S4E8 - The Magic Formula (Long Term Capital Management)

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Chris: And as I mentioned before, the kicker is that from a certain point of view, the LTCM guys were right. The math was correct. Markets do eventually stabilize after a disruption. But as the quote goes, markets can stay irrational longer than you can stay solventhe. I'm ready, I'm ready.

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Kayla: You're SpongeBob all the time now.

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Chris: Yeah.

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Kayla: All SpongeBob all the time.

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Chris: Cause we started watching. Or I started watching SpongeBob for the first time.

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Kayla: Yay. This is called self care.

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Chris: We're adults.

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Kayla: Self care is watching children's cartoons. It really is.

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Chris: Yeah. I mean, okay, but SpongeBob has a lot of humor that is either explicitly, like, adult oriented. Like, there was, like, a reference to that, like, french poster art style.

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Kayla: The other loose the track.

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Chris: Yeah. Or like, jokes that adults get. And also, like, as somebody who grew up with Ren and stimpy, like, I kind of see that DNA there.

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Kayla: Absolutely a spiritual successor in the Ren and stimpy Rocko's modern life. SpongeBob bloodline.

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Chris: Yeah. I'm surprised. Like, it's quite good. And also, as I mentioned this to you, but I think our listeners deserve to hear this too, because it's just such a fascinating insight that I had.

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Kayla: Ooh, a fascinating insight into your mind.

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Chris: Into my mind. I know, but it was weird watching it for the first time because of how heavily memed SpongeBob is on the Internet, on Twitter and TikTok and everywhere. So it felt like, even though I'd never seen it before, it kind of felt like I had, in a weird way.

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Kayla: You saw these memories were triggered by things that are memed and your brain was confused over. Do I remember this because I saw it memed or do I remember this?

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Chris: Yeah, yeah. It was like I had the experience of. It was like, false memories. It was totally like a teal swan thing.

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Kayla: Yeah.

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Chris: Like I had false memories implanted, except, like, I had, like, the full context that I knew where they were from. So it was like I had the feeling of it even though I knew that it wasn't.

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Kayla: I don't know how you knew how the memories were implanted.

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Chris: Yeah, I was tripping balls and weren't even high.

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Kayla: No.

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Chris: Watching SpongeBob, it's enjoyable on its own. I know, I know. Pro spongeBob. This is not the topic, by the way.

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Kayla: It could be.

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Chris: It could be maybe one day. SpongeBob, actually. Yeah, it totally could be. There's a lot of weirdness around SpongeBob.

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Kayla: Yeah.

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Chris: Yeah. Anyway, I'm Chris.

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Kayla: I'm Kayla.

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Chris: And this is cult or just weird? Thanks for joining us, everybody. Oh, we didn't do our credentials.

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Kayla: Oh, I'm no one.

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Chris: You're no one.

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Kayla: And so am I. I write for tv.

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Chris: I do game design and also data science. So the only business I have is Patreon. Business.

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Kayla: Patreon. If you want to support us, go to the patreon. Patreon.com culturesweird.

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Chris: Since our last shouting out, we have one brand new patron. So thank you to Rose Korczynski for subscribing to our Patreon. Hopefully you're enjoying the content there. Thank you so much for supporting the show. And also an existing patron, an old time an OG patron. Annika Raman, I believe I'm pronoun. I hope I'm pronouncing that right. She was at the $1 tier, what do we call that one?

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Kayla: Initiate?

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Chris: Initiate. She was an initiate, and she graduated through the ranks to cultist, which is just such an inappropriate way for us to brand our stuff. But it's fun, so I don't care, you guys.

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Kayla: The word cult is no good.

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Chris: Yeah, no, it sucks. It's not a good. It's not good.

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Kayla: It's no good. I have a friend right now who is. They're writing something about, like, they're writing a feature about cults, and they want to sit down with me to talk about cult stuff. And I'm like, cults aren't a thing.

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Chris: Well, but that's a good thing for you.

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Kayla: This is the word cult.

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Chris: Yeah, no, but that's.

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Kayla: I use it every day.

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Chris: I'm allowed to use it.

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Kayla: I'm allowed to use it.

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Chris: You shouldn't.

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Kayla: You're not.

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Chris: Oh, that's. But that's podcasting, right? Is that I'm allowed to do something that everyone else is not. Yeah.

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Kayla: One day we'll change the name of the podcast to new religious movements and or other such groups or just weird.

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Chris: Catchy. Anyway, thank you so much to Rose Korchinski for supporting us. And thank you to Annika Raman for supporting us for so long. And now for supporting us even more. Thank you guys so much.

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Kayla: Thanks.

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Chris: Good. Good. That was a good. Thank you. So, Kayla.

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Kayla: Yes.

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Chris: Here's the thing. Several of our recent episodes have been, interestingly, have been, like, finance related. Like finance business, money related.

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Kayla: Like the worm one.

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Chris: Yeah. Like two episodes ago, we talked about that wormy Ponzi scheme that was basically like a financial ish sort of episode.

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Kayla: Right?

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Chris: The episode before that, I talked about the rise of international banking, which history of the Rothschild family.

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Kayla: I talked about tea companies.

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Chris: You talked about tea companies. Patreon Bonus episode. I literally just talked about boring finance stuff with our cat. I hope some people got value out of that.

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Kayla: I talked about another Ponzi scheme. Yeah, we've got a great theme going here for our self care season.

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Chris: Yeah, money. That's right. But, yeah, I guess it's kind of like, I don't know, finance and money stuff has sort of been on my mind lately.

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Kayla: Is it because capitalism has leveraged and appropriated the term self care to commodify it into something that is totally just purchased now and it is not actually self care? And what we actually need now is community care?

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Chris: Is it that until capitalism eats that, too, it will. Packages. We're probably only like, a month or two away.

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Kayla: Yeah.

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Chris: Honestly, that's the first time I've heard that as a buzzword. So that usually means that about a month or two away. Yes. That dystopian notion sucks. Thank you for reminding me of it. You're welcome. But this is less about the existential crisis we find ourselves in right now and more about a financial one.

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Kayla: Oh, less. Thank God.

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Chris: Well, it's. We'll get to that. So, yeah. Anyway, all this stuff has kind of been on my mind. It made me remember about this, like, little period drama about a plucky little startup that I learned about when I was growing up in the 1990s.

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Kayla: What are you doing today?

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Chris: Well, to be more accurate, I learned about this story in business school. It's not Earthlink or Netscape or prodigy. Do you remember prodigy?

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Kayla: I just remember prodigy.

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Chris: Prodigy. Well, prodigy was an ISP as an Internet service provider, but Netscape was a browser. Different things.

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Kayla: An earthlink.

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Chris: Wait, all of them are gone now?

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Kayla: Which one just is gone? Internet Explorer.

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Chris: Yeah, Internet explorer. Explorer just died. But they've been phasing it out for a long time in favor of their edge browser. Now. It's called edge. So they don't not have a browser.

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Kayla: Kayla can't not have a browser.

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Chris: Anyway. I think it's just as crappy. I don't know. Like, that's good nineties reference, though, because that's what today's show is about. This is actually a story. I didn't really learn about it when I was a kid in the nineties because I was a kid. But I did learn about it in business school. In fact, my sources today include my own shoddy memory of the story, as well as a bunch of the usual suspects. Right? A few Wikipedia articles to jog my memory. There's a Guardian article from 2003 that has some really funny, in retrospect, quotes. There's a couple Business Insider articles, investopedia, a book called when Genius failed, and then a few other tidbits and videos from YouTube, mostly.

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Kayla: I'm so excited.

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Chris: Listeners with a background in the financial industry or who also attended business school might already know what I'm talking about. It's a simple little company with the most mundane name.

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Kayla: Tell me.

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Chris: Long term capital management.

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Kayla: Ew. That's nothing. No, I'm not giving them any of my angel investor dollars.

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Chris: Long term capital management.

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Kayla: Long term capital management. That's the most mundane thing I've ever heard in my life.

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Chris: Absolutely. And, in fact, the mundanity of the name is, like, part of it. It's part of their branding strategy. Okay, but we'll get to that.

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Kayla: It sounds like the company that, like, a character in fight club would have worked for.

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Chris: Yeah, or like american psycho, basically.

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Kayla: Yeah.

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Chris: Yeah, yeah. That's exactly right. Caleb, before I transport us all back to 1994.

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Kayla: Oh, God, I wish.

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Chris: First I want to talk with you about some gaming stuff. I'm all ears now. This is casino gaming stuff.

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Kayla: Oh, I'm less ears.

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Chris: Gaming. Gaming stuff. I took a trip many years ago. It wasn't quite the 1990s. I was a child then, so, you know, no gambling then. This is more like late two thousands. I'm not much of a gambler myself. I do like sports betting. I do have a bit of a soft spot for that, but that's a long story for another day. But when it comes to.

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Kayla: It was immortalized in a little film called Uncut Gems.

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Chris: Yeah, just watch uncut gems and you'll. That's. That is basically me when I get to a casino. But when it comes to table games or slot machines or that kind of thing, like, I just, like, I can't. Just can't get into it. Like, with my background in math and statistics, I just have, like, a bit of a hard time getting the dopamine flowing when I know that the math is stacked against me. Like, with sports betting, like, sure. Like, I can convince myself that I have a say in the matter, right? I'm like, ooh, I'm so sports smart, right? I'm smarter than the. I'm smarter than the guys setting the betting lines at the casino. Like, you can kind of, like, tell yourself that narrative.

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Kayla: Well, it just feels like, well, sports. The outcomes are just, like, kind of totally, like, by chance at a certain point, it's not the house. Designing a system that will encourage cash flow to them continuously.

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Chris: Right, right. Exactly right. Sort of the same thing with poker. Right. Like poker, you can tell yourself the narrative that, like, I'm. You know, if I'm at a table with ten people, I don't have a one in ten chance of winning. I have, like, a one in two chance of winning because I am just the smartest person here.

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Kayla: I never tell myself that.

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Chris: Yeah. I mean, I am. I'm absolutely not the smartest person at the table, but I can tell myself that, and that makes all the difference, actually. Slots, though, like, I know that's designed. Like you were just saying, that's designed to have a negative expected value for me. Expected value. Just in case you're not sure. It's just a calculation of the odds of winning something multiplied by the value if you do win. So, for example, if you flip a coin and if it comes up heads, you win $2, then your expected value of each flip is $1 because you have a 50% chance of getting heads and a 50% chance of getting tails. If it's tails, it's $0. If it's heads, it's two. So 50% times two equals $1. Does that make sense?

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Kayla: Yeah.

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Chris: Expected value.

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Kayla: Yes.

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Chris: Okay. Now, in reality, your expected value also has to take into account how much you paid for this experience.

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Kayla: Right?

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Chris: So, like, that was like a. I don't know, like a free coin flip example. But if you put your quarter into a slot machine, you also have to subtract a quarter from the expected value, which can put these expected value calculations into the negatives. And that's exactly how casinos work. Right? So, like, let's say there's a. There's a quarter slot machine game, and you're supposed to put a quarter into play, and it could give you zero or it could give you $100 or whatever. But if you do all. If you multiply all of the odds by all of the payouts, then it comes out that, like most. Most slot machines, you are essentially losing, like a penny or a fraction of a penny each time on average. Right. The casino is always going to have the math stacking up in their favor.

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Chris: Now, sure, if you're lucky, like, you can win money on a short time scale, right? Like, if you flip enough heads and get enough $2. Right. Then, like, you can kind of walk away from the table, right? If you get enough jackpots at the. At the slot machine before you keep playing so much that eventually it evens back out. Yeah. You could earn money at the slot machine as long as you're lucky in a short time frame. Roulette is another good example to kind of illustrate some of the stuff at the casino. I like as an example because it's like the one game on the casino floor where you can kind of basically just pretend it's a coin flip. The roulette wheel has two different colors. You can bet on black and red.

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Chris: There's other bets you can make, but if you want to make it real simple, there are black colors and there are red colors. Just about half of the roulette numbers are red and half are black. So if you're going to bet on red, it's essentially like a 50% outcome. If you're going to bet on black, it's essentially a 50% outcome. It's a little bit stacked in these casinos favor, but that's. You can kind of think of it like that, like a coin flip.

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Kayla: Roulette stresses me out a lot.

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Chris: Why does roulette stress you out?

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Kayla: I don't like it.

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Chris: Oh, wow. Really? That's enlightening. It stresses you out because you don't like it? Do you not like it because it stresses out you out?

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Kayla: I think that it's. It's one of the more, like when a movie or a tv show needs, like, a real stressful, like, gambling moment where you're like, everything's on the line for this character, and they've just got to land one number. And then either they'll be, like, dead in the water, or they'll, like, win everything. They use roulette. Like, I'm thinking of. I feel like roulette's been in a. Like, it's either roulette or, like, that other one. That's craps. Is it craps?

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Chris: Craps because craps has dice throwing.

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Kayla: Yeah, it's roulette and craps. Those are the ones that stress me out.

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Chris: But roulette is so much better for that, because roulette, like, the. You have so much time for the thing to spin around and the little ball to bounce around. Like, the physical elements of roulette make it, like, so great for, like, an on screen experience where somebody has, like, gambling.

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Kayla: That's why I'm stressed about it.

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Chris: Okay. That actually makes a lot of sense now. All right, you with me so far on the, like, roulette is, like, kind of 50% chance you win. 50 chance you lose.

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Kayla: Yes.

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Chris: Okay. So when I visited Vegas these number of years ago, I thought to myself, hang on, though. Even though I don't normally like those types of games. What if I go in with a particular strategy first?

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Kayla: Did you count cards?

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Chris: No, roulette isn't cards.

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Kayla: Did you count balls?

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Chris: I count balls. I was a ball counter. No, here's the strategy. I was like, what if I take. I just pick a color, and that's the one I'm gonna bet on, right? I'll pick. I'll pick black. I'm gonna put $1 on black. If I win, great. I won a dollar, right?

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Kayla: Love to win a dollar.

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Chris: There we go. We won. If I lose now, instead, the next time I bet on the same color, I bet on black, but I double my bet to $2 if I win this bet. Great. I've still won a dollar total, because since I doubled my bet, that means now I won $2. Right? But I still have to subtract the one that I lost on the first bethe. So I'm still up $1. All I have to do is double my bet. What if I also lose the second bet? Simple. Just double it again. Now, I bet $4. If I win now, that's $4. I'm up minus the one from the first bet that I lost, minus the two from the second bet that I lost. Four minus two minus one equals one, right?

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Kayla: I don't know.

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Chris: This is starting, so I still just won a dollar.

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Kayla: This is starting to sound a little crazy to me, but.

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Chris: And if I lose that beta, I just double it again, right? Double down again. And if I win that one, the math still checks out. I still win a dollar, and so on and so forth. I just. As long as. If I keep losing, all I have to do is just keep doubling my bet until I eventually win, and I'm always guaranteed to win a dollar.

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Kayla: I don't know. That sounds. The maths, but it also sounds like the mind of a madman.

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Chris: Wow. What's. What's. I mean, what's the flaw there?

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Kayla: It just sounds like you've set yourself up a little system to.

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Chris: To guarantee myself to win a dollar.

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Kayla: To keep gambling and getting further and further into debt.

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Chris: No, no. Because I always just double the amount that I bet.

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Kayla: That sounds bad.

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Chris: Why does that sound bad?

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Kayla: Because eventually you're gonna be. If you double, double, double, you're gonna be in the thousands.

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Chris: Yeah, that's a good point. So, of course, like, even though I thought that I kind of came up with this was not anything new. This is actually a system known as the martingale system, or the Martingale strategy, which was in quite what's the strategy here.

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Kayla: You just keep betting. That just sounds like gambling, but it's.

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Chris: Not just still betting, it's the strategy of betting on the same thing on like a 50% chance to win and then doubling your bet, doubling down each time. And then eventually you are guaranteed to win that dollar. Right?

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Kayla: Are you?

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Chris: Eventually. Okay, so the Martingale strategy was invented by. Can you guess?

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Kayla: Margo Martindale.

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Chris: Paul Pierre Levy. Right. I couldn't figure out why that was.

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Kayla: It's like, probably they just named it after Margot Martindale. Cause she's that great.

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Chris: Well, it's Martin Gale, but yeah, you're probably right. They probably changed the G and just named it after her ten to not get sued. Yeah, but, yeah, using this bet, I can always guarantee, quote unquote, that I win as much as my initial bet. I just have to double down each time, lose, and eventually my winnings make up for it. So this must break the casino then, right?

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Kayla: I'm gonna say no, because there's still a lot of casinos.

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Chris: There's still casinos, and they don't prevent you from doing the strategy. This is just a very, this is a normal betting strategy. You can just do the catch here, and you kind of hit on this earlier, is that your money isn't infinite.

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Kayla: It is not.

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Chris: It's far from infinite. So it is true that this system gives you a very high likelihood of earning your initial small investment back, right? Because, like, I mean, in this course of like three, four, five coin flips, you're probably going to get a winning flip there, right?

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Kayla: Most likely, yeah.

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Chris: It's pretty unlikely you're going to roll, you know, that you're going to get that six coin flips at all, or the same thing. In fact, it's exactly two to the six power. But the problem is, there's this nagging small probability that you lose, like, basically everything. So if tails happens enough times in a row to outlast your wallet now, you've actually lost your wallet. Now, funnily enough, there's actually a famous saying by economist John Maynard Keynes that goes, the market can remain irrational longer than you can remain solvent.

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Kayla: See, that's the thing, man. That's the. Ruben, that's the stuff.

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Chris: Now, he's talking about the stock market here, not gambling. But the idea is kind of the same, is that you can be sort of correct about the probabilities of a bet, you know, even mathematically so, but you can't necessarily predict how long the market is going to stay in its weird, off kilter quote, irrational state. You can't predict how many times the coin will come up tails in a row and you very much are able to run out of cash while you're waiting for that one. Heads. And it would be fine if the heads. If it would be fine if this strategy allowed you to like make a decent amount of money. And then when you lose a decent amount of money. But the problem is here is that the amount of money that you win by doing this guarantee thing is teeny tiny.

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Chris: And the amount of money that you stand to lose on the off chance that it doesn't work is biggie. Biggie, basically everything.

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Kayla: Yeah.

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Chris: Right? And like, yeah, it's weird to get ten or 20 tails in a row. It's definitely out of the ordinary, but with the nature of probability it will happen sometime.

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Kayla: It's like that experience every kid has when you're taking a standardized test and all of a sudden you hit a point in the test where you've got like ten c answers in a row and you're like, there's no way there could be ten c answers in a row. There's something wrong here. I have to go back. I have to at least change a couple of them. And you end up doing something irrational. Because the thing itself is irrational.

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Chris: Yeah. Actually it's well known that if you ask people to write a list of random numbers, or even if you just ask people to say, write out a list of 50 coin flips, just write out ht. Ht. Ht. Whatever and make it random. People are really bad at doing that because when we think of random, we tend to think of like evenly distributed. But that's not what random is. Random is not evenly distributed. So like, you can always tell when it's a real random list of tales versus like a human generated one. Right, sorry. Not coin flips because the human one will never have more than like three or four in a row of something. Whereas like the real list is always gonna have some like unexpected streak of like seven tails or like eleven heads.

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Kayla: And isn't it that like regular people are actually really bad at determining which of those is the random one? Because when we see something that has a lot of repetition, we go, that's not random.

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Chris: Right. That's the converse of that is that like, somebody who doesn't know this little tidbit, looking at those two lists would not think that they would think the wrong list is the random one. Because sort of the weird base assumption that we have in our heads is.

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Kayla: That random doesn't mean it's going to repeat six times.

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Chris: Yeah. Random means evenly distributed. Yeah. Yeah. So this martingale style strategy, again, really small chance of failing big, a really high chance of getting a tiny little payout. So here's the other thing with that. If you're only winning small amounts, like, who cares, right? Like, nobody goes back to the party penthouse bragging about like their $3 and winnings at the roulette table. Yeah. Like, I spent 3 hours there doing like, the super strategy and I got, and I'm up $4. Woo. Like, you can only make it rain for like 3 seconds if you only have $3.

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Kayla: Right, right. I I'm gonna, can I make a prediction?

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Chris: Yeah.

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Kayla: Are you about to talk about what happens if your initial bet is not a dollar, is bigger than a dollar? Because I was wondering about that.

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Chris: That is exactly what I'm gonna start talking about. Yeah, I mean, the dollar example was, there's sort of two reasons for that example. One is that it's easier to kind of comprehend just, you know, round small numbers like that. But also what I was trying to illustrate was like, the vast gulf between the small earnings potential and the big wipeout potential. But yeah, you don't really want to, like, again, go back up to the penthouse with only $3 in your winnings. You want to go up there with like, a lot of money. Right?

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Kayla: So how else are you going to throw it on the bed and swim in money?

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Chris: I know if you only have $3, you can't swim in it like Scrooge McDuck. So you got to get what we call in the financial industry leverage tv.

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Kayla: Shows Tuesday nights on TNT.

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Chris: No, no, not the show you used to work on. Leverage in the financial industry is just a fancy word for borrowing. It's a fancy word for debt. But unlike most jargon, I actually really like the word leverage because it's actually, like, way more instructive than simply saying borrowing. Because when you borrow money to make a bet or purchase a stock, you amplify or you leverage everything that happens, win or lose. So let's go back to the roulette table. If you and I pool our money now, we can make a two dollar bet every time instead of a $1 bet. Pretty awesome, right? What's not to like? We doubled our potential earnings. Shit. Why don't we also take out like a big ass loan from the bank? Now we can make $5, $100 bets.

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Kayla: No, this is giving me anxiety.

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Chris: I mean, there's like, very little risk of loss, right? Like, we've already talked about how low the risk is. Like, yeah, there's, like, a tiny risk that we lose everything, and then we have $0 left to even. And then the bank. We have debt. We're in debt to the bank at that point. But. But that's a small. That's a small risk. That's a small risk. And besides, we'll be able to pay the bank back tonight after we get all these sweet winnings, right? So, like, in order for us to even, like, have anything worthwhile, in order for us to be able to pay for these, like, you know, $60 macadamia nuts in the mini fridge up in the penthouse, we pretty much have to borrow money from the bank, or else we just don't have enough.

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Chris: We're not making enough money each time to do that. And we'll just pay them back. We're protected by this fancy martingale system. We have math on our side. Kayla, you can't argue with math.

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Kayla: You know what? I can argue with math. Go back and look at all of my grades from high school math. I argued real long and real hard. I lost.

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Chris: In fact, if you really want to get into the headspace of some of these folks, I'll be talking about in a minute. Just pretend for a second, actually, that you can't lose. You know for a fact that if you run this strategy long enough, it will eventually win? Well, in that case, like, not only would you leverage, not only would you borrow money, you'd borrow a lot of it. Right? Like, who wants to make a $1 trade when you can make thousands or millions of the trade? There's no if. There's no risk. If you think that you cannot possibly lose, you'd take out a lot of money to leverage up those small bets, right?

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Kayla: Right.

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Chris: Why not? So this brings me to hedge funds.

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Kayla: I don't want to go to hedge funds.

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Chris: Sorry, Kayla. We have to go to hedge funds. That's what the episode's about.

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Kayla: Oh, man.

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Chris: Hedge funds. Of which long term capital management was one. And heretofore, I'll probably say LTCM at this point because it's fewer syllables. And also, that's what people call it. Hedge funds are big business. And in some cases, like, you've maybe heard of some of their managers. I don't know if you've ever heard the name of Ray Dalio. He's, like, a controversial figure that heads up the world's largest hedge fund, Bridgewater associates.

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Kayla: Bernie Madoff.

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Chris: Was that a hedge fund? No, that was more of a. Just like a raw scam. I don't know if he claimed that it was a hedge fund or what, but that was like a pure Ponzi scheme. There's like, definitively this is a scam. And then there's like, oopsie, we gambled bad. We're more in that ladder camp in this episode.

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Kayla: All I know is that R. Wallstreetbets says, boo. Down with the hedge fund guys, right?

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Chris: Probably. I think. Yes. Yes, they do. Yes. Actually, so for the Ray Dally thing, I almost switched the topic to Bridgewater associates from LTCM.

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Kayla: Oh, really?

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Chris: Because the company sounds like they're still around. I mean, they're the biggest hedge fund in the world right now, and they sound absolutely batshit. Or actually, you know what? Don't google them, because, like, maybe I might do those. I might do them for the bonus content. Bonus content for this episode on Patreon. Anyway, George Soros is also a hedge fund guy. Yeah, our buddy.

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Kayla: Oh, is that how he is so wealthy?

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Chris: That's how he's a billionaire for being a hedge fund.

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Kayla: And that's where my monthly protester checks.

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Chris: That's right. So thank you, hedge funds. But, like, you know, just because he's a lightning rod for anti semitic conspiracy vomit doesn't mean he isn't also a billionaire with all the problematicness of that kind of wealth concentration. But that's just to kind of give you an idea of like, yeah, you've heard. You've heard of some of these guys. Yes, but what is a hedge fund? Well, hedge funds like to hedge. They like to hedge their bets, so to speak. You've heard of hedging bets, right?

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Kayla: Yes. Is that where hedge fund comes from?

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Chris: That's what the name comes from, hedging your bets.

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Kayla: Or hedge fund, which comes from which.

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Chris: Oh, hedgehead. Hedging your bets came first. Hedging is sort of always meant, like, to kind of play both sides or whatever.

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Kayla: So a hedge fund comes from.

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Chris: Hedge fund comes from hedging your bets.

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Kayla: That's cute. Nice little linguistic tidbit.

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Chris: So they still trade stocks and bonds and other assets and stuff, but they use advanced trading strategies that aren't really available to your typical mutual fund that just like a normal mutual fund just buys, like, a portfolio of stocks and hopes it goes up. Right, right. But hedge funds don't just buy stocks. They short sell. They trade derivatives, like options. They trade futures contracts. So that's like the whole pork bellies and whatever. Corn sugar. I forget what futures contracts are out there, but they do that kind of stuff. They do all kinds of advanced trading strategies that are complex and sophisticated, much more so than simply buying and holding a stock.

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Chris: So if you want to picture the idea of how they, quote, unquote, hedge their bets, imagine that a fund manager buys some stock in, like, an entertainment company, and then they also, at the same time, short sell another stock in a different entertainment company. They think the first stock will go up, but if there's a downturn in the whole entertainment sector, they still make money from their short sell. So they kind of try to set up their trading strategy so that whether the market goes up or down, they still make money. Does that make sense?

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Kayla: It makes sense, and I just hope that, you know, that you are radicalizing me further.

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Chris: Just wait. Although I will say that betting that short selling is not always, like, short selling is sort of like a controversial thing in trading. Some people are like, oh, short selling means you're betting on things going down. That's horrible, you piece of shit.

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Kayla: Right?

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Chris: But at the same time, like, short sellers also provide liquidity to markets when things are going poorly.

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Kayla: Right?

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Chris: So liquidity means like, hey, if you have, if you own stock that's going down and you want to get rid of it before it goes down further, you need to have a buyer. You need to have somebody that's actually willing to buy it from you. And having willing buyers is essentially means liquidity. It means somebody, the more willing buyers you have for an asset that you own, the more liquid it is said to be. So that's something that short sellers do provide, even though they're sort of like, bad and evil, because they're betting on things going down. At the same time, they're also providing liquidity for people that are not interested in the risk of, like, holding onto a crashing stock.

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Kayla: Gotcha. Who wouldn't be interested in that?

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Chris: The other thing about hedge funds is that they are, like, completely unregulated, deliberately. Regular mutual funds and traders are heavily regulated because normal, like the, you know, Joe investor can invest in a regular mutual fund. Right? But hedge funds are.

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Kayla: Is that a real guy?

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Chris: Yeah, Joe investor is a real guy. Yeah, he invests a lot of money. Hedge funds, though, are not regulated. Now, part of the thinking here is that hedge funds, they tend to have very large minimum investment requirements. And also, you can't just buy and sell shares of them on the market like you can with mutual funds. Like, if you want to log on to, like, ally invest or TD Ameritrade or something right now. You could totally just like go buy shares of any of one of hundreds or thousands of different mutual funds that are out there. They trade on the market just like everything else. You can just go in, click a button and buy some, like spy or something. You can buy some mutual funds really easily, but you won't find any hedge funds in the open market like that.

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Chris: If you want to invest in one of those, it's like a much more deliberate, detailed and involved process that's really only available to, like, elite investors and institutions. On top of that, as I mentioned, hedge funds have a minimum investment requirement, and that can be anywhere as low as like $100,000.

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Kayla: Oh, just that.

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Chris: Up to like multiple millions of dollars. And again, this is minimum investment.

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Kayla: Oh, no.

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Chris: So if you want a piece of the action, then you have to actually pony up quite a bit of money upfront, which pretty much limits investors and hedge funds to, like, institutional investors. So that means like other banks, other, you know, investment banks, for example, and very wealthy people. All of this means that regulators basically say like, okay, if you get into a hedge fund, you must know what you're doing. So we don't need to protect you. Enter at your own risk. So that's why they part of why they don't regulate. There's a big problem with this philosophy, though, which we'll see later, and that's that the financial industry is a tightly linked web of actors. And nothing anybody does in a financial market, even in markets like across the ocean, happens in a vacuum.

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Chris: Everything kind of affects everything else, but we'll get to that anyway. So if mutual funds can be thought of like, I don't know, like the, it's like a broker that your parents have, just some nice old man that pushes his glasses up on his nose and reads the stock quotes in the Sunday paper, then hedge funds are like the cocaine addled wolves of Wall street, okay? They get into this shit in order to one. So they want to beat the market, right? They want to earn a higher rate of return than average. And as I mentioned before, they also want to avoid the risk of downturn, in theory, the reason hedge funds are hedging what they're doing, and they actively trade on these crazy strategies so that even if the market does go down, they still make money regardless. What's that, you ask?

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Chris: How is that possible that they make money regardless of the way the market goes?

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Kayla: How is it possible that they make money regardless of the way the market goes?

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Chris: Oh, Kayla, I'm so glad you asked. There are many strategies that you can use to make money whether the market goes up or down. We already talked about the idea of just like the simple idea of I'm going to buy one stock and then in the same industry I'm going to short sell another stock so that either way I make money. Okay, let's talk about another particular strategy for, you know, reasons. So have you heard of bonds? You know what bonds are?

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Kayla: I've heard of bonds. I don't know what they are.

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Chris: Okay. Bonds are just debt. They're basically just debt that a company or a city or a country or whatever issues. And then once they issue those bonds, like, let's say you buy a bond from a company, okay? Right? You can then sell that bond to somebody else, to me, right? So you can sell it on the secondary market, okay? Right. That's not something you can normally do with debt, but with bonds, you can do that, okay? Right. So, like, hi, I'm cult or just weird Inc. I need $100,000 to build a hot yoga studio where I can recruit and brainwash people. So I go out to the bond market and I issue 1000 bonds for $100 each. And now I've got $100,000 and blah, blah. It's debt, of course.

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Chris: So all those bonds have a little bit of interest, of course, that I have to pay to whoever owns them. Then the folks buy up my bonds. I have my money. I can build my hot yoga studio. Now all these bond owners have these little slips of paper that say I owe them $100 plus interest, which is neat for them. And then on top of that, they can sell these bonds to other people if they want to. Does that make sense?

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Kayla: Yes, that makes sense.

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Chris: Okay, so that's bonds in a nutshell. The smallest nutshell I can possibly get them into. So the thing about bonds is that they're like much more stable than stocks, right? Like, you're not going to make like a ton of money on bonds. They're, they're pretty safe, but you're also not going to, like, lose a ton of money on bonds. Like, stock prices are affected by, like, all kinds of different factors, right? Like economic factors, market conditions. The company itself has a million different things that can affect its stock growth. Bonds, on the other hand, the prices do change, but not by much because they're just debt. And all they say is like, hey, this company eventually owes you $100 back with interest, right? So there's like, there's not much. There's fewer things that can affect the price of a bond.

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Chris: Like, I'm not going to be willing to pay you much more than like a $100 for your hundred dollar bond, right? So on top of that, if you're talking about something like a government issued bond instead of like a corporate bond, it's even more stable because the thing that makes bonds risky at all is like, can the company actually pay back this debt? Like, will the company go out of business? Or is there some other reason that it's not going to be able to pay this back? So that's why government bonds tend to be much more stable, because the government has outlasted most companies in the world. No matter which government it is, like, it's probably going to be around. It's got the ability to raise taxes to pay back their government bonds, so they're considered very safe.

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Chris: So if you're a smart cookie and you pay attention to all these different types of bonds out there, government bonds, corporate bonds, municipal bonds with different interest rates and different maturity dates. So, like, some bonds have to be paid back in one year. Some bonds, you get paid back in like ten years or whatever. And because you're a smart cookie, you notice there are two particular bonds out there on the market that always behave in almost the exact same way. When one of these bonds moves up two cent, the other one also moves up two cent. When the other one's price moves down $0.04, this one also moves down $0.04, more or less like clockwork. Because remember, bond prices are pretty stable.

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Chris: So, like, if you find something where this is like, they're kind of always moving in concert, you can be like, okay, this is always going to happen. This is always going to move in the same way. So you, the smart cookie, might say, aha, these bond prices move together. If they're ever closer together or farther apart than they quote unquote, should be, maybe I can take advantage of that and make some money. I can buy the one that's too cheap and short, the one that's too expensive, until they come back into their quote unquote correct price spread. So this is what's called a price spread is when there's like a particular difference between the price of one thing or another, that's called a spread.

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Kayla: Okay?

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Chris: And because bonds are so stable, there's lots of bond types out there that can, like, move with each other and pretty synchronous concert. And if they ever move apart or too close, then you can act on that information until they go back to what their quote unquote, historically, their normal price spread is okay. Does that make sense so far? So whenever you have two things that historically move together in price. So, like, let's say a Big Mac is always $1 more expensive than a whopper. If a Big Mac is $4, a whopper will be $3. If the prices go up, a Big Mac will still be $1 more expensive than a whopper. If prices go down, a Big Mac will still be $1 more expensive than a whopper.

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Chris: So no matter which way the market goes, whether it goes up or down, the price spread is something you can take advantage of. So that's kind of the answer to how do these, at least this certain hedge fund that I'm about to talk about, how do they make money? No matter whether the market goes up or down, the price spread doesn't care whether the market goes up or down. It just cares about the spread between these two things. And if you go over to one town and big Macs are $2 more expensive than whoppers, you can take advantage of that. Sell big Macs where they're overpriced relative to whoppers and make money. This type of strategy is called arbitrage, and it involves much more than just bond price spreads. But bond price spreads are the bread and butter of. Get it? Butter spreads.

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Kayla: Get out of here.

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Chris: Anyway. Bond price spreads were the specialty of a company that we mentioned at the top of the show called long term capital management. As long as LTCM was correctly tracking and pricing different pairs of bonds that historically moved in tandem on their price, just like with the Big Mac and whoppers, it doesn't matter whether they're going up or down. They're always a dollar different.

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Kayla: Right?

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Chris: It doesn't matter if those bonds get more expensive or cheaper. All that matters is whether the price gap between them has widened or shrunk more than it should. As long as that is their strategy, they don't care if the market goes up or down. And this is one way hedge funds attempt to fulfill the promise that they can return money to their investors and clients, regardless of market conditions.

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Kayla: It's one way to hedge.

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Chris: That's exactly right. Now, your next question might be, okay, but how do you know that these bonds are always going to have their prices linked that way?

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Kayla: How do you know these bonds are always going to have their prices linked that way?

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Chris: How do you know when the spread is bigger than it's supposed to be, quote unquote, what counts as supposed to? How do you know it's going to move back to its, quote unquote natural spread. Well, Kayla, this is why LTCM makes the big bucks, because this is not actually necessarily an I easy problem to solve. You need only the most genius of geniuses with mathematical modeling that just can't fail. And that's exactly what LTCM was founded on. The year was 1994. The Houston Rockets had won the NBA Finals against my Orlando magic, breaking my little 13 year old heart.

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Kayla: Sorry.

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Chris: And not even 1990. Four's biggest films, Forrest Gump, the Lion King, nor Shawshank redemption, could make me feel better. The top song of the year was boys to men's I'll make love to you. And the George foreman Grill started appearing on kitchen counters. And gas only cost.

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Kayla: Please don't.

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Chris: $1.11 per gallon.

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Kayla: Okay.

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Chris: Also in 1994, a man by the name of John Meriwether started a small little company called long Term Capital Management. Mister Merryweather, was he a robot?

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Kayla: Like, where did this name.

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Chris: God, John Merriweather. I know. Isn't it a great name?

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Kayla: No, his name of his company. Yes, it's a great name, but I mean.

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Chris: Oh, yeah, company name again, part of it. I think I mentioned this later, but, like, part of what LTCM was trying to do was, like, give off this aura of, like, being above the fray of being, like, this intellectual, like, long term capital management and what. Well, actually, we do get to that in just a second. So part of why it's so boring is, like, on purpose.

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Kayla: Gotcha.

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Chris: So Mister Merriweather was a star performer at Solomon Brothers. He headed up its most profitable division, specializing in bond arbitrage trading. The thing I just described, in the early 1990s, he was let go for an ethics violation, but it was one of his subordinates, and from what I can tell, it was, like, a pretty technical violation. It wasn't anything, like, really crazy, like.

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Kayla: Steal money from orphans or something.

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Chris: Yeah, it wasn't like stealing money from orphans. It was like one of his team members had, like, you know, broken, like, rule 47, subsection a by, like, trading $11,000 when he was supposed to only trade, like, ten or something. It was something like that. So anyway. But he was let go from Solomon. So he started his own hedge fund, the aforementioned LTCM, and was joined by a bunch of his former team at Solomon. They being pretty loyal to Mister Merriweather and also probably pretty jazzed to make money with the former head of Solomon's most profitable division. And by the way, most profitable division is, like, an understatement. Some estimates put Meriwether's bond group at, like, over 80% of Solomon's total business when it operated.

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Kayla: And they let him go over a tiny ethics violation. My God.

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Chris: I know. I know. Business Insider described Meriwether's bond trading group as such, saying it, quote, became known within Solomon for its clicky culture, its confidence, and its substantial profits, end quote. And there were some true superstar heavyweights of the financial industry that came over from his team, and they joined other superstar heavyweights. The eleven founding partners of LTCM had among them, seven PhDs, an MBA, several professors of economics, a former vice chair of the Fed. So, vice chair means second in command to the head of the Fed at the time, Alan Greenspan. And all of these guys had either had degrees from and or were currently teaching at MIT, Harvard, the University of Chicago and Stanford, as well as others.

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Kayla: Over educated.

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Chris: Yeah. Over educated, elitist scum. Scumbags. Yeah. But, like, the resume is insane.

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Kayla: Yeah.

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Chris: Oh, sorry. I also forgot. Among the founding partners included two future Nobel laureates.

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Kayla: Oh, jeez.

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Chris: In the field of economics, a man by the name of Robert Merton and Byron Scholes. Who. That name may ring a bell if you have ever heard of something called the black skulls equation.

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Kayla: I have not.

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Chris: And in fact, this mathematical model, the black Scholes equation, was what they ended up winning the Nobel Prize for. If you haven't heard of the black skulls equation, then let me put it this way. In 2013, mathematician and science author Ian Stewart wrote a book called the 17 equations that changed the course of history. And it's got the usual suspects on there, like, you know, the pythagorean theorem, the bell curve, normal distribution, Schrodinger's wave equation for quantum mechanics.

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Kayla: Heard of all of these?

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Chris: E equals MC squared.

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Kayla: That's a biggie.

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Chris: And alongside all those guys, you've also got the black Scholes equation.

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Kayla: Gotcha.

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Chris: Co created byron Scholes, partner at LTCM, and by God. They use this equation in two different ways. The first way is that this equation essentially is a way to use advanced mathematics to predict prices of certain kinds of assets, such as the bonds I mentioned earlier. This equation allowed LTCM to produce models that allowed them to predict the, quote, unquote correct price spreads for these bonds. And again, when the real world spread, deviated from that, LTCM stepped in, made some trades, waited for the price spread to return to what the model predicted. Bada bing, you make some money.

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Kayla: That sounds a little too good to be true.

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Chris: Yeah, I know. But this is the first thing the black skulls equation did for them. The second thing was like, it was much more subtle. But maybe more important is that it was like fucking like magic runes, man.

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Kayla: That's what I mean. This is like, this sounds like a. Man. This sounds like, buy these worms and we'll buy them back.

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Chris: Yeah, well, so it's. It's not that. The thing is, the equation is it's not like a bullshit thing. It's not like a scam. It's not like worms where it's like, oh, no, those don't exist. It's not that. It's that having this formula allowed LTCM to basically say, like, well, we're not making trades on foolish things like emotion or intuition.

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Kayla: Gotcha.

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Chris: Or even analyzing a company's fundamentals like a rube. Like, we're making trades based on our top secret formula. And the top secret formula was being applied by a cadre of PhDs and Nobel laureates. So you can't argue with the math, Kayla.

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Kayla: Again, I can, but I'd be wrong. Yes, this.

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Chris: Nobody other than you can argue with the math, Kayla. And speaking of top secret, LTCM kept everything they did extremely obfuscated as well. They were notoriously non transparent. And after all, why should they disclose anything that might let other folks copy their methods? Why should they disclose anything to you, a client or an investor, when they are going to be making you so much money? Trust them. They've got this, you big bank. You don't need to know what we're doing. We have the magic formula. And look at all these PhDs. We're the experts, not you. Trust us. We have the formula and the strategy, and there's no way you're peeking over this wall and fort its worth. The walls of LTCM were headquartered in the Nice, quiet town of Greenwich, Connecticut, way above the fray from noisy, greedy Wall street in Manhattan.

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Chris: Like LTCM was a hedge fund. But it kind of wasnt really viewed that way. It was viewed as like this financial technology company ahead of the curve, making money, not because theyre dirty traders, but because they are just the smartest guys in economics, which, according to what I read, they definitely themselves believed they were the smartest guys in economics, maybe even like the whole world. Like they very much thought that they were just the smartest. They were very arrogant.

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Kayla: They've got all dismissive, they've got all those credentials that are upheld as being the, like, this is the be all and end all of intelligence, so.

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Chris: Right, and we talked about, like, and.

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Kayla: They'Ve got a secret formula, right?

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Chris: And we talked about, like, the boringness of the name, right. All of that played into this sort of like very, like academic branding. Right, right. An aura of intellectual invincibility that brought in a lot of capital.

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Kayla: This sounds dangerous, though.

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Chris: Everyone wanted a piece of LTCM in the mid nineties, baby, and, well, it paid off, actually.

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Kayla: Oh, it was a happy story, happy ending. Everybody got rich and then the end.

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Chris: Everyone got rich and then nothing happened. The end.

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Kayla: Wow.

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Chris: This strategy I described earlier, using their supermath, piloted by super geniuses, to figure out which bonds had the price spreads that they were, like, out of whack, that whole strategy actually made them a lot of money once it got going.

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Kayla: Wow.

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Chris: In their first three years of existence, they achieved 21% returns, then 43% on their next year. And in their third year of existence, 41% returns on their investments, which are, if you're not familiar with this kind of stuff, crazy high percentages for a single year. Crazy high.

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Kayla: Wow.

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Chris: Okay, so, like, for reference, the stock market goes up as a whole, on average, like 10% per year. So just to put that in perspective, and then, like, even beating the market is like, oh, like 15%. I think I read that, like, other hedge funds during those years were averaging like 17%.

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Kayla: Geez.

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Chris: So 40 is like more than double like the other.

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Kayla: Like, yeah, that's.

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Chris: It's more than double the people that are supposed to beating the market, it's more than double that.

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Kayla: Jesus.

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Chris: So between the aloof super genius aura, the top secret Nobel prize winning math, and these crazy returns, literally everyone in finance wanted to get in on the LTCM action.

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Kayla: Yeah, this sounds too good to be true. It sounds like the best. Sounds like the Bee's knees.

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Chris: It was the bee's knees for a bit. Big banks like ubs, other funds, and investment banks like Goldman Sachs, all of Wall street, you name it. And again, LTCM was able to do it by using this formula to determine which bond prices were out of whack. Now, there's one thing I didn't really mention about this bond price strategy, but we did talk about when were talking about the martingale system, and that's the following. Bond prices, especially spreads between two bonds. Move very small. So small, like just the tiniest little movements. Fractions of a percent. In fact, one of the partners of LTCM likened their trading strategy to vacuuming up pennies. There's all these pennies lying around that nobody can see because they need our smart math and smart guys in order to see these invisible pennies.

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Chris: So we can just happily walk around vacuuming up invisible pennies. While everyone else is running around doing dumb, normal trading stuff.

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Kayla: Idiots.

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Chris: The only thing. Yeah, I mean, that's. They probably would have thought that exact thing.

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Kayla: Losers.

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Chris: The only thing is we just need to borrow a lot of money because we need to get a big enough vacuum to make all this worth it. Because we're vacuuming up pennies. We gotta have to vacuum up a lot of them to make the millions of dollars that we're promising, right. To get to 40% return on the type of money that they were investing. That is a lot of pennies that you gotta vacuum up. So remember back to the top of the episode when were talking about like placing $1 bets at the roulette table with our special strategy, and we're like, hey, they're like kind of sure bets. They're just very small bets. So we got to borrow money and leverage the amount we can win. Right. Remember that?

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Kayla: Yes.

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Chris: That's kind of what's happening here with LTCM. They have this sure bet, they have this bond price strategy. That's a sure bet that they're making. It's just got a really small payout. So they have to borrow money for the biggest vacuum cleaner possible. And they borrowed a lot of money to the point where they are like, basically famous now for how highly leveraged they were. Okay, at one point in 1998, they were leveraged at a ratio of 25 to one.

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Kayla: That sounds like a lot.

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Chris: Yeah. What that basically means is that they had $25 of debt for every $1 of cash. Now, I know this ratio might not sound like much to the student debt generation, but it should sound like a lot when your business is making trades. Because the thing about leverage is that it works both ways. As we said before, it helps you earn a lot more money when the trade goes your way, but when it doesn't go your way, you are already owing more money than you actually have. And then that problem just gets worse and worse. And that's when things really start going wrong. Okay, so this leverage strategy makes things so risky that LTCM actually did have its skeptics even starting out.

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Chris: So, I know I said they had this, like, aura of invincibility that attracted a lot of investors, which it did, but it actually had its skeptics too. Despite the initial wild success, a lot of industry heavyweights actually turned down the opportunity to get in on the LTCM action early on because they were worried about that exact leverage risk, including one Mister Warren Buffett.

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Kayla: The real smarties in the room.

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Chris: Well, I mean, that's the thing, right. It's like. It's hard to tell. Like, it's. In retrospect, he's the smarty, and the other ones are the dummies. But, I mean, again, we're talking to PhD economists and Nobel laureates. One LTCM skeptic famously said, yeah, you guys are vacuuming up pennies in front of a moving bulldozer.

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Kayla: Ooh.

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Chris: In other words, yeah, like, you guys have the magic vacuum and you know how to get the pennies. But one wrong move. Well, actually, I mean, that's not something LTCM would ever do, Kayla. They don't make wrong moves.

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Kayla: No wrong moves.

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Chris: But one unlucky happening, though.

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Kayla: Oh.

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Chris: One unforeseen event, one black swan, and you get rolled over by the steamroller, you lose everything. But, you know, the LTCM guys, they were too smart for this. And besides, the math knows now, I wanted. There's some. There's a subtle difference here between what I was talking about with, like, the casino martingale strategy and what LTCM was doing. The analogy that I'm trying to get across is the idea that, of, like, it's the similarity between the two strategies where you have this really small potential reward that is pretty likely to happen, and then you have this really unlikely thing that might just destroy you.

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Kayla: Right.

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Chris: However, in the casino, that's guaranteed to basically happen because the odds are stacked against you. It's not quite a 50% chance to win. It's like a. It's like, a little bit smaller than 50% chance to win at roulette. So eventually, that's stacked against you. In the case of, like, trading. And even, I think in LTCM's case, it's not stacked against you. It's actually stacked for you. Like, stocks go up, and their formula was actually good. So the thing here is that even when you are correct, even when you are the casino, you can still get yourself destroyed if you leverage yourself enough and you don't take into account, you know, these sort of, like, unforeseen risks, right? The unknown. Unknowns. And so the people that were skeptics of LTCM, that's what they were skeptical of. They were like, yeah, you guys are right.

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Chris: You know, this is a great model that does predict bond prices and whatever, but with the amount that you're leveraged, if something goes wrong, the bulldozer runs you over.

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Kayla: Right? They're not taking into account access of God. It's like, yes, the math keeps our house standing up, and we're totally safe and fine, but it's not. There's no protection for. If a tornado.

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Chris: Right. That's the problem with being over leveraged. Yeah, it's like you. You've got a. You're like, yeah, I'm just filling my house with lighter fluid. It's. It's totally fine as long as, like, a thing doesn't happen to blow it up.

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Kayla: Yeah, we just don't bring matches around.

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Chris: Yeah, we just don't bring matches and it's fine. But like, oops, little Timmy from next door brought a match by accident or oops, like, somebody light a cigarette.

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Kayla: Right.

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Chris: So that's. That's the difference between this and gambling. Like the, like the Martingale system, like you were, you're guaranteed to lose. It's actually the negative expected value with this. It's a positive expected value. But the risk, when you leverage that much is great enough that it can still wipe you out even when you're correct. And again, the only way you're making money with these tiny little price movements is by leveraging a whole lot. Anyway, in 1997, just as LTCM was riding high, there was indeed a financial crisis in the asian markets.

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Kayla: Oh, no.

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Chris: They really didn't quite figure into their calculations. But I mean, actually the math knows, though, so completely counterintuitively, they saw this crisis actually as somewhat of a good thing and doubled down on a lot of their bets. Okay, a good thing because their worldview was that market disruptions are temporary. So you can always just bet on conditions returning to normal and make money that way. Right. Like their whole thing was bonding innocent 90%. Exactly. Right. Well, yeah, that's. But that's part of the problem, right. Is that like, the years that LTCM was riding high were stable years, right. Particularly financially, there was a lot of, like, economic growth. Energy prices were low, right. So when you base your. Your strategy on a period of stability and then a period of instability shows up and you're like, well, it's going to get back to stable.

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Chris: So all we have to do is double down our bet, and then when it does, we'll make a ton of money. That's what the math tells us. And actually, that's literally what the math was telling them. The math was saying, you need to double down your bets here, because the math was built on this presumption, which we will get to. You know, it's just like Michael Scott would say, kayla, like while driving into a lake, he would say, the machine knows. Right? The machine knows. We gotta keep going.

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Kayla: The math knows. It wouldn't tell us to drive into a lake if there wasn't a reason.

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Chris: That's right. And as I mentioned before, the kicker is that from a certain point of view, the LTCM guys were right. The math was correct. Markets do eventually stabilize after a disruption. But as the quote goes that we said before, markets can stay irrational longer than you can stay solvent. I can roll more tails than I have money to fund. Keep rolling tails.

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Kayla: Right.

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Chris: The same thing is even true for large hedge fund companies like LTCM. They can be correct, but they may not be able to stay in their position long enough to not go bankrupt. And with the amount of leverage that LTCM was running at, and again, remember, that's debt being astronomical as it was, it made it astronomically more difficult to stay solvent long enough for their correctness to even pay off. This wasn't the only problem, though. The rest of Wall street had also had several years to kind of get wise to LTCMs bond arbitrage trading strategy.

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Kayla: Oh, they found the secret ingredients.

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Chris: They didn't find the secret ingredients, but they don't have to. You don't need to have the magic formula when you're simply able to just copy someone's trading strategy. Like, you don't need to know why. Exactly. So with a lot of other Wall street funds and traders running the same strategy now as LTCM, and copying them became harder and harder for them to make money with it. And that was their real bread and butter.

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Kayla: Right?

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Chris: And as an aside here, I'll say, like, this is a big part of why it's really difficult to use math and data to trade stocks is because the market is chaotic. And when I mean mathematically chaotic, right? It's not the same people trading using the same strategies day after day, ad infinitum, there's a feedback system at play, even if and when a winning strategy is ever discovered. Like this bond arbitrage thing, right? It has a limited lifespan until it gets copied, and then that, well, effectively dries up. Rinse, repeat, year after year, as long as trading stocks is a thing. That's how this works. In fact, sometimes folks like to divide investors into two different camps. So there's fundamental analysis and technical analysis.

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Chris: Fundamental analysis means you're looking at a company's fundamental attributes when you're trying to decide whether to buy or sell its stock, right? What sort of long term, defensible advantages do they have as a company? Do they have, like, a key patent, good leadership, good brand ip of some sort? Are they in a good industry? Etcetera, technical analysis, means you're looking at nothing but the charts. You literally do not care about any aspect of the company at all, only the charts. And you're, like, invoking, like, pseudo mathematical jargon. And I think you can tell I'm, like, pretty biased against technical analysis, but, like, I. I thought about even doing technical analysis as its own. Like, is this a cult on the show? Because it's like a whole body of not. It's a whole way of trading stocks.

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Chris: And I really think that it's just exactly like reading chicken entrails, except, like, with a false sense of confidence, because you have charts.

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Kayla: You got the math on your side.

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Chris: But anyway, to be fair, LTCM wasn't really doing technical analysis. They weren't, like, doing chart stuff. They had their magic formula. But again, competitors didn't need to have their own Ubermensch economists with fancy formulas. They just had to copy LTCM at what they did. And that made it harder for them to make the profits that their clients and investors demanded. And not just demanded, but were used to. LTCM had been doing great, beyond great. The returns it had given its investors over the last few years were unrealistically high. It was the darling of Wall street, and some of the most powerful people and institutions in the world were into them for a lot of money. So the pressure to continue to churn out those same profit levels was overwhelming, immense, gargantuan pressure.

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Kayla: This is the kind of stress that I hope to never, ever feel in my entirety of existence.

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Chris: Well, some people like it.

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Kayla: Do they?

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Chris: I don't know.

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Kayla: Or do they need therapy?

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Chris: Some people are addicted to it, probably, yeah. So LTCM did what they felt like they had to do and started getting into other kinds of trading strategies that not only were riskier than this bond arbitrage, but they also had far less expertise in. There was another problem in all this, and I've got some bad news, Kayla. I don't really know how to say this. See, there was a problem with the magic formula itself.

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Kayla: Oh, no, the one that was a Nobel Prize winning formula.

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Chris: Yeah.

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Kayla: Oh.

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Chris: Yeah. The formula itself was very good. Totally deserves a Nobel prize. It's like a really interesting and advanced way of looking at pricing certain classes of assets. It totally deserves it from an economic standpoint. And the data used, I mean, it was good data. A lot of good data. Yeah. But there's just this one little thing. See, the data that was used to build these models that were based off of this formula didn't actually go that far back in time. Which means that the models they were using were built on a foundation of data that didn't include things like, I don't know, like the Black Monday crash of 1987. Things that today.

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Kayla: Wait, things that had already happened.

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Chris: Yeah. It only had a small subset of data. It was only a small window of data. Right. It was only like.

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Kayla: Well, you think that the black Monday crash would be an important thing.

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Chris: Well, I know, but it just.

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Kayla: They weren't thinking like they killed themselves cause of that. It was a big deal.

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Chris: Well, yeah, okay, but. So picture it this way. It's not that they're like, when you build models off of this formula, you're not building them based on, like, let's cherry pick certain events. You're just saying, like, okay, I don't know, let's take everything from, like, 1989 to 1993 and plug that in and build a model based on that. And if you're not. If your time frame isn't long enough to include things like that, right, then the model is going to be built on this false assumption that outlier events are probably not going to happen. Right. Even if you don't intend for that. If the. If we talked about this earlier, right, like, the period during which LTCM was making a lot of money was a relatively stable period.

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Chris: If you base your models off of only that period and you don't widen the data, widen the scope enough to include some of these, like, black swan events, then it's not going to take that into account. And. Oopsie daisy. Oh. In a black swan event, by the way, for those that don't know, this basically just means an event that was wildly unpredictable before it actually happened and perhaps even, like, kind of impossible to predict. So things like Black Monday, nobody saw that coming. That was a market crash that was both severe and unpredictable.

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Kayla: We still don't really know why it happened. Right.

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Chris: I. I'm not sure about that, but I think I'd have to look that up. But I think that tracks.

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Kayla: But it's like, we don't really know what.

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Chris: Yeah, I think that tracks. Like, and that's the thing about the chaoticness of the market, is that sometimes there's just, like, it's gonna go down. Sometimes there's just insane price swings. Wait, why did that happen?

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01:05:11,116 --> 01:05:11,658
Kayla: Right.

368
01:05:11,804 --> 01:05:30,102
Chris: Another example of a black swan event would be the asian financial crisis in 1997 that we talked about, or the next crisis up on the plate for LTCM. And this is actually a perfect example of a black swan. The Russian Federation defaulted on its government issued bonds.

369
01:05:30,206 --> 01:05:30,982
Kayla: Oh.

370
01:05:31,086 --> 01:05:40,998
Chris: Now, this may not sound that crazy to you, but here's how much of a black swan this was at the time. It was the first time something like that happened in the long history of countries raising money by using bonds.

371
01:05:41,054 --> 01:05:41,746
Kayla: Oh, wow.

372
01:05:41,878 --> 01:06:21,622
Chris: In fact, it was thought to be impossible, because, after all, a country could always just, like, issue more money, right? Print more money, basically to pay off their debts. And doing that kind of thing gives you all kinds of fucked up inflation. Like, that's kind of what happened after World War One, right? Germany owed a shit ton of money and reparations, and so they solved that by just, like, basically printing money, which made all of their value bread, all cost $100 exactly like their money. Their money became worthless because of how much of it they had to print to pay off their debts. But historically, that's what had been done. So nobody thought that a country would actually default on their debt rather than just printing money to pay off their debt until it happened. So, a true black swan event.

373
01:06:21,806 --> 01:07:07,124
Chris: And so in this particular case, with. With the Russian Federation defaulting on all their bonds, it sent financial markets around the globe reeling. Terror gripped investors who had their whole notion of what was possible. All of their figuring out of risk on everything they were doing, all of that was all swept away. And in place of it was fear. And the worldwide disruption was pretty huge. And as I just mentioned, the problem with LTCM's magic formula is that it wasn't trained on data that included events like these. So it was essentially blind to this potential problem. Finally, there was a size problem here, too. LTCM had trading positions open that were so large it was impossible for them to exit without just tanking the price.

374
01:07:07,212 --> 01:07:08,404
Kayla: Oh, that sounds bad.

375
01:07:08,492 --> 01:07:41,908
Chris: It's not good. It just compounds all this like gasoline on top of all the lighter fluid. So, like, for example, Kayla, if you or I own a few shares of a stock, there's no problem for us to sell it, right? We're just going to go sell it. We're going to get what's called the market price, which is its current price, when we sell them, because it's just this. We're just one little tiny drop of water in the pond. But when you start talking about owning, like, billions of dollars worth of shares and something, there ain't no way you can offload all of that without tanking the price. Massive sell offs of anything, like stocks or anything else lower the price of that thing.

376
01:07:42,044 --> 01:08:03,310
Chris: It's like if someone tries to unload, like, ten truckloads of corn at a farmer's market, you better believe those ears of corn are going to be cheap. So some of LTCM's stock positions were so huge that they were like, trying to offload ten trucks of corn at a farmer's market. So they had no good way to get out of these positions, even as the price was dropping all by itself. Any questions so far?

377
01:08:03,470 --> 01:08:06,718
Kayla: I just want to know. I want to know how this all shook out. I want to know what happened.

378
01:08:06,894 --> 01:08:49,716
Chris: Well, we are almost there, so let's tally up these problems. Just to summarize. LTCM, they're flying high on their bond arbitrage strategy as long as the markets were stable. But eventually, competitors started copying them, making it harder and harder for them to make money that way, pushing them into other areas that they have less experience in. The second, LTCM's mathematical models were trained on data that were essentially blind to unlikely but really bad events. And one of these events actually happened. Financial crisis in Asia. Next, LTCM was over reliant on their models, which told them to double down during this crisis rather than sell and be safe. Rather than.

379
01:08:49,747 --> 01:08:54,020
Kayla: They trusted the gps when it said, turn right, and they turn right into the lake.

380
01:08:54,100 --> 01:09:17,229
Chris: They trusted the machine. The machine knows. And they drove straight into the lake. And then an additional crisis happened, totally unpredictable, to experts. Russia defaulted on their national debt and it sent global financial markets spiraling. And then finally, LTCM couldn't even sell their investment safely because their positions were so big that selling would tank the price even further.

381
01:09:17,930 --> 01:09:25,194
Kayla: Kind of sounds like maybe all that Harvard and Stanford and MIT on those.

382
01:09:25,242 --> 01:09:30,761
Chris: PhDs over educated elites couldn't save you.

383
01:09:30,786 --> 01:09:32,870
Kayla: From a big downfall, could it?

384
01:09:36,130 --> 01:10:01,890
Chris: I think the problem is that when you have been told how genius you are for as long as they have, and they had as much success as they had, and they really were, like, economic mathematical geniuses. But the problem is that really can put some severe blinders onto you, not let you see some things that other people on the outside might see.

385
01:10:01,970 --> 01:10:07,202
Kayla: So the moral of the story is, tell your friends that they're dumb every once in a while, just to keep them humble.

386
01:10:07,386 --> 01:10:11,778
Chris: That's probably good for them. All right, so, given all this, you might imagine that when the house of.

387
01:10:11,794 --> 01:10:13,990
Kayla: Cards comes, don't call your friends dumb.

388
01:10:14,630 --> 01:10:16,654
Chris: Why not? I call my friends dumb all the time.

389
01:10:16,742 --> 01:10:20,262
Kayla: Be nice to your friends. Call anybody who comes out of Harvard.

390
01:10:20,366 --> 01:10:26,254
Chris: Is this why I don't have any friends? Yes. Oh, okay. Anyway, this house of cards, you might guess, it came down pretty hard.

391
01:10:26,302 --> 01:10:28,150
Kayla: Did it crumble? Did it tumble?

392
01:10:28,230 --> 01:10:42,786
Chris: It tumbled. It tumbled hard and fast. On August 21, 1998, in one single day, LTCM lost $520 million. That's a lot of dollars for a single day.

393
01:10:42,858 --> 01:10:45,470
Kayla: That was only four years after they got started, right?

394
01:10:45,970 --> 01:10:46,538
Chris: Yeah.

395
01:10:46,634 --> 01:10:47,378
Kayla: Oh, no.

396
01:10:47,474 --> 01:10:57,066
Chris: They had three really good years, and then their fourth year was not good. One month after that, again, in one single day, lost another $500 million.

397
01:10:57,138 --> 01:10:59,426
Kayla: That's a billion dollars total so far.

398
01:10:59,498 --> 01:11:02,802
Chris: Huh. And that's just on those two days, so why.

399
01:11:02,866 --> 01:11:04,738
Kayla: Oh, my God. I can't even imagine what that would.

400
01:11:04,754 --> 01:11:05,866
Chris: Feel like, put together.

401
01:11:05,938 --> 01:11:10,902
Kayla: Wait, but just hold on. Just try and imagine what that would feel like.

402
01:11:11,046 --> 01:11:15,174
Chris: I wish to not do that. I don't want that anxiety that's like.

403
01:11:15,262 --> 01:11:16,318
Kayla: Oh, my lord.

404
01:11:16,414 --> 01:11:41,856
Chris: That's one of those extremes of human experience that Dan Carlin talks about. Like, if you wanted to really be extreme, like the battle of cannae or LTCM in August of 1998. No, thanks. I don't know how that would feel. Yeah. I think I would just. I would either feel, like, sick to my stomach and, like, I'd probably, like, be vomiting and, like, shaking.

405
01:11:41,968 --> 01:11:42,696
Kayla: Right.

406
01:11:42,888 --> 01:11:46,632
Chris: Or I would just. I would be like. You know how sometimes you get really stressed?

407
01:11:46,656 --> 01:11:50,232
Kayla: You're just, like, totally numb out. Everything's fine. Yeah. Like, surreal.

408
01:11:50,336 --> 01:11:53,952
Chris: Hey, we lost $500 million anyway. I'm just gonna go for a quick walk.

409
01:11:54,016 --> 01:11:54,680
Kayla: Yeah.

410
01:11:54,840 --> 01:11:56,800
Chris: Like, I would actually. I'd probably be like that.

411
01:11:56,840 --> 01:11:57,460
Kayla: Yeah.

412
01:11:58,400 --> 01:12:19,320
Chris: But, yeah. Over a billion dollars over the course. And it wasn't two consecutive days, but it was only over the course of two days. Oopsie daisy. Now, after all the dust had settled and LTCM was getting audited, it was found that their total losses summed up to $4.6 billion.

413
01:12:20,220 --> 01:12:23,560
Kayla: That's a. That's a. That's a. That's a big chunk of change.

414
01:12:24,340 --> 01:12:49,004
Chris: As this was all happening, celebrity investor Warren Buffett, we mentioned him earlier. He was a skeptic at first and ended up being right, but at this point, he made, like, this fucking, like, Giga Chad play, so listen to this shit. His firm, Berkshire Hathaway, got together with Goldman Sachs and AIG, and they put together an offer to buy out LTCM from its partners for $250 million.

415
01:12:49,092 --> 01:12:49,812
Kayla: Okay.

416
01:12:49,956 --> 01:13:01,016
Chris: Which was probably worth. But also, like, insanely low, given that just like, a few months earlier, right. It was. The company was worth, like, $4.7 billion.

417
01:13:01,088 --> 01:13:01,512
Kayla: Right.

418
01:13:01,616 --> 01:13:33,690
Chris: So that's like an extreme low ball offer, but, like, if you're being, like, completely rational, you're like, man, it's probably worth that at this point, but it's so low ball. It's like the type offer that makes you grind your teeth. Like, you know it's right and safe, but if you'd only sold at the peak. It's so unfair to. It's just the type of thing that, like, takes you a while to sit and really think about. Right? Except when Warren Buffett sent the deal to LTCM's managing partners, he gave them less than 1 hour to accept it or it would expire.

419
01:13:34,670 --> 01:13:39,438
Kayla: That's kind of cold. Geez. That's kind of cold.

420
01:13:39,534 --> 01:13:41,530
Chris: Yeah, that's icy veins right there.

421
01:13:42,590 --> 01:13:45,590
Kayla: I kind of always thought that he was just a nice little man. Obviously, he's a bad. No.

422
01:13:45,670 --> 01:13:46,942
Chris: Do you know how much money he has?

423
01:13:47,006 --> 01:13:48,068
Kayla: Yeah, he's a bad guy.

424
01:13:48,174 --> 01:13:51,432
Chris: I mean, I don't know if he's bad, but he's definitely ruthless.

425
01:13:51,536 --> 01:13:52,144
Kayla: Yeah.

426
01:13:52,272 --> 01:14:05,720
Chris: Like, don't forget Kayla. Like, this is not an orphanage. That he's like, no, I know. This is, like, guys that were, like, maybe gonna tank the us economy, but, you know, certainly ruthless. Can you guess whether they took the deal or not?

427
01:14:05,800 --> 01:14:06,392
Kayla: Yes.

428
01:14:06,536 --> 01:14:07,896
Chris: They did not. It expired.

429
01:14:07,968 --> 01:14:08,780
Kayla: Oh, no.

430
01:14:09,200 --> 01:14:13,544
Chris: Because they just couldn't come to an agreement on it in that short amount of time.

431
01:14:13,592 --> 01:14:15,130
Kayla: I think they should have taken it.

432
01:14:15,280 --> 01:14:27,086
Chris: They probably should have, because things continued to get worse after that until you might remember some of this rhetoric from what would be a decade later in the 2008 financial crisis.

433
01:14:27,158 --> 01:14:28,102
Kayla: I remember that one.

434
01:14:28,206 --> 01:14:32,486
Chris: But LTCM was seen at the time as sort of, like, too big to be allowed to fail.

435
01:14:32,598 --> 01:14:34,726
Kayla: Oh, right, that thing.

436
01:14:34,878 --> 01:14:51,960
Chris: Tons of banks, investors, like all of Wall street, basically were into LTCM for lots and lots of money. So if they were allowed to crash all the way to zero, the worry was that they would bring down the rest of the financial industry with them, which could then bring down the rest of the economy with it.

437
01:14:52,260 --> 01:15:03,988
Kayla: I kind of feel like maybe we just shouldn't have this system if just all of a sudden, one day, a single company can tank the entire economy. It's like something seems a little broken there.

438
01:15:04,084 --> 01:15:23,618
Chris: Yeah, it's both all of a sudden, one day, and also, like, in retrospect, totally could have seen this coming. Like, once we can do the forensics on it's like, oh, yeah, this was gonna happen for sure. So this was somewhat unprecedented at the time, but the government actually stepped in to bail them out.

439
01:15:23,714 --> 01:15:24,346
Kayla: Cool.

440
01:15:24,498 --> 01:16:09,130
Chris: Now, this was slightly different than the 2008 bailouts. Those were literally paid for with taxpayer money. Right. Like the LTCM bailout. On the other hand, the government wasn't the one footing the bill. Rather, they organized a super team of banks to foot the bill, which is much more palatable to me. I don't know why weren't able to do that in 2008, but because get fucked numbers were probably too high. Yeah, and also get fucked. So in 1998, the Federal Reserve bank of New York got together a who's who of banks and investment banks. So this is like Goldman Sachs, JP Morgan, Merrill Lynch, Chase, et cetera. Like about a dozen household name banks you would recognize, like pretty much all of the names in the. Listen. To buy out LTCM for essentially pennies on the dollar. The terms were harsh but fair.

441
01:16:10,350 --> 01:16:27,294
Chris: Quoting Wikipedia here. Quote. In return for the bailout money, the participating banks got a 90% share in the fund and a promise that a supervisory board would be established. So basically, like, we own it. And also now we have like a, we want you to have chaperones.

442
01:16:27,462 --> 01:16:29,232
Kayla: That is understandable.

443
01:16:29,326 --> 01:16:35,012
Chris: The LTCM partners received a 10% stake still worth about $400 million.

444
01:16:35,116 --> 01:16:35,780
Kayla: Jeez.

445
01:16:35,900 --> 01:17:04,024
Chris: Which you might think, like, what? They got $400 million out of it? Like, that's not fair. But the quote continues. But this money was completely consumed by their debts. The partners once had $1.9 billion of their own money invested in LTCM, all of which was wiped out, end quote. Yeah. So LTCM's partners were so self enamored that they were getting high off their own supply.

446
01:17:04,152 --> 01:17:06,464
Kayla: Cool. Love it. Would love to do that.

447
01:17:06,592 --> 01:17:19,128
Chris: They were making a ton of money as partners in the hedge fund, doing hedge fund job. Like, you know, they're that, like their day job. Right, right. But they believed in their own abilities so much that they collectively had nearly $2 billion invested in their own firm.

448
01:17:19,224 --> 01:17:22,204
Kayla: I think that maybe they should not have done that.

449
01:17:22,332 --> 01:17:34,300
Chris: In retrospect, probably not. So in case, if you were wondering, like, whether you're, like, the classic question, scammers are true believers, right? In this case, definitely true believers.

450
01:17:34,380 --> 01:17:35,492
Kayla: Yeah, sounds like it.

451
01:17:35,556 --> 01:17:41,964
Chris: Like, in a way, I almost admire them putting their own money on the line like that. Like, putting their money where their mouth is, kind of.

452
01:17:42,012 --> 01:17:51,700
Kayla: At least they were leveraging themselves and not just. Not just taking advantage of, like, what could potentially be the downfall of other people's fortunes. Like, they were.

453
01:17:51,780 --> 01:18:03,500
Chris: Right. Yeah, but in terms of, like, putting all your eggs in one basket that way, not so bright. They kind of seemed like these hedge fund managers didn't really believe in hedging their bets.

454
01:18:03,620 --> 01:18:05,200
Kayla: They did not hedge.

455
01:18:06,100 --> 01:18:15,740
Chris: As for the aftermath of all this, the rise and fall of LTCM shook the financial industry to its core. And still resonates today. Did the industry learn from all this?

456
01:18:16,640 --> 01:18:21,312
Kayla: Well, I'm gonna. Okay, wait, can I make a prediction?

457
01:18:21,456 --> 01:18:22,900
Chris: You can make a prediction.

458
01:18:23,680 --> 01:18:25,020
Kayla: No, they did not.

459
01:18:26,200 --> 01:19:02,182
Chris: A little. So, like, the financial industry learns its lessons and significant fits and starts, right? Like, there's several steps back for every step forward. People, companies all have short memories, right? Like older folks with firsthand experience with things like this retire and younger folks enter the industry with less of this kind of experience, but still all the same pressures to find that next penny vacuum, that next big thing that's going to make a ton of money. Right. There's a lot of pressure for that, right? So the industry did learn a lot of lessons. But on the other hand, you might remember 2008.

460
01:19:02,366 --> 01:19:16,694
Kayla: I do remember 2008 because that was not good. And that is when folks my age and your age were like, had just been in the job market for a little bit or were entering into the job market or were about to enter into the job market.

461
01:19:16,782 --> 01:19:17,118
Chris: Yeah.

462
01:19:17,174 --> 01:19:18,902
Kayla: And no one had jobs.

463
01:19:19,086 --> 01:19:57,700
Chris: Yeah, 2008 was kind of like LTCM, but like even almost. I think it was even like a larger scale. Like, it was sort of like a whole industry thing and not just like one company that might take down the. The other thing is that the bailout of LTCM was actually considered pretty successful. Oh. The banks that bought them were actually able to liquidate LTCM's positions in sort of what they call like an orderly fashion that didn't crash everything and tank prices and whatever. I like that they were actually able to do that successfully. LTCM stopped existing as a company a few years after that, but they were able to liquidate them in a way that didn't, like, fuck everything. But yeah, 2008 was bad.

464
01:19:58,080 --> 01:20:18,832
Chris: I want to read you a quote from a Guardian article published in 2003 entitled five years on from the hedge fund disaster, subtitled, the industry is bigger than ever, but have the factors that brought down LTCM really gone away? And Kayla, what do we know about when an article title is formed as a question?

465
01:20:18,976 --> 01:20:22,000
Kayla: The answer is almost always no.

466
01:20:22,120 --> 01:20:56,640
Chris: No. So this article, which I'll link in the show notes, talks about this exact question of, like, have we learned lessons from this? Are we going to prevent this again? And the quote I'm going to read you here is from a man named Simon Hopkins, and he's a founder of a London based hedge fund group involved investing and startup financing. In the article, he says, quote, the areas to worry about are the ones that are capable of collapse because they are artificial markets effectively created by investment banks. Things like convertible bonds and I. Mortgage backed securities.

467
01:20:59,140 --> 01:21:00,476
Kayla: That's interesting.

468
01:21:00,668 --> 01:21:25,494
Chris: Remember, this article is from 2003. So for those of you who are either too young or didn't get into the forensics around the 2008 financial crisis, Mister Hopkins here was exactly right because mortgage backed securities were the murder weapons in the case of who killed the 2008 economy. And as for LTCM's founder, John Merriweather, what do you think he did after this?

469
01:21:25,582 --> 01:21:28,582
Kayla: I think he's probably a big wig at some other company.

470
01:21:28,646 --> 01:21:33,130
Chris: Well, you don't think he got consequences? There's no consequences for him.

471
01:21:33,430 --> 01:21:34,422
Kayla: What's that?

472
01:21:34,566 --> 01:21:36,610
Chris: Well, the consequences, I forget this was in the nineties.

473
01:21:37,230 --> 01:21:41,374
Kayla: I know the consequence is that he lost his company, essentially.

474
01:21:41,542 --> 01:21:45,910
Chris: Yeah. So he definitely did face consequences in the financial sense.

475
01:21:45,990 --> 01:21:48,792
Kayla: I don't necessarily think this guy should go to jail or something.

476
01:21:48,926 --> 01:21:50,716
Chris: No, he, like, he wasn't doing.

477
01:21:50,748 --> 01:21:58,396
Kayla: Yeah, I'm not expecting consequences. Like, I was expecting consequences for 2008 where people were like, yeah, let's just do a bunch of predatory home lending and then get bailed out.

478
01:21:58,428 --> 01:22:27,588
Chris: And then, yeah, this was, like I said at the top of the show, this was less of a case of, like, scam or even like, predatory and more of just a case of like, hubris blindness. Right, right. Like, they were like, clearly by how much money they were into their own company. Like, they did believe in what they were doing. Like, they weren't just trying to scam people, but it didn't work. And, you know, they faced monetary consequences for that. But after this, he went on to start more hedge funds.

479
01:22:27,644 --> 01:22:30,492
Kayla: That is absolutely what I would have guessed.

480
01:22:30,556 --> 01:22:33,820
Chris: I know. Like, I read about that and I was like, yeah, that tracks. That tracks a whole hell of a lot.

481
01:22:33,860 --> 01:22:42,676
Kayla: I would be. I would honestly have been like. I would have been jaw on the floor if it had been like. And then he went back to school and became a teacher. Like, you know, I would have been shocked.

482
01:22:42,748 --> 01:23:15,364
Chris: Right? He just takes cares of puppies. The funds he started since then have had mixed success, but nothing quite so high as LTCM's highs or quite so low as the lows. Anyway, listeners, if you are lucky enough to own any investments like stocks or anything else, maybe you've made a bad trade or lost money, or maybe your bank account has just been having a tough time lately. Just remember, at least you didn't lose $4.6 billion in one year. Like LTCM. You want to talk criteria?

483
01:23:15,452 --> 01:23:17,240
Kayla: I always want to talk criteria.

484
01:23:18,100 --> 01:23:35,620
Chris: So it's actually, it's been like, a little bit since I've done criteria on the episode, like, since you've done the crit. Yeah, actually, I don't think I've done it at all this season, because we had. The first episode we did was Mike Caulfield, and we just talked about sift and information literacy, and then we talked about, like, tools for self care.

485
01:23:35,740 --> 01:23:37,028
Kayla: You did it for the Rothschilds.

486
01:23:37,084 --> 01:23:37,476
Chris: Did I?

487
01:23:37,508 --> 01:23:38,636
Kayla: I think so, yes.

488
01:23:38,708 --> 01:23:41,804
Chris: Because they weren't the cult, though. They were. The cult was, like, rothschild conspiracy.

489
01:23:41,852 --> 01:23:43,148
Kayla: Right. But went through the.

490
01:23:43,284 --> 01:23:44,012
Chris: Oh, we did. Yes.

491
01:23:44,036 --> 01:23:46,388
Kayla: We went through the criteria. So let's do it again.

492
01:23:46,484 --> 01:23:53,484
Chris: All right. Yeah, let's. Let's do the thing that people are here for. Charismatic leader John Merriweather. Yeah, I think that was pretty high. Right?

493
01:23:53,532 --> 01:23:58,012
Kayla: Like, it seems like. I'm assuming he was the one, like, being like, give me all your money.

494
01:23:58,196 --> 01:23:59,400
Chris: Yeah, he was the one.

495
01:23:59,700 --> 01:24:02,020
Kayla: Formula. Well, here's some magic beans.

496
01:24:02,180 --> 01:24:22,940
Chris: Yeah. So he was the magic beans slash pied Piper guy. And I'll also note that again, he brought a ton of people over with him from Solomon brothers. Literally had a lot of charisma to bring over. And charisma can just be like, I believe this guy will make me money. It doesn't have to be just good speaking voice. It can be that, right?

497
01:24:23,020 --> 01:24:30,522
Kayla: No, charisma is. Yeah, it's a lot of things. This guy has enough PhDs that I believe he'll give me money.

498
01:24:30,626 --> 01:24:32,350
Chris: Right. So very high.

499
01:24:32,730 --> 01:24:33,850
Kayla: Yeah, it's up there, baby.

500
01:24:33,890 --> 01:24:35,430
Chris: Okay. Expected harm.

501
01:24:37,370 --> 01:24:53,870
Kayla: It's. This one's hard for me because it's like, oh, with the formula. With the formula, it's. The harm is low. But I'm like, it's fucking hedge fund, Wall street bullshit market stuff. It's gonna hurt you, boyo.

502
01:24:54,690 --> 01:25:00,826
Chris: And I would say in this case, it did hurt them. Right. It maybe even was, like, gonna cascade out to the rest of society.

503
01:25:00,938 --> 01:25:01,258
Kayla: Right.

504
01:25:01,314 --> 01:25:08,580
Chris: I. So I would say the expected harm here was. Was pretty high. Right? Like, they lost a lot of money. Now, it wasn't like, expects the harm.

505
01:25:09,000 --> 01:25:10,584
Kayla: Because they didn't expect the harm.

506
01:25:10,632 --> 01:25:22,592
Chris: They didn't. But there were skeptics that did expect it. There were skeptics that warned them of a harmful bulldozer that was tracking their every move as they were attempting to suck up pennies. So I would say expected harm is fairly high.

507
01:25:22,656 --> 01:25:26,528
Kayla: I'm always down to say that the hedge funds are causing us harm and that.

508
01:25:26,544 --> 01:25:29,266
Chris: Well, and they were causing their own members harm. Remember, they lost a ton of money.

509
01:25:29,368 --> 01:25:30,210
Kayla: Not good.

510
01:25:30,950 --> 01:25:32,330
Chris: Presence of ritual.

511
01:25:33,190 --> 01:25:34,850
Kayla: I'll let you answer that one.

512
01:25:35,150 --> 01:25:36,166
Chris: Formula, baby.

513
01:25:36,606 --> 01:25:38,126
Kayla: Formula the almighty formula.

514
01:25:38,158 --> 01:25:38,742
Chris: Trust the math.

515
01:25:38,806 --> 01:25:39,438
Kayla: Trust me.

516
01:25:39,534 --> 01:25:39,774
Chris: Do it.

517
01:25:39,782 --> 01:25:52,294
Kayla: The formula could not be more ritualistic. At the end of the day, is the formula the charismatic leader? Oh, my God. The formula is the charismatic leader. Because they were investing in their own thing. The formula was the leader. The formula was the leader.

518
01:25:52,462 --> 01:26:07,966
Chris: You're right. You're right. Cause that was the thing that really got them. It was the person. It was the sort of branding as the intellectual, like, you know, superpowers and what underlies all that. We have the Nobel Prize.

519
01:26:08,038 --> 01:26:09,750
Kayla: They were just all worshipping the formula.

520
01:26:09,790 --> 01:26:14,334
Chris: And on top of that, they followed it. Sort of like, especially during the asian financial crisis.

521
01:26:14,382 --> 01:26:14,970
Kayla: Right?

522
01:26:15,270 --> 01:26:18,286
Chris: They followed with the formula. So they followed the models.

523
01:26:18,318 --> 01:26:19,070
Kayla: Oh, geez.

524
01:26:19,190 --> 01:26:22,710
Chris: The model said double down, and they were like, okay, yes.

525
01:26:22,790 --> 01:26:25,210
Kayla: Guess I'll drive into something never been wrong before.

526
01:26:26,430 --> 01:26:30,490
Chris: So. Hi. Niche within society. Niche. Niche.

527
01:26:30,990 --> 01:26:43,430
Kayla: It sounds like for, like, before doing this episode, I would say no, but hearing all of this stuff at the time, it doesn't sound like it was very niche. It sounds like they were the rock stars of the hedge fund world.

528
01:26:43,590 --> 01:26:46,830
Chris: It's always hard to answer this question, I think, because I'm never sure.

529
01:26:46,870 --> 01:26:51,708
Kayla: We need to get rid of this question. Criteria has been problematic since day one.

530
01:26:51,894 --> 01:27:17,760
Chris: But I think it's not defined. I know, because, like, the thing that I struggle with now, it's not so much, before it was like, what does size mean? But now it's like, what does niche mean? Like, is it niche within society or niche within its own fear? Yeah, so I would say it definitely wasn't niche within its own sphere. Like, they were the biggest players on Wall street for several years, but, like, a lot of people haven't heard of it. So, like, I would say, though, because.

531
01:27:17,800 --> 01:27:19,980
Kayla: It'S like, hedge funds aren't niche.

532
01:27:20,640 --> 01:27:23,336
Chris: No, but have you heard of lTCM?

533
01:27:23,488 --> 01:27:27,272
Kayla: No, but, like, I. I don't know.

534
01:27:27,376 --> 01:27:27,992
Chris: It's tough.

535
01:27:28,056 --> 01:27:29,712
Kayla: It's hard to say, look, this is.

536
01:27:29,736 --> 01:27:44,992
Chris: The criteria that medium. I think it's medium. This is the thing that differentiates cults from religions. So I think as something that was, like, a brief flash in the pan that was only specific to a certain industry and luckily didn't spread out too much more than that.

537
01:27:45,056 --> 01:27:45,328
Kayla: Right.

538
01:27:45,384 --> 01:27:52,910
Chris: I. I think that's a good argument for niche antifactuality. Boy.

539
01:27:52,990 --> 01:28:43,290
Kayla: Okay, so again, let's go back to the formula. This sounds like a thing where it was like, the formula knows. The formula knows. The formula knows. And it turns out that the formula did not know. And even though the formula was, like, right. Quote, unquote, for however long it was. Right. I'm really troubled by the fact that it didn't take into account the things like black swans, the known unknowns. Yeah, the black swans. That it didn't take. Just the fact that it didn't take into account black Monday, which had been, what, seven years before, 87 to 94. Like, it wasn't super in the rear view. The people who were working at LTCM, some of those people had probably been working when Black Monday happened. Take that into account. Feels. It feels really like bury your head in the sand.

540
01:28:43,590 --> 01:28:55,726
Chris: It does. And it's subtle, right. Because, again, it's not that they're like. It's not that they don't know about it. It's not that they wouldn't take that into account. It's not like they didn't know of the. Like you said, they didn't know the existence of these black swans.

541
01:28:55,798 --> 01:28:56,246
Kayla: Right.

542
01:28:56,358 --> 01:29:50,360
Chris: It's that having this formula, there's, like. There's like, a disconnect, right? It's like the formula is this beautiful piece of math that works. And then you train models. You use that formula to build these models that require data to go into them, to, like, say, okay, it means this versus this. When you do that, you're basically like, everything downstream from the formula. Like, inherits its authority. Right. So by the time you get to, like, well, the math says so, then there might be something broken under the hood that if. You know, it's like. I don't know, like, the guy was wearing a lab coat, so he said to do it. And it's like, if you check under the lab coat, he's actually, like, three kids total. Yeah, he's three kids stacked. But because this lab coat gets inherited, everything downstream from the formula.

543
01:29:50,480 --> 01:30:06,330
Chris: So it's not that these guys didn't know that they were black swans. It's just that, like, I don't know, the formula set. Does the formula account for those? I don't know. Probably. It's. It's a Nobel winning formula. Like, it. We train like, the smartest minds in the world. Trained it on these data sets. Right?

544
01:30:07,430 --> 01:30:11,170
Kayla: Is having blind spots anti factuality? I don't know.

545
01:30:11,630 --> 01:30:12,470
Chris: I don't know either.

546
01:30:12,550 --> 01:30:13,950
Kayla: We could do an entire episode on that.

547
01:30:13,990 --> 01:30:14,406
Chris: I know.

548
01:30:14,478 --> 01:30:17,022
Kayla: I think we'll. Let's pull a question mark on this one, I think.

549
01:30:17,046 --> 01:30:24,362
Chris: A question mark. Because usually this criteria means, like, this criterion means circular reasoning, logical clause loops.

550
01:30:24,386 --> 01:30:25,386
Kayla: Whatever we call them.

551
01:30:25,498 --> 01:30:25,986
Chris: Right?

552
01:30:26,098 --> 01:30:26,482
Kayla: Yeah.

553
01:30:26,546 --> 01:30:27,554
Chris: Conspiracy type thing.

554
01:30:27,602 --> 01:30:29,754
Kayla: Literally just saying the wrong thing.

555
01:30:29,882 --> 01:30:46,110
Chris: This is. Yeah, but this is blind spots. This is, like, not really all of that, right. But it is something that, like, gets in the way of, like, identifying the truth in things and certainly hurt them and other people. All right. Life, consumption.

556
01:30:46,530 --> 01:30:47,514
Kayla: Oh, hi.

557
01:30:47,682 --> 01:30:48,922
Chris: Yeah, yeah. I mean, it's.

558
01:30:48,946 --> 01:30:50,610
Kayla: Well high for the people involved. Yeah.

559
01:30:50,690 --> 01:31:00,048
Chris: I mean, like, I. I don't. I didn't get any information on, like, you know, whether these people were doing, like, crazy, like, boiler room hours. You know, like, I don't know if they were working 90 hours a week or what.

560
01:31:00,104 --> 01:31:00,792
Kayla: Okay, mid.

561
01:31:00,896 --> 01:31:05,736
Chris: But. Yeah, I'll say mid because I know that's, like, a thing on Wall Street. I just don't know if it was a thing for LTCM.

562
01:31:05,808 --> 01:31:06,184
Kayla: Right.

563
01:31:06,272 --> 01:31:16,048
Chris: You know, they might have been like, we're. You know, we're not crazy traders. We're academics. We have a normal work week, or normal ish, maybe, compared to Wall Street. I know. Academics. Also academia.

564
01:31:16,184 --> 01:31:17,000
Kayla: It gets crazy.

565
01:31:17,080 --> 01:31:17,368
Chris: Yeah.

566
01:31:17,424 --> 01:31:21,018
Kayla: The crunch in academia, particularly amongst the, like, quote unquote lower levels.

567
01:31:21,184 --> 01:31:24,958
Chris: Fair enough. Fair enough. Dogmatic beliefs.

568
01:31:25,014 --> 01:31:56,274
Kayla: I'm gonna say the almighty. This is kind of what the antifactuality was hitting out for me. The almighty formula giving you blinders and giving you blind spots. That feels dogmatic to me. I know. It's not like we're the in group. We're the only one that's right, blah, blah. But when you are getting high on your own supply, when you're so blind to the black swans, when you just keep turning right, because the. The machine knows and you drive into the lake, everybody go watch that episode of the office if you don't know what we're talking about. That feels dogmatic to me.

569
01:31:56,442 --> 01:32:03,530
Chris: I think I agree with you here. Yeah. It's not quite like, you know, we have the answers and nobody else has the answers, but it's a little bit like that.

570
01:32:03,570 --> 01:32:07,338
Kayla: It's a little bit like we're just gonna. Yeah, we can vacuum up these panties in front of this bulldozer.

571
01:32:07,434 --> 01:32:10,550
Chris: Right. So I'd say hi there, too. Chain of victims.

572
01:32:11,170 --> 01:32:12,790
Kayla: I'll let you answer that.

573
01:32:13,660 --> 01:32:15,520
Chris: I will defer to you.

574
01:32:15,940 --> 01:32:32,396
Kayla: I don't know. Yes. It seems like if they were. If they were able to tank the entire Us economy, potentially. Yeah, that feels. I mean, I know it's different than the MLM chain of victims, which is the very classic one, but it feels like there is a cascading effect of victims here.

575
01:32:32,468 --> 01:32:41,714
Chris: Yeah, there's definitely people outside of the cult inheriting problems from it aspect, so I would say fairly high here, too.

576
01:32:41,802 --> 01:32:42,442
Kayla: Yeah.

577
01:32:42,586 --> 01:33:22,998
Chris: And then our newest one, safe or unsafe exit it. Was it safe or unsafe to exit from this thing? I didn't get a lot of information. Like, there was no. I didn't get any in my research or in my knowledge from just when we learned about this in business school, nobody was like, yeah. And then, like, somebody left the firm and was ostracized and, like, right. You know, stalked and, you know, investigated. Like, there wasn't anything like that. So I'd say this is probably pretty low, although I don't think people really, like, everything happened so quickly that there wasn't a lot of turnover. It was just like a bunch of smart people got together, did this thing, and made a shit ton of money and then lost all of it and then left.

578
01:33:23,134 --> 01:33:24,810
Kayla: The american dream.

579
01:33:25,950 --> 01:34:09,090
Chris: By the way, I'm going to put instagram. There's a really fun graph that shows, over the course of his existence, rate of return for LTCM is one of the lines. And this is actually going to be in our Twitter social media teaser picture as well. So there's, like, this blue line that's going up real fast and that's LTCM, right. And then there's, like, a red line, which is like the Dow Jones industrial stock, right? Like stock market average. And then there's a yellow line, which is, like, super. Say it's a little bit lower than that, which is, like, super safe. I think it's like us treasury bonds or something. It's like you'll earn just like, a tiny little bit of investment over time. It's not going to go as low risk, but you're only going to earn a tiny little bit.

580
01:34:09,210 --> 01:34:44,354
Chris: And so, like, LTCM line goes up, up so fast, way higher than everything else. And then in, like one or two blips, it, like, crashes all the way, like, below, like, all the way to zero. Like, all the way below us treasury lines. So it's like an absolutely, like, tortoise in the hare thing, right? Yeah. You're not going to get those juicy 40% returns by investing in treasury bonds, but at the end of three or four years, you're going to have a little more money versus nothing. So it's. It's a funny graph, you know, I'll put it on our instagram.

581
01:34:44,402 --> 01:34:45,710
Kayla: Please share that graph.

582
01:34:47,290 --> 01:34:51,590
Chris: So that. So what are we saying? Is it a cult or is it just weird?

583
01:34:52,930 --> 01:35:36,920
Kayla: It's got a lot of highs. It was high charismatic leader, high dogmatic. It's got a lot of mids. It's got some question marks. I think given its brevity, given its. While we did say how to chain of victims, it didn't seem super predatorially recruited. Given that there wasn't difficulty exiting and given that at the end of the day, I don't think there was a lot of anti factuality going on here. I think it was more dogmatic beliefs versus antifactuality. We've teased those two out from each other. I'm gonna say just weird. And because the leader is the formula, not a guy.

584
01:35:38,820 --> 01:35:45,468
Chris: Yeah, I don't know. I was gonna say cult, actually. Like, before we talked about the criteria, I was thinking it's this company. It's a weird company.

585
01:35:45,564 --> 01:35:45,844
Kayla: Right?

586
01:35:45,892 --> 01:35:46,540
Chris: They fucked up.

587
01:35:46,580 --> 01:35:47,160
Kayla: Right.

588
01:35:47,980 --> 01:35:51,500
Chris: But some of these things, like, I don't know, like high ritual, high horror.

589
01:35:51,540 --> 01:35:55,200
Kayla: Oh, I guess, high charismatic leader, high rituals of biggie.

590
01:35:55,940 --> 01:36:17,252
Chris: Like that. That inheritance of that authority from all these lab coders and this, like, magic formula is just. I don't know. And the fact that it was, like, harm this harmful. Yeah, I don't know, man. Like, I know it's just a company that, you know, only lasted a short amount of time, but that almost makes it feel more culty to me. Right?

591
01:36:17,316 --> 01:36:25,192
Kayla: Like Rajneesh Purim. I guess Rajneesh Purrham was wrong, but it's like one of those things where it's spins up real fast like a lularoe and then crash.

592
01:36:25,256 --> 01:36:34,312
Chris: Yeah, it's like, it, like, burns brightly and then, like, combusts. Right? Like, that feels more culty to me. I'm going with cult on this one myself. Split decision.

593
01:36:34,416 --> 01:36:35,340
Kayla: Split decision.

594
01:36:36,120 --> 01:36:43,384
Chris: Anyway, thank you for going on that financial journey with me. I know that's been top of the brain. I promise next one, I won't talk about money.

595
01:36:43,472 --> 01:36:45,500
Kayla: Yeah, I think next one will not be financial.

596
01:36:47,310 --> 01:36:52,038
Chris: It's like, I guess there's like a sub theme for this season that we totally didn't realize were gonna do.

597
01:36:52,094 --> 01:37:00,662
Kayla: No, it's just this podcast is slowly, ever so slowly and swiftly closing in on the.

598
01:37:00,766 --> 01:37:02,262
Chris: Did you say slowly and swiftly?

599
01:37:02,326 --> 01:37:23,876
Kayla: Slowly and swiftly closing in on capitalism as a cult? Unfortunately, I think that's kind of what we keep circling around, that there's so many aspects of to our economic system that can be topics for this episode, including the system itself. And one day we will do that episode.

600
01:37:23,948 --> 01:37:25,440
Chris: Will that be like the finale?

601
01:37:25,740 --> 01:37:27,196
Kayla: That'll be the finale of it all.

602
01:37:27,268 --> 01:37:40,260
Chris: Are we all living in a cult and have been for hundreds of years? All right. With that, I hope everyone has a wonderful day or we never sign off like this, do we? How do we usually sign off?

603
01:37:40,300 --> 01:37:41,572
Kayla: We usually just say our names.

604
01:37:41,716 --> 01:37:42,724
Chris: Have a good day.

605
01:37:42,812 --> 01:37:44,636
Kayla: Have a good day. I'm Kayla.

606
01:37:44,708 --> 01:37:49,480
Chris: I'm Chris. And this has been cult or just hedge funds.