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Jeff Guo
This is Planet Money from NPR.
Mary Childs
In the mid-1990s, a group of people thought they'd finally achieved this dream that had existed since the dawn of financial markets. They'd figured out how to take risk. They built a model that could help them generate great investment returns consistently over time. Perhaps unsurprisingly, they were math nerds.
Victor Hagani
We were mostly cut from the same cloth.
Jeff Guo
This is Victor Hagani. He was the youngest of the group.
Victor Hagani
Like, we were all, you know, kind of game playing, geeky kind of kind of people. And we just really felt attracted to the same kinds of problem solving and the same kinds of thoughts, thought processes and intellectual challenges.
Jeff Guo
Victor was part of this new crew of traders on Wall Street. Where before people had made investment decisions based on, like, what they thought about a company's prospects or maybe just based on a hunch, these guys used data, lots of data, and computers.
Mary Childs
It was math over emotions. Risk taking had always been an art, but now they could turn risk taking into a science.
Victor Hagani
To a large extent you can get rid of certain risks, but if you're going to make money, then you have to be taking risk.
Mary Childs
Victor had gone from working at an investment bank to getting hired into this elite, illustrious group, a group that included Myron Scholes and Bob Merton, the guys who'd figured out how to mathematically derive prices for stock options, bets on a stock's future price. For this work, Myron Scholz and Bob Merton would go on to win a Nobel Prize in economics.
Jeff Guo
Myron and Bob's model provided them with, like, this X ray vision. They could spot all these discrepancies in the market where what the price should be didn't quite match what the price actually was. And the idea was those were opportunities to make money.
Mary Childs
And Victor and his friends made so.
Victor Hagani
Much money, I think that we averaged like 40% annual returns over 30% way, way higher than what we ever anticipated was possible.
Jeff Guo
They were doing amazing. And part of their investing strategy was sometimes not investing.
Victor Hagani
When the opportunities aren't good, you just shouldn't do very much.
Jeff Guo
So sometimes they didn't do very much.
Mary Childs
Were there like game nights?
Victor Hagani
I mean, it was constantly. Well, it was like game afternoon and game night.
Mary Childs
What games?
Victor Hagani
Well, a lot of poker.
Mary Childs
Poker during the day, poker at night, different types of poker. They would turn their desk chairs away from their computer screens of price charts and yield curves to face each other and ante up. They got to play games of risk and probability with actual living legends Bob Merton and Myron Scholes.
Victor Hagani
Well, playing poker with Bob Merton was terrifying because he was really a poker expert. Like, he had programmed and written and solved aspects of poker very early on. So, you know, like we, you know, we played with Bob, but we just knew that Bob was going to walk away with some of our money.
Jeff Guo
Okay, okay. It wasn't all just for fun.
Victor Hagani
I think we kind of felt guilty about it at the time, but it was like giving an outlet to risk taking so that if you kind of like to take risk, it was good to take the risk here and be very risk averse in what we were doing for the firm. So it was an interesting and fun example of risk taking and risk not taking.
Jeff Guo
Yeah, it was like they could take their risks in the game, but when it came to the markets, Victor and his friends only wanted to take these smart, profitable risks.
Mary Childs
They applied their lofty, perfect academic models of cold rationality to the busy, chaotic, real financial markets, to great, great profit.
Victor Hagani
I just always felt that, you know, this was all just sort of too good to be true. It was amazing. I was so happy, I was so grateful and so on.
Mary Childs
And then it all came crashing down. Hello and welcome to Planet Money. I'm Mary Childs.
Jeff Guo
And I'm Jeff Guo. Today on the show, it's maybe the most famous story in all of finance. The legendary rise and fall of long term capital management. A story of perfection gone spectacularly wrong when risk taking should have been risk not taking.
Mary Childs
Perfect, safe, clever bets that turn into a perfect disaster that threatened the entire financial system and how we have learned perfectly nothing from it.
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Jeff Guo
Victor Hagani and his poker playing co workers at the fund, Long Term Capital Management, had cracked the code of how to invest using their perfect mathematical models. The way they went about it was like this. First they would find something cheap.
Victor Hagani
That wasn't very difficult. If you were looking, it was pretty easy to see it.
Jeff Guo
But finding something cheap actually means finding two things.
Victor Hagani
If we were going to buy something that was cheap, we had to find something that was. That it was cheap relative to. Otherwise it didn't mean anything.
Mary Childs
Yeah. What is cheap if it's not?
Victor Hagani
If it's just relative to something else?
Mary Childs
Yeah, because they weren't just buying a stock because they thought it was going to go up. They were betting on a discrepancy. They saw that one bond or stock cost too little relative to another very similar bond or stock. They were balancing the price of one thing off of another, like some kind of asset price parkour. Like, for example, they bet on Russian debt denominated in rubles because everyone else was more scared of it than they needed to be. And they bet against Russian debt denominated in dollars because it was overpriced. That is called a relative value trade.
Jeff Guo
So that's step one, find something underpriced and find something similar that's overpriced. Then they have to figure out why those discrepancies might exist.
Victor Hagani
You had to explain it like, okay, why is this the case? And then you had to decide whether the reasons that were causing it were going to get stronger and make it go further apart, or whether they were going to dissipate over time and whether there would be a convergence. In many cases, the idea was just to hold it long enough so that they had to converge, hold on to.
Mary Childs
The trade for the long term. That's how they managed the capital. You get it?
Jeff Guo
Nice. Now, often a reason for these price discrepancies was that people were being irrational. They were pricing these things wrong. And Long Term Capital's mathematical models could show just how wrong these other people were. So Long Term Capital could take the other side of the bet. They take the rational, empirically correct position and then wait.
Mary Childs
So step one, find an opportunity like Russian debt in dollars is overpriced relative to Russian ruble debt. Step two, explain why that opportunity exists, come up with a good explanation and understand what directions the prices should go.
Jeff Guo
But these opportunities, these price discrepancies, they were generally not that big because, you know, everyone else is also out here in these financial markets looking for underpriced things. So the big discounts Are aren't going to happen. Whatever you find is going to be little.
Mary Childs
Hence step three.
Victor Hagani
And then you use leverage to try to give yourself a good return on investor capital.
Mary Childs
What is leverage?
Victor Hagani
Well, leverage means that you're borrowing money so that you can have more of the trade on than just investing the.
Mary Childs
Capital that you have, borrowing money to double up on the trade or triple up. So if you have $1, you could invest $2 or $3 or $20. And if your bet is correct, you get, you know, 20 times the profit you were gonna with your just $1. Leverage amplifies whatever you're doing. You can win that much more, but you can also lose that much more. Most hedge funds do this, but Long Term Capital did it to the extreme.
Jeff Guo
Because, come on, if you have a great trade opportunity and you believe in it, you should bet big. You shouldn't be limited by your fund's little bank account. You should bet as big as humanly possible.
Victor Hagani
I forget who said that relative value trading is like picking up nickels in front of a steamroller.
Jeff Guo
Nickels. Because these are teeny tiny opportunities to profit. Steamroller, because what if something goes wrong? You've borrowed so much more than you have, all your leverage could flatten you. So the idea is to grab all the nickels, avoid the steamroller.
Mary Childs
So step four, put on the trade. Take the opportunity. They'd call their bank or broker and say, hello, I have $20, 19 of it borrowed, and I'd like to use it to bet on this bond or option or whatever, please. And so that is a game that Victor and the group at Long Term Capital Management were playing. And it was working.
Roger Lowenstein
For the first three years plus of their fund, the world moved exactly the way they thought it would move.
Mary Childs
This is Roger Lowenstein. He wrote the book on Long Term capital management. And he says, in the beginning, this fund was free, verging on mystical.
Roger Lowenstein
You know, they seem to have a formula. People are always looking for a formula, a technique, a model, you know, something they can say, I just plug this in and tomorrow I'll be x percent richer. The day after tomorrow I'll be, you know, x plus Y percent richer.
Jeff Guo
Clients loved them. So much so that they had too many people calling them up, hitting up their pagers, begging them to take their money, to invest. They were turning clients away.
Mary Childs
And in his first few years, their bets were right. Nickels upon nickels upon nickels. Long Term Capital started in February 1994 with $1.3 billion of investor money. By late 1997, that was over $7 billion. But with all that success came a few problems.
Roger Lowenstein
If you own a stock and it triples, that stock that you own is a lot more expensive than it used to be. That might still be a good investment, but it's probably not as good an investment as before. It tripled.
Jeff Guo
Yeah. The opportunities for the future were looking a lot less profitable. And Roger says at some point, you know, a prudent money manager would say, okay, it's all played out just like I thought it would now I should adjust what I'm doing, re evaluate. It's just that it's difficult to know when to adjust.
Roger Lowenstein
All you know is, hey, the math isn't as good as yesterday. We're a little richer today, but that means tomorrow doesn't. It doesn't look as enticing. And they could and should have adjusted their portfolio.
Mary Childs
They'd wrung so much profit out of the markets. In 95, they generated 43% in returns. And the next year, 41%. And another thing about too much success, everyone else notices. Everyone else started copying them. Trading desks at other hedge funds, at banks. Long Term Capital now had more competition, more people buying up the same stuff, scooping up those nickels.
Victor Hagani
It was the hot thing, you know, so it just was attracting money. Just as we were making a lot of money, those trading desks were making a lot of money. So the bank management gave them more money and said, do make me make even more. Here's more capital. And it expanded really quickly. And the opportunity set just looked a lot less attractive than it had looked.
Jeff Guo
There was a smaller and smaller set of opportunities, fewer nickels to pick up.
Victor Hagani
We could see that sadly, we probably didn't make the right. We didn't respond in the right way to it all.
Mary Childs
That phenomenon was starting to show up in the returns for their clients. Instead of 40 something percent returns in 1997, they generated just 17%, which didn't even beat the S&P 500.
Jeff Guo
And right about then, by 1998, things had started happening around the world that would fundamentally change Long Term Capital's future.
Mary Childs
First, financial markets were getting interesting. There was a financial crisis roiling Asia, sparked in Thailand, now hitting Indonesia and South Korea. Long Term Capital's models hadn't really predicted that, but so far, not that big a deal. The trouble was pretty contained.
Victor Hagani
There were these currency devaluations, stock markets dropping, but we weren't super active in these emerging southeast Asian markets. We had some little things on here and there, but very, very small. And we weren't too worried about it.
Mary Childs
Okay, little stuff all fine. Not that big a deal for Long Term Capital Management.
Victor Hagani
What was happening in the spring of 1998 was that Citigroup was shutting down their proprietary trading operation. And we didn't really know it.
Jeff Guo
Citi was shutting down the group that had been doing the same basic strategy that Long Term Capital Management was meaning. They had owned very similar things to Long Term Capital and were now having a going out of business sale. So prices were going down, which, okay.
Mary Childs
Maybe some buying opportunities in there.
Victor Hagani
You know, everything was starting to behave a little bit differently. But we didn't realize, you know, it created a reshuffle and I think it kind of got things started.
Mary Childs
In August of 1998, things really got started. Russia acted in a way that was unexpected. It defaulted on its ruble debt and devalued its currency.
Victor Hagani
We didn't actually have much exposure in Russia. I mean, we lost money in Russia.
Mary Childs
But not a lot, not a lot losses they could handle. That wasn't the problem.
Victor Hagani
When that happened, that triggered all kinds of risk managers all over the financial system to say, hey, you know, we're going to take, we got to take risk off the table.
Mary Childs
And this is when and why things went so sideways for Long Term Capital risk managers. People whose jobs were to make sure their firm wasn't doing anything crazy. They were suddenly acting in a way that no model had predicted. They were like, whoa, this Russia default really surprised us. That's scary. Can we ratchet down how much money we have out there? Can we sell the riskier stuff until we feel better?
Victor Hagani
And it just freaked everybody out. And all of a sudden everybody was like, we gotta reduce risk. Where can we reduce risk? And then that started to set something in motion at that point.
Jeff Guo
So the partners of Long Term Capital Management, they're at their desks, nobody's playing poker, they are watching their nickels evaporate, some of the prices are dropping. All of are moving faster than they normally do.
Victor Hagani
We're losing money. The market is much more volatile than it's been. Lots of different positions we have, we're losing money, but not all of them. That was very disturbing, it was very stressful. And we were trying to figure out how to react to different things. But the market was still functioning, the.
Mary Childs
Group was still able to function, to sell things to other people into a very falling market. Stock markets in Europe dropped more than 5% in a decade day. For the month of August, the Dow Jones industrial average dropped 15%.
Jeff Guo
And then the dynamic of the market Sell off changed and then one day.
Victor Hagani
We look at our screens, their screens.
Mary Childs
Start showing something weird. Some of the things they owned, their positions that shouldn't be affected at all by Thailand or Russia. They're also having huge swings and some.
Victor Hagani
Of the exact positions that we had all of a sudden, you know, made a huge gap move. Just got repriced instantly and you know, very far away from where it had been.
Jeff Guo
Long Term Capital's bets were wrong, but they were getting too wrong. Like this one bet which, you know.
Victor Hagani
I mean it would never move more than 1% but it moved by 12%.
Mary Childs
Up against us and then they're offsetting bet in the other direction. Shouldn't that bet be working out?
Jeff Guo
It was not.
Victor Hagani
When we just saw things that didn't make any sense anymore, we're okay. When we saw the thing went down, when it should have gone up, then we knew what was happening for sure. And it was like that was like that stomach dropping moment.
Roger Lowenstein
It wasn't that one asset went against them or another did, but that every asset, every asset that they traded went against them.
Jeff Guo
Roger Lowenstein says basically everything Long Term Capital owned was going against them. It was no longer just a market sell off sparked by panic over world events. The now it was a market sell off swirling around Long Term Capital.
Mary Childs
Because in all their beautiful perfect mathematical models of risk taking and risk not taking, Roger could see that Long Term Capital had failed to account for something. A big thing.
Roger Lowenstein
You had what I called the human factor which tilted the odds.
Mary Childs
Yeah, the sell off may have started with Russia, but then the human factor people got spooked across the board. And then when Long Term Capital started to stumble, Wall street saw an opening.
Roger Lowenstein
The street knew what their basic trade was. So the street, either for self protective reasons because they were in the same trades as LTCM and they said, hey, I don't want to be exposed to the kind of losses they're having. I'm going to get out which move markets against them or sort of more aggressive posture saying I think LTCM is vulnerable. What they own. I'm going to bet against the Wall Street.
Jeff Guo
Banks that Long Term Capital traded with knew their trades. The funds who'd been copying them basically knew their trades. And all of these banks and competitors were now taking the opportunity to bet against Long Term Capital in order to topple them.
Mary Childs
And this was something else that their perfectly rational models had failed to predict. That their peers and competitors had been jealous and were more than willing to help them fail.
Jeff Guo
Now there was still a way to get through this. It's in the long term part. Long Term Capital just had to have enough money and enough capital so that they could ride this out until prices recovered.
Victor Hagani
And it was like, we've got to raise this capital fast, you know, otherwise there's no, you know, this is, this is not going to end well.
Mary Childs
So they called up all their clients and all the people who had been beating their door down to give them money to invest.
Victor Hagani
So we went out to all these people that were begging to invest with us and said, okay, here you go. Here's your, here's your big opportunity.
Jeff Guo
Yeah, your big opportunity, right? Just like you wanted to invest your money with Long Term Capital Management.
Mary Childs
And people were interested even at that point, but not if they were going to be the only ones doing it.
Victor Hagani
People would say, I'll give you $200 million, but only if you raise $3 billion. I don't want to give you $200 million. If you only raise 500 million, that's not going to be enough for you to survive this.
Jeff Guo
Long Term Capital needed a lot of money because they'd borrowed so much to invest in their smart perfect trades, which were now all upside down.
Mary Childs
And this chapter, this is the steamroller part. Their model had not predicted the panic over Russia's default. It didn't understand how people act when they're scared. And now by the summer of 1998, people were too scared to save them.
Victor Hagani
And we just never quite got there. And a lot of, you know, it was just. The whole thing was in motion very quickly.
Jeff Guo
Some days they lost hundreds of millions of dollars. It was dizzying and it was spreading.
Roger Lowenstein
Wall street stocks were crashing. Credit all around Wall street was drying up because nobody knew how far or deep the reverberations from LTCM would run.
Mary Childs
By late September, Long Term Capital management was effectively over because sometimes emotions triumph over math.
Roger Lowenstein
In four years, they'd quadrupled their investors money. They seemed to have the black box. Over the next month, they lost half their assets. And in the ensuing couple of weeks, they lost virtually all the rest. It was all over.
Jeff Guo
After the break, we find out just how far the reverberations of Long Term Capital's collapse would go. Foreign.
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Mary Childs
Is this saying attributed to industrialist J. Paul Getty, if you owe the bank a hundred dollars, that's your problem. If you owe the bank $100 million, that's the bank's problem. And by the fall of 1998, long term capital Management had loved leverage so much that the fund had borrowed from the banks over $100 billion. They weren't just the bank's problem, they were everyone's problem.
Jeff Guo
The entire financial market was destabilized, which is why Roger lowenstein says on September 22nd, the Federal Reserve stepped in.
Roger Lowenstein
Bill McDonough, the president of the New York Federal Reserve, called in the 16 biggest banks.
Mary Childs
The Fed president said, please come in for a visit. He gathered the banks in a conference room and said, let's figure this out. Long Term Capital was not invited.
Jeff Guo
Now, the banks were not required to.
Roger Lowenstein
Help here, but, but when the Fed calls you, you go, obviously. And he said, it's up to you guys as private money, but I don't want to see these guys fail chaotically. Is there a way that we can, we can, you know, orchestrate their funeral, so to speak?
Mary Childs
I envision this Fed meeting as a group of somewhat guilty children, like their siblings, their cousins or something, and a parent has locked them in a room and said, okay, maybe you didn't make the mess, but you have a mess. How are you going to clean it up?
Jeff Guo
Victor Hagani says that at first, each individual bank was kind of behaving like children. They're like, this isn't my problem.
Victor Hagani
They were like, I don't know. We'll just see what happens, you know. And the Fed said, no, no, no, this is, this is a Risk to the market. You guys have to do something about this. We think that you should all put in a couple hundred million dollars each and take over the fund and resolve this crisis in that manner.
Mary Childs
A couple of the banks were still like, thank you for this opportunity, but no, and left the room.
Victor Hagani
But 14 of the banks agreed to do this and put in about $3.6 billion.
Mary Childs
In the end, the 14 banks bought all the stuff that Long Term Capital had at an enormous discount. Eventually, those prices would recover and the banks made money.
Jeff Guo
Just a few years before, Long Term Capital had been the toast of Wall Street. They were geniuses, throwing around over $100 billion, only a little bit of it theirs. And now it was no more.
Mary Childs
For the partners at Long Term Capital, including Victor, this was personally and financially painful.
Victor Hagani
It was very sad for ourselves. It was very sad for the investors that we lost all this money for. It was really painful for several years afterward. You know, we had built something and we made mistakes and, you know, it was unfortunate.
Mary Childs
Victor's professional reputation was invested in the fund. His career was in the fund, and he'd had money in the fund.
Victor Hagani
Well, I lost, you know, call it 80% of. I lost about 80% of my net worth.
Mary Childs
But that Fed orchestrated funeral, it worked. It stopped the panic. And Roger says there are two main reasons why it worked.
Roger Lowenstein
The Federal Reserve chief had his thumb on their necks. And the other thing is they each had the comfort that no one potential investor would have had a loan, which is, I'm not going in alone. So they could put in enough capital, presumably to withstand more market moves against them. It took a group effort to staunch the bleeding.
Jeff Guo
But Victor wants to make something clear about what happened here. He and his fellow partners of the now defunct Long Term Capital Management lost money. Nobody swooped in to make them whole again. And certainly the government did not send taxpayer money to fill in their losses.
Mary Childs
The rescue effort was a rescue of the financial system, not of Long Term Capital Management.
Victor Hagani
We didn't get bailed out. You know, there was no government money involved. You know, there was. There was just. No, there was no bailout as we would commonly think of a bailout.
Mary Childs
Victor says this was a private recapitalization. The 14 private banks got to buy a bunch of assets at buyer sale prices from a private company. Victor says while the Fed did babysit, it was just hosting a hedge fund yard sale.
Jeff Guo
Now, to Roger, whether the Fed just babysat or the government used its actual money ultimately ended up being kind of a matter of semantics.
Roger Lowenstein
I think it was Better from a public policy, certainly, that there was no, you know, they didn't take money from food stamps and give it to ltcm.
Mary Childs
Yeah, that does sound bad.
Roger Lowenstein
That would sound worse. But I think from the standpoint of the example it set for markets, it didn't make, you know, much difference by intervening.
Mary Childs
The Fed set a precedent because just 10 years later, in 2008, the financial system would again be on the brink of collapse. Except this time the problem was much bigger.
Jeff Guo
Yeah, the big banks, Lehman Brothers and Bear Stearns and Merrill lynch and Deutsche bank and all the rest of them had been gleefully using leverage to bet on mortgage debt. Mortgage debt that was way riskier than their models predicted. And in this case, the government really did bail out some banks and financial institutions.
Victor Hagani
I feel, I feel that somehow, I feel that somehow the LTCM experience had to be unheeded for 2008 and 9 to have unfolded the way that they did.
Mary Childs
Victor and Roger agree on this point. Yes, the Fed or the government has some interest in a stable financial system. But because in 1998 the Fed intervened and orchestrated Long Term Capital's funeral. We didn't see what would have happened had it been allowed to fail chaotically. We didn't really feel the consequences of all that risk taking and all that leverage. So we didn't really learn that maybe that was too much risk.
Roger Lowenstein
I think that's a bad example. I think capitalism works best with real traders taking real losses when they occur. It disciplines the way people try to make real profits.
Jeff Guo
Because if the government is going to come in and fix everyone's mistakes, is there really any difference between risk taking and risk not taking?
Mary Childs
And Roger says it is folly to think that anyone would ever solve that age old dream of a perfect mathematical solution to risk being able to predict the future because you can't. That's the only thing that history does promise us.
Roger Lowenstein
It was just sort of the height of financial hubris. I don't mean hubris in a personal way, that they were bad people. I don't mean that at all. But I think they were wrong on a key point, which is the assumption that any black box, any formula based on the historic patterns of how prices have moved can be a guarantee and therefore can give you license to take such tremendous leverage. Black box has not been invented.
Mary Childs
But maybe this time, Roger.
Roger Lowenstein
Maybe this time. Maybe this time.
Mary Childs
This episode of Planet Money was produced by Sam Yellow Horse Kessler and edited by Jess Jiang. It was fact checked by Sierra Juarez and engineered by Robert Rodriguez. Alex Goldmark is our executive producer. I'm Mary Childs.
Jeff Guo
I'm Jeff Glow. This is npr. Thanks for listening.
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Planet Money: The Rise and Fall of Long Term Capital Management
Episode Release Date: February 22, 2025
Host: NPR's Planet Money (Mary Childs and Jeff Guo)
In this compelling episode of Planet Money, hosts Mary Childs and Jeff Guo delve into the legendary tale of Long Term Capital Management (LTCM), a hedge fund that epitomized the heights of financial ingenuity and the depths of systemic risk. The story unpacks LTCM's meteoric rise, driven by mathematical prowess and aggressive leverage, followed by its dramatic collapse that nearly shook the global financial system.
Key Players and Vision
In the mid-1990s, LTCM emerged as a beacon of quantitative finance. Comprised predominantly of mathematically inclined individuals, including Victor Hagani—the youngest member of the group—the fund aimed to revolutionize investment strategies through data-driven models.
Victor Hagani (00:48): "We were all, you know, kind of game playing, geeky kind of kind of people. And we just really felt attracted to the same kinds of problem solving and the same kinds of thoughts, thought processes and intellectual challenges."
Innovative Strategies
LTCM's approach diverged sharply from traditional investment methods. Instead of relying on company prospects or gut feelings, the fund leveraged vast amounts of data and sophisticated computational models to identify market inefficiencies.
Mary Childs (00:23): "They built a model that could help them generate great investment returns consistently over time."
Academic Excellence and Initial Success
The team included esteemed economists like Myron Scholes and Robert Merton, pioneers in option pricing theory who later won the Nobel Prize. Their models provided LTCM with unparalleled insight into market discrepancies, allowing the fund to capitalize on mispriced assets.
Victor Hagani (02:16): "I think we averaged like 40% annual returns over 30% way, way higher than what we ever anticipated was possible."
Step 1: Identifying Underpriced and Overpriced Assets
LTCM’s method involved finding pairs of similar assets where one was undervalued compared to the other. For instance, they might bet on Russian debt denominated in rubles if it was cheaper relative to its dollar-denominated counterpart.
Mary Childs (06:21): "They were betting on a discrepancy. They saw that one bond or stock cost too little relative to another very similar bond or stock."
Step 2: Understanding Discrepancies
The team scrutinized why these price differences existed, determining whether they would widen or converge over time, and held positions accordingly.
Victor Hagani (07:06): "You had to explain it like, okay, why is this the case?"
Step 3: Leveraging to Amplify Returns
To magnify returns on these slight discrepancies, LTCM employed significant leverage, borrowing extensively to increase their investment capacity.
Victor Hagani (08:32): "And then you use leverage to try to give yourself a good return on investor capital."
Step 4: Executing the Trades
With identified opportunities and amplified capital, LTCM placed substantial bets on their models, believing in their mathematical certainty.
Mary Childs (09:47): "They'd call their bank or broker and say... please."
Exponential Growth
LTCM's strategy yielded extraordinary returns initially, attracting significant investor interest and rapidly increasing assets under management from $1.3 billion in 1994 to over $7 billion by 1997.
Roger Lowenstein (10:07): "They seem to have a formula... you just plug this in and tomorrow I'll be x percent richer."
Diminishing Opportunities
As LTCM extracted profits, the very opportunities they exploited became scarce, leading to shrinking returns. By 1997, returns dropped from 43% to 41%, failing to surpass the S&P 500.
Victor Hagani (12:31): "We could see that sadly, we probably didn't make the right. We didn't respond in the right way to it all."
Increased Competition
Their success drew competitors, who mimicked LTCM’s strategies, further eroding the profit margins and intensifying the competition for the remaining "nickels."
Global Financial Instability
In 1998, a series of global financial crises, including the Asian financial meltdown sparked by Thailand's default, began to destabilize markets. LTCM's models failed to predict these widespread disruptions.
Victor Hagani (13:37): "What was happening in the spring of 1998 was that Citigroup was shutting down their proprietary trading operation."
Chain Reaction of Losses
LTCM's leveraged positions amplified losses as market volatility surged. Their once-reliable models couldn't account for the cascading effect of peer actions and irrational market behaviors.
Victor Hagani (16:23): "Every asset that they traded went against them."
Human Factor and Market Psychology
Roger Lowenstein highlights that LTCM underestimated the "human factor"—the collective reaction of market participants eroding the stability that LTCM's models presumed.
Roger Lowenstein (17:41): "You had what I called the human factor which tilted the odds."
Desperate Measures and Failed Recapitalization
In a frantic attempt to salvage the fund, LTCM sought additional capital. However, with banks and investors wary of further losses, LPCM struggled to raise the necessary funds, leading to a rapid depletion of assets.
Victor Hagani (19:10): "People would say, I'll give you $200 million, but only if you raise $3 billion."
Systemic Risk and Federal Involvement
Recognizing LTCM's collapse as a threat to the broader financial system, the Federal Reserve intervened by orchestrating a private bailout. President Bill McDonough convened the 16 largest banks to stabilize LTCM without directly injecting taxpayer money.
Roger Lowenstein (25:47): "The Federal Reserve chief had his thumb on their necks."
Private Recapitalization
Fourteen of the banks contributed approximately $3.6 billion, purchasing LTCM’s distressed assets at discounted rates. This collective action prevented a chaotic market fallout but marked LTCM's end.
Victor Hagani (26:37): "We didn't get bailed out... it was just hosting a hedge fund yard sale."
Personal and Professional Fallout
For LTCM’s partners, including Victor Hagani, the collapse was both financially devastating and personally disheartening. Professional reputations were tarnished, and significant personal wealth was lost.
Victor Hagani (25:28): "I lost about 80% of my net worth."
Impact on Financial Policy and Future Crises
The LTCM episode set a precedent for future financial rescues, influencing responses to subsequent crises, notably the 2008 financial meltdown. However, the fundamental issues of excessive leverage and overreliance on mathematical models persisted.
Victor Hagani (27:00): "LTCM experience had to be unheeded for 2008 and 9 to have unfolded the way that they did."
Critical Reflections
Roger Lowenstein critiques the hubris of relying solely on quantitative models, emphasizing the irreplaceable role of human judgment and the unpredictability of markets.
Roger Lowenstein (29:09): "...they were wrong on a key point, which is the assumption that any black box... can be a guarantee and therefore can give you license to take such tremendous leverage."
The rise and fall of Long Term Capital Management serves as a cautionary tale about the limits of mathematical modeling, the dangers of excessive leverage, and the unpredictable nature of financial markets. While LTCM achieved unprecedented success through quantitative strategies, their downfall underscores the essential balance between analytical rigor and the inherent uncertainties of human behavior and global economics.
This episode was produced by Sam Yellow Horse Kessler, edited by Jess Jiang, fact-checked by Sierra Juarez, engineered by Robert Rodriguez, and executive produced by Alex Goldmark.
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