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When Genius Failed: The Rise and Fall of Long-Term Capital Management
“A riveting account that reaches beyond the market landscape to say something universal about risk and triumph, about hubris and failure.”— The New York Times
NAMED ONE OF THE BEST BOOKS OF THE YEAR BY BUSINESSWEEK
In this business classic—now with a new Afterword in which the author draws parallels to the recent financial crisis—Roger Lowenstein captures the gripping roller-coaster ride of Long-Term Capital Management. Drawing on confidential internal memos and interviews with dozens of key players, Lowenstein explains not just how the fund made and lost its money but also how the personalities of Long-Term’s partners, the arrogance of their mathematical certainties, and the culture of Wall Street itself contributed to both their rise and their fall.
When it was founded in 1993, Long-Term was hailed as the most impressive hedge fund in history. But after four years in which the firm dazzled Wall Street as a $100 billion moneymaking juggernaut, it suddenly suffered catastrophic losses that jeopardized not only the biggest banks on Wall Street but the stability of the financial system itself. The dramatic story of Long-Term’s fall is now a chilling harbinger of the crisis that would strike all of Wall Street, from Lehman Brothers to AIG, a decade later. In his new Afterword, Lowenstein shows that LTCM’s implosion should be seen not as a one-off drama but as a template for market meltdowns in an age of instability—and as a wake-up call that Wall Street and government alike tragically ignored.
Praise for When Genius Failed
“[Roger] Lowenstein has written a squalid and fascinating tale of world-class greed and, above all, hubris.” —BusinessWeek
“Compelling . . . The fund was long cloaked in secrecy, making the story of its rise . . . and its ultimate destruction that much more fascinating.” — The Washington Post
“Story-telling journalism at its best.” — The Economist
NAMED ONE OF THE BEST BOOKS OF THE YEAR BY BUSINESSWEEK
In this business classic—now with a new Afterword in which the author draws parallels to the recent financial crisis—Roger Lowenstein captures the gripping roller-coaster ride of Long-Term Capital Management. Drawing on confidential internal memos and interviews with dozens of key players, Lowenstein explains not just how the fund made and lost its money but also how the personalities of Long-Term’s partners, the arrogance of their mathematical certainties, and the culture of Wall Street itself contributed to both their rise and their fall.
When it was founded in 1993, Long-Term was hailed as the most impressive hedge fund in history. But after four years in which the firm dazzled Wall Street as a $100 billion moneymaking juggernaut, it suddenly suffered catastrophic losses that jeopardized not only the biggest banks on Wall Street but the stability of the financial system itself. The dramatic story of Long-Term’s fall is now a chilling harbinger of the crisis that would strike all of Wall Street, from Lehman Brothers to AIG, a decade later. In his new Afterword, Lowenstein shows that LTCM’s implosion should be seen not as a one-off drama but as a template for market meltdowns in an age of instability—and as a wake-up call that Wall Street and government alike tragically ignored.
Praise for When Genius Failed
“[Roger] Lowenstein has written a squalid and fascinating tale of world-class greed and, above all, hubris.” —BusinessWeek
“Compelling . . . The fund was long cloaked in secrecy, making the story of its rise . . . and its ultimate destruction that much more fascinating.” — The Washington Post
“Story-telling journalism at its best.” — The Economist
264 pages, Paperback
First published January 1, 2000
About the author
Roger Lowenstein
24 books440 followersRoger Lowenstein is an American financial journalist and writer. He graduated from Cornell University and reported for The Wall Street Journal for more than a decade, including two years writing its Heard on the Street column, 1989 to 1991. Born in 1954, he is the son of Helen and Louis Lowenstein of Larchmont, New York. Lowenstein is married to Judith Slovin.
He is also a director of Sequoia Fund. In 2016, he joined the board of trustees of Lesley University. His father, the late Louis Lowenstein, was an attorney and Columbia University law professor who wrote books and articles critical of the American financial industry.
Roger Lowenstein's latest book, Ways and Means: Lincoln and His Cabinet and the Financing of the Civil War, was released on March 8, 2022, and won the 2022 Harold Holzer Lincoln Forum Book Prize.
He is also a director of Sequoia Fund. In 2016, he joined the board of trustees of Lesley University. His father, the late Louis Lowenstein, was an attorney and Columbia University law professor who wrote books and articles critical of the American financial industry.
Roger Lowenstein's latest book, Ways and Means: Lincoln and His Cabinet and the Financing of the Civil War, was released on March 8, 2022, and won the 2022 Harold Holzer Lincoln Forum Book Prize.
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February 14, 2011
Long Term Capital Management was a hedge fund made up of a group of former hotshot bond traders from Solomon Bros., together with some high powered financial academics (including two Nobel prize winners), and one former central banker. They were the biggest stars in the business, and they had all the arrogance and greed that you could possibly imagine. They also seemed to be as good as they thought themselves. In five years, they turned a billion dollars into 4.5 billion dollars. Then they lost it all in just a few months and came close to bringing down the financial sector in the process.
It's a great story, and Lowenstein tells it well. He makes the complicated trading structures fairly easy to understand. For example, he does a good job of explaining how a fund could go long or short on volatility in equities. And I'm not going to try to repeat that here.
There are two main themes here: first, is the arrogance and greed involved. This led LTCM to trade at leverage of 30:1, and even greater as they started to collapse. That means they were controlling about 120 billion dollars in assets when they had 4 billion in equity in the fund. And that didn't include their risks in more complicated derivatives. I'm not sure anyone knows what their exposure was there. The second main theme is the over-reliance on mathematical models. Here the models derive from the Black-Scholes method for pricing options (indeed, Scholes was a partner in LTCM). And these, in turn, stem from the efficient market hypothesis, and the random walk theory that goes along with it. In a nutshell, these theories are that the current price always reflects everything that is known, and that future moves in price are randomly distributed according to a bell curve.
There are a few ironies here. LTCM, who believed so firmly in the efficient market, did everything it possibly could to cut better deals with the banks who gave them financing, and with their clearing bank. In other words, they didn't simply go with the price that was better. One tactic they used was to cozy up to these people by inviting them to a posh golf club in Ireland owned by one of the partners. When dealing with their bankers, at least, they felt there was some room for market inefficiency.
Worse, for the first four years, the fund did unbelievably well. In all that time, the worst month they had was down 2.9%. The partners saw this as a pure confirmation of their method, and of their own genius. And they took this success as a justification for adding on even more leverage. But no-one, not even the book, seems to get that the early success was already a red flag that their models didn't work. The success they had was not something that their models would predict. The event that wiped out the company, according to their own models, was a 10 sigma event: it was something that might happen once in several lifetimes of the universe, but probably not. (It's worth noting that this 10 sigma event happened a second time the year after the company collapsed. So instead of once in forever, the event happened twice in just over a year.) But no-one has said how unlikely their success was according to their own models. It may not have been as unlikely as the collapse, but it was far from what anyone, including the partners, expected from the outset. In short, the firm lived through two black swan events. The first worked in their favor, as volatility shrank and shrank without so much as a hiccup for four years. And the second blew up the firm. My point is that they should have been paying attention to the first black swan event as well.
It's a great story, and Lowenstein tells it well. He makes the complicated trading structures fairly easy to understand. For example, he does a good job of explaining how a fund could go long or short on volatility in equities. And I'm not going to try to repeat that here.
There are two main themes here: first, is the arrogance and greed involved. This led LTCM to trade at leverage of 30:1, and even greater as they started to collapse. That means they were controlling about 120 billion dollars in assets when they had 4 billion in equity in the fund. And that didn't include their risks in more complicated derivatives. I'm not sure anyone knows what their exposure was there. The second main theme is the over-reliance on mathematical models. Here the models derive from the Black-Scholes method for pricing options (indeed, Scholes was a partner in LTCM). And these, in turn, stem from the efficient market hypothesis, and the random walk theory that goes along with it. In a nutshell, these theories are that the current price always reflects everything that is known, and that future moves in price are randomly distributed according to a bell curve.
There are a few ironies here. LTCM, who believed so firmly in the efficient market, did everything it possibly could to cut better deals with the banks who gave them financing, and with their clearing bank. In other words, they didn't simply go with the price that was better. One tactic they used was to cozy up to these people by inviting them to a posh golf club in Ireland owned by one of the partners. When dealing with their bankers, at least, they felt there was some room for market inefficiency.
Worse, for the first four years, the fund did unbelievably well. In all that time, the worst month they had was down 2.9%. The partners saw this as a pure confirmation of their method, and of their own genius. And they took this success as a justification for adding on even more leverage. But no-one, not even the book, seems to get that the early success was already a red flag that their models didn't work. The success they had was not something that their models would predict. The event that wiped out the company, according to their own models, was a 10 sigma event: it was something that might happen once in several lifetimes of the universe, but probably not. (It's worth noting that this 10 sigma event happened a second time the year after the company collapsed. So instead of once in forever, the event happened twice in just over a year.) But no-one has said how unlikely their success was according to their own models. It may not have been as unlikely as the collapse, but it was far from what anyone, including the partners, expected from the outset. In short, the firm lived through two black swan events. The first worked in their favor, as volatility shrank and shrank without so much as a hiccup for four years. And the second blew up the firm. My point is that they should have been paying attention to the first black swan event as well.
June 30, 2019
Lowenstein displays remarkable prescience. Not only is "When Genius Failed" a great read, it accurately foreshadows the "weapons of mass destruction" risks, to quote Warren Buffett, that would lead to the subprime meltdown and Great Recession. Reading this book, along with Kindleberger's "Manias, Panics, and Crashes" allowed me to foresee the Great Recession, steer clear, and avoid damage. It also helped me to better understand booms and busts in my own upcoming book "Cleantech Con Artists."
April 1, 2014
As a student of the efficient market idea I has always wondered what these guys were up to in more detail even after seeing the Nova program about the meltdown of Long Term Capital Management in 1998. This is an excellent book that explains as well as can be in a general work of literature less than 300 pages.
There are several lessons here, that apparently will not be learned.
Mathematical models are based on very good math with very many assumptions required to make the computations workable. The real world is under no obligation to stay within either the quantitative nor temporal boundaries required to survive an investment program based on these models in the applicable markets. The quote from Keynes applies "Markets can remain irrational longer than you can remain solvent". The technique employed by hedge fund such as Long Term only works by means of very large bets with very big leverage. Without these elements there is insufficient return compared to the costs and risk. Unfortunately leverage is a two edged sword, if leveraged 10 to 1, a 10% loss in the asset wipes out the investor. As things go wrong leverage increases as base equity declines. In the example, a 5% loss in the asset means a 50% loss to the investor. LTCM was leveraged 20-30 to 1 routinely, and of course much higher, eventually more than 100 to 1 as relentless losses hammered their capital.
Many events that affect investments are truly unpredictable both as to their source and their impact when they occur. For example, a little nation defaults or devalues. Maybe no big deal. If the little country defaults in the midst of a larger default by a larger nation (e.g. Russia) there might be a disproportionate effect larger than simple sum of the two together, especially if the world's largest players are margined up to the eyeballs on a different outcome when it happens. (or are tied together by a poorly understood network of derivative contracts that ostensibly hedge the risk, but in practice become linked together to become the rock that sinks the world.)
Crisis scenarios are poorly represented in such models which always are based on predicting the future based on the past. In a crisis, linkages occur that are not normally apparent, as the book says correlations converge to one. As it happens it was a self-delusion on the part of LTCM partners that there was any true diversity in their bets. While most were hedged, all were essentially the same bet made on similar goods in many locations. They were counting on diversity over thousands of positions to prevent my simple leverage example above from simply taking them out in short run of adverse market conditions. But as conditions deteriorated all of their trades suffered in unison and LTCM took the full force of leverage against its equity. Another non-mathematical fact is that their markets are a small place full of people not automatons. Once their distress started to become evident, trading behavior compounded their troubles. Although LTCM's secretiveness, arrogance and its deal making practices that skinned safety and profit to the bone for those who helped them finance their trades (e.g. Sholes' "warrant") would account for malicious trading designed to hit them when they were down that is not the main story. The main story is that their success spawned imitators, who had a two fold effect. One, it reduced the quantity and quality of the opportunities for which their models work as others sought out and bought the same opportunities. Two, when things started to go wrong the arbitrage departments of their lenders were trying to unload positions virtually identical to those held by LTCM flooding an inherently thin market leaving them no good way to liquidate their enormous holdings.
On top of that, they did not know when to quit. After a few years of great success when their choice market was decaying, partly due to their size and success in it. They looked for ways to apply the model to other investments that were a much poorer fit, and eventually started to make "directional" trades, a fancy term for ordinary speculation without any hedge at all, and still leveraged. You may know that buying stock in the US is limited to 2 to 1 leverage. LTCM got around this by use of complex derivatives that served as proxies for the actual stock that are not governed by that rule.
Summing up we have:
1. Sheer hubris.
2. Greed.
3. Plain foolishness (dealing in trades that do not fit the model, where LTCM has no expertise and no real edge, even in principle.
4. Reliance on defective technology.
When it all came apart, LTCM was bought out by a consortium of banks coordinated by the Federal Reserve with no public funds involved. The banks had to be persuaded to do this with great difficulty, since they had losing arbitrage units of their own and most figured they had less to lose by LTCM's immediate failure than the sum required for the buyout and a later failure. The fearful unknown that brought them around was what the effects of an LTCM failure would have on markets where their own stock had already lost 40-50%, and the very markets where they would have to unload their own LTCM wannabe positions in the near future in the midst of the massive liquidation of LTCM.
At the time this move was decried by many as something government should not do, or setting a bad example of a soft landing for the excesses of private enterprise in a free market. But note, that no public funds were used, it was only the prestige of the Fed that was used to create a private sector solution to a private sector problem.
Compare that to today when upwards of a trillion dollars of public money will be used to bail-out the damage caused by financial institutions, many the same banks that knowingly bet on LTCM despite the risk, as they went on to even larger and imprudent excesses in pursuit of profit without a sound basis for making it. The LTCM fiasco was a small dress rehearsal for the potential and realized consequences of massive, complex and poorly understood instruments and unsupervised, unregulated hedge funds, and reckless risk taking on the part of the financial community. The modern financial world is a 747 with one engine, no backup systems, and crew more than a bit unclear on how it works. Everything must work right all the time or there is a crash with little in between. It is an inherent problem. LTCM committed no crimes, no one went to jail, it cannot be dismissed as an isolated event due to a rogue operator (as when Russian oligarchs steal the IMF bailout money). This all happened with the best and brightest (and the most arrogant) following the latest principles completely within the law, with the blessing of the great Greenspan, and a maximal embodiment of the spirit of the "free market". It's cleaner than Enron (a rogue) but it still does not work.
There are several lessons here, that apparently will not be learned.
Mathematical models are based on very good math with very many assumptions required to make the computations workable. The real world is under no obligation to stay within either the quantitative nor temporal boundaries required to survive an investment program based on these models in the applicable markets. The quote from Keynes applies "Markets can remain irrational longer than you can remain solvent". The technique employed by hedge fund such as Long Term only works by means of very large bets with very big leverage. Without these elements there is insufficient return compared to the costs and risk. Unfortunately leverage is a two edged sword, if leveraged 10 to 1, a 10% loss in the asset wipes out the investor. As things go wrong leverage increases as base equity declines. In the example, a 5% loss in the asset means a 50% loss to the investor. LTCM was leveraged 20-30 to 1 routinely, and of course much higher, eventually more than 100 to 1 as relentless losses hammered their capital.
Many events that affect investments are truly unpredictable both as to their source and their impact when they occur. For example, a little nation defaults or devalues. Maybe no big deal. If the little country defaults in the midst of a larger default by a larger nation (e.g. Russia) there might be a disproportionate effect larger than simple sum of the two together, especially if the world's largest players are margined up to the eyeballs on a different outcome when it happens. (or are tied together by a poorly understood network of derivative contracts that ostensibly hedge the risk, but in practice become linked together to become the rock that sinks the world.)
Crisis scenarios are poorly represented in such models which always are based on predicting the future based on the past. In a crisis, linkages occur that are not normally apparent, as the book says correlations converge to one. As it happens it was a self-delusion on the part of LTCM partners that there was any true diversity in their bets. While most were hedged, all were essentially the same bet made on similar goods in many locations. They were counting on diversity over thousands of positions to prevent my simple leverage example above from simply taking them out in short run of adverse market conditions. But as conditions deteriorated all of their trades suffered in unison and LTCM took the full force of leverage against its equity. Another non-mathematical fact is that their markets are a small place full of people not automatons. Once their distress started to become evident, trading behavior compounded their troubles. Although LTCM's secretiveness, arrogance and its deal making practices that skinned safety and profit to the bone for those who helped them finance their trades (e.g. Sholes' "warrant") would account for malicious trading designed to hit them when they were down that is not the main story. The main story is that their success spawned imitators, who had a two fold effect. One, it reduced the quantity and quality of the opportunities for which their models work as others sought out and bought the same opportunities. Two, when things started to go wrong the arbitrage departments of their lenders were trying to unload positions virtually identical to those held by LTCM flooding an inherently thin market leaving them no good way to liquidate their enormous holdings.
On top of that, they did not know when to quit. After a few years of great success when their choice market was decaying, partly due to their size and success in it. They looked for ways to apply the model to other investments that were a much poorer fit, and eventually started to make "directional" trades, a fancy term for ordinary speculation without any hedge at all, and still leveraged. You may know that buying stock in the US is limited to 2 to 1 leverage. LTCM got around this by use of complex derivatives that served as proxies for the actual stock that are not governed by that rule.
Summing up we have:
1. Sheer hubris.
2. Greed.
3. Plain foolishness (dealing in trades that do not fit the model, where LTCM has no expertise and no real edge, even in principle.
4. Reliance on defective technology.
When it all came apart, LTCM was bought out by a consortium of banks coordinated by the Federal Reserve with no public funds involved. The banks had to be persuaded to do this with great difficulty, since they had losing arbitrage units of their own and most figured they had less to lose by LTCM's immediate failure than the sum required for the buyout and a later failure. The fearful unknown that brought them around was what the effects of an LTCM failure would have on markets where their own stock had already lost 40-50%, and the very markets where they would have to unload their own LTCM wannabe positions in the near future in the midst of the massive liquidation of LTCM.
At the time this move was decried by many as something government should not do, or setting a bad example of a soft landing for the excesses of private enterprise in a free market. But note, that no public funds were used, it was only the prestige of the Fed that was used to create a private sector solution to a private sector problem.
Compare that to today when upwards of a trillion dollars of public money will be used to bail-out the damage caused by financial institutions, many the same banks that knowingly bet on LTCM despite the risk, as they went on to even larger and imprudent excesses in pursuit of profit without a sound basis for making it. The LTCM fiasco was a small dress rehearsal for the potential and realized consequences of massive, complex and poorly understood instruments and unsupervised, unregulated hedge funds, and reckless risk taking on the part of the financial community. The modern financial world is a 747 with one engine, no backup systems, and crew more than a bit unclear on how it works. Everything must work right all the time or there is a crash with little in between. It is an inherent problem. LTCM committed no crimes, no one went to jail, it cannot be dismissed as an isolated event due to a rogue operator (as when Russian oligarchs steal the IMF bailout money). This all happened with the best and brightest (and the most arrogant) following the latest principles completely within the law, with the blessing of the great Greenspan, and a maximal embodiment of the spirit of the "free market". It's cleaner than Enron (a rogue) but it still does not work.
March 30, 2022
Still pertinent as ever....
Less a Science than Blind Faith
In 1999, the year before this book was published, my brother and I published a similar book, “The Internet Bubble” (HarperCollins). It was a Business Week bestseller for six months.
But that financial bubble and the crisis that followed was certainly not on the level of LTCM.
When our book was in the publishing pipeline word got back to me from an editor at Fortune magazine that the author of this book had started a book about the tech bubble, but changed course when he found out about our book. Well, good thing, because he went on to write this masterpiece.
When the original LTCM crisis happened I certainly heard about it, but never looked into the details until now. I was too busy covering the tech frenzy in Silicon Valley for Red Herring Magazine.
The concept of “efficient market hypothesis” immediately jumped out to me from this book.
"The efficient-market hypothesis (EMH) is a theory in financial economics that states that asset prices fully reflect all available information. It was developed by Eugene Fama who argued that investment instruments always trade at their fair value, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices."
Consequently, some economists claimed financial bubbles were impossible.
Others argued that it was a "new economy" and it was okay for stock prices to be way out of line relative to a company's value. We did the math. After Yahoo was added to the S&P 500 in early 2000, it's paper value almost doubled. We plugged that value into our spreadsheet and it showed that Yahoo would have to have $60 BILLION in revenue in five years to justify it's current stock price.
People would often bring up these theories regarding our book. I used to laugh and say: “Haven’t you read any history? Human beings are irrational.” (See tulip mania. See railroad stock speculation. See betting on bitcoin with no underlying value).
I am no expert on the nuances of bond trading LTCM was involved in, but I can recognize false assumptions when I see them.
The intricacies of LTCM's academically-driven system earned Myron Scholes and Robert Merton the Nobel Prize for Economics (it's actually the Swedish Bank Prize) in 1997, a year before their fund went into a free fall that almost brought down the world economy.
The author nails the problem in these three short excerpts....
“As the English essayist G. K. Chesterton wrote, life is "a trap for logicians" because it is almost reasonable but not quite; it is usually sensible but occasionally otherwise: "It looks just a little more mathematical and regular than it is; its exactitude is obvious, but its inexactitude is hidden; its wildness lies in wait”
“Lawrence Summers, now the U.S. Treasury secretary, told The Wall Street Journal after the crash, "The efficient market hypothesis is the most remarkable error in the history of economic theory.”
"After tech entrepreneur, Mitchell Kapor, took Merton's finance course, he decided that quantitative finance was less a science than a faith - a doctrine for ideologues "blinded by the power of the model." It appealed to intellectuals who craved a sense of order, but could lead them disastrously astray if markets moved outside the model.”
In the case of LTCM, what fell outside the model ended up being the fall of Asian markets and Russia following them. A crash resulted.
Such events are sometimes referred to as "black swans" because they deviate beyond what is normally expected of a situation and are extremely difficult to predict. Black swan events are typically random and unexpected.
The metaphor is taken from what Europeans saw upon their first arrival to Australia. They thought all swans were white, but were shocked to see black swans on that continent.
Our tech bubble book came out in November 1999 with a clear warning of what was ahead, but most people disagreed with us. We racked up one-star reviews on Amazon. Meanwhile, Myron Scholes had moved to San Francisco and became a lecturer at Stanford. But it seemed Scholes still hadn’t learned his lesson.
In the early months of 2000, I read an interesting snippet in a local paper about a Q & A session at Stanford after a lecture Scholes gave there. He was asked if there was a tech stock bubble and he said no. I sent a brief letter to the editor refuting his answer and it was published. Lo and behold, the prime market for tech stocks, NASDAQ, imploded two months later. The Noble Prize winner was wrong again.
Less a Science than Blind Faith
In 1999, the year before this book was published, my brother and I published a similar book, “The Internet Bubble” (HarperCollins). It was a Business Week bestseller for six months.
But that financial bubble and the crisis that followed was certainly not on the level of LTCM.
When our book was in the publishing pipeline word got back to me from an editor at Fortune magazine that the author of this book had started a book about the tech bubble, but changed course when he found out about our book. Well, good thing, because he went on to write this masterpiece.
When the original LTCM crisis happened I certainly heard about it, but never looked into the details until now. I was too busy covering the tech frenzy in Silicon Valley for Red Herring Magazine.
The concept of “efficient market hypothesis” immediately jumped out to me from this book.
"The efficient-market hypothesis (EMH) is a theory in financial economics that states that asset prices fully reflect all available information. It was developed by Eugene Fama who argued that investment instruments always trade at their fair value, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices."
Consequently, some economists claimed financial bubbles were impossible.
Others argued that it was a "new economy" and it was okay for stock prices to be way out of line relative to a company's value. We did the math. After Yahoo was added to the S&P 500 in early 2000, it's paper value almost doubled. We plugged that value into our spreadsheet and it showed that Yahoo would have to have $60 BILLION in revenue in five years to justify it's current stock price.
People would often bring up these theories regarding our book. I used to laugh and say: “Haven’t you read any history? Human beings are irrational.” (See tulip mania. See railroad stock speculation. See betting on bitcoin with no underlying value).
I am no expert on the nuances of bond trading LTCM was involved in, but I can recognize false assumptions when I see them.
The intricacies of LTCM's academically-driven system earned Myron Scholes and Robert Merton the Nobel Prize for Economics (it's actually the Swedish Bank Prize) in 1997, a year before their fund went into a free fall that almost brought down the world economy.
The author nails the problem in these three short excerpts....
“As the English essayist G. K. Chesterton wrote, life is "a trap for logicians" because it is almost reasonable but not quite; it is usually sensible but occasionally otherwise: "It looks just a little more mathematical and regular than it is; its exactitude is obvious, but its inexactitude is hidden; its wildness lies in wait”
“Lawrence Summers, now the U.S. Treasury secretary, told The Wall Street Journal after the crash, "The efficient market hypothesis is the most remarkable error in the history of economic theory.”
"After tech entrepreneur, Mitchell Kapor, took Merton's finance course, he decided that quantitative finance was less a science than a faith - a doctrine for ideologues "blinded by the power of the model." It appealed to intellectuals who craved a sense of order, but could lead them disastrously astray if markets moved outside the model.”
In the case of LTCM, what fell outside the model ended up being the fall of Asian markets and Russia following them. A crash resulted.
Such events are sometimes referred to as "black swans" because they deviate beyond what is normally expected of a situation and are extremely difficult to predict. Black swan events are typically random and unexpected.
The metaphor is taken from what Europeans saw upon their first arrival to Australia. They thought all swans were white, but were shocked to see black swans on that continent.
Our tech bubble book came out in November 1999 with a clear warning of what was ahead, but most people disagreed with us. We racked up one-star reviews on Amazon. Meanwhile, Myron Scholes had moved to San Francisco and became a lecturer at Stanford. But it seemed Scholes still hadn’t learned his lesson.
In the early months of 2000, I read an interesting snippet in a local paper about a Q & A session at Stanford after a lecture Scholes gave there. He was asked if there was a tech stock bubble and he said no. I sent a brief letter to the editor refuting his answer and it was published. Lo and behold, the prime market for tech stocks, NASDAQ, imploded two months later. The Noble Prize winner was wrong again.
August 13, 2018
Imagine losing US$5 billion in 5 weeks. This is the real-life account of how Long Term Capital Management, run by a bunch of the (supposedly) smartest guys in the world, including two Nobel laureates, went bust. It is a tale of recklessness and arrogance and most of all, lack of experience in real markets. It's also a good reminder to turn away and run whenever an academic tries to lecture you on how to trade the markets. The amazing thing is, some of these guys managed to "return from the dead" not once, but several times by starting new funds. I can't understand how any investor could still give them money to manage after the first debacle. I've even seen one of them going around giving TED Talks. Jeez.
This was a great read with not too many technicalities that non-financial readers would find difficult to digest. Anyway the technical explanations on markets and derivatives are not really essential to get the full benefit of the book.
This was a great read with not too many technicalities that non-financial readers would find difficult to digest. Anyway the technical explanations on markets and derivatives are not really essential to get the full benefit of the book.
June 2, 2018
This books gets three stars because it is a serviceable summary of its topic but is in now way outstanding. If you like finance, specifically statistical modeling and hedging strategies, you will find this tale of Nobel Prize hubris gone wrong because "muh models" didn't predict multiple standard deviation events intriguing. If you like reading about bad actors using arms of the federal government to engineer golden parachutes for them, you'll REALLY like this book.
What is tough about this book is that it is difficult to differentiate the personalities of a bunch of middle-aged finance guys. Thus, when there is some sort of conflict, we are SUPPOSED to remember that Harvard MBA #1 is timid while Wharton MBA#3 is assertive, but the average reader will find the many, many names in this book running together.
The definition of a three-star book.
What is tough about this book is that it is difficult to differentiate the personalities of a bunch of middle-aged finance guys. Thus, when there is some sort of conflict, we are SUPPOSED to remember that Harvard MBA #1 is timid while Wharton MBA#3 is assertive, but the average reader will find the many, many names in this book running together.
The definition of a three-star book.
November 24, 2015
(3.5) Eerily similar to a crisis almost exactly 10 years later
An interesting, well-told if brief account of the rise and fall of Long-Term Capital Management (you remember that one, don't you?). When things get heated it was along the lines of Sorkin's Too Big to Fail, but otherwise a decent treatment of the significant events in the life and death of LTCM.
Don't have too much more to share other than how prescient the following quotation (the book was written in 2000) was (or, perhaps how Wall Street is quick to forget the lessons of the past, or perhaps how Wall Street is building a great track record of huge compensation for finding and exploiting moral hazard):
"""
None other than Merrill Lynch ovservd in its annual report for 1998, "Merrill Lynch uses mathematical risk models to help estimate its exposure to market risk." In a phrase that suggested some slight dawning awareness of the dangers in such models, the bank added that they, "may provide a greater sense of security than warranted; therefore, the reliance on these models should be limited." If Wall Street is to learn just one less from the Long-Term debacle, it should be that. The next time a Merton proposes an elegant model to manage risks and foretell odds, the next time that a computer with perfect memory of the past is said to quantify risks in the future, investors should run--and quickly--the other way.
"""
Too bad they didn't when it came to CDOs and such. You really almost could've substituted collateralized debt obligations, credit default swaps and mortgage-backed securities in for interest rate swaps and equity volatility trades and the story runs pretty similar. Sad thing is that for the most recent crisis, we needed the additional participation of ratings agencies to perpetuate the whole charade. One would hope that with an additional historical near-crisis and organizations charged with evaluating risk of securities, we'd do a better job of avoiding bringing the financial world to ruin. Sigh.
An interesting, well-told if brief account of the rise and fall of Long-Term Capital Management (you remember that one, don't you?). When things get heated it was along the lines of Sorkin's Too Big to Fail, but otherwise a decent treatment of the significant events in the life and death of LTCM.
Don't have too much more to share other than how prescient the following quotation (the book was written in 2000) was (or, perhaps how Wall Street is quick to forget the lessons of the past, or perhaps how Wall Street is building a great track record of huge compensation for finding and exploiting moral hazard):
"""
None other than Merrill Lynch ovservd in its annual report for 1998, "Merrill Lynch uses mathematical risk models to help estimate its exposure to market risk." In a phrase that suggested some slight dawning awareness of the dangers in such models, the bank added that they, "may provide a greater sense of security than warranted; therefore, the reliance on these models should be limited." If Wall Street is to learn just one less from the Long-Term debacle, it should be that. The next time a Merton proposes an elegant model to manage risks and foretell odds, the next time that a computer with perfect memory of the past is said to quantify risks in the future, investors should run--and quickly--the other way.
"""
Too bad they didn't when it came to CDOs and such. You really almost could've substituted collateralized debt obligations, credit default swaps and mortgage-backed securities in for interest rate swaps and equity volatility trades and the story runs pretty similar. Sad thing is that for the most recent crisis, we needed the additional participation of ratings agencies to perpetuate the whole charade. One would hope that with an additional historical near-crisis and organizations charged with evaluating risk of securities, we'd do a better job of avoiding bringing the financial world to ruin. Sigh.
September 11, 2018
"They had forgotten the human factor." Sometimes 'vulgar Marxist' accounts of economics can be eerily similar to efficient markets theory because they assume a sort of natural outcome of exploitation and trading. This allows them to make simple predictions about the future. Yet people in markets continuously do things that aren't even in their narrow self-interest. And they do these things because of their personalities and prejudices. They are arrogant or bold or timid. You can't understand financial crises without digging into these more difficult and confusing issues of psychology. This book is pretty straightforward journalism but it makes one point very well - without considering relationships between people you can't understand why the most celebrated finance types in the world could make bets of a size that no reasonable person would otherwise ever agree to.
December 13, 2008
I started reading this book in summer of 2007 and then picked it up again this fall. In 1997 I was blithely running around France checking out art while this country's financial system nearly came to a halt, the Fed had to step in and major banks suffered huge losses as a result of hubris and lack of understanding the true risks they were taking. Lowenstein brilliantly takes us behind this scenes to unravel how real geniuses-- Long-Term's marketing strategy was touting the number of Nobel prize-winning economists they had on staff-- took on huge amounts on highly leveraged bets based on data that was fundamentally flawed (um, sound familiar?). In short, Long-Term bet on bond spreads, and that rational actors will buy and sell stocks and bonds in a more or less random pattern. Lowenstein never dismisses this idea entirely, but what he does show is how human behavior and the newly interconnectedness of global markets mean that the odds can go against your favor big time (again, sound familiar?) just as your money runs out. He also points out how other investment banks (Goldman in particular) were trying to go public so that they could place even more bets with shareholder money (one of the real crimes of this era). He then at the end goes on a (well justified) tirade against Greenspan (and this is written in the "Maestro" era) and the Fed's lack of oversight of the derivatives market and how this would lead to more government intervention. Lowenstein's book, published in 2000, was the warning bell. Well worth taking another look.
July 15, 2012
Too big to fail.... LTCM might have not been the first to be bailed out. It wasn't the last. However, it might have the dubious distinction of being possibly the only firm who had a lion’s share to play in what eventually turned into a global contagion. Read and re-read. Save for posterity.
The fund boys: Meriwether, the leader, Victor Haghani & Larry Hilibrand, the overbearing maverick traders, Profs Merton and Scholes, the Nobel laureates and tutors to the rest of the street and many others.
The Others: Corzine @ Goldman: Intentions unclear, ability unquestioned
Herb Allison @ Merrill: Early mover, chief negotiator, fall guy
Buffet: Yes, No, Missing
Sandy Weill: Salomon, travellers, Citi! Maintained a safe distance.
And humble folks @ Bear, UBS, Swiss Bank,
A must read for macro enthusiasts.
An example that 1) risks, even if measured cannot be contained always 2) Leverage amplifies the whiplash in times of trouble 3) Human ingenuity can cause and overcome a lot of problems 4) Genius can fail
The fund boys: Meriwether, the leader, Victor Haghani & Larry Hilibrand, the overbearing maverick traders, Profs Merton and Scholes, the Nobel laureates and tutors to the rest of the street and many others.
The Others: Corzine @ Goldman: Intentions unclear, ability unquestioned
Herb Allison @ Merrill: Early mover, chief negotiator, fall guy
Buffet: Yes, No, Missing
Sandy Weill: Salomon, travellers, Citi! Maintained a safe distance.
And humble folks @ Bear, UBS, Swiss Bank,
A must read for macro enthusiasts.
An example that 1) risks, even if measured cannot be contained always 2) Leverage amplifies the whiplash in times of trouble 3) Human ingenuity can cause and overcome a lot of problems 4) Genius can fail
December 27, 2020
Surprisingly read this book in 36 hours. Couldn’t put it down - the folly of over leveraged bond market trading was just too interesting for me to handle.
November 12, 2020
Absolutely riveting writing! Lowenstein writes about financial stories like Dan Brown writes his thrillers.
The book is on Long Term Capital Management, containing a bunch of math, computer and financial wizards who wanted to tame the market using statuses and probability. Add in two noble prize winners, champion traders and an ex-Federal Banker, and you have one of the most illustrious funds.
They strong armed everyone on the market, got the best deals, made a stunning portfolio and for the first 4 years, quadrupled their funds value.
But great rewards come with great risks, and underestimating risk is what led to LTCM’s downfall. Relying on Gaussian models and standard deviations as measures of uncertainty, they conjured a Gaussian world where every risk was quantified, but as they would later find out, erroneously.
What followed next was the greatest ever decline: the fund lost 92% in 6 weeks. Saying more would be spoiling one of the best stories I’ve read on the market. The two main emotions that a trader must fight are greed and fear. This taught me about both.
The book is on Long Term Capital Management, containing a bunch of math, computer and financial wizards who wanted to tame the market using statuses and probability. Add in two noble prize winners, champion traders and an ex-Federal Banker, and you have one of the most illustrious funds.
They strong armed everyone on the market, got the best deals, made a stunning portfolio and for the first 4 years, quadrupled their funds value.
But great rewards come with great risks, and underestimating risk is what led to LTCM’s downfall. Relying on Gaussian models and standard deviations as measures of uncertainty, they conjured a Gaussian world where every risk was quantified, but as they would later find out, erroneously.
What followed next was the greatest ever decline: the fund lost 92% in 6 weeks. Saying more would be spoiling one of the best stories I’ve read on the market. The two main emotions that a trader must fight are greed and fear. This taught me about both.
February 3, 2021
Models are bad!!
May 9, 2023
Factual and informative, I'll walk away from this book having learned about a company and a crisis I was rather ignorant of beforehand. I thought the book did a great job breaking down the technicality of the subject matter (though I wish it had incorporated more pictures or graphics). The book also did a great job characterizing and motivating the major players, though it was a struggle at the end where the sheer volume of names caused everyone to blur together. I wish the book had a updated epilogue for where the key players are 20 years later though.
August 20, 2014
Roger Lowenstein's book is a captivating look at what happens when even brilliant people rely on models and ignore the human element in investing. Their models did not take into consideration that when people are motivated by fear and greed, they are capable of extreme behavior. And as John Maynard Keynes is quoted as saying in the book, "Markets can remain irrational longer than you can remain solvent." LTCM discovered the truth of that statement too late.
LTCM earned great returns in the early years through the use of leverage, derivatives and easy credit terms from its banks. But when the market failed to behave as LTCM's models predicted they would, LTCM's leverage and large, illiquid trades caused them to quickly spiral downward. Even if they had ultimately been proven correct, they could not remain solvent long enough to benefit from their risky trades.
The story of LTCM, as told by Lowenstein, is fascinating. But the thing that intrigued me the most is that it does not appear that the Wall Street banks learned a lasting lesson from the debacle. In order to avoid systemic losses throughout the financial system, there were 14 banks that ultimately bailed out the LTCM fund, including firms like Lehman Brothers, Merrill Lynch, Chase, Goldman Sachs, Salomon Smith Barney, UBS, etc. These financial institutions saw firsthand the devastating losses that could occur due to overleveraging, excessive use of derivatives and providing easy credit terms to borrowers, and yet many of these same firms suffered severe losses in 2008 due to these very same factors. It does make you wonder if this cycle of greed and fear is bound to repeat itself, or if a new paradigm will emerge among financial institutions and regulators to prevent these meltdowns in the future.
LTCM earned great returns in the early years through the use of leverage, derivatives and easy credit terms from its banks. But when the market failed to behave as LTCM's models predicted they would, LTCM's leverage and large, illiquid trades caused them to quickly spiral downward. Even if they had ultimately been proven correct, they could not remain solvent long enough to benefit from their risky trades.
The story of LTCM, as told by Lowenstein, is fascinating. But the thing that intrigued me the most is that it does not appear that the Wall Street banks learned a lasting lesson from the debacle. In order to avoid systemic losses throughout the financial system, there were 14 banks that ultimately bailed out the LTCM fund, including firms like Lehman Brothers, Merrill Lynch, Chase, Goldman Sachs, Salomon Smith Barney, UBS, etc. These financial institutions saw firsthand the devastating losses that could occur due to overleveraging, excessive use of derivatives and providing easy credit terms to borrowers, and yet many of these same firms suffered severe losses in 2008 due to these very same factors. It does make you wonder if this cycle of greed and fear is bound to repeat itself, or if a new paradigm will emerge among financial institutions and regulators to prevent these meltdowns in the future.
November 10, 2015
I think that if I didn't work in the financial sector and didn't already find it rather fascinating, I would have rated this book a bit lower. Lowenstein shows a command of the subject (which is no small feat for someone not in the industry) but the writing itself was just a bit too cold and clinical to consistently hold my attention. The figures mentioned in the book are staggering (trillions and billions are thrown around freely) as are the number of players involved in the rise and fall of LTCM. After a while one's head starts spinning and one hasn't even started to pierce the intricacies of how the hedge fund was conducting business!
As this book is now 15 years old, it was interesting to view it against the backdrop of the financial crisis of 2008. Many would say that LTCM is now just a footnote when viewed today, but I rather like to think of it more as a warning sign that should have been heeded prior to the financial crisis. We tend to think that the notion of "too big to fail" was a concept that was born as a result of the federal bailout of AIG during the financial crisis, but bailouts had occurred at least dating back to the savings and loan collapse in the 1980s and more recently, to LTCM. As the author says late in the book, Wall Street tends not to learn lessons, no matter how financially or publicly painful they might be.
"Past performance is not necessarily indicative of future performance." This mantra of financial markets was eschewed by the gurus at LTCM and this book thoroughly explains the early payoffs and late demise of their hedge fund. A must read for industry professionals, though readers with only a passing interest or knowledge of the derivatives market will find it difficult to keep up.
As this book is now 15 years old, it was interesting to view it against the backdrop of the financial crisis of 2008. Many would say that LTCM is now just a footnote when viewed today, but I rather like to think of it more as a warning sign that should have been heeded prior to the financial crisis. We tend to think that the notion of "too big to fail" was a concept that was born as a result of the federal bailout of AIG during the financial crisis, but bailouts had occurred at least dating back to the savings and loan collapse in the 1980s and more recently, to LTCM. As the author says late in the book, Wall Street tends not to learn lessons, no matter how financially or publicly painful they might be.
"Past performance is not necessarily indicative of future performance." This mantra of financial markets was eschewed by the gurus at LTCM and this book thoroughly explains the early payoffs and late demise of their hedge fund. A must read for industry professionals, though readers with only a passing interest or knowledge of the derivatives market will find it difficult to keep up.
December 31, 2020
Everyone has their own opinion on what should be under compulsory literature at school. Here's mine: finance students should all read When Genius Failed. I was taught in university about the Bell curve, Black-Scholes option pricing formula, and all other various ways on how to assess risk and return. It is human nature to seek certainty, or the ability to assess probabilities. In financial markets this has been so for decades, but we do not seem to be any closer to the answer today than we were 30 years ago.
Markets are inherently unpredictable, and wild swings that sometimes do not even seem to have an underlying reason happen once in a while. No formula is able to accommodate for that, no matter how high the IQ of the person who put it together. Thus, the models become dangerous. We seek guidance where we can't find it. We bet houses on things that seem to be *certain*. Until something unexpected happens. Then we explain that this unexpected thing had never happened before! It was a hundred year flood, apparently. Somehow these hundred-year-floods happen every 5-10 years, sometimes more often. Memory is a fragile thing.
Markets are inherently unpredictable, and wild swings that sometimes do not even seem to have an underlying reason happen once in a while. No formula is able to accommodate for that, no matter how high the IQ of the person who put it together. Thus, the models become dangerous. We seek guidance where we can't find it. We bet houses on things that seem to be *certain*. Until something unexpected happens. Then we explain that this unexpected thing had never happened before! It was a hundred year flood, apparently. Somehow these hundred-year-floods happen every 5-10 years, sometimes more often. Memory is a fragile thing.
September 10, 2015
O livro levanta dois questionamentos interessantes:
1) até que ponto os modelos de risco que se utilizam do passado para tentar prever o futuro conseguem ser úteis em momentos de grande irracionalidade nos mercados?
2) o salvamento organizado pelo FED não poderia dar espaço para Moral Hazard no futuro?
Bem, acho que a crise de 2008 nos dá algumas respostas para isso....
1) até que ponto os modelos de risco que se utilizam do passado para tentar prever o futuro conseguem ser úteis em momentos de grande irracionalidade nos mercados?
2) o salvamento organizado pelo FED não poderia dar espaço para Moral Hazard no futuro?
Bem, acho que a crise de 2008 nos dá algumas respostas para isso....
November 4, 2012
It works until it doesn't. Hard to believe that after LTCM's fall John Meriwether went on to found a new firm, JWM Partners, which, not surprisingly, blew up in the 2008-2009 downturn. What is surprising? In 2010, he founded a third firm, JM Advisors Management; so much for high-water marks.
December 21, 2020
like a michael lewis book but without the sex. i was left wondering what the fuck was going on at all times. the epilogue was clear, but not enough to save the book. financial reporting needs to do better.
April 1, 2020
Can’t believe this is my first book for 2020😂
May 2, 2012
NOTE: this "review" is less about what I thought of the book, and more about what the book itself is about. So - spoiler alert?
It's All About the Fund
As the title suggests, "When Genius Fails" is about the "Rise and Fall of Long-Term Capital Management." Don't expect to learn why the economy itself went to shit, causing LTCM to lose ungodly sums of money. The main character of this tale is the fund itself, and Lowenstein does a fine job of documenting its meteoric rise and catastrophic fall.
LTCM began as the "largest startup of all time"; the first round of fundraising weighed in at $1.25B. Started by John Meriwether and a group of quants, LTCM's strategy was to find arbitrage opportunities and magnify them using a tremendous amount of leverage. Lowenstein does a pretty good job of explaining LTCM's various trading strategies.
Bond Arbitrage
Initially, LTCM engaged primarily in "bond arbitrage"; they would search the markets for unusually large spreads between treasury bills and futures on those bills. If a spread seemed too large, LTCM would buy the futures, sell the bills, and wait for the spread to converge. At this point they would liquidate their positions and take home a nice, "riskless" profit.
Risk vs. Uncertainty
Now, nothing is "riskless," and this is especially true in financial markets. The book does a good job of explaining why. The reason has to do with the difference between risk ("will there be an earthquake tomorrow?') and uncertainty ("will the coin land heads or tails?").The difference here is that while we don't know how the coin will land, we can exactly specify the odds: it's 50/50. On the other hand, it's unclear what the "odds" of an earthquake occurring tomorrow are. We can examine geological data, examine historical records, and so on, but it's unclear exactly how this risk should be quantified.
The primary mistake of LTCM, according to the author, was to mistakenly equate risk with uncertainty. In this case, "risk" refers to the fact that we don't know what the price of securities will be in the future. More specifically, the traders at LTCM looked at past volatility and assumed that future volatility would be the same. They assumed that predicting the future price of a security is like predicting the outcome of a coin flip: though we don't know what will happen, we do know what the distribution of outcomes looks like. However, predicting the future price of securities is more like predicting an earthquake – that is, we don't really know what the distributions of outcomes looks like.
Uncertain Assumptions
Many of LTCM's models were based assumptions that are commonly made in mathematical finance:
- volatility is constant over time
- prices change in continuous time
- the distribution of returns is given by a lognormal distribution
- returns are independently and identically distributed
These are common assumptions; they simplify models, make calculations tractable, and are often quite accurate. The keyword here is "often." The problem with LTCM was that they took these assumptions very seriously. Under these assumptions, their strategies were calculated to be incredibly non-risky. And for a couple years, while the economy was chillin', the modeling assumptions seemed to apply, and LTCM made insane amounts of money.
Beyond Bond Arbitrage
Before long, LTCM wasn't the only kid on the block engaging in bond arbitrage, which meant that opportunities started drying up. Sitting on mountains of unused cash, LTCM had to branch out, and started engaging in new strategies. These included
- Merger Arbitrage: betting that an announced acquisition would close, meaning that the stock prices of the two merging companies would become the same
- Purchasing exotic bonds from countries like Russia
- Betting on equity volatility: one of the things that dictates the price of an option is the presumed volatility of the underlying asset. LTCM made bets that this "presumed volatility" (as implied by option prices) was too high
All Goes to Shit
And then, a couple of "earthquakes" hit. Russia defaulted on its debt (there go those exotic bonds); spreads on bonds began to widen; and equity volatility kept going up. The shit of a couple of countries around the world hit the fan, and the world economy was affected to an unprecedented and unexpected extent.
Too Much Leverage
Now, this might not have been an issue: though spreads kept widening and volatility kept going up, LTCM, in theory, could have just sat on its assets and waited for everything to settle down. In practice, they were leveraged at more than 30:1, and thus as their positions dropped, they had to start paying out.
And their positions continued to drop – to extremes that their models predicted shouldn't occur in more than once every couple of lifetimes of the universe. It turns out that in times of crisis, returns are not independent and identically distributes; prices aren't continuous; and volatility isn't constant. Indeed, returns are not lognormally distributed – they have fat tails, allowing for extreme outcomes that are much more likely to occur than a normal distribution would predict. In good times, LTCMs returns were compounded by its insane leverage; in bad times, its losses were magnified.
The Fed Steps In
In less than 5 weeks, LTCM would go on to lose more than 3.6 billion of their money. They were on the verge of going under, and – with $100 billion in assets under management and $1 trillion in derivative exposure – they were going to do some serious damage to the various banks that had lent them money. Thus, the fed stepped in. The federal reserve got together some 15 banks, and asked them to piece together some $4 billion to buy LTCM – in effect, it asked the banks to get together and "bail the hedge fund out."
Now, here an important point that I've always misunderstood and that has been inaccurately portrayed by the media: the fed did not bail out LTCM. The fed simply organized the bailout committee. In other words, it was not taxpayer money that financed the bailout. The extent to which this has been underemphasized by the media is ridiculous.
Surveying the Damage
These 15 or so banks accumulated $3.65 billion, and essentially bought the fund out (they did this to avoid the damage they would have incurred had it gone down in a firesale). I was always under the impression that most of LTCM's losses resulted from Russia defaulting on its debt. And indeed, LTCM lost $420M on Russia. But they lost much more betting on swaps – $1.6B – and almost as much betting on volatility – $1.3B. Altogether, LTCM lost most than $4.5B, $3.6B of which they lost over the course of 5 weeks. Over the course of four years, a dollar invested quadrupled to $4.11. Less than five months later, this same dollar was worth only 30 cents.
Final Comments
Lowenstein is a good writer, and this account is entertaining throughout. I was hoping for some more context – you don't get a good sense for what was happening in the economy at large during this time –but as far as LTCM's story is concerned, you get the full scoop. If you don't much care about what happened to Long Term Capital Management, you won't mush care for this book – but if you've even a passing interest, it's a surprisingly assessable and pretty entertaining account.
It's All About the Fund
As the title suggests, "When Genius Fails" is about the "Rise and Fall of Long-Term Capital Management." Don't expect to learn why the economy itself went to shit, causing LTCM to lose ungodly sums of money. The main character of this tale is the fund itself, and Lowenstein does a fine job of documenting its meteoric rise and catastrophic fall.
LTCM began as the "largest startup of all time"; the first round of fundraising weighed in at $1.25B. Started by John Meriwether and a group of quants, LTCM's strategy was to find arbitrage opportunities and magnify them using a tremendous amount of leverage. Lowenstein does a pretty good job of explaining LTCM's various trading strategies.
Bond Arbitrage
Initially, LTCM engaged primarily in "bond arbitrage"; they would search the markets for unusually large spreads between treasury bills and futures on those bills. If a spread seemed too large, LTCM would buy the futures, sell the bills, and wait for the spread to converge. At this point they would liquidate their positions and take home a nice, "riskless" profit.
Risk vs. Uncertainty
Now, nothing is "riskless," and this is especially true in financial markets. The book does a good job of explaining why. The reason has to do with the difference between risk ("will there be an earthquake tomorrow?') and uncertainty ("will the coin land heads or tails?").The difference here is that while we don't know how the coin will land, we can exactly specify the odds: it's 50/50. On the other hand, it's unclear what the "odds" of an earthquake occurring tomorrow are. We can examine geological data, examine historical records, and so on, but it's unclear exactly how this risk should be quantified.
The primary mistake of LTCM, according to the author, was to mistakenly equate risk with uncertainty. In this case, "risk" refers to the fact that we don't know what the price of securities will be in the future. More specifically, the traders at LTCM looked at past volatility and assumed that future volatility would be the same. They assumed that predicting the future price of a security is like predicting the outcome of a coin flip: though we don't know what will happen, we do know what the distribution of outcomes looks like. However, predicting the future price of securities is more like predicting an earthquake – that is, we don't really know what the distributions of outcomes looks like.
Uncertain Assumptions
Many of LTCM's models were based assumptions that are commonly made in mathematical finance:
- volatility is constant over time
- prices change in continuous time
- the distribution of returns is given by a lognormal distribution
- returns are independently and identically distributed
These are common assumptions; they simplify models, make calculations tractable, and are often quite accurate. The keyword here is "often." The problem with LTCM was that they took these assumptions very seriously. Under these assumptions, their strategies were calculated to be incredibly non-risky. And for a couple years, while the economy was chillin', the modeling assumptions seemed to apply, and LTCM made insane amounts of money.
Beyond Bond Arbitrage
Before long, LTCM wasn't the only kid on the block engaging in bond arbitrage, which meant that opportunities started drying up. Sitting on mountains of unused cash, LTCM had to branch out, and started engaging in new strategies. These included
- Merger Arbitrage: betting that an announced acquisition would close, meaning that the stock prices of the two merging companies would become the same
- Purchasing exotic bonds from countries like Russia
- Betting on equity volatility: one of the things that dictates the price of an option is the presumed volatility of the underlying asset. LTCM made bets that this "presumed volatility" (as implied by option prices) was too high
All Goes to Shit
And then, a couple of "earthquakes" hit. Russia defaulted on its debt (there go those exotic bonds); spreads on bonds began to widen; and equity volatility kept going up. The shit of a couple of countries around the world hit the fan, and the world economy was affected to an unprecedented and unexpected extent.
Too Much Leverage
Now, this might not have been an issue: though spreads kept widening and volatility kept going up, LTCM, in theory, could have just sat on its assets and waited for everything to settle down. In practice, they were leveraged at more than 30:1, and thus as their positions dropped, they had to start paying out.
And their positions continued to drop – to extremes that their models predicted shouldn't occur in more than once every couple of lifetimes of the universe. It turns out that in times of crisis, returns are not independent and identically distributes; prices aren't continuous; and volatility isn't constant. Indeed, returns are not lognormally distributed – they have fat tails, allowing for extreme outcomes that are much more likely to occur than a normal distribution would predict. In good times, LTCMs returns were compounded by its insane leverage; in bad times, its losses were magnified.
The Fed Steps In
In less than 5 weeks, LTCM would go on to lose more than 3.6 billion of their money. They were on the verge of going under, and – with $100 billion in assets under management and $1 trillion in derivative exposure – they were going to do some serious damage to the various banks that had lent them money. Thus, the fed stepped in. The federal reserve got together some 15 banks, and asked them to piece together some $4 billion to buy LTCM – in effect, it asked the banks to get together and "bail the hedge fund out."
Now, here an important point that I've always misunderstood and that has been inaccurately portrayed by the media: the fed did not bail out LTCM. The fed simply organized the bailout committee. In other words, it was not taxpayer money that financed the bailout. The extent to which this has been underemphasized by the media is ridiculous.
Surveying the Damage
These 15 or so banks accumulated $3.65 billion, and essentially bought the fund out (they did this to avoid the damage they would have incurred had it gone down in a firesale). I was always under the impression that most of LTCM's losses resulted from Russia defaulting on its debt. And indeed, LTCM lost $420M on Russia. But they lost much more betting on swaps – $1.6B – and almost as much betting on volatility – $1.3B. Altogether, LTCM lost most than $4.5B, $3.6B of which they lost over the course of 5 weeks. Over the course of four years, a dollar invested quadrupled to $4.11. Less than five months later, this same dollar was worth only 30 cents.
Final Comments
Lowenstein is a good writer, and this account is entertaining throughout. I was hoping for some more context – you don't get a good sense for what was happening in the economy at large during this time –but as far as LTCM's story is concerned, you get the full scoop. If you don't much care about what happened to Long Term Capital Management, you won't mush care for this book – but if you've even a passing interest, it's a surprisingly assessable and pretty entertaining account.
June 12, 2021
Can a tightening of regulation prevent the next LTCM? Possibly, but complex financial products keep coming up in the name of derivatives. Esoteric financial models, such as Black–Scholes model, are useful in many industries that wish to hedge risks. My take from this detailed account of the LTCM debacle is that when genius failed, there were limited consequences. Wall Street can take risks because even the disgraced boys can move on with their lives and have another go at an adventure that may cause havoc to the rest of the world.
July 8, 2022
The book narrates the failure of Long Term Capital Management principally due to the obstinate reliance upon financial models and a ridiculous amount of leverage. High leverage no matter how smart or accurate a model or a strategy is, eventually ends in failure. The hedge fund included academic superstars and Nobel price winners, the so called geniuses: Myron Scholes and Robert Merton, champions of the Efficient Market Hypothesis (EMH). Even though markets, crisis after crisis, have proved to be inefficient and irrational, EMH, its models and assumptions are still taught in finance. Students are seldom told about the risks in such models and assumptions. This book was a very interesting and insightful read, and I recommend it to anyone interested in the topic.
January 16, 2023
Really interesting look at what now feels like a practice run for the 2008 financial crisis (and, undoubtedly, our next financial crisis too). I don’t think much in here will be a revelation to those familiar with what happened in 2008, but it’s still pretty fascinating to read a book written in 2000 that has no idea just how relevant it’s about to become. The author does a good job introducing all the various personalities and giving a sense of their role in the crisis without getting bogged down in needless biographical details.
I think readers need some level of existing knowledge about how derivatives and other financial instruments work, because although the author gives some explanation of concepts like margin and yield, there’s a lot you’re presumed to already know.
I think readers need some level of existing knowledge about how derivatives and other financial instruments work, because although the author gives some explanation of concepts like margin and yield, there’s a lot you’re presumed to already know.
June 8, 2023
Beach reading during my vacation. I don’t know why I’m addicted to reading about hedge funds and their declines. I barely understand the instruments described and the bets they made. But I guess this is my version of ‘dick lit’ that I just love to hate.
October 22, 2020
"The efficient market hypothesis is the most remarkable error in the history of economic theory.”
When you believe that you have achieved the impossible (AKA believing you can manage complexity) and become blind to any of the factors that don't fit or conflict with your statistical model and then also manage to convince the mob (Wall Street) of the lie let greed to amplify it almost without limit until you are about to collapse the world economy as a whole... When reading about the development of this issue in retrospective it seems unbelievable that it could develop so far without any correction but such things happen if we continuously erode what is considered tolerable. I would say that we can see similar situation with stock markets euphoria VS COVID19 reality today or in the crisis of liberal democracy VS extreme nationalism and protectionism.
I would call the book quite "heavy" in strong quotes and statements that would take time and effort to properly digest all the relations and implications (except for insiders), definitely very relevant reminder in today's world.
“If Wall Street is to learn just one lesson from the Long-Term debacle, it should be that. The next time a Merton proposes an elegant model to manage risks and foretell odds, the next time a computer with a perfect memory of the past is said to quantify risks in the future, investors should run—and quickly—the other way. On Wall Street, though, few lessons remain learned.”
“As Keynes observed, there cannot be "liquidity" for the community as a whole. The mistake is in thinking that markets have a duty to stay liquid or that buyers will always be present to accommodate sellers. The real culprit in 1994 was leverage. If you aren't in debt, you can't go broke and can't be made to sell, in which case "liquidity" is irrelevant. But a leveraged firm may be forced to sell, lest fast-accumulating losses put it out of business. Leverage always gives rise to this same brutal dynamic, and its dangers cannot be stressed too often.”
“As Peter Bernstein has written, nature's pattern emerges only from the chaotic disorder of many random events.”
“But after Kapor took Merton's finance course, he decided that quantitative finance was less a science than a faith - a doctrine for ideologues "blinded by the power of the model." It appealed to intellectuals who craved a sense of order but could lead them disastrously astray if markets moved outside the model.”
“Merton ... humbly warned, however, "It's a wrong perception to believe that you can eliminate risk just because you can measure it.”
“And in the late summer of 1998, the bond-trading crowd was extremely fearful, especially of risky credits. The professors hadn't modeled this. They had programmed the market for a cold predictability that it had never had; they had forgotten the predatory, acquisitive, and overwhelming protective instincts that govern real-life traders. They had forgotten the human factor.”
When you believe that you have achieved the impossible (AKA believing you can manage complexity) and become blind to any of the factors that don't fit or conflict with your statistical model and then also manage to convince the mob (Wall Street) of the lie let greed to amplify it almost without limit until you are about to collapse the world economy as a whole... When reading about the development of this issue in retrospective it seems unbelievable that it could develop so far without any correction but such things happen if we continuously erode what is considered tolerable. I would say that we can see similar situation with stock markets euphoria VS COVID19 reality today or in the crisis of liberal democracy VS extreme nationalism and protectionism.
I would call the book quite "heavy" in strong quotes and statements that would take time and effort to properly digest all the relations and implications (except for insiders), definitely very relevant reminder in today's world.
“If Wall Street is to learn just one lesson from the Long-Term debacle, it should be that. The next time a Merton proposes an elegant model to manage risks and foretell odds, the next time a computer with a perfect memory of the past is said to quantify risks in the future, investors should run—and quickly—the other way. On Wall Street, though, few lessons remain learned.”
“As Keynes observed, there cannot be "liquidity" for the community as a whole. The mistake is in thinking that markets have a duty to stay liquid or that buyers will always be present to accommodate sellers. The real culprit in 1994 was leverage. If you aren't in debt, you can't go broke and can't be made to sell, in which case "liquidity" is irrelevant. But a leveraged firm may be forced to sell, lest fast-accumulating losses put it out of business. Leverage always gives rise to this same brutal dynamic, and its dangers cannot be stressed too often.”
“As Peter Bernstein has written, nature's pattern emerges only from the chaotic disorder of many random events.”
“But after Kapor took Merton's finance course, he decided that quantitative finance was less a science than a faith - a doctrine for ideologues "blinded by the power of the model." It appealed to intellectuals who craved a sense of order but could lead them disastrously astray if markets moved outside the model.”
“Merton ... humbly warned, however, "It's a wrong perception to believe that you can eliminate risk just because you can measure it.”
“And in the late summer of 1998, the bond-trading crowd was extremely fearful, especially of risky credits. The professors hadn't modeled this. They had programmed the market for a cold predictability that it had never had; they had forgotten the predatory, acquisitive, and overwhelming protective instincts that govern real-life traders. They had forgotten the human factor.”
January 30, 2021
This book is incredibly enlightening. The history of LTCM offers invaluable lessons about the fundamental characteristics of human nature through the financial world.
Pride, arrogance, greed and confidence are crystal clear in the conduct of Meriwether and his associates. They were doing the best trades in the market, with the most robust theoretical backing. Nevertheless, life does not follow the normal distribution, and uncertainty can not be mitigated. A series of unpredictable events will bring the fall of LTCM and almost all of Wall Street with it.*
As for the writing, Lowenstein masterfully aggregates multiple accounts of the events and leaves the reader utterly engrossed. I have given it 4 stars because the book misses more explanations to make it accessible to the broad public and the layperson.
*As a side note, it's interesting to learn about how the FED acts in such cases.
Pride, arrogance, greed and confidence are crystal clear in the conduct of Meriwether and his associates. They were doing the best trades in the market, with the most robust theoretical backing. Nevertheless, life does not follow the normal distribution, and uncertainty can not be mitigated. A series of unpredictable events will bring the fall of LTCM and almost all of Wall Street with it.*
As for the writing, Lowenstein masterfully aggregates multiple accounts of the events and leaves the reader utterly engrossed. I have given it 4 stars because the book misses more explanations to make it accessible to the broad public and the layperson.
*As a side note, it's interesting to learn about how the FED acts in such cases.
March 18, 2024
If you owe the bank $100, that's your problem. If you owe them $100m... that's their problem. Add 3 zeros and you've got Long Term Capital Management. With $100b in assets, a 25 to 1 leverage ratio and panicked markets, LTCM threatened to bring down the whole of Wall Street forcing the Fed to intervene and orchestrate a bailout.
With wit and lightness, Roger Lowenstein recounts the frenzy story of John Meriwether and his boys; how they came to create Long Term Capital Management, amass eye-watering returns for their investors and epically lost everything in a matter of months. Paired with 2 Nobel prize winners, Merton and Scholes, who would have thought that the brightest minds on Wall Street would fail with such panache? In some ways, Wall Street is a never ending play of bigheaded, witty and ambitious characters all fighting for the last word. If that’s your kind of show, When Genius Failed is your front row ticket.
With wit and lightness, Roger Lowenstein recounts the frenzy story of John Meriwether and his boys; how they came to create Long Term Capital Management, amass eye-watering returns for their investors and epically lost everything in a matter of months. Paired with 2 Nobel prize winners, Merton and Scholes, who would have thought that the brightest minds on Wall Street would fail with such panache? In some ways, Wall Street is a never ending play of bigheaded, witty and ambitious characters all fighting for the last word. If that’s your kind of show, When Genius Failed is your front row ticket.
April 4, 2017
At first, the book did not feel that easy to read: price-to-equity ratios, risk multipliers, derivatives, swap contracts... But the more I read the more it felt like a financial thriller, only more captivating and eye-opening.
The book tells the story of a darling of the Wall Street in the 1990s, the firm that attracted awe of investors, financial regulators, academia and business leaders in general. The firm which was called Long-Term Capital Management was established and ran by the cream of the cream in the U.S. financial industry and financial education. Its investment placements were based on sophisticated mathematical models developed largely by the founders themselves. The partners managed to raise huge amount of investment in a very short time (because everyone else was blindfolded by the partners' credentials) making it one of the most successful start-ups in history. At certain moments, the firm was managing rather astronomical volumes of investments.
And then it all failed. It required an unlikely cooperation of the largest Wall Street banks to avoid a larger financial shock, similar to what happened in 2008 after the fall of Lehman.
There are many lessons to draw from this book:
Financial lessons:
- There is a big difference between investing and gambling. Similarity is that the risk is involved in both.
- Quantifying and estimating risks does not equal avoiding them- one should not mix up these two
Management/business lessons:
- An assembled dream team is the best one can make - it would attract the other dream players, clients and investors alike. Everyone wants to be part of success and it is contagious
- Loyalty and companionship is something that can and shall be fostered
- Risk-taking in a company shall be checked and balanced (to a certain extent)
Personal lessons:
- Greed and hubris have their big limits - you can only go further that much with them
A great example of how a book based on investigative journalism shall be written.
The book tells the story of a darling of the Wall Street in the 1990s, the firm that attracted awe of investors, financial regulators, academia and business leaders in general. The firm which was called Long-Term Capital Management was established and ran by the cream of the cream in the U.S. financial industry and financial education. Its investment placements were based on sophisticated mathematical models developed largely by the founders themselves. The partners managed to raise huge amount of investment in a very short time (because everyone else was blindfolded by the partners' credentials) making it one of the most successful start-ups in history. At certain moments, the firm was managing rather astronomical volumes of investments.
And then it all failed. It required an unlikely cooperation of the largest Wall Street banks to avoid a larger financial shock, similar to what happened in 2008 after the fall of Lehman.
There are many lessons to draw from this book:
Financial lessons:
- There is a big difference between investing and gambling. Similarity is that the risk is involved in both.
- Quantifying and estimating risks does not equal avoiding them- one should not mix up these two
Management/business lessons:
- An assembled dream team is the best one can make - it would attract the other dream players, clients and investors alike. Everyone wants to be part of success and it is contagious
- Loyalty and companionship is something that can and shall be fostered
- Risk-taking in a company shall be checked and balanced (to a certain extent)
Personal lessons:
- Greed and hubris have their big limits - you can only go further that much with them
A great example of how a book based on investigative journalism shall be written.
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