idea of creating packages of loans and being able to get more and more money into the mortgage system was really an idea that came about through this whole notion of the ownership society.
SPEAKER_3: Our politicians wanted to provide more affordable housing to lower income individuals that couldn't afford it.
SPEAKER_1: So ownership of real estate.
SPEAKER_3: That's right.
SPEAKER_3: And so we wanted to increase the amount of ownership that the people of the United States were able to undertake.
SPEAKER_1: Did you see the meltdown coming?
SPEAKER_3: Actually, you know, in 2000...
SPEAKER_1: That's a yes or no question.
SPEAKER_2: Did you tweet it?
SPEAKER_2: Let's just ask this.
SPEAKER_2: Did you tweet about the meltdown before it happened?
SPEAKER_3: We didn't tweet it.
SPEAKER_2: That's the only proof we could have.
SPEAKER_3: Actually, we published an article about it.
SPEAKER_3: In fact, in 2005.
SPEAKER_1: Wait, wait, wait, wait, wait.
SPEAKER_1: So, remember...
SPEAKER_1: Okay, so you published an article in 2005.
SPEAKER_1: The real question is, how often do you publish articles about the demise of the stock market?
SPEAKER_1: And is this just happened to be the one that got published within a zone of when it actually happened?
SPEAKER_1: So, what's the baseline of your prediction?
SPEAKER_3: That's a great question.
SPEAKER_3: But it wasn't an article that we published.
SPEAKER_3: It was actually a New York Times article that wrote about our research.
SPEAKER_3: In September 2005, we actually had a Sunday New York Times reporter write about the fact that we were predicting a very significant disruption in the hedge fund industry because of these kinds of markets.
SPEAKER_1: A significant disruption?
SPEAKER_2: Yes.
SPEAKER_1: What's that euphemism for?
SPEAKER_3: Big blowout.
SPEAKER_2: If only Malcolm Gladwell had seen it in 2007 and written a book, this could have all been avoided.
SPEAKER_1: Okay, so but there's the, had you known about it, had everyone known about it, they would have invested in a way that would have exploited the drop and then it wouldn't have dropped.
SPEAKER_1: Isn't that right?
SPEAKER_1: Isn't that a kind of a, if you know it's going to drop, you're going to bet against that.
SPEAKER_3: Yeah, that's one of the Zen paradoxes of finance.
SPEAKER_1: Exactly.
SPEAKER_1: Zen paradox.
SPEAKER_1: I knew Zen had to get in here at some point.
SPEAKER_2: I'm glad it has.
SPEAKER_3: So clearly not everybody knew about it, but there were.
SPEAKER_2: Where was your money?
SPEAKER_2: What did you do with all your money?
SPEAKER_3: Actually, my money was invested in a hedge fund that I had started and we were actually able to get through the crisis reasonably well.
SPEAKER_2: When that happened, did you call all your friends and make fun of them?
SPEAKER_3: That would be rude.
SPEAKER_2: That would be rude.
SPEAKER_1: Please quantify what you mean by reasonably well.
SPEAKER_3: Something like a 12% return.
SPEAKER_1: Oh, it's return.
SPEAKER_3: Yeah.
SPEAKER_1: Instead of a 40% drop.
SPEAKER_3: Right.
SPEAKER_1: Yeah, I would call that reasonably well.
SPEAKER_2: I'm going to just say now, hearing that, math is relevant.
SPEAKER_1: And my dollar that I gave you, I want a $1.40 when we're done here.
SPEAKER_2: $1.12.
SPEAKER_1: $1.12, that's right.
SPEAKER_1: So in my interview with Suze Orman, her name is spelled S-U-Z-E, as you surely know, and I'm tempted to call it Suze, but she's Suze Orman.
SPEAKER_1: I asked her, what was her reaction to these complicated investments strategies that people have?
SPEAKER_1: Because that clearly isn't another level of math that most people wouldn't get.
SPEAKER_1: And let's find out what role that plays in this business.
SPEAKER_1: We read about these exotic investment instruments.
SPEAKER_1: I can tell you that some of my colleagues helped invent some of this stuff.
SPEAKER_1: So is science and their mathematical brilliance, is that bad for the market?
SPEAKER_4: Yes.
SPEAKER_1: Okay, next question.
SPEAKER_4: It is bad for the market because here's why it's bad.
SPEAKER_4: People walk in to their investing life already thinking they don't understand it.
SPEAKER_4: Nobody wants to be able to say, especially a man, they do not want to say, I don't get that, can you explain it again?
SPEAKER_4: Not in your DNA.
SPEAKER_4: You won't even ask for directions, sir.
SPEAKER_4: So if you won't even ask for directions, you are not going to say to a financial advisor, I didn't understand anything you said.
SPEAKER_4: So that financial advisor, the more complicated the investments got, the less people were willing to say, I don't understand it, just do it.
SPEAKER_4: And here's what's so very sad.
SPEAKER_1: There's a whole psychology to all of this.
SPEAKER_4: The financial advisors didn't even understand the investments as well.
SPEAKER_4: They just knew the commission that they were going to be paid to sell this investment and that was it.
SPEAKER_4: It was a business transaction, and they did not even know what they were selling because you can ask any financial advisor on the street, give me a succinct definition of a derivative.
SPEAKER_4: They cannot do it.
SPEAKER_4: So if you can't define something, you can't understand something.
SPEAKER_4: If you can't understand something, you're about to get yourself into trouble.
SPEAKER_1: Suze Orman telling it like it is, but it seems to me that if you do understand it, then you not only won't get into trouble, you'd be flying high.
SPEAKER_1: Is that right?
SPEAKER_1: Professor Andrew Low.
SPEAKER_3: Well, you know, there were a number of hedge fund investors, including John Paulson, that did understand it and that bet against it and made literally billions of dollars.
SPEAKER_3: So it is possible, but it's complicated.
SPEAKER_3: And like anything else, it takes education.
SPEAKER_1: Right, but does that complication, yes, it accrues to your advantage, but does it exploit the decisions of other people in ways that leaves them at a disadvantage?
SPEAKER_3: Well, I think that it can, yeah.
SPEAKER_3: I mean, it's a zero-sum game.
SPEAKER_1: Can or does?
SPEAKER_1: Well, right.
SPEAKER_1: So there it is then.
SPEAKER_1: He walks away with billions, and everyone else is like in the poorhouse.
SPEAKER_3: Well, but on the other hand, what he's betting against is the fact that housing markets continue going up, and it gets to a point where it's insane.
SPEAKER_3: So one could argue that he's actually doing a service by telling people, look, you guys are out to lunch.
SPEAKER_3: This makes no sense.
SPEAKER_2: When you say one could argue, you mean he could argue?
SPEAKER_3: And he did argue quite effectively.
SPEAKER_1: That's the academicians one can argue.
SPEAKER_2: One could argue that it's great to make billions of dollars.
SPEAKER_1: So these financial crises, is there a way to prevent them in the future?
SPEAKER_3: I don't think so.
SPEAKER_1: Then what do you do up there at MIT?
SPEAKER_3: Well, I'll tell you, financial crises...
SPEAKER_2: He keeps his money in check.
SPEAKER_2: He's just hoping there's no war that takes away America.
SPEAKER_3: You know, financial crises are like a force of nature.
SPEAKER_3: You can't legislate away hurricanes, but what you can do is you can prepare for them.
SPEAKER_3: And I think that we can actually prepare for financial crises even if we can't get rid of them.
SPEAKER_3: And preparing for them actually is 90% of...
SPEAKER_1: Well, if preparing for them means I put my money in my pillow instead of giving it to the bank, then I don't lose my money, and therefore there's no financial crises at all.
SPEAKER_2: But maybe in a refrigerator, which is safer.
SPEAKER_3: See, that's the problem.
SPEAKER_3: And I think Ms.
SPEAKER_3: Orman would agree with that.
SPEAKER_3: If you put your money in the refrigerator, you earn no return, you're going to have a very hard time retiring.
SPEAKER_1: Wait, wait, wait, wait, wait.
SPEAKER_1: I'd rather earn no return than drop 40%.
SPEAKER_2: I think you have no idea how much money I want to put in a refrigerator.
SPEAKER_2: So let's first of all start there.
SPEAKER_1: You first start there, and you can retire on what you fit in your refrigerator.
SPEAKER_1: No, no.
SPEAKER_1: So my point is, so what if it has no return if everyone else is losing money?
SPEAKER_1: That's a tantamount to a return.
SPEAKER_3: Sure, for a year or two, that's not a problem.
SPEAKER_3: But if you think about a 20 or 30 year horizon, when you're investing money for your retirement, inflation can eat away at the value of your wealth.
SPEAKER_1: Yeah, that whopping 1.5% inflation is going on today.
SPEAKER_3: For now, but remember the 1970s and 80s, we had inflation of 15 or 20%.
SPEAKER_1: When we come back, more on the financial state of America and the science behind it.
SPEAKER_1: Thanks Welcome back, on today's show, we're analyzing the science of finance.
SPEAKER_1: How much sense does finance make?
SPEAKER_1: That was a pun.
SPEAKER_2: I put it together, I was gonna comment on it.
SPEAKER_2: I was gonna leave it at peace.
SPEAKER_1: That's the baritone voice of Eugene Merman.
SPEAKER_1: And of course, we have, back in the studio, Professor Andrew Lowe, finance expert, academic finance expert from MIT.
SPEAKER_1: Thanks for being in New York for this.
SPEAKER_1: You're at a conference now, aren't you?
SPEAKER_1: That's right.
SPEAKER_1: Yeah, so thanks for taking time out of your day to do this.
SPEAKER_1: You can, StarTalk Radio has a website, and it's startalkradio.net.
SPEAKER_1: And I tweet the universe, mostly brain droppings, if you're interested, follow me at Neil Tyson, N-E-I-L-T-Y-S-O-N.
SPEAKER_1: In this segment, I wanna talk about the technology that has been brought to bear on the execution of financial trades.
SPEAKER_1: Because in the old days, Andrew, what was it?
SPEAKER_1: It was somebody with a ticket who would walk it across an aisle, and that ticket was an instruction to buy or sell somebody's shares.
SPEAKER_1: Now it's done like in a nanosecond by a computer.
SPEAKER_3: At the speed of light.
SPEAKER_1: At the speed of electrons through wires, and even at the speed of light, if it's a wireless connection.
SPEAKER_1: So is this, how do you feel about that?
SPEAKER_3: Well, you know, this is progress, and one has to deal with it.
SPEAKER_1: Well, you sound like it's bad.
SPEAKER_3: I think that it has some unintended consequences.
SPEAKER_1: Let's find out what Suze Orman says, and then we'll come back to your unintended consequences.
SPEAKER_1: As she reflects on the role of technology in how finance is now conducted.
SPEAKER_1: Technology has influenced how trades are conducted on Wall Street.
SPEAKER_1: Now, there's no person, there's no runner, there's no billet.
SPEAKER_1: Is that good or bad?
SPEAKER_1: I mean, it means it happens instantaneously.
SPEAKER_1: A buyer and a seller are found immediately.
SPEAKER_4: I think it's good because...
SPEAKER_1: These are more of these jobs that are not coming back.
SPEAKER_4: I understand that, but again, hopefully, other jobs are created somewhere because of technology, as you were saying.
SPEAKER_4: But it's easier to track, it's harder to manipulate the systems.
SPEAKER_4: Now, years and years and years ago, when there were all these people on the exchanges, especially on the option exchanges, the guys, and there were mainly guys, they would get together and say, let's take him out.
SPEAKER_4: And they would get together and they can manipulate it and get one of the traders out by ganging against them.
SPEAKER_4: It's not so easy to do that anymore.
SPEAKER_4: So I like that there are computers, you can go back and see what happened.
SPEAKER_4: This doesn't make sense.
SPEAKER_4: But at the same time, you have crashes that happened in May 10th of 2010, where the market went down a thousand points in one day because of a computer glitch.
SPEAKER_4: So would that have happened if we didn't have computers?
SPEAKER_4: You know, you never know.
SPEAKER_1: So that's a lesson to make it better, not to not do it at all.
SPEAKER_4: That's correct.
SPEAKER_4: But I think computers are essential to keep up with the global economy we now have.
SPEAKER_4: You know, back then, we didn't have such a global economy.
SPEAKER_1: Today, you're basically traded 24-7, because some market is open somewhere in the world.
SPEAKER_4: That's right.
SPEAKER_4: So you need computers to do that.
SPEAKER_1: So Andrew, do you like computers in their applications to the manipulation of money in the world?
SPEAKER_3: Well, I do like computers.
SPEAKER_3: I think that they make things faster, smoother, more reliable.
SPEAKER_3: But at the same time, every once in a while, computers have glitches and we have to deal with those glitches.
SPEAKER_1: And those glitches come from humans who had programmed the computers.
SPEAKER_2: Yeah, but it is how we will defeat robot armies in the future.
SPEAKER_2: So it's a little comforting, I find, that they make mistakes.
SPEAKER_1: In fact, that's the matrix scenario, right?
SPEAKER_1: You can out hack the program.
SPEAKER_1: But so if computers are manipulating money all over the world and human beings program those computers, can you program it in a way that channels a billionth of a penny into your account every day and no one will notice it and then you walk away with a billion dollars?
SPEAKER_3: Well, in fact, years ago, somebody did just that.
SPEAKER_3: They basically collected the very, very tiny slivers of one millionth of a penny and they ultimately ended up trying to defraud a bank of that kind of money.
SPEAKER_3: They were caught and now we actually have double precision mathematics on our computers.
SPEAKER_2: How long did they get away with it for?
SPEAKER_3: I think it was probably a year or two before somebody discovered this.
SPEAKER_1: But is this a lesson to not do it or the fact that there are a hundred other people who did it that you don't know about?
SPEAKER_2: It's a lesson to do it for half a year.
SPEAKER_2: That's the lesson.
SPEAKER_2: Don't do it for two years.
SPEAKER_2: I mean, how many billions of a cent do you need?
SPEAKER_1: You only have a story of those people who were caught, not those who weren't.
SPEAKER_3: Well, but very quickly, we figured out how to improve our computers.
SPEAKER_3: In the same way that now we have online shopping, early days you had problems, we figured out how to deal with those problems.
SPEAKER_1: And so that, when you say deal with them, what do you mean?
SPEAKER_1: You had to close the loophole.
SPEAKER_3: Close these loopholes.
SPEAKER_2: What were the problems with early online shopping?
SPEAKER_3: Oh, well, people would take your credit card numbers and be able to charge other items.
SPEAKER_2: Oh, you mean stealing.
SPEAKER_4: I see.
SPEAKER_3: You could call it that.
SPEAKER_2: Problems.
SPEAKER_2: I think you mean identity theft and stealing.
SPEAKER_1: My favorite of these was someone got a booklet of payment slips for a piano they just bought.
SPEAKER_1: And they accidentally one day used the last slip in the payment sequence to pay.
SPEAKER_1: And then the next week they got back a letter, thank you for completing all your payments for the piano.
SPEAKER_1: It's now yours.
SPEAKER_1: It had no concept of how much total money was paid into it.
SPEAKER_1: It was only checking that you must be done when you use the last slip.
SPEAKER_2: Right, so they would use slips out of order.
SPEAKER_1: Right, right, who would possibly do it?
SPEAKER_1: That was an early glitch in the computer system.
SPEAKER_3: Yeah, I bet they fixed that pretty quickly.
SPEAKER_1: So are there algorithms that people come up with?
SPEAKER_1: Algorithm, by the way, is an Arabic word, dating from 1,000 years ago, when mathematics was big in the Middle East.
SPEAKER_2: It's still popular today, Neil, don't get so down on it.
SPEAKER_1: Sorry, let me clarify, when algebra was invented in the Middle East, in Baghdad, actually.
SPEAKER_1: So there are algorithms that people apply to either buy and sell, and they're at the beach waiting for the algorithms to do their thing.
SPEAKER_1: That's basically computer taking control of a portfolio.
SPEAKER_1: And you endorse this, or what?
SPEAKER_3: Sure, I think as long as you do it responsibly, these algorithms are actually very helpful because they automate the management of portfolios that would be impossible to manage with human intervention.
SPEAKER_1: You mean huge, unwieldy portfolios.
SPEAKER_3: That's right, large numbers of securities across different countries.
SPEAKER_2: Even puts and calls?
SPEAKER_2: Absolutely.
SPEAKER_1: I was ready to go with you on that, and I said, no, he really doesn't know.
SPEAKER_2: No, it's two of the eight words in finance that I'm aware of.
SPEAKER_1: And so, what I'm curious about is, in this world of managing and manipulating money, what role does emotion play?
SPEAKER_3: Well, I think emotion is hugely important because ultimately you're dealing with human investors.
SPEAKER_3: And while all of these algorithms make it seem like we've got scientific principles for investing, at some point, an individual has to decide whether or not they want to buy or sell.
SPEAKER_3: And so, emotion can actually be the downfall of even the savviest investor.
SPEAKER_1: So, every emotional person should have a computer black box algorithm in their utility belt to invoke it at times when they're just emotionally distraught and they can't make rational decisions.
SPEAKER_3: Or to be able to come up with good rules that will work and deal with these kinds of emotional stresses.
SPEAKER_2: So, if I can put enough emotional stress against other investors, I can potentially come out on top.
SPEAKER_3: That's right.
SPEAKER_2: Perfect.
SPEAKER_1: Let's get back to my clips with Suze Orman.
SPEAKER_1: We chatted briefly about R&D and what role that plays and sort of the growth of economy and what a company might need to do to make that work for them.
SPEAKER_1: Let's see what she has to say.
SPEAKER_1: Can you come up with the magic number, the magic percent of a company's revenue that they should spend on R&D?
SPEAKER_4: No, I can't because so many things are at play right now, especially given that they still haven't recovered.
SPEAKER_4: It's hard to invest logically in R&D research and development when you can't even meet your own payroll.
SPEAKER_4: You're about to go under.
SPEAKER_4: You have all these people, you can't even pay the debt.
SPEAKER_4: Ask the government.
SPEAKER_4: Look at the government right now.
SPEAKER_4: You're asking them to invest in research and development and some of your things.
SPEAKER_4: When what do they want to do?
SPEAKER_4: They want to get rid of the EPA.
SPEAKER_4: They want to get rid of Planned Parenthood.
SPEAKER_4: They want to get rid of all of these things.
SPEAKER_1: They want to cut PBS.
SPEAKER_4: They want to cut PBS by a lot.
SPEAKER_4: So when you're sinking, it's very hard to say anything other than throw me a financial life preserver.
SPEAKER_4: It's hard to say, oh, throw me something that I'm going to be able to see 20 years from now, save me, when they feel like they're drowning right now.
SPEAKER_1: Because before then, you're dead.
SPEAKER_1: You've drowned.
SPEAKER_1: There it is.
SPEAKER_1: So what, so Andrew, let me ask you, is there, you guys, is there a formula for what makes a successful company?
SPEAKER_3: I don't think there's a simple formula because if there were, everybody would want one and we'd all be rich.
SPEAKER_3: I think there are lots of them.
SPEAKER_1: And the downside of that is, what's the, you say that as though, and your point is?
SPEAKER_3: Well, we're not gonna all be rich.
SPEAKER_1: Why not?
SPEAKER_3: Well, because there's a limited amount of resources and we can't all get access to them.
SPEAKER_1: Okay, but we can get rich while the whole rest of the world gets poor.
SPEAKER_1: That can happen.
SPEAKER_2: It's true.
SPEAKER_2: You're thinking of it too big.
SPEAKER_1: And I think of the universe, which has essentially unlimited resources.
SPEAKER_2: It's true.
SPEAKER_1: And plus you could be rich in your heart.
SPEAKER_3: Absolutely.
SPEAKER_2: Is that the rich we're talking about?
SPEAKER_2: Is that how you use math to become rich in your heart?
SPEAKER_1: And so, do people have hearts in the financial industry?
SPEAKER_3: Sometimes.
SPEAKER_2: Four of them, at least.
SPEAKER_2: But I wouldn't say.
SPEAKER_1: Not how many chambers in their heart.
SPEAKER_1: I'm talking about hearts.
SPEAKER_1: And so, what I wonder is, you have these things called hedge funds and other kinds of funds that are not just, let me invest in some stocks.
SPEAKER_1: Are these good for the economy or bad?
SPEAKER_3: Well, you know, I think overall they're good.
SPEAKER_3: They basically provide resources and liquidity.
SPEAKER_3: When people want to buy things.
SPEAKER_1: Wait, tell me what a hedge fund is first.
SPEAKER_3: Well, a hedge fund is sort of like mutual funds on steroids.
SPEAKER_3: It's investing where there's no constraints and where the investors are high net worth and sophisticated clients that can afford to lose a lot of money so they can engage in pretty high-risk strategies.
SPEAKER_1: This is like that room in the back at the, in Vegas.
SPEAKER_3: The high rollers.
SPEAKER_1: The high roller table.
SPEAKER_2: So a hedge fund is like a very risky mutual fund for wealthy people who are gambling.
SPEAKER_3: Yeah, I guess so.
SPEAKER_2: The amount you resist calling it gambling and the amount that is gambling, I find charming.
SPEAKER_3: It's taking calculated bets.
SPEAKER_2: Yeah, yeah.
SPEAKER_2: Well, sure, I don't mean like, I don't mean it's like slot machines.
SPEAKER_2: I mean it's like poker.
SPEAKER_3: Well, there's professional gambling and there's compulsive gambling.
SPEAKER_2: Right.
SPEAKER_1: And so, but if you have a million to drop, then you go into the back room and you play, what's it, Baccarat?
SPEAKER_1: What's the game in the back room?
SPEAKER_2: Oh, I don't know.
SPEAKER_2: Sure.
SPEAKER_2: I like the, you're asking me like, well, as someone who always loses a million dollars and doesn't care.
SPEAKER_1: Well, billionaire, you can lose a million and not sweat it.
SPEAKER_2: Then it's no fun to make a million.
SPEAKER_2: That's the problem with being a billionaire.
SPEAKER_1: We've got to take a quick break, but more StarTalk when we return.
SPEAKER_1: This is StarTalk Radio, welcome back.
SPEAKER_1: I'm always curious what role emotion plays in people's decisions at all, but in particular in their decisions to invest.
SPEAKER_1: Now, Andrew, you had a story you started to tell us over the break about a Superman costume, and I have no idea how this will ultimately connect to the subject of this program, but I'll let you try.
SPEAKER_3: Well, thank you, I'll give it a try.
SPEAKER_3: You know, we all come up with rules of thumb for how we make decisions, and it's important to realize that emotions can be good or bad in helping us develop these rules of thumb.
SPEAKER_3: So the example that I often give my students is getting dressed in the morning.
SPEAKER_3: Suppose you have 10 shirts and 10 pairs of pants and two pairs of shoes.
SPEAKER_3: How many different outfits do you have with that kind of a wardrobe?
SPEAKER_3: It turns out that that simple wardrobe that I just described has 200 unique outfits.
SPEAKER_3: And so if you take a typical person's closet and figure out how to get dressed in the morning, it's an incredibly daunting job.
SPEAKER_3: If you tried to optimize the best outfit out of all of those combinations, you would spend three or four days getting dressed.
SPEAKER_1: No, only if you're an MIT person that doesn't know how to match colors.
SPEAKER_3: Good point.
SPEAKER_1: All right, I would not be considering the purple with the green.
SPEAKER_3: Well, you know, and my wife tells me that all the time.
SPEAKER_2: If I told you you wouldn't have purple or green.
SPEAKER_2: Yeah, well, purple for sure, green probably.
SPEAKER_3: But the point is that people don't optimize.
SPEAKER_3: They don't use heavy duty mathematics.
SPEAKER_3: They basically use rules of thumb.
SPEAKER_3: And in my case, I get dressed really quickly.
SPEAKER_3: It drives my wife crazy.
SPEAKER_3: And the way that I get dressed quickly, the reason that I get dressed quickly is I had an event that happened to me when I was six years old.
SPEAKER_3: I grew up in a single parent household in Queens, and we didn't have a lot of extra money, but some clever marketing genius figured at the time that if you put a Superman emblem on a jacket, you can sell a lot of those jackets to six year old kids.
SPEAKER_3: So I nagged my mother for weeks on end to get me this jacket.
SPEAKER_3: And ultimately, like any good mom, she gave in, and so she got me the jacket.
SPEAKER_3: I remember that day very clearly.
SPEAKER_3: It was a Friday night after work.
SPEAKER_3: She took me to Alexander's on Queens Boulevard, got the jacket, spent the weekend playing around in it.
SPEAKER_3: Monday morning, stood in front of a mirror with the jacket, looking at how good I'm gonna look at school, and I was late for school.
SPEAKER_3: I had to get a note from my mom, walked into the class late, and I had to give the note to my teacher, walk to my seat where all the students were snickering.
SPEAKER_1: But you had your Superman jacket.
SPEAKER_3: But I had my Superman jacket, and I was completely mortified.
SPEAKER_3: And from that day on, it never took more than five minutes for me to get dressed in the morning.
SPEAKER_3: I learned a different rule of thumb based upon some pretty negative emotional feedback.
SPEAKER_3: And you know it's negative, because 46 years later, I still remember that day.
SPEAKER_1: So you were traumatized.
SPEAKER_1: That's the most traumatizing event in your life.
SPEAKER_1: You've led a charmed life, I think.
SPEAKER_2: Yeah, wait.
SPEAKER_2: In your story, you were five minutes late as a sixth grader, and then you decided to go to Yale and Harvard?
SPEAKER_3: Well, there's more-
SPEAKER_2: That's what you overcame?
SPEAKER_3: There's more to the story.
SPEAKER_2: Which is that you developed actual powers and responsibilities.
SPEAKER_1: No, he developed Superman powers from having worn the jacket.
SPEAKER_3: Or at least I figured out how to get dressed very quickly.
SPEAKER_1: Let's see what Suze Orman says about the role of emotion in making financial decisions.
SPEAKER_1: What is the balance in your life experience between the analytic mind and the emotional mind in making financial decisions?
SPEAKER_4: I think 100% it comes from emotions.
SPEAKER_1: But should it?
SPEAKER_4: No, it should not.
SPEAKER_1: It shouldn't, okay.
SPEAKER_4: The three internal obstacles to wealth are the three emotions, fear, shame and anger.
SPEAKER_4: And that is where people come from almost constantly when they're investing their money, which is why they have a negative experience when it comes to investing.
SPEAKER_1: The victims of their own emotional state.
SPEAKER_4: Correct.
SPEAKER_4: If they just were willing to take the emotions out of it and analyze it, is this a good idea?
SPEAKER_4: Does it make sense?
SPEAKER_4: Can I relate to it?
SPEAKER_4: Is there a future in it?
SPEAKER_4: Do I like the management?
SPEAKER_1: I've met people that it's hard, if not impossible, for them to think that way.
SPEAKER_1: They're so emotionally driven.
SPEAKER_4: And that's when they usually get a financial advisor that preys off of those emotions and then they become really victims to their own circumstances.
SPEAKER_4: So again, I will go back to, it's better to do nothing than something that you do not understand.
SPEAKER_1: That's quite a bit of wisdom there.
SPEAKER_1: Would you agree, Andrew?
SPEAKER_3: Absolutely.
SPEAKER_1: And so, from what I know in our previous chats, part of your professional interest is on decision making and what role emotions play, the research, literature on this.
SPEAKER_1: And so what have you found?
SPEAKER_3: Well, one of the things we discovered.
SPEAKER_1: And does neuroscience, the new science of neuroscience influence what your work does?
SPEAKER_3: Yeah, there's some fascinating intersections between neuroscience and evolutionary biology and finance.
SPEAKER_3: One of the things that we found is that emotion plays an incredibly important role, but the proper balance of emotion and logic has to be done.
SPEAKER_3: In other words, too much emotion, that's bad.
SPEAKER_3: But too little emotion is also bad.
SPEAKER_1: But if you're a painter or sculptor or artist, too much emotion is good.
SPEAKER_3: It can be, unless you're Vincent van Gogh.
SPEAKER_2: I think probably a combination of both is really helpful.
SPEAKER_2: Unless you're Vincent van Gogh.
SPEAKER_2: But during his lifetime, it wasn't that great.
SPEAKER_1: So, there's some, do you know what the proper mixture is of emotion and logic?
SPEAKER_3: Well, we're actually documenting that now.
SPEAKER_3: We're doing experiments with traders where we're measuring their emotional responses as they trade.
SPEAKER_2: Is it 65, 35?
SPEAKER_3: More like 60, 40.
SPEAKER_1: Well, wait, so you put-
SPEAKER_2: Oh, off by 5%.
SPEAKER_1: Well, wait, so you're putting electrodes on the heads of traders as they make financial decisions.
SPEAKER_3: Exactly.
SPEAKER_1: Measuring brain activity.
SPEAKER_3: Well, brain activity and also emotional state.
SPEAKER_3: We wanna know how much of their emotional responses are actually feeding into their trading decisions.
SPEAKER_1: So, of the various emotional states, there's fear, anger, love.
SPEAKER_2: Do you endanger their families and tell them as they're trying to invest money that you've-
SPEAKER_3: Not yet.
SPEAKER_1: I mean, is there amorous emotions by traders?
SPEAKER_1: I mean, are traders in love with money?
SPEAKER_3: Well, you know, at this point, the science isn't that far long.
SPEAKER_3: What we can do is to measure something called skin conductance, basically sweaty palms.
SPEAKER_3: If they've got some very strong reactions, the same kind of reactions that a lie detector test would show, what that's telling you is that they've got a strong emotional reaction.
SPEAKER_3: And it turns out that traders have emotional reactions like professional athletes.
SPEAKER_3: Not too much, but not too little, within a range that actually helps them make better decisions.
SPEAKER_1: So sweaty palms.
SPEAKER_1: So on your first date with someone, you get sweaty palms?
SPEAKER_3: Absolutely.
SPEAKER_2: You're a good decision maker.
SPEAKER_1: So there's a future to this that we can still learn from that you're researching.
SPEAKER_2: So if I invest money in the 401k I get, I'll know I'm making the right choice as I get sweatier, just to be clear.
SPEAKER_3: But there's just the right amount of sweat.
SPEAKER_2: Just the right amount of sweat.
SPEAKER_2: There's a perfect amount of sweat.
SPEAKER_2: They'll be like, this is a good choice.
SPEAKER_1: Wait, wait, wait.
SPEAKER_1: And if a person is especially sweaty, you have to calibrate against their basic sweat level.
SPEAKER_3: That's right.
SPEAKER_3: So it's actually a very complicated process.
SPEAKER_2: Is that true?
SPEAKER_2: Do you take basic sweat measurements of a person?
SPEAKER_1: You have to.
SPEAKER_1: It's a science experiment.
SPEAKER_3: Absolutely.
SPEAKER_2: I'm saying you wouldn't.
SPEAKER_2: Just making sure that that's how you approach people.
SPEAKER_3: You got to get the baseline.
SPEAKER_1: Well, we've got to wrap up the show now, but I want to thank my guests.
SPEAKER_1: And as always, I want you.