Asset-backed oversold? Paulson ready to get back in!

John Paulson made $15 billion for his fund ($3.7 billion for himself!) betting against subprime securities last year. Now Bloomberg reports that he’s ready to get back in on the upside!

I’m as dismayed as anyone else about taxpayer dollars going to bail out mortgage holders, commercial banks and the GSE’s (Fannie, Freddie). I complained about Fannie back in 2004 when Franklin Raines was still CEO and the story first got out about their smoothing of earnings and use of derivatives accounting.

But, on the other hand, maybe Uncle Sam can actually generate positive return by buying oversold securities! Rumor says that current prices of subprime mortgage backed securities suggest implied default rates which are unrealistically high (e.g., like 50% !). Barring a complete economic meltdown these assets are underpriced and will generate a handsome return for an intelligent investor willing to take some risk. Is Uncle Sam smart? Let’s hope that the other Paulson negotiates some upside for us taxpayers in any bailout organized by the Treasury.

Bloomberg: John Paulson, the money manager whose wagers against the U.S. housing market helped him earn an estimated $3.7 billion last year, is now seeking to profit from Wall Street’s search for capital to offset mortgage writedowns.

Paulson plans to open a hedge fund by December that will provide capital to the world’s biggest banks and brokers as they add to the $345 billion they’ve raised in the past year, according to two people with knowledge of the matter. His Paulson & Co., which oversees $33 billion, hasn’t set a size target for the fund, said the people, who declined to be identified because the plans aren’t final.

The New York-based firm’s credit funds rose as much as sixfold last year, helped by bets that rising defaults on subprime home loans would pummel the value of mortgage-backed securities. The meltdown has forced the world’s biggest banks and securities firms to take $467 billion in asset write-offs and credit losses and led to the collapse of Bear Stearns Cos.

“Investors who are able to make money in a declining market and then rapidly turn around and profit from a rising market is highly unusual,” said Thomas Whelan, president of Greenwich, Connecticut-based Greenwich Alternative Investments, which advises clients on investing in hedge funds.

Paulson declined to comment. His 2007 earnings made him the highest-paid hedge-fund manager, according to Institutional Investor’s Alpha magazine.

The New Math

Alpha magazine has a long article on the current state of quant finance. It may be sample bias, but former theoretical physicists predominate among the fund managers profiled.

I’ve always thought theoretical physics was the best training for applying mathematical techniques to real world problems. Mathematicians seldom look at data, so are less likely to have the all-important intuition for developing simple models of messy systems, and for testing models empirically. Computer scientists generally don’t study the broad variety of phenomena that physicists do, and although certain sub-specialties (e.g., machine learning) look at data, many do not. Some places where physics training can be somewhat weak (or at least uneven) include statistics, computation, optimization and information theory, but I’ve never known a theorist who couldn’t pick those things up quickly.

Physicists have a long record of success in invading other disciplines (biology, computer science, economics, engineering, etc. — I can easily find important contributions in those fields from people trained in physics, but seldom the converse). Part of the advantage might be pure horsepower — the threshold for completing a PhD in theoretical physics is pretty high. However, a colleague once pointed out that the standard curriculum of theoretical physics is basically a collection of the most practically useful mathematical techniques developed by man — the high points and greatest hits! Someone trained in that tradition can’t help but have an advantage over others when asked to confront a new problem.

Having dabbled in fields like finance, computer science and even biology, I’ve come to consider myself as a kind of applied mathematician (someone who applies mathematical ideas to the real world) who happens to have had most of his training from working on physical systems. I suspect that physicists who have left the field, as well as practitioners of biophysics, econophysics, etc. might feel the same way.

Readers of this blog sometimes accuse me of a negative perspective towards physics. Quite the contrary. Although I might not be optimistic about career prospects within physics, or the current state of the field, I can’t think of any education which gives a richer understanding of the world, or a greater chance of contributing to it.

…Finkelstein, who also grew up in Kharkov, has a Ph.D. in theoretical physics from New York University and a master’s degree in the same discipline from the Moscow Institute of Physics and Technology. Before joining Horton Point as chief science officer, he was head of quantitative credit research at Citadel Investment Group in Chicago.

Most of the 12 Ph.D.s at Horton Point’s Manhattan office are researching investment strategies and ways to apply scientific principles to finance. The firm runs what Finkelstein, 54, describes as a factory of strategies, with new models coming on line all the time. “It’s not like we plan to build ten strategies and sit on them,” he says. “The challenge is to keep it going, to keep this factory functioning.”

Along with his reservations about statistical arbitrage, Sogoloff is wary of quants who believe the real world is obliged to conform to a mathematical model. He acknowledges the difficulty of applying scientific disciplines like genetics or chaos theory — which purports to find patterns in seemingly random data — to finance. “Quantitative work will be much more rewarding to the scientist if one concentrates on those theories or areas that attempt to describe nonstable relationships,” he says.

Sogoloff sees promise in disciplines that deal with causal relationships rather than historical ones — like mathematical linguistics, which uses models to analyze the structure of language. “These sciences did not exist five or ten years ago,” he says. “They became possible because of humongous computational improvements.”

However, most quant shops aren’t exploring such fields because it means throwing considerable resources at uncertain results, Sogoloff says. Horton Point has found a solution by assembling a global network of academics whose research could be useful to the firm. So far the group includes specialists in everything from psychology to data mining, at such schools as the Beijing Institute of Technology, the California Institute of Technology and Technion, the Israel Institute of Technology.

Sogoloff tells the academics that the goal is to create the Bell Labs of finance. To align both parties’ interests, Horton Point offers them a share of the profits should their work lead to an investment strategy. Scientists like collaborating with Horton Point because it combines intellectual freedom with the opportunity to test their theories using real data, Sogoloff says. “You have experiments that can be set up in a matter of seconds because it’s a live market, and you have the potential for an amazing economic benefit.” …

And the winner is…

We all know who the losers are in the subprime meltdown: shareholders of Citi, Merrill, Countrywide Financial, etc. One of the winners is profiled below, a hedge fund manager who made $15B (keeping $3-4B himself!) from the bursting subprime housing bubble.

WSJ: Trader Made Billions on Subprime
John Paulson Bet Big on Drop in Housing Values

By GREGORY ZUCKERMAN
January 15, 2008

On Wall Street, the losers in the collapse of the housing market are legion. The biggest winner looks to be John Paulson, a little-known hedge fund manager who smelled trouble two years ago.

Funds he runs were up $15 billion in 2007 on a spectacularly successful bet against the housing market. Mr. Paulson has reaped an estimated $3 billion to $4 billion for himself — believed to be the largest one-year payday in Wall Street history.

Now, in another twist in financial history, Mr. Paulson is retaining as an adviser a man some blame for helping feed the housing-market bubble by keeping interest rates so low: former Federal Reserve Chairman Alan Greenspan. (See article.)

On the way to his big score, Mr. Paulson did battle with a Wall Street firm he accused of trying to manipulate the market. He faced skepticism from other big investors. At the same time, fearing imitators, he used software that blocked fund investors from forwarding his emails.

One thing he didn’t count on: A friend in whom he had confided tried the strategy on his own — racking up huge gains himself, and straining their friendship. (See article.)

Like many legendary market killings, from Warren Buffett’s takeovers of small companies in the ’70s to Wilbur Ross’s steelmaker consolidation earlier this decade, Mr. Paulson’s sprang from defying conventional wisdom. In early 2006, the wisdom was that while loose lending standards might be of some concern, deep trouble in the housing and mortgage markets was unlikely. A lot of big Wall Street players were in this camp, as seen by the giant mortgage-market losses they’re disclosing.

“Most people told us house prices never go down on a national level, and that there had never been a default of an investment-grade-rated mortgage bond,” Mr. Paulson says. “Mortgage experts were too caught up” in the housing boom.

In several interviews, Mr. Paulson made his first comments on how he made his historic coup. Merely holding a different opinion from the blundering herd wasn’t enough to produce huge profits. He also had to think up a technical way to bet against the housing and mortgage markets, given that, as he notes, “you can’t short houses.”

Also key: Mr. Paulson didn’t turn bearish too early. Some close students of the housing market did just that, investing for a downturn years ago — only to suffer such painful losses waiting for a collapse that they finally unwound their bearish bets. Mr. Paulson, whose investment specialty lay elsewhere, turned his attention to the housing market more recently, and got bearish at just about the right time. …

How to run a hedge fund

Via Mark Thoma, this nice summary of how to run a hedge fund, taking advantage of the fee structure and the asymmetry of compensation and risk. If the fund goes up, the manager gets paid. If the fund goes down, the manager still gets paid the management fee, if not the performance component. This means he is incentivized to take asymmetric bets like selling insurance policies, which have a high probability of a decent return from the premium, but a small chance of blowing up due to a rare event. In the latter case the investors lose their money but not the manager. What looks like a decent return by the fund might in fact reflect crazy risk taking — it’s hard for investors to know.

But don’t be too critical. These people are making our economy more efficient 😉

Most managers don’t behave this way, although it’s an example of the more general agency problem, which arises whenever the incentives and interests of a principal differ from those of an agent (e.g., hired to manage a company or financial portfolio owned by the principal).

Washington Post: …It is extremely difficult to tell, based on past performance, whether a fund is being run by true financial wizards, by no-talent managers who happen to get lucky or by outright scam artists.

To illustrate how easy it is to set up a hedge fund scam, consider the following example. An enterprising man named Oz sets up a new fund with the stated aim of earning 10 percent in excess of some benchmark rate of return, say 4 percent. The fund will run for five years, and investors can cash out at the end of each year if they wish. The fee is the standard ‘2 and 20’: 2 percent annually for funds under management, and a 20 percent incentive fee for returns that exceed the benchmark.

Although he has no investment track record, Oz has a smooth manner, a doctorate in physics and many rich acquaintances. He raises $100 million and opens shop. He then studies the derivatives market and finds an event on which the market places fairly long odds, say 9:1. In other words, it costs $.10 to buy an option that pays $1 if the event occurs and $0 otherwise. The nature of the event is unimportant: it might be a large fall in the stock market, Florida getting hit by a Category 5 hurricane or Russian President Vladimir Putin dying before the end of the year.

Next Oz writes some covered options on this event and sells 110 million of them in the derivatives market. This obligates him to pay the option holders $110 million if the event does occur and nothing if it does not. He collects $11 million on the options. To cover his obligations in case the ‘bad’ event occurs, he uses the investors’ money plus the proceeds from the options to buy $110 million in one-year Treasury bills yielding 4 percent, which he deposits in escrow. This leaves $1 million in “pocket money,” which he uses to lease some computer terminals and hire a few geeks to sit in front of them, just in case his investors drop by.

The probability is ninety percent that the bad event does not occur and Oz owes nothing to the option holders. With a gross return (before expenses) of $15,400,000, the investors are thrilled, and so is Oz. He collects $2 million in management fees (of which he has only spent $1 million), plus a performance bonus equal to 20 percent of the ‘excess return’, namely, 20 percent of $11,400,000. All in all, Oz nets over $3 million for doing absolutely nothing.

Oz can then repeat the same gambit next year. When the fund terminates after five years, the chances are nearly 60 percent that the unlucky event will never have occurred. Oz looks like a genius and gets paid like a genius. …

The quants of August

Why the rough markets in August? Why the big losses for certain quant funds? This paper claims the following:

1) many funds are pursuing the same strategies, using significant leverage

2) problems in the credit markets forced some multi-strategy funds to sell liquid equity positions in order to meet margin calls

3) positions commonly held by quant funds deteriorated in a correlated manner

Conclusion: systemic risk galore!

More discussion in the Economist.

What Happened to the Quants in August 2007?

AMIR KHANDANI
ANDREW W. LO
Massachusetts Institute of Technology

September 20, 2007

Abstract:

During the week of August 6, 2007, a number of high-profile and highly successful quantitative long/short equity hedge funds experienced unprecedented losses. Based on empirical results from TASS hedge-fund data as well as the simulated performance of a specific long/short equity strategy, we hypothesize that the losses were initiated by the rapid unwinding of one or more sizable quantitative equity market-neutral portfolios. Given the speed and price impact with which this occurred, it was likely the result of a sudden liquidation by a multi-strategy fund or proprietary-trading desk, possibly due to margin calls or a risk reduction. These initial losses then put pressure on a broader set of long/short and long-only equity portfolios, causing further losses on August 9th by triggering stop-loss and de-leveraging policies. A significant rebound of these strategies occurred on August 10th, which is also consistent with the sudden liquidation hypothesis. This hypothesis suggests that the quantitative nature of the losing strategies was incidental, and the main driver of the losses in August 2007 was the firesale liquidation of similar portfolios that happened to be quantitatively constructed. The fact that the source of dislocation in long/short equity portfolios seems to lie elsewhere – apparently in a completely unrelated set of markets and instruments – suggests that systemic risk in the hedge-fund industry may have increased in recent years.

Masters of the Universe

The Times reports on a recent dinner hosted by Institutional Investor.

NYTimes: Not since Michael Milken’s Predators’ Ball in the 1980’s have so many of Wall Street’s bold-faced names dared to mingle together. Until last night.

Institutional Investor, the first trade magazine to cover Wall Street, celebrated its 40th birthday Monday by throwing itself a party at the American Museum of Natural History in Manhattan. Masters of the Universe from around the nation and the world flew in for the event. There was Henry Kravis, seated next to Jean-Claude Trichet, president of the European Central Bank. Across the way was Mr. Milken himself, whom Mr. Kravis praised in a brief speech for helping to create the modern private equity industry.

Mr. Milken didn’t make a speech to the crowd, but he circulated among them and seemed to take pleasure at being surrounded by so many of what he referred to DealBook as his “disciples.”

Also on hand was James D. Wolfensohn, former president of the World Bank. John C. Bogle, the founder of the Vanguard Group, mingled during the cocktail hour with other luminaries such as John Whitehead, the former chairman of Goldman Sachs, credited with creating the securities firm’s vaunted culture.

John Thornton, the former president of Goldman Sachs, who now splits his time between New York and Beijing, also attended, as did Joseph L. Rice III, co-founder of the private equity firm Clayton, Dubilier & Rice.

James Simons, founder of Renaissance Technologies, one of the most successful “quant” hedge funds in history, mixed with younger hedge fund managers such as William Ackman, the activist investor, and David Einhorn of Greenlight Capital.

Perhaps the highlight of the evening was when Mr. Kravis jokingly apologized to his peers in the audience for charging his investors 20 percent of profits in 1976, which became a benchmark for private equity and hedge funds. He said that, at the time, there was no going rate, so he and his partners decided 20 percent was fair. In retrospect, he said with a laugh, “You could have gotten 25 percent.”

The room burst out laughing.

Then Mr. Simons of Renaissance took the stage. He famously takes more than 40 percent of all profits from his fund investors. “We blissfully ignored” the benchmark Mr. Kravis created, he said.

Mr. Simons also explained how the summer’s credit crunch caused his fund briefly to lose 8.7 percent in only a few days ––”a remarkable amount of money,” he said nonchalantly — though it later rebounded. At the time, he wrote a note to his investors about the losses, observing with a laugh that it took a couple of “gin and tonics to get that letter out.”

He went on to jokingly taunt Mr. Kravis into buying his firm. “If he wants to buy my company for $30 billion, I’m going to make it damn easy for him,” Mr. Simons said.

From the comments:

This convention was made up of people who sacrificed their personal lives to use their extreme intellects and incredible work ethics to strive to be the best in their fields. This is exactly what America was built on and should be what keeps us going forward. We as a country should reward winners, but instead we encourage mediocrity with the whole “everyone is a winner, everyone is great” mentality. Congratulations to those invited to this great event and if you really don’t like it then work harder to change the system, but that does mean actually working which you may not be inclined to do.
— Posted by Eric

Why are people assuming these people make money by plundering society? Jim Simons makes money as fairly and squarely as anyone in the world. Anyone can do what he does…if they come up with the magic formula. There’s nothing unfair about that, and it does society a world of good. The huge creation of wealth around the world is largely due to capital being deployed to its most productive use. What are masters of the universe but the “central planners” of the free market — the better the job they do, the more money they make, and the richer we all become.
— Posted by James

The poor are different

Michael Lewis, commentary for Bloomberg. Note to humor impaired: it’s tongue in cheek.

A little terminology: the SEC defines a qualified investor (i.e., someone who can invest in a hedge fund) as

Rule 215 — Accredited Investor

Any natural person whose individual net worth, or joint net worth with that person’s spouse, at the time of his purchase exceeds $1,000,000;

Any natural person who had an individual income in excess of $200,000 in each of the two most recent years or joint income with that person’s spouse in excess of $300,000 in each of those years and has a reasonable expectation of reaching the same income level in the current year

Lateley people have been complaining that this threshold is too low and needs to be raised 😉

A Wall Street Trader Draws Some Subprime Lessons: Michael Lewis
2007-09-05 00:05 (New York)

    Sept. 5 (Bloomberg) — So right after the Bear Stearns funds blew up, I had a thought: This is what happens when you lend money to poor people.

     Don’t get me wrong: I have nothing personally against the poor. To my knowledge, I have nothing personally to do with the poor at all. It’s not personal when a guy cuts your grass: that’s business. He does what you say, you pay him. But you don’t pay him in advance: That would be finance. And finance is one thing you should never engage in with the poor. (By poor, I mean anyone who the SEC wouldn’t allow to invest in my hedge fund.)

    That’s the biggest lesson I’ve learned from the subprime crisis. Along the way, as these people have torpedoed my portfolio, I had some other thoughts about the poor. I’ll share them with you.
 
1) They’re masters of public relations.
    I had no idea how my open-handedness could be made to look, after the fact. At the time I bought the subprime portfolio I thought: This is sort of like my way of giving something back. I didn’t expect a profile in Philanthropy Today or anything like that. I mean, I bought at a discount. But I thought people would admire the Wall Street big shot who found a way to help the little guy. Sort of like a money doctor helping a sick person. Then the little guy wheels around and gives me this financial enema. And I’m the one who gets crap in the papers! Everyone feels sorry for the poor, and no one feels sorry for me. Even though it’s my money! No good deed goes unpunished. 

2) Poor people don’t respect other people’s money in the way money deserves to be respected.
     Call me a romantic: I want everyone to have a shot at the American dream. Even people who haven’t earned it. I did everything I could so that these schlubs could at least own their own place. The media is now making my generosity out to be some kind of scandal. Teaser rates weren’t a scandal. Teaser rates were a sign of misplaced trust: I trusted these people to get their teams of lawyers to vet anything before they signed it. Turns out, if you’re poor, you don’t need to pay lawyers. You don’t like the deal you just wave your hands in the air and moan about how poor you are. Then you default.
   
3) I’ve grown out of touch with “poor culture.”
    Hard to say when this happened; it might have been when I stopped flying commercial. Or maybe it was when I gave up the bleacher seats and got the suite. But the first rule in this business is to know the people you’re in business with, and I broke it. People complain about the rich getting richer and the poor being left behind. Is it any wonder? Look at them! Did it ever occur to even one of them that they might pay me back by WORKING HARDER? I don’t think so.

    But as I say, it was my fault, for not studying the poor more closely before I lent them the money. When the only time you’ve ever seen a lion is in his cage in the zoo, you start thinking of him as a pet cat. You forget that he wants to eat you.

4) Our society is really, really hostile to success. At the same time it’s shockingly indulgent of poor people.
    A Republican president now wants to bail them out! I have a different solution. Debtors’ prison is obviously a little too retro, and besides that it would just use more taxpayers’ money. But the poor could work off their debts. All over Greenwich I see lawns to be mowed, houses to be painted, sports cars to be tuned up. Some of these poor people must have skills. The ones that don’t could be trained to do some of the less skilled labor — say, working as clowns at rich kids’ birthday parties. They could even have an act: put them in clown suits and see how many can be stuffed into a Maybach. It’d be like the circus, only better.
    Transporting entire neighborhoods of poor people to upper Manhattan and lower Connecticut might seem impractical. It’s not: Mexico does this sort of thing routinely. And in the long run it might be for the good of poor people. If the consequences were more serious, maybe they wouldn’t stay poor.

5) I think it’s time we all become more realistic about letting the poor anywhere near Wall Street.
    Lending money to poor countries was a bad idea: Does it make any more sense to lend money to poor people? They don’t even have mineral rights! There’s a reason the rich aren’t getting richer as fast as they should: they keep getting tangled up with the poor. It’s unrealistic to say that Wall Street should cut itself off entirely from poor — or, if you will, “mainstream” — culture. As I say, I’ll still do business with the masses. But I’ll only engage in their finances if they can clump themselves together into a semblance of a rich person. I’ll still accept pension fund money, for example. (Nothing under $50 million, please.) And I’m willing to finance the purchase of entire companies staffed basically with poor people. I did deals with Milken, before they broke him. I own some Blackstone. (Hang tough, Steve!)

    But never again will I go one-on-one again with poor people. They’re sharks.

Talkin’ bout my generation

Michael Lewis, writing in the Times magazine, profiles John Seo, one of the new generation of quant hedge fund managers. Seo trades catastrophe bonds, instruments that let insurers and reinsurers transfer risk from natural disasters. An interesting point discussed later in the article is that the typical premium charged for rare event insurance (tail risk) is about 4-5 times the expected loss, and that this rough rule of thumb is found across many different kinds of risk.

Seo’s path to finance is a typical one for physicists in my generation, including the objections from his traditional Asian family 🙂 People often ask me why I am interested in quant finance. If the majority of friends you knew in college and graduate school (all of them brilliant and highly trained scientists) ended up doing something different than you, wouldn’t you naturally be curious about what they were up to? The most common sentiment I’ve heard expressed by former physicists who are now in finance is “I can’t believe I waited so long to leave”!

Whatever image pops to mind when you hear the phrase “hedge fund manager,” Seo (pronounced so) undermines it. On one hand, he’s the embodiment of what Wall Street has become: quantitative. But he’s quirky. Less interested in money and more interested in ideas than a Wall Street person is meant to be. He inherited not money but math. At the age of 14, in 1950, his mother fled North Korea on foot, walked through live combat, reached the United States and proceeded to become, reportedly, the first Korean woman ever to earn a Ph.D. in mathematics. His father, a South Korean, also came to the United States for his Ph.D. in math and became a professor of economic theory. Two of his three brothers received Ph.D.’s — one in biology, the other in electrical engineering. John took a physics degree from M.I.T. and applied to Harvard to study for his Ph.D. As a boy, he says, he conceived the idea that he would be a biophysicist, even though he didn’t really know what that meant, because, as he puts it, “I wanted to solve a big problem about life.” He earned his doctorate in biophysics from Harvard in three years, a department record.

His parents had raised him to think, but his thoughts were interrupted once he left Harvard. His wife was pregnant with their second child, and the health plan at Brandeis University, where he had accepted a job, declared her pregnancy a pre-existing condition. He had no money, his parents had no money, and so to cover the costs of childbirth, he accepted a temp job with a Chicago trading firm called O’Connor and Associates. O’Connor had turned a small army of M.I.T. scientists into options traders and made them rich. Seo didn’t want to be rich; he just wanted health insurance. To get it, he agreed to spend eight weeks helping O’Connor price esoteric financial options. When he was done, O’Connor offered him 40 grand and asked him to stay, at a starting salary of $250,000, 27 times his post-doc teaching salary. “Biophysics was starved for resources,” Seo says. “Finance was hurling resources at problems. It was almost as if I was taking it as a price signal. It was society’s way of saying, Please, will you start solving problems over here?”

His parents, he suspected, would be appalled. They had sacrificed a lot for his academic career. In the late 1980s, if you walked into the Daylight Donuts shop in Dallas, you would have found a sweet-natured Korean woman in her early 50s cheerfully serving up honey-glazed crullers: John’s mom. She had abandoned math for motherhood, and then motherhood for doughnuts, after her most promising son insisted on attending M.I.T. instead of S.M.U., where his tuition would have been free. She needed money, and she got it by buying this doughnut shop and changing the recipe so the glaze didn’t turn soggy. (Revenues tripled.) Whatever frustration she may have felt, she hid, as she did most of her emotions. But when John told her that he was leaving the university for Wall Street, she wept. His father, a hard man to annoy, said, “The devil has come to you as a prostitute and has asked you to lie down with her.”

A willingness to upset one’s mother is usually a promising first step to a conventional Wall Street career. But Seo soon turned Wall Street into his own private science lab, and his continued interest in deep questions mollified even his father. “Before he got into it, I strongly objected,” Tae Kun Seo says. “But now I think he’s not just grabbing money.” He has watched his son quit one firm to go to work for another, but never for a simple promotion; instead, John has moved to learn something new. Still, everywhere he goes, he has been drawn to a similar thorny problem: the right price to charge to insure against potential losses from extremely unlikely financial events. “Tail risk,” as it is known to quantitative traders, for where it falls in a bell-shaped probability curve. Tail risk, broadly speaking, is whatever financial cataclysm is believed by markets to have a 1 percent chance or less of happening. In the foreign-exchange market, the tail event might be the dollar falling by one-third in a year; in the bond market, it might be interest rates moving 3 percent in six months; in the stock market, it might be a 30 percent crash. “If there’s been a theme to John’s life,” says his brother Nelson, “it’s pricing tail.”

And if there has been a theme of modern Wall Street, it’s that young men with Ph.D.’s who approach money as science can cause more trouble than a hurricane. John Seo is oddly sympathetic to the complaint. He thinks that much of the academic literature about finance is nonsense, for instance. “These academics couldn’t understand the fact that they couldn’t beat the markets,” he says. “So they just said it was efficient. And, ‘Oh, by the way, here’s a ton of math you don’t understand.’ ” He notes that smart risk-takers with no gift for theory often end up with smart solutions to taking extreme financial risk — answers that often violate the academic theories. (“The markets are usually way ahead of the math.”) He prides himself on his ability to square book smarts with horse sense. As one of his former bosses puts it, “John was known as the man who could price anything, and his pricing felt right to people who didn’t understand his math.”

Talkin’ bout my generation

Michael Lewis, writing in the Times magazine, profiles John Seo, one of the new generation of quant hedge fund managers. Seo trades catastrophe bonds, instruments that let insurers and reinsurers transfer risk from natural disasters. An interesting point discussed later in the article is that the typical premium charged for rare event insurance (tail risk) is about 4-5 times the expected loss, and that this rough rule of thumb is found across many different kinds of risk.

Seo’s path to finance is a typical one for physicists in my generation, including the objections from his traditional Asian family 🙂 People often ask me why I am interested in quant finance. If the majority of friends you knew in college and graduate school (all of them brilliant and highly trained scientists) ended up doing something different than you, wouldn’t you naturally be curious about what they were up to? The most common sentiment I’ve heard expressed by former physicists who are now in finance is “I can’t believe I waited so long to leave”!

Whatever image pops to mind when you hear the phrase “hedge fund manager,” Seo (pronounced so) undermines it. On one hand, he’s the embodiment of what Wall Street has become: quantitative. But he’s quirky. Less interested in money and more interested in ideas than a Wall Street person is meant to be. He inherited not money but math. At the age of 14, in 1950, his mother fled North Korea on foot, walked through live combat, reached the United States and proceeded to become, reportedly, the first Korean woman ever to earn a Ph.D. in mathematics. His father, a South Korean, also came to the United States for his Ph.D. in math and became a professor of economic theory. Two of his three brothers received Ph.D.’s — one in biology, the other in electrical engineering. John took a physics degree from M.I.T. and applied to Harvard to study for his Ph.D. As a boy, he says, he conceived the idea that he would be a biophysicist, even though he didn’t really know what that meant, because, as he puts it, “I wanted to solve a big problem about life.” He earned his doctorate in biophysics from Harvard in three years, a department record.

His parents had raised him to think, but his thoughts were interrupted once he left Harvard. His wife was pregnant with their second child, and the health plan at Brandeis University, where he had accepted a job, declared her pregnancy a pre-existing condition. He had no money, his parents had no money, and so to cover the costs of childbirth, he accepted a temp job with a Chicago trading firm called O’Connor and Associates. O’Connor had turned a small army of M.I.T. scientists into options traders and made them rich. Seo didn’t want to be rich; he just wanted health insurance. To get it, he agreed to spend eight weeks helping O’Connor price esoteric financial options. When he was done, O’Connor offered him 40 grand and asked him to stay, at a starting salary of $250,000, 27 times his post-doc teaching salary. “Biophysics was starved for resources,” Seo says. “Finance was hurling resources at problems. It was almost as if I was taking it as a price signal. It was society’s way of saying, Please, will you start solving problems over here?”

His parents, he suspected, would be appalled. They had sacrificed a lot for his academic career. In the late 1980s, if you walked into the Daylight Donuts shop in Dallas, you would have found a sweet-natured Korean woman in her early 50s cheerfully serving up honey-glazed crullers: John’s mom. She had abandoned math for motherhood, and then motherhood for doughnuts, after her most promising son insisted on attending M.I.T. instead of S.M.U., where his tuition would have been free. She needed money, and she got it by buying this doughnut shop and changing the recipe so the glaze didn’t turn soggy. (Revenues tripled.) Whatever frustration she may have felt, she hid, as she did most of her emotions. But when John told her that he was leaving the university for Wall Street, she wept. His father, a hard man to annoy, said, “The devil has come to you as a prostitute and has asked you to lie down with her.”

A willingness to upset one’s mother is usually a promising first step to a conventional Wall Street career. But Seo soon turned Wall Street into his own private science lab, and his continued interest in deep questions mollified even his father. “Before he got into it, I strongly objected,” Tae Kun Seo says. “But now I think he’s not just grabbing money.” He has watched his son quit one firm to go to work for another, but never for a simple promotion; instead, John has moved to learn something new. Still, everywhere he goes, he has been drawn to a similar thorny problem: the right price to charge to insure against potential losses from extremely unlikely financial events. “Tail risk,” as it is known to quantitative traders, for where it falls in a bell-shaped probability curve. Tail risk, broadly speaking, is whatever financial cataclysm is believed by markets to have a 1 percent chance or less of happening. In the foreign-exchange market, the tail event might be the dollar falling by one-third in a year; in the bond market, it might be interest rates moving 3 percent in six months; in the stock market, it might be a 30 percent crash. “If there’s been a theme to John’s life,” says his brother Nelson, “it’s pricing tail.”

And if there has been a theme of modern Wall Street, it’s that young men with Ph.D.’s who approach money as science can cause more trouble than a hurricane. John Seo is oddly sympathetic to the complaint. He thinks that much of the academic literature about finance is nonsense, for instance. “These academics couldn’t understand the fact that they couldn’t beat the markets,” he says. “So they just said it was efficient. And, ‘Oh, by the way, here’s a ton of math you don’t understand.’ ” He notes that smart risk-takers with no gift for theory often end up with smart solutions to taking extreme financial risk — answers that often violate the academic theories. (“The markets are usually way ahead of the math.”) He prides himself on his ability to square book smarts with horse sense. As one of his former bosses puts it, “John was known as the man who could price anything, and his pricing felt right to people who didn’t understand his math.”

Talkin’ bout my generation

Michael Lewis, writing in the Times magazine, profiles John Seo, one of the new generation of quant hedge fund managers. Seo trades catastrophe bonds, instruments that let insurers and reinsurers transfer risk from natural disasters. An interesting point discussed later in the article is that the typical premium charged for rare event insurance (tail risk) is about 4-5 times the expected loss, and that this rough rule of thumb is found across many different kinds of risk.

Seo’s path to finance is a typical one for physicists in my generation, including the objections from his traditional Asian family 🙂 People often ask me why I am interested in quant finance. If the majority of friends you knew in college and graduate school (all of them brilliant and highly trained scientists) ended up doing something different than you, wouldn’t you naturally be curious about what they were up to? The most common sentiment I’ve heard expressed by former physicists who are now in finance is “I can’t believe I waited so long to leave”!

Whatever image pops to mind when you hear the phrase “hedge fund manager,” Seo (pronounced so) undermines it. On one hand, he’s the embodiment of what Wall Street has become: quantitative. But he’s quirky. Less interested in money and more interested in ideas than a Wall Street person is meant to be. He inherited not money but math. At the age of 14, in 1950, his mother fled North Korea on foot, walked through live combat, reached the United States and proceeded to become, reportedly, the first Korean woman ever to earn a Ph.D. in mathematics. His father, a South Korean, also came to the United States for his Ph.D. in math and became a professor of economic theory. Two of his three brothers received Ph.D.’s — one in biology, the other in electrical engineering. John took a physics degree from M.I.T. and applied to Harvard to study for his Ph.D. As a boy, he says, he conceived the idea that he would be a biophysicist, even though he didn’t really know what that meant, because, as he puts it, “I wanted to solve a big problem about life.” He earned his doctorate in biophysics from Harvard in three years, a department record.

His parents had raised him to think, but his thoughts were interrupted once he left Harvard. His wife was pregnant with their second child, and the health plan at Brandeis University, where he had accepted a job, declared her pregnancy a pre-existing condition. He had no money, his parents had no money, and so to cover the costs of childbirth, he accepted a temp job with a Chicago trading firm called O’Connor and Associates. O’Connor had turned a small army of M.I.T. scientists into options traders and made them rich. Seo didn’t want to be rich; he just wanted health insurance. To get it, he agreed to spend eight weeks helping O’Connor price esoteric financial options. When he was done, O’Connor offered him 40 grand and asked him to stay, at a starting salary of $250,000, 27 times his post-doc teaching salary. “Biophysics was starved for resources,” Seo says. “Finance was hurling resources at problems. It was almost as if I was taking it as a price signal. It was society’s way of saying, Please, will you start solving problems over here?”

His parents, he suspected, would be appalled. They had sacrificed a lot for his academic career. In the late 1980s, if you walked into the Daylight Donuts shop in Dallas, you would have found a sweet-natured Korean woman in her early 50s cheerfully serving up honey-glazed crullers: John’s mom. She had abandoned math for motherhood, and then motherhood for doughnuts, after her most promising son insisted on attending M.I.T. instead of S.M.U., where his tuition would have been free. She needed money, and she got it by buying this doughnut shop and changing the recipe so the glaze didn’t turn soggy. (Revenues tripled.) Whatever frustration she may have felt, she hid, as she did most of her emotions. But when John told her that he was leaving the university for Wall Street, she wept. His father, a hard man to annoy, said, “The devil has come to you as a prostitute and has asked you to lie down with her.”

A willingness to upset one’s mother is usually a promising first step to a conventional Wall Street career. But Seo soon turned Wall Street into his own private science lab, and his continued interest in deep questions mollified even his father. “Before he got into it, I strongly objected,” Tae Kun Seo says. “But now I think he’s not just grabbing money.” He has watched his son quit one firm to go to work for another, but never for a simple promotion; instead, John has moved to learn something new. Still, everywhere he goes, he has been drawn to a similar thorny problem: the right price to charge to insure against potential losses from extremely unlikely financial events. “Tail risk,” as it is known to quantitative traders, for where it falls in a bell-shaped probability curve. Tail risk, broadly speaking, is whatever financial cataclysm is believed by markets to have a 1 percent chance or less of happening. In the foreign-exchange market, the tail event might be the dollar falling by one-third in a year; in the bond market, it might be interest rates moving 3 percent in six months; in the stock market, it might be a 30 percent crash. “If there’s been a theme to John’s life,” says his brother Nelson, “it’s pricing tail.”

And if there has been a theme of modern Wall Street, it’s that young men with Ph.D.’s who approach money as science can cause more trouble than a hurricane. John Seo is oddly sympathetic to the complaint. He thinks that much of the academic literature about finance is nonsense, for instance. “These academics couldn’t understand the fact that they couldn’t beat the markets,” he says. “So they just said it was efficient. And, ‘Oh, by the way, here’s a ton of math you don’t understand.’ ” He notes that smart risk-takers with no gift for theory often end up with smart solutions to taking extreme financial risk — answers that often violate the academic theories. (“The markets are usually way ahead of the math.”) He prides himself on his ability to square book smarts with horse sense. As one of his former bosses puts it, “John was known as the man who could price anything, and his pricing felt right to people who didn’t understand his math.”