A Portfolio of Readings

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|Plymouth State University |

|A Portfolio of Readings |

|BU 5120 Financial Analysis |

| |

|Edward Harding |

|3/26/2012 |

|[Type the abstract of the document here. The abstract is typically a short summary of the contents of the document. Type the abstract |

|of the document here. The abstract is typically a short summary of the contents of the document.] |


1. Bogle, John C. and Malkiel, Burton G. "Turn on a Paradigm?" WSJ, 27 Jun 2006 2

2. Cassidy, John. "Hedge Clipping" New Yorker, 2 Jul 2007 5

3. Chernow, Ron. "Madoff and his Models", New Yorker, 23 Mar 2009 13

4. Gladding, Kent W. “Timely Topics: Active v. Passive” Citizens Bank 23

5. Gladwell, Malcolm “Blowing Up”, The New Yorker 22 Apr 2002 25

6. Hilsenrath,J. "As Two Economist Debate Markets…” WSJ, 18 Oct 2004 37

7. Kolbert, Elizabeth. "What was I Thinking" The New Yorker, 25 Feb 2008 42

8. Lanchester, John. "Outsmarted" The New Yorker, 1 Jun 2009 47

9. Lewellen, Jonathan “"How the World Works. Sort of." Tuck Forum Winter 2007 54

10. Malkiel, Burton G. "Keep Your Money in the Market" WSJ 13 Oct 08 55

11. Mann, Charles C. ”Fama’s Market” Investment Vision Oct/Nov 1991 57

12. Markowitz, Harry. Markets and Morality, WSJ 14 may 1991 63

13. Mollenkamp,C. & Flemming,C. “Why Students of Prof. El Karoui Are in Demand” WSJ 09Mar06 70

14. Patterson, Scott "Math Wizards Working On Spells to 'Cure'" WSJ 23 Feb09 74

15. Soros, George. "One Way to Stop Bear Raids" WSJ 24 Mar 09 76

16. Surowiecki, James. "Performance Pay Perplexes" The New Yorker 12 Nov 2007 78

17. Van Horne, James C. Financial Management and Policy, Prentice-Hall 1974 80

18. Varian, Hal “A Portfolio of Nobel Laureates: Markowitz, Miller, and Sharpe” Journal of Economic Perspectives Winter 1993 83


John C. Bogle and Burton G. Malkiel.

Wall Street Journal. New York, N.Y. 27 Jun 06

As index funds gain an increasing share of the portfolios of mutual funds, institutional equity and bond funds, academics and practitioners are hotly debating how these portfolios should be composed. Capitalization-weighted indexing, until now the dominant approach, has come under fire for overweighting portfolios with (temporarily) overvalued stocks and underweighting them with undervalued ones.

Eugene Fama and Kenneth French have suggested that higher returns can be generated by indexed portfolios of stocks with small capitalizations and low price-to-book-value ratios. Robert Arnott has argued that a better method for indexing is to weight the stocks in the index not by their total capitalization, but rather by certain "fundamental" factors such as sales, earnings or book values. Jeremy Siegel has proposed that the "fundamental factor" should be the dividends that companies pay. These analysts have all argued that fundamentally weighted indexes represent the "new paradigm" for index- fund investing.

Are they correct? We think not. There is no doubt that fundamentally weighted indexes have outperformed capitalization-weighted indexes during the past six years, which witnessed the collapse of the "new economy" bubble and partial recovery. But we need to be cautious before accepting any "new paradigm" that implicitly suggests that the "old paradigm" -- reflected in more than $3 trillion of capitalization-weighted index investment funds -- is in error. During the three-plus decades that such passively managed funds have been available, they have provided for their investors returns substantially superior to the returns achieved by actively managed equity funds. We need to understand why capitalization-weighted indexes make sense -- even if market prices are "noisy" and can fluctuate above or below the values they would have in a perfectly efficient market.

First let us put to rest the canard that the remarkable success of traditional market-weighted indexing rests on the notion that markets must be efficient. Even if our stock markets were inefficient, capitalization-weighted indexing would still be -- must be -- an optimal investment strategy. All the stocks in the market must be held by someone. Thus, investors as a whole must earn the market return when that return is measured by a capitalization-weighted total stock market index. We can not live in Garrison Keillor's Lake Wobegon, where all the children are above average. For every investor who outperforms the market, there must be another investor who underperforms. Beating the market, in principle, must be a zero-sum game.

But only before the deduction of investment management costs. In practice, investors as a group will fail to earn the market return after these costs, and as a group, they will fall far short of the low-expense index funds. For the typical actively managed equity mutual fund, annual operating expense ratios are well over 100 basis points (one percentage point). Add in the hidden costs of portfolio turnover and sales loads, where applicable, and effective annual costs are undoubtedly considerably higher, perhaps as much as 200 to 250 basis points. In total, simply because the average actively managed fund must underperform the capitalization-weighted market as a whole by the amount of financial intermediation costs that are deducted from the gross return achieved, active investing must be, and is, a loser's game.

Purveyors of fundamentally weighted indexes also tend to charge management fees well above the typical index fund. While index funds also incur expenses, they are available at costs below 10 basis points. The expense ratios of publicly available fundamental index funds range from an average of 0.49% (plus brokerage commissions) to 1.14% (plus a 3.75% sales load), plus an undisclosed amount of portfolio turnover costs.

The portfolios of market-weighted index funds are automatically adjusted for changes in the market caps of their portfolio holdings, and they require no turnover. But fundamentally weighted indexes gain no such advantage. Suppose, for example, we use a fundamental index based on dividends. If one company doubles its dividend, the portfolio manager then needs to buy enough of the stock (and sell enough of the other stocks) to double the weight of the stock in his fundamentally weighted portfolios. All fundamentally weighted indexes must incur turnover costs to align the weights of the portfolio with changing fundamental factors and changes in the market price of different securities.

Fundamental weighting also fails to provide the tax efficiency of market weighting. If a stock doubles in price and its fundamental weighting factor (be it dividends, book value or anything else) remains unchanged, the portfolio manager must sell enough of the stock to bring its weight back into balance. Thus, a fundamental index fund will tend to realize capital gains (and highly taxed short-term gains if adjustments are made frequently). Taxes are a crucially important financial consideration because the premature realization of capital gains will substantially reduce net returns.

One important characteristic of fundamental indexing needs to be emphasized, for it explains why such indexing can often appear to produce outperformance. Every method of fundamental indexing tends to overweight smaller capitalization stocks and so-called value stocks. Consider the rationale for fundamental indexing. If, during some speculative bubble, money pours into high-tech stocks, their weight in a cap-weighted index increases. Since their price rise generally exceeds any fundamental measures of value, such as dividends or book value, such stocks will tend to have increased cap weights versus fundamental weights.

Consequently, fundamental weighting will tend to produce portfolios that give more weight to companies that are smaller in size (capitalization) and that have "value" characteristics such as low prices relative to earnings, dividends, sales and book values. Fundamental indexing will tend to do well in periods when small-cap stocks and "value" stocks tend to outperform. Thus it is not surprising that most of the long-term excess return attributed to fundamentally weighted portfolios was achieved between 2000 and 2005 alone, one of the best periods in history for the relative returns of dividend-paying stocks, "value" stocks and small-cap stocks.

We concede that there is some evidence, based on numbers compiled by Ibbotson Associates, that long-run excess returns have been earned from dividend-paying, "value" and small-cap stocks -- albeit returns that are overstated by not taking into account management fees, operating expenses, turnover costs and taxes. But to the extent that investors are persuaded by these data, the premiums offered by such stocks may well now have been "arbitraged away" in the stock market, as price-earnings multiples have become extremely compressed.

We are impressed by the inexorable tendency for reversion to the mean in security returns. Consider the chart showing the difference between mutual funds with a "value" mandate and those with a "growth" mandate. Since the late 1960s, "value" funds have generally outperformed growth funds. But since 1977 -- indeed since 1937 -- there is little to choose between the two. Indeed, for the first 30 years, growth funds rather consistently trumped value funds. Never think you know more than the markets. Nobody does.

We never know when reversion to the mean will come to the various sectors of the stock market, but we do know that such changes in style invariably occur. Before we too easily accept that fundamental indexing -- relying on style tilts toward dividends, "value" and smallness -- is the "new paradigm," we need a longer sense of history, as well as an appreciation that capitalization-weighted indexing does not depend on efficient markets for its usefulness.

While we have witnessed many "new paradigms" over the years, none have persisted. The "concept" stocks of the Go-Go years in the 1960s came, and went. So did the "Nifty Fifty" era that soon followed. The "January Effect" of small-cap superiority came, and went. Option- income funds and "Government Plus" funds came, and went. High-tech stocks and "new economy" funds came as well, and the survivors remain far below their peaks. Intelligent investors should approach with extreme caution any claim that a "new paradigm" is here to stay. That's not the way financial markets work.


by Cassidy, John

New Yorker; 7/2/2007, Vol. 83 Issue 18, p28-33,

Is there a way to get above-market returns on the cheap?

In 2000, Harry Kat got a call from a corporate headhunter who asked whether he would be interested in joining a financial firm that invested in hedge funds - a so-called fund of funds. Kat, a forty-three-year-old Dutch economist, had recently left a high-paying job at the London office of Bank of America to pursue a career in academe. He didn't know much about hedge funds, but he agreed to be interviewed by an executive at the firm.

Hedge funds are privately owned financial companies that raise cash from very wealthy individuals and institutional investors, such as pension funds and charitable endowments. Unlike banks and brokerage firms, hedge funds are largely unregulated, which gives them considerable latitude in investing their clients' money. During the past fifteen years, the number of hedge funds has increased from about five hundred to perhaps ten thousand, and some hedge-fund managers have made vast fortunes. Last year, three reportedly earned more than a billion dollars each: James Simons, of Renaissance Technologies; Kenneth Griffin, of Citadel Investment Group; and Edward Lampert, of ESL Investments.

Hedge funds go to great lengths to maintain their mystique: Simons and other managers rarely grant interviews, and the mostly young analysts and traders who make up the funds' staffs sign confidentiality agreements barring them from discussing their work. The public, denied information about the industry's methods, has focused instead on the conspicuous spending it has enabled, seeing in the life styles of the funds' managers proof of their ingenuity. Steven Cohen, the founder of SAC Capital Advisors, lives in a thirty-two-thousand-square-foot house in Greenwich, Connecticut, and last year reportedly paid $143.5 million for a painting by Willem de Kooning.

In the jargon of Wall Street, hedge funds seek "alpha": returns greater than those provided by standard market indices, such as the Dow Jones Industrial Average and the S. & P. 500. Investing in hedge funds can be lucrative, but it is also risky: the funds, many of which are highly leveraged, have a tendency to implode when their investments turn against them. (Last week, two hedge funds run by Bear Stearns, the investment bank, were brought to the brink of closure after losing hundreds of millions of dollars, largely in bonds tied to the sub-prime mortgage market.) Funds of funds hold stakes in a variety of hedge funds, so they are somewhat safer. However, as the executive made clear to Kat, investing in them is costly.

Typically, hedge-fund managers charge their clients a management fee equal to two per cent of the amount they invest, plus twenty per cent of any profits that the fund generates. (This fee structure is known as "two and twenty.") On top of these charges, funds of funds often add a management fee of one per cent, plus a commission of ten per cent on investment gains. Thus, people who invest in funds of funds are effectively paying a three-per-cent management fee plus a "success fee" of thirty per cent - "three and thirty."

This arithmetic helps explain the astronomical wealth of leading hedge-fund managers, and suggests why even less successful competitors make plenty of money. If a fund manager does well, he gets to keep a large portion of the profits he makes using his clients' money; if he does poorly, he still receives the generous management fees, at least until his clients withdraw their money, which isn't always easy to do. (Some funds impose "lockup" periods of several years.) Kat had worked in the financial markets for almost fifteen years, but what he learned about hedge-fund fees shocked him. An investor who puts a million dollars in a fund of funds whose value goes up ten per cent in twelve months would face deductions of about sixty thousand dollars on the gains he makes. "Who wants to pay that kind of money?" Kat asked the executive who was interviewing him. "You can't seriously expect there to be anything interesting left after somebody takes out three and thirty." The executive was nonplussed. "I don't know," he said. "But they pay it."

The executive's firm offered Kat a job as the head of research, but he turned it down. The following year, he began teaching finance at the University of Reading, and in 2003 he became a professor of risk management at Sir John Cass Business School, which is part of City University in London. He continued to think about hedge funds. "When I became an academic, I said, 'That's the thing I want to investigate,' " he recalled recently. "Is it really possible to generate investment returns to the extent that you can take out three and thirty and still be left with something you can call superior?"

Kat had moved to London in 1996, several years after completing a Ph.D. in economics and statistics at the University of Amsterdam. He worked in the derivatives department of an investment bank, where he traded futures and options - financial contracts in which a buyer has an obligation or option to pay a fixed price for a commodity or a security at a future date. Futures and options are relatively simple derivatives; for decades, farmers and businessmen have relied on them to stabilize their incomes. In the past twenty years, however, new kinds of custom-built derivatives have emerged, which allow investors to make bets on, say, the future creditworthiness of corporations, or the future volatility of the stock market.

Kat became an expert in these complex securities, and by the late nineties he was head of the equity-derivatives desk at Bank of America. He never adjusted to corporate life, though. "If you really want to get up at 5 A.M., get the train, and spend all day in the office for twenty-five years, well, good luck," he said. "I didn't want to do that."

Studying hedge funds proved to be a more satisfying, if less remunerative, challenge. (As a professor, Kat earns less than a hundred thousand pounds a year - about a tenth of what he was earning as a financier.) Aside from their fee structure, hedge funds generally have little in common. A few make long-term investments; most buy and sell incessantly. Some trade individual stocks; others place bets on entire industries and markets. Some rely on human intuition to identify plum investments; many use computer software programs to ferret out profitable trades.

Kat, realizing that it would be nearly impossible to determine the trading strategies of individual hedge funds - the companies would never agree to divulge them - decided to study their results instead. Hedge funds aren't required to file quarterly reports with the Securities and Exchange Commission, so it isn't easy to get accurate information about their earnings. However, several financial-publishing companies now collate data on monthly returns which hedge funds supply to them voluntarily, presumably in order to impress potential investors. The databases that these publishers have assembled are neither complete nor entirely reliable, but they include information on thousands of funds, some of it dating back to the nineteen-eighties.

When Kat examined the databases, he noticed that in most years hedge funds outperformed the Dow and the S. & P. 500; they appeared to have produced alpha. But the figures in the databases don't take into account the unusual risks that hedge funds take. Many funds use borrowed money to leverage their investments; they short stocks; and they speculate on the price of volatile commodities, such as gold and coffee.

It is well known that risk and return tend to go together. If you go to Atlantic City and bet your life's savings on a roulette wheel's coming up black, you have a good chance of earning an instant return of a hundred per cent; you also have a good chance of going broke. Playing roulette is a high-risk, high-return activity. Putting your money in a bank C.D. is a low-risk, low-return activity. Truly outstanding investors, such as Warren Buffett, somehow generate consistently high returns at low risk. Kat decided to determine whether hedge funds met this standard; only if they did could they genuinely be said to have created alpha. In a study published in the June, 2003, issue of the Journal of Financial and Quantitative Analysis, he and a co-author, Gaurav Amin, an analyst at Schroder Investment Management, a British financial firm, compared the fee-adjusted returns of seventy-seven hedge funds between 1990 and 2000 with the returns generated by a market benchmark that had a similar risk profile. Seventy-two of the funds - more than ninety per cent - failed to outperform their benchmarks.

With the help of a graduate student, Helder Palaro, Kat also undertook a larger study, in which he examined more than nineteen hundred funds. The results, which Kat and Palaro posted online as a working paper last year, showed that only eighteen per cent of the funds outperformed their benchmarks, and returns even at the most successful funds tended to decline over time. "Our research has shown that in at least eighty per cent of cases the after-fee alpha for hedge funds is negative," Kat told me. "They are charging more than they are adding. I'm not saying they don't have skill; I'm just saying they don't have enough skill to make up for two and twenty."

Other economists had been scrutinizing hedge funds closely. In a widely discussed 2005 paper, Burton Malkiel, a Princeton professor, and Atanu Saha, a New York investment analyst, argued that many published estimates of hedge-fund returns are misleading. Malkiel and Saha discovered that funds tend to exaggerate how well they performed in the past, and that those which perform badly often close and disappear from databases, leaving a biased sample. After examining results of now defunct firms, Malkiel and Saha found that between 1996 and 2003 hedge funds made an average return of 9.32 per cent, significantly less than the 13.74-per-cent average return of funds included in the published databases.

Stephen Brown, William Goetzmann, and Bing Liang, researchers at New York University, Yale, and the University of Massachusetts at Amherst, respectively, have published data suggesting that the fees paid by investors in many funds of funds negate most or all of what is generated in extra returns. And several groups of researchers - including William Fung, of the London Business School, and David Hsieh, of Duke; and Jasmina Hasanhodzic and Andrew Lo, of M.I.T. - have shown that broad market movements in the prices of stocks, bonds, and other common securities account for a good deal of the variation in hedge-fund returns. These findings suggest that stock picking, trading smarts, and computer algorithms are less important than many scholars had thought. "Our idea was to see how much of the variation in hedge-fund returns you could explain using very simple, passive investment strategies," Lo said. "Given all the hype and mystique surrounding hedge funds, we expected the answer to be 'very little.' We were quite surprised to find that it was about forty per cent."

Kat, though, has gone farther than other researchers in challenging the hedge-fund industry's reputation - and threatening its sources of funding. Much of the money in such funds comes not only from the industry's traditional clients - rich people hoping to get richer - but from institutional investors that manage money on behalf of the middle classes. In 2000 and 2001, when the stock market collapsed, most hedge funds held up pretty well. Some made money by shorting stocks; others were holding commodities and other kinds of assets that were unaffected by the crash. The ability to generate positive returns at a time when most financial investments were faltering suggested that hedge funds had lived up to their name: they had provided valuable hedges. Among the institutional investors that have put their clients' money in hedge funds are several large pension funds, including those for employees of General Motors and those for state workers in New Jersey and California. (Earlier this year, William Thompson, Jr., the comptroller for New York City, announced that he was considering investing some of the city's pension funds in hedge funds.) Such institutional investors aren't merely chasing high returns; they are seeking to diversify their holdings as insurance against another bear market.

However, Kat remained skeptical. As he conducted his research on hedge funds, he became convinced that it might be possible to generate similar returns in a mechanical way and with much less effort. Two years ago, he and Palaro began to sketch out ideas for a software program that could mimic the returns of individual hedge funds by trading futures. "We may be able to do without expensive hedge-fund managers and all the hassle, including the due diligence, the lack of liquidity, the lack of transparency, the lack of capacity and the fear of style drift" - changes in a fund's strategy - "which comes with investing in hedge funds," Kat and Palaro wrote in a working paper about the project which they published last year.

Kat provided many of the mathematical ideas. Palaro, an experienced programmer, did most of the computer work. Rather than trying to emulate a hedge fund's monthly return - a nearly impossible task - the researchers sought to match the fund's results over a period of several years, as well as the other statistical properties of its performance that investors were likely to care about most: the volatility of the returns, their correlation with the stock market, the likelihood of suffering extreme losses.

In the spring of last year, Kat sent me an e-mail in which he expressed confidence that he and Palaro would succeed. "It is possible to design mechanical futures-trading strategies which generate returns with the same, and often better, risk-return properties as hedge funds," he said. "This means investors can have hedge-fund returns but without the massive fees and all the other drawbacks that come with the real thing."

By the end of 2006, Kat and Palaro had finished writing their software program, which they called FundCreator, and had conducted several successful trials. In April, Kat demonstrated the software for me at his office on the Cass Business School's campus. A hefty man with blue eyes and spiky brown hair, Kat was wearing jeans, sneakers, and a garish striped polo shirt. When he turned on his computer, a hideous animal's head, replete with fangs and horns, appeared on the screen. Kat, an avid heavy-metal fan who plays the electric guitar, said, "That's the FundCreator monster. Now let's get started."

I entered my name and address and the amount of money - a hundred million dollars - I wanted the system to manage. Then I had to select the kinds of futures contracts I wanted to trade. The choices included equity futures, interest-rate futures, commodity futures, and currency futures. These futures are the building blocks that FundCreator uses to simulate hedge-fund investments. Next, I was directed to a screen that allowed me to choose from a list of several thousand hedge funds. I asked Kat if I could replicate one run by George Soros. Using a pull-down menu, Kat clicked on Quantum Fund NV, which for many years was Soros's investment flagship and often had an annual return of twenty-five per cent or more. A Web page appeared that was full of statistics detailing Quantum's record going back to 1985. It showed that the annual volatility of Quantum's returns - the amount they varied from year to year - was high (twenty-four per cent), indicating that the fund was a risky investment. The coefficient of correlation between Quantum's returns and the S. & P. 500 - a statistical measure of how closely the fund's performance tracked the stock index - was low (0.35), indicating that Quantum provided valuable diversification. "If you say you want to replicate Quantum, you leave it all as it is," Kat said, pointing to boxes displaying each figure. "But you can also do some genetic engineering. If you want zero correlation with the S. & P. 500, you write in zero. If you leave it all as it is, that is called fund replication. If you change something, that is called fund creation."

I decided not to change any of the fund's parameters. The next step was to determine, by pressing a button, whether the software could perform what I'd asked it to. "You might be asking for something it is just impossible to pull off," Kat said. "I get e-mails every week from people saying, 'Harry, can you make a twenty-five-per-cent average return with no volatility?' Of course I can't. The interest rate on Treasury bonds is five per cent. That is what I can achieve without any volatility."

FundCreator indicated that it could replicate Quantum. Kat pressed a few more buttons. On a new page, a list of the futures I had chosen appeared, along with numbers next to them indicating how many contracts I needed to buy and sell. The software doesn't carry out actual futures trades. An investor may do those himself, or he can enlist the help of one of two brokerage firms that have agreed to provide such services for FundCreator. Each night, after the markets have closed, FundCreator downloads financial data from all over the world and determines what new trades each of its users needs. When a user logs on in the morning, a red light flashes to indicate that action is needed. "You just click on it every day, it tells you what you need to do, you do it, and you get Quantum," Kat said proudly. "It's simple."

What goes on behind the screen is more complicated. After I entered my choices, FundCreator ran through fifty-four different statistical models, picking the one that best fit the monthly returns for Quantum Fund NV. Then the program, using the model it had selected, together with some sophisticated mathematical formulas, chose the investments I needed to make. These calculations were completed within seconds.

The theoretical ideas behind FundCreator are well established. Most ultimately derive from what is known as the Black-Scholes formula, which was developed by economists in the early nineteen-seventies to determine the price of stock options. Kat and Palaro relied on a version of Black-Scholes similar to the one that investment banks use to design hedging strategies for their own derivatives portfolios. However, Kat and Palaro were the first to apply the formula to create virtual hedge funds based on existing ones. "The new thing is that it allows you to generate returns with predefined properties," Kat said. "Normally, managers of hedge funds will give you some idea of the properties they are looking for, but they won't pin themselves down to a certain number. They'll tell you they are aiming for a volatility of eight per cent or so, but, if you give them a few years and calculate what it was, it could have been six, it could have been eight, or ten, or even more. Our method allows you to pinpoint a certain number."

In the past twelve months, several investment banks, among them Goldman Sachs and Merrill Lynch, have launched their own low-cost alternatives to hedge funds. These so-called tracker funds, inspired by academic research, including work by Fung and Hsieh and by Hasanhodzic and Lo, try to mimic the performance of a basket of hedge funds by accumulating many of the same types of assets that are in the funds' portfolio - stocks, bonds, currencies, commodities, credit swaps. "Unlike Kat's model, tracker funds are not designed to replicate individual funds," Lo told me. "They try to capture some of what hedge funds do as a class. The idea is to provide institutional investors with a relatively inexpensive vehicle by which to achieve the risk-reward tradeoffs they are looking for, without some of the drawbacks of investing in hedge funds, such as lack of transparency."

Kat and Palaro originally intended to use FundCreator to demonstrate for business students and scholars the feasibility of replicating hedge-fund returns. Late last year, after several articles about the software appeared in the British financial press, and professional investors approached Kat and Palaro about using it, they launched it as a business - though not, Kat insists, with the expectation of making much money. "I like my life as it is," he told me. "If we made a lot of money, I wouldn't know what to do with it. I've got a house here. I've got a summer house in Spain. That's enough. The only thing I need more of is time."

FundCreator's launch coincided with the end of a particularly bad year for hedge funds: in 2006, the majority failed to match the 15.8-per-cent return of the S. & P. 500. In February, Russell Read, the chief investment officer for the California state employees' pension fund, complained at a financial conference that many hedge funds were charging clients large sums that weren't matched by large returns. "A lot of people are waking up to the fact that hedge-fund fees are a bit steep, and they are looking for alternatives," Kat said.

In the London financial community, word of FundCreator's abilities has spread rapidly. As of last week, Kat said, two institutional investors were paying to use it, and more than fifty were experimenting with it. Kat and Palaro charge their clients an annual fee of roughly a third of one per cent of the money they invest using the software - less than a fifth of what most hedge funds charge. The cost of executing futures trades must be added on to FundCreator's management fees, but, unlike at hedge funds, investors keep all the gains they make. "Why would you pay the high fees that hedge funds charge if you are able to get the same risk characteristics, in a statistical sense, by using a dynamic futures-trading strategy?" Bas Peeters, the head of structured products at ING Investment Management, said to me. "FundCreator is potentially a very cost-efficient solution." Pete Eggleston, the head of quantitative solutions at the Royal Bank of Scotland, one of the biggest banks in Europe, said of FundCreator, "Such approaches may revolutionize the industry in terms of providing investors with access to lower-cost investment returns."

Some scholars remain skeptical. "As a renegade statistician, I am a little bit suspicious of Kat's methods," Stephen Brown, of N.Y.U., said to me. He pointed out that, unlike Quantum, many hedge funds have been around for just a few years and there is little information about their performance. "On the basis of very limited data, it is a real challenge to construct an accurate and robust model of hedge-fund returns," Brown said. Andrew Lo said that using FundCreator may not be as straightforward as it seems. "From the point of view of theory, there is nothing wrong with what Kat is doing," he said. "But all dynamic trading strategies involving derivatives carry some risk. They rely on very specialized mathematical assumptions. If the assumptions turn out to be wrong, you can be mis-estimating the risks in a big way." Faulty assessments of risk contributed to major financial losses suffered by Long-Term Capital Management and several other companies that have encountered problems trading derivatives.

Veryan Allen, an investment adviser and former hedge-fund executive who writes a blog about hedge funds (hedgefund.), said in a post last December, "If Goldman Sachs, Dow Jones, Merrill Lynch, Andrew Lo, or Harry Kat think they can do it, great . . . but I suspect investors will end up disappointed if they think the returns from hedge-fund clones will be anywhere near the performance of the best hedge funds." Allen went on, "No matter what occurs in the markets, well-managed 'expensive' hedge funds operating proprietary strategies with skilled traders, robust risk management, and technology will perform, even under pessimistic economic scenarios. . . . That is why it is worth paying the two and twenty. . . . Average or generic hedge funds can certainly be replicated, but not the best hedge funds."

When I asked Kat about the hedge-fund industry's reaction to FundCreator, he said, "People say, 'Look, you don't generate any alpha.' After fees, I generate a lot of alpha. I just generate it differently. Instead of trying to beat the market, I get the fees down." He conceded that there will always be hedge funds whose returns FundCreator can't hope to match, but he argued that even some of the most prestigious funds owe much of their success to luck. "You can be fortunate," he said. "You can live off market trends for quite a while. As in credit spreads" - the difference in yields between different types of bonds. "Credit spreads start to come down, and you make lots of money in credit. A couple of guys from an investment bank's credit desk jump out and start a fund. If they are lucky, the trend continues for another couple of years, and they will look like masters of the universe. But when the trend reverses, or when there is no trend left, they are in trouble. If a guy has done well for two years, what does that mean? He could be really smart, or he could be really lucky. If I had bought stocks at the end of 1997 and you had looked at me at the end of 1999, I would have looked brilliant."

It is notoriously difficult to distinguish between genuine investment skill and random variation. But firms like Renaissance Technologies, Citadel Investment Group, and D. E. Shaw appear to generate consistently high returns and low volatility. Shaw's main equity fund has posted average annual returns, after fees, of twenty-one per cent since 1989; Renaissance has reportedly produced even higher returns. (Most of the top-performing hedge funds are closed to new investors.) Kat questioned whether such firms, which trade in huge volumes on a daily basis, ought to be categorized as hedge funds at all. "Basically, they are the largest market-making firms in the world, but they call themselves hedge funds because it sells better," Kat said. "The average horizon on a trade for these guys is something like five seconds. They earn the spread. It's very smart, but their skill is in technology. It's in sucking up tick-by-tick data, processing all those data, and converting them into second-by-second positions in thousands of spreads worldwide. It's just algorithmic market-making."

Almost by definition, there can be only a handful of genius investors, Kat continued. "And even if they are there, the chances that you will find them and that they will let you in are very, very slim," he said. "That's what I tell people. If you are really convinced that you can find those super managers, then don't waste your time with our stuff. Go look for them. But if you are a bit more realistic, if you know that eighty per cent of hedge-fund managers aren't worth the fees they charge, then the rational thing to do is to give up trying to find a super manager, and just go for a good, efficient diversifier instead."

Not so long ago, Kat recalled, one hedge-fund manager, a "global macro" investor who specializes in betting on currencies and stock markets around the world, approached him with an offer. "He said, 'Harry, I want to buy your thing so I can replicate myself. Then I'll be able to enjoy life a bit more and keep sending my clients bills for two plus twenty. It'll take them years to figure it out, if they ever do.' "


CHERNOW, RON New Yorker; 3/23/2009, Vol. 85 Issue 6, p28-33, 6p

Where are the snow jobs of yesteryear?

In financial history, Ponzi schemes - the fraudulent enterprise of paying off old investors with money collected from new ones - are the most peculiar of crimes. Before they are detected, they seem exquisitely pleasing to perpetrators and victims alike. The fraud appears to be a bountiful gift that the confidence trickster, a generous soul and a financial wizard to boot, has bestowed upon a grateful world. Investors frequently revere the schemer, endowing him with magical properties. The schemer, in turn, may come to believe that his scheme isn't altogether shady and that he will someday generate the sensational returns advertised. For the duration of a Ponzi scheme, it may seem like a victimless crime. Not surprisingly, when the impostor is exposed, the victims experience profound hurt and disillusionment, having trusted implicitly in the schemer against a chorus of naysayers.

Charles Ponzi was probably the most colorful and outlandish practitioner of the scheme that bears his name. An Italian immigrant and postman's son who arrived in Boston in 1903, he had charm, imagination, and chutzpah of epic proportions. At first, he worked as a grocery clerk and dishwasher, but he soon got a job with a bank in Montreal that paid exorbitant interest rates and stole money from depositors - invaluable training for his future exploits. After being arrested for forging a signature on a check, Ponzi was clapped into a Quebec jail for twenty months and told his unsuspecting mother that he had landed a job as a "special assistant" to the warden. Returning to the United States, he served a two-year stint in an Atlanta prison for smuggling Italian immigrants into the country.

Ponzi's mind was a small factory for cranking out get-rich-quick schemes. Back in Boston in 1919, Ponzi had the epiphany that secured his place in the annals of financial larceny. An avid stamp collector, he received a letter from Spain that contained a voucher called an International Reply Coupon, which the recipient could redeem for a return-postage stamp at a fixed price in sixty-three countries. Many European currencies had slumped after the war, and Ponzi reasoned that he could buy such coupons, say, in debased Italian lire, redeem them in America, then sell the stamps at a sizable profit. It was an elementary form of currency arbitrage - exploiting discrepancies in the prices of the coupons in different currencies. In December of 1919, Ponzi launched a firm called the Securities Exchange Company - it preceded by more than a decade the creation of the Securities and Exchange Commission in Washington, D.C., established to police swindlers like Ponzi - and wooed investors by promising a fifty-per-cent return on their money in forty-five days.

Financial fraud is the crime of choice for arrivistes, insecure dreamers with a yearning eye for high society. Desperate to feel rich and important, they tend to be excellent mimics of respectability. The diminutive Ponzi fit the bill perfectly. A dandy in a straw boater with spats and a showy gold-tipped cane, he strutted about Boston, greeting reporters with ready quips and quotable lines, and his press coverage was, at first, highly laudatory.

Like many confidence men, Ponzi preyed first on his own kind, and the Boston Italian community embraced him with delirious joy. As insurance against future trouble, Ponzi also recruited Boston policemen and reporters as investors. In February, 1920, he collected a meagre five thousand dollars; five months later, he was raking in a million dollars weekly. Ponzi's business drew in thousands of investors, bewitched by his supposed prowess. With considerable skill, he portrayed himself as a populist champion who would enable small investors to earn their rightful places in the world. He claimed to accept money from investors as a form of altruism, and they rewarded him with fanatic loyalty.

Ponzi's investment strategy wasn't illegal, and the postal coupons could, in theory, have yielded a profit. In practice, however, the scheme was preposterous and unworkable. Nobody could buy and transport stamps in sufficient quantities to earn the returns that Ponzi promised. In "Ponzi's Scheme" (2005), Mitchell Zuckoff, a journalism professor at Boston University, regards his subject as a chronic dreamer with a cockeyed scheme that went awry. Ponzi was indeed a strange amalgam of petty visionary and big-time crook. Soon after he announced his scheme, postal authorities in Italy, France, and Romania suspended the sale of postal coupons, destroying any chance that Ponzi could implement his plan or reward investors with outsize returns. When anyone pressed him about his investment methods, he hinted that he couldn't reveal his lucrative strategies.

As he paid off old clients with money from new ones, the press scented criminal mischief afoot. The New York Postmaster, Thomas G. Patten, pointed out that too few coupons existed to sustain a scheme of such magnitude. When reporters dredged up Ponzi's criminal past in Montreal, complete with mug shots, his fate was sealed. Eight months after he founded the Securities Exchange Company, federal agents padlocked the offices. It turned out that Ponzi had never actually got around to buying many postal coupons and that it was all a colossal hoax. Sentenced to five years in a federal prison in Plymouth, Massachusetts, Ponzi had fancy stationery printed up that said "Charles Ponzi, Plymouth, Mass." He was deported to Italy in 1934, and later made his way to South America, where he died in the charity ward of a Rio de Janeiro hospital in 1949.

Ponzi was convinced that he was a wizard who had stumbled upon a form of financial alchemy that had eluded others. Incapable of moral clarity, he could never quite admit to himself that he was a charlatan and that his scheme was an impossible fiasco. He fooled others because he fooled himself. Right up until the end, he found refuge in fantasies that he might take over a chain of banks or shipping lines that would enable him to pay off his legions of worshipful investors. He never suffered serious remorse or second thoughts.

Ponzi's scheme has enjoyed a rich afterlife, often in far more adept hands. As one ponders the scandal of Bernard L. Madoff, who has pleaded guilty to fraud in a scheme thought to have cost nearly sixty-five billion dollars in investor money, one is tempted to say that Ponzi lacked ambition. Madoff imitated Ponzi in a few particulars, such as victimizing his own community (in his case, Jewish) and inventing fictitious returns, but his improvements on the traditional Ponzi scheme are breathtaking.

Where Ponzi pandered to uneducated investors and promised gargantuan returns, Madoff trimmed annual returns to a modest but wondrously reliable eight to twelve per cent. Madoff's seductive appeal lay not so much in his purported profits as in his consistency. Although that consistency was far more suspect than his returns, given the volatility of financial markets, the reasonable-sounding profits gave his operation an air of respectability. Wealthy investors could flatter themselves that, far from being greedy, they were sacrificing yield for security. Madoff's method enabled him to swindle rich people who prided themselves on their financial conservatism and sophistication, enabling him to appeal to avarice of a quiet, upper-crust sort.

Forever dependent on a growing supply of fresh victims, Ponzi schemers can't be fussy about their clients and are typically in an unseemly hurry to snare them. Here, Madoff made his most audacious innovation. Instead of openly courting investors, he pretended to fend them off. Back in the nineteen-twenties, sophisticated investors joined together in pools that manipulated individual stocks, and such funds acquired a certain cachet. Something similar happened in recent years with hedge funds, which retained snob appeal even when returns flagged. Madoff made it seem impossibly difficult to invest with him. As a rule, his fund was closed to new investors, requiring special introductions to the club. "I know Bernie, I can get you in" was the open sesame whispered throughout the world of Jewish society, where "Uncle Bernie" was affectionately touted as "the Jewish bond." The aura of exclusivity was bogus, of course: he ended up with almost five thousand client accounts.

Even when he deigned to accept people's money, Madoff emphasized his extreme reluctance. "Bernie would tell me, 'Let them start small, and if they're happy the first year or two, they can put in more,' " one investor told the Wall Street Journal. Madoff pretended that his investment-advisory business was merely a lucrative sideline for select friends, while his real business lay in a market-making operation that matched buyers and sellers. Thus Madoff posed as a man beleaguered by his own generosity, who took on new clients as a favor to friends. It was a bravura performance.

As word spread that Madoff made heaps of money for investors, he acquired a social glow at the country clubs where he recruited his victims, burnished by his mansion in the Hamptons, his villa on the French Riviera, and yachts moored in various places. Dressed in charcoal-gray bespoke suits from Seville Row and fond of expensive watches, he took on the protective coloration of his environment - a specialty of Ponzi schemers - and both admired and resented the moneyed crowd that he emulated. Only his facial twitches and the ghost of an old stammer gave the lie to his calm, avuncular image. His low-profile approach appealed to a class of investors who would have cringed at Ponzi's crass hucksterism.

Although he came from modest origins in the outer boroughs of New York - he earned the seed money for Bernard L. Madoff Investment Securities from working as a lifeguard at Rockaway Beach and installing sprinkler systems - Madoff clothed himself in establishment credentials. He was a trustee of Hofstra University, a nonexecutive chairman of the Nasdaq stock exchange, and a member of a government advisory panel on securities regulation. Like Ponzi, he posed as a paladin of small investors, and he ingratiated himself with government regulators. Every large Ponzi scheme needs an active network of agents - carnival barkers who pull people into the big tent - and Madoff strategically deployed people in places such as Greenwich, Connecticut, and Palm Beach, Florida. His mystique led prominent personalities - including Steven Spielberg, Mortimer Zuckerman, Senator Frank Lautenberg, Elie Wiesel, Sandy Koufax, and Kevin Bacon - to invest with Madoff directly or through charities they established.

Madoff's spectacular downfall has sparked a cottage industry of journalists trying to fathom his psychopathology. The enigmatic smirk he has shown to the news media, giving the impression of a man savoring a little joke on the world, has only heightened curiosity. In late January, the Times business section ran a piece that typed Madoff as a psychopath and quoted forensic psychologists who likened him to Ted Bundy, the serial killer: "They say that whereas Mr. Bundy murdered people, Mr. Madoff murdered wallets, bank accounts and people's sense of financial trust and security." These analysts assumed that Madoff intended from the outset to create a gigantic fraud and destroy thousands of people. Did he?

Although Madoff's scheme dates back to at least the early nineteen-nineties, we understand little about the genesis of his criminal operation. Still, a new biography of another grand-scale Ponzi schemer, to be published next month, allows for some educated guesses. "The Match King," by Frank Partnoy, a law professor at the University of San Diego, is an engrossing study of Ivar Kreuger, a Swedish financier of the nineteen-twenties and the operator of a global safety-match business so enormous that he was dubbed the Match King. Although his empire started only a few years after Ponzi's scheme imploded, Partnoy calculates that Kreuger's machinations lasted ten times longer and involved sums fifty times larger. He lifted the prosaic Ponzi fraud to a new level of sophistication and engaged in corporate finagling on a dizzying scale.

Kreuger didn't merely fabricate returns. He was a genuine businessman, backed by factories, mines, and other tangible assets. Like other industrialists, Kreuger planned to amass a huge fortune by manufacturing something ubiquitous and banal, much as John D. Rockefeller had done with kerosene. Kreuger wanted to monopolize the sale of the tiny boxes of safety matches that people used to light stoves or tobacco; cigarette smoking had become faddish among women as well as men in the nineteen-twenties, stoking demand for the product. By the 1929 crash, Kreuger's Swedish Match Company, a subsidiary of his holding company, Kreuger & Toll, had cornered the market on two-thirds of the forty billion matchboxes sold worldwide each year. Kreuger & Toll also earned a reputation as a proficient builder that completed construction projects reliably and on time. John Maynard Keynes extolled Kreuger as "perhaps the greatest constructive business intelligence of his age."

As a young man, Kreuger had rebelled against the monotony of his father's job as a factory manager in a small family match business on the Baltic Sea. The young man hatched grandiose plans as he studied engineering. Like Madoff, Kreuger was somewhat colorless and unassuming. He wore tastefully tailored suits, spoke five languages fluently, and projected an air of stability. He seldom laughed, was ascetic in his eating habits, and, aside from occasional flings with young women, was obsessed by business. A consummate actor who followed a scripted life, he always prepared a face to meet the faces that he met. Partnoy opens his story with Kreuger taking a transatlantic liner in the early nineteen-twenties and staging vignettes to impress other passengers. He undertook detailed preparations for meetings, then made sure specific questions were asked so that he could rattle off the string of facts he had memorized. He punctuated his speeches with meaningful pauses and long stares at the audience. Secretive and aloof, Kreuger, like Madoff, built his mystique by playing hard to get and retreating into a tight little zone of privacy.

Kreuger scarcely merits attention as a personality, although he had charm enough to court another great Swedish enigma, Greta Garbo. As a financial manipulator, however, Kreuger deserves study. In 1922, Swedish Match offered a dividend equal to twelve per cent of its share price, which Kreuger & Toll topped with a dividend worth twenty-five per cent. Kreuger believed that he could produce such lofty returns on a regular basis. Both his fame and his subsequent undoing came about because he was held hostage to those unrealistically high guarantees.

The alluring dividends dulled the critical faculties of investors, who didn't pry too closely into his affairs. With Europe devastated after the First World War, the only place where Kreuger could raise the vast capital to bankroll his empire was Wall Street. "You haggle about giving me money," Kreuger chided a Swedish banker. "But when I get off the boat in New York I find men on the pier begging me to take money off their hands." In 1923, Kreuger set up a new firm called International Match to act as a conduit for that money. American investors gave Kreuger a rapturous reception: by the time the Great Depression struck, his stocks and bonds ranked as the most widely held securities on Wall Street.

The American connection was all-important to Kreuger because of a daring plan he had concocted to take over the world match industry. He would approach governments with an irresistible deal: he'd lend them money at single-digit interest rates if, in exchange, they granted him domestic monopolies on matchbox production. Kreuger always hoped that his interest payments to Wall Street would be equalled by the interest on the money he was lending abroad, giving him the matchbox monopolies for free. But things never quite worked out that way, and he finally had to borrow at much higher interest rates on Wall Street than he received from foreign governments. By late 1927, Kreuger had parlayed his scheme into match monopolies in nearly a dozen countries. The whole operation was premised on an uninterrupted flow of capital from Wall Street, which hinged, in turn, on dangling those hefty returns before investors.

As he doled out stupendous dividends, Kreuger developed a loyal following among American investors, who profited handsomely from his securities. Before the New Deal, there were few disclosure requirements for securities. In the nineteen-twenties, fewer than a third of the firms listed on the New York Stock Exchange even bothered to publish quarterly reports. So it's not surprising that satisfied investors swallowed Kreuger's brief, cryptic statements. With the federal government gripped by a laissez-faire ideology, the states tried to compensate with so-called "blue sky" laws, which regulated the sale of securities to discourage fraud, but they were inadequate to the cunning of a transnational swindler such as Kreuger.

Like Ponzi, Kreuger didn't set out to create a fraudulent enterprise. Nor was he booking only phantom profits. Rather, he aroused exaggerated expectations that he couldn't live up to. Annual returns in the match industry fluctuated wildly, denying Kreuger the steady high earnings he needed. So he turned to the venerable robbing-Peter-to-pay-Paul racket. To pay his dividends, he took out secret loans, imagining that they were temporary, only to have the deception take on a permanent life of its own. Financial engineering had, instead of acting as the servant of his business, evolved into its very essence.

Ivar Kreuger's empire previews the multinational corporations of the nineteen-sixties which regarded themselves as sovereign states and aimed to soar above the regulatory snares of any single country. Like Harold Geneen, of I.T.T., and other conglomerate chieftains of that era, Kreuger thought that all businesses could be reduced to ledgers studied in the antiseptic atmosphere of a corporate suite. By the late nineteen-twenties, his Swedish Match division alone employed twenty-six thousand people in ninety match plants scattered across the globe. Tellingly, Partnoy's biography doesn't contain a single scene of Kreuger inspecting a factory, chatting with a floor manager or worker, or strolling through one of the forests from which his matchsticks were chopped. Nor, as far as we know, did his bankers or accountants evince the least bit of curiosity about seeing these places. Kreuger's haunts were banks, boardrooms, and government ministries. He was always shopping for tax havens and pliant governments, such as the Duchy of Liechtenstein - "droll little countries with droll little laws," he called them. By striking deals with politicians, he was able to negotiate monopolies that he could never have attained in the marketplace. And countries desperate for Kreuger's loans enabled him to charge their citizens artificially high prices for matches.

Kreuger was a virtuoso at financial shell games, shuffling assets from one subsidiary to another to produce the desired results. He converted corporate balance sheets from transparent tools to instruments of deceit. His maze of companies was so baffling that secret subsidiaries spawned other secret subsidiaries in a never-ending chain of concealment. Anticipating the murky world of Enron and A.I.G., Kreuger pioneered off-balance-sheet entities, shunting debt to invisible firms and dummy companies. At times, it seemed as if Ivar Kreuger alone understood the corporate behemoth he had created, and he showed how easily legitimate companies, with a little creative accounting, can turn into outlaw enterprises.

Those who wonder how Madoff duped his auditors will find an instructive case study in Partnoy's account of Kreuger's relationship with A. D. Berning, a junior auditor with Ernst & Ernst, the accounting firm that earned lucrative fees from representing Kreuger's business interests. The young functionary prided himself on handling the mogul's account, and was pathetically eager to please him. Berning wasn't disposed to question shocking discrepancies that surfaced in the ledgers, especially after the Kreuger account led to his making partner. The Match King softened him up with perks and presents, inviting him along on fancy trips that stroked the auditor's ego. Berning gradually became complicit in the fraud without ever quite realizing that he had strayed across the line. Later, he achieved heroic stature by his part in exposing the fraud that he had helped to perpetuate. Kreuger's American bankers, the Boston Brahmin house of Lee, Higginson & Company, were no less credulous toward their foremost underwriting client. Every time the firm got too nosy, Kreuger boosted the fees he paid it. Like Madoff, Kreuger presented himself as a public benefactor, but Kreuger did so on a global scale, since he was ostensibly helping to rescue the French and German economies and advising President Herbert Hoover.

As Kreuger slipped deeper into debt and deceit, his personality became impenetrable. In his tightly guarded world, his motto was "Silence, silence, and more silence." For days on end, he sequestered himself in his Stockholm headquarters and warded off unwanted visitors. Outside his boardroom he posted red and green lights to signal to his secretary whether visitors could enter. In his office, he had a dummy phone that rang whenever he stepped on a secret button under his desk; he would then cite urgent business to chase away guests who had overstayed their welcome. At times, he pretended to field calls from Mussolini or Stalin. At one point, he even hired Swedish actors to attend a reception and pose as ambassadors from various countries.

The inner sanctum that Kreuger created and the way he dodged spontaneous encounters presage aspects of how Madoff did business. Madoff operated his investment-advisory business on the seventeenth floor of the Lipstick Building, in midtown Manhattan, in offices that have been described as "icily cold modern." Even though he supposedly managed billions of dollars, he concentrated the operation in a small space, run by a handful of longtime associates and family members, who thus far haven't been charged with any wrongdoing. For a time, his wife, Ruth, supervised the firm's bank accounts. Madoff fostered a subtle climate of fear among investors. He grew testy when quizzed about his methods and forbade investors from discussing their conversations with him. When one client dared to do just that in an e-mail to other clients, Madoff threatened to banish the man from his fund. A tacit understanding arose that Madoff wouldn't discuss financial matters in social settings, preventing confrontations with inquisitive investors or encounters that might surprise him into unwanted revelations. Most of all, Madoff protected himself by being plain elusive. "You couldn't meet Madoff," one banker told the Wall Street Journal. "He was like a pop star."

In the classic account "The Great Crash," John Kenneth Galbraith notes that booms always mask many cases of embezzlement, which come to light during the bust. "Within a few days" of the 1929 crash, Galbraith writes, "something close to universal trust turned into something akin to universal suspicion." Such a climate was bound to undermine Ivar Kreuger, who appeared on the cover of Time the week of the crash, perhaps confirming the old journalistic adage that any phenomenon appearing on the cover of Time has already peaked. Kreuger's entire career had been predicated on access to American money markets. When they shut down, he couldn't survive long. In 1931, to lay to rest any doubts about his solvency, Kreuger actually boosted the International Match dividend from three dollars and twenty cents to four dollars per share, a promise that only worsened his predicament.

Kreuger had previously skirted the rules but, technically speaking, didn't engage in outright fraud. Only after the crash did he stoop to old-fashioned criminal behavior. He forged a series of Italian treasury bills, misspelling the name of an Italian finance official. However adroit in financial larceny, he was an amateur in more rudimentary forms of crime. Kreuger let it be known that he hoped to revive his sinking fortune by cutting a deal with Mussolini's government, and hinted at other secret deals in the works. Meanwhile, he shifted assets frantically from one account to another to hide an over-all shortage of funds, a shortage on the order of a hundred million dollars.

As rumors spread about his troubles, Kreuger became increasingly reclusive, avoiding meetings with bankers and auditors. He drank and smoked heavily and barricaded himself in a room in Stockholm that he had labelled the Silence Room. By early 1932, the gates of the New York credit markets had slammed shut for Ivar Kreuger. As he foresaw ruin, he grew manic, greeting his bankers on one occasion in yellow silk pajamas and a purple silk dressing gown. As the self-control of this skillful actor crumbled, he started to babble in sudden outbursts and heard imaginary phones ringing and people knocking at the door.

In March, 1932, at the age of fifty-two, Ivar Kreuger left his Paris apartment and bought a 9-mm. Browning pistol. As a dozen bankers awaited an important meeting with him, he retired to his bedroom, lay in bed, and shot himself in the heart. His suicide note began, "I have made such a mess of things that I believe this to be the most satisfactory solution for everybody concerned." Two weeks later, accountants at Price Waterhouse declared his companies insolvent. He left behind widespread destruction. The venerable house of Lee, Higginson went bankrupt, and one partner had the decency to admit, "I suddenly knew we had all been idiots." Unlike the Madoff scandal, Kreuger's downfall didn't leave investors completely bereft. Swedish Match retained a major portion of the world match market, and Kreuger also left behind substantial gold, timber, iron-ore, and real-estate interests. The trustees of International Match recovered a third of lost investor value after thirteen years - about the same amount that Ponzi's investors eventually recovered.

Frank Partnoy, as a fair-minded biographer, renders a mixed verdict on Ivar Kreuger. "He was not merely the greatest financial fraudster of the century," he writes. "He was a builder, as well as a destroyer." Certainly, Kreuger, like all great Ponzi schemers, had a willing army of dupes and confederates behind him; as is often the case, the victims were so gullible that they seem like eager accomplices to, as well as casualties of, the fraud. And, no less than Ponzi, Kreuger had also deceived himself.

Few financiers become embroiled in Ponzi schemes voluntarily, for the simple reason that such schemes are mathematically certain to fail. At some point, the incoming money cannot keep pace with the outgoing claims, and the fraud must unravel. And so the saga of Ivar Kreuger presents a credible explanation of how giant Ponzi enterprises come about: not as sudden inspirations of criminal masterminds but as the gradual culmination of small moral compromises made by financiers who aren't quite as ingenious as they think. As Charles Baudelaire once said, we descend into hell by tiny steps. Indeed, in pleading guilty last Thursday, Madoff explained that he had initially thought his fraud would be short-lived. He may well have fancied himself a brilliant money manager. Perhaps, early on, he even had a few good, legitimate years. When his lucky streak suddenly ended, he might have thought that he would temporarily make whole the losses of old investors by giving them money from new ones. And then he was off and running.


Gladding, Kent W. Timely Topics Citizens Investment Management Services, Fall 2005

Indexing as a strategy gained enormous popularity over the last decade. The trillions of dollars invested in index products is proof that indexing strategies are widely accepted by both institutional investors and retail investors. In short, indexing is a fashionable investing trend, and like any other investing trend, it comes along with its own set of risk and return characteristics.

Indexing is a logical extension of the efficient market theory, which asserts that changing fundamentals are immediately reflected in security prices, and unless the investor is in possession of non-public information, it is virtually impossible for active managers to generate alpha. Investors who watch their manager struggle to beat the benchmark often conclude that indexing is an attractive low cost alternative to guaranteeing at least a benchmark return.

Investors who index are by definition emphasizing the largest companies in the benchmark because most all of the institutional benchmarks currently in use are market capitalization weighted. This means the current stock market value of the company determines the weight of that company in the index. If the market is efficient and correctly discounts future cash flows of the firm on a risk adjusted basis, then investing in cap weighted indices makes sense. There are reasons to believe however that the market is not always efficient. From time to time, market bubbles develop thanks to irrational exuberance. Indexers should be wary of their exposure to an index when the benchmark takes on extraordinary risk characteristics, and they should seek to mitigate the risk through active management or enhanced indexing.

At the peak of the technology bull market in 1999 to 2000, technology represented 40% of the S&P 500, and many of the largest stocks and biggest index components carried PIE multiples between 40 and 100x earnings. Many active managers performed as poorly as the index by simply emulating it. At the same time, investors who avoided extravagantly priced tech stocks came through the bear market relatively unscathed. Investors who indexed against the S&P 500 during the bear market lost 40% of their investment over a three year period. Clearly, even the use of d broad based market index like the S&P 500 in and of itself does not always provide adequate diversification.

Critics of indexing point out that cap-weighted indices are a function of investor sentiment rather than fundamentals. In other words, if the indices were constructed based on alternative metrics such as total revenues, dividends paid, earnings etc., the ranking of companies would change dramatically. Walmart for example would leap ahead of Microsoft in an index based on these fundamentals. If in fact the alternative measures are more predictive of long run economic returns, and stock prices reflect economic returns in the long run, then cap-weighted indices will not generate optimal returns. Returns from indices based on fundamentals should in theory produce higher returns. Academic studies indicate that in fact alternative indices based on fundamental metrics produce higher than market returns regardless of market cycles.

Strangely, the popularity of indexing is in itself a source of noise in security prices. Cash pours into index products automatically based on asset allocation decisions that are made with no reference to underlying fundamentals. Obviously if all investors pursued indexing simultaneously, it would be impossible to achieve a rational allocation of capital.

Many investors choose to emphasize fundamentals that differ significantly from a popular index. For example, the dividend yield on the S&P 500 is 2.0%. However, many stocks pay almost twice this rate, and regularly increase their dividend, resulting in a very high effective yield on the original investment. Investing in stocks that consistently increase dividends is just one example of an investment strategy that requires active management. Purchasing the best stocks in an index, and avoiding the weakest, is another example of an active strategy that intuitively makes sense while representing a significant departure from indexation.

At Citizens, we often suggest strategies that emphasize active management complemented with passive indexation. As Benjamin Graham once remarked, "in the short run, the market is a voting machine, but in the long run it is a weighing machine." In other words, fundamentals do matter, and it makes sense to combine a passive portfolio with an active portfolio of stocks that exhibit superior fundamental characteristics. It will help everyone involved sleep at night.


How Nassim Taleb turned the inevitability of disaster into an investment strategy

The New Yorker April 22 & 29, 2002

One day in 1996, a Wall Street trader named Nassim Nicholas Taleb went to see Victor Niederhoffer. Victor Niederhoffer was one of the most successful money managers in the country. He lived and worked out of a thirteen-acre compound in Fairfield County, Connecticut, and when Taleb drove up that day from his home in Larchmont he had to give his name at the gate, and then make his way down a long, curving driveway. Niederhoffer had a squash court and a tennis court and a swimming pool and a colossal, faux-alpine mansion in which virtually every square inch of space was covered with eighteenth- and nineteenth-century American folk art. In those days, he played tennis regularly with the billionaire financier George Soros. He had just written a best-selling book, "The Education of a Speculator," dedicated to his father, Artie Niederhoffer, a police officer from Coney Island. He had a huge and eclectic library and a seemingly insatiable desire for knowledge. When Niederhoffer went to Harvard as an undergraduate, he showed up for the very first squash practice and announced that he would someday be the best in that sport; and, sure enough, he soon beat the legendary Shariff Khan to win the U.S. Open squash championship. That was the kind of man Niederhoffer was. He had heard of Taleb's growing reputation in the esoteric field of options trading, and summoned him to Connecticut. Taleb was in awe.

"He didn't talk much, so I observed him," Taleb recalls. "I spent seven hours watching him trade. Everyone else in his office was in his twenties, and he was in his fifties, and he had the most energy of them all. Then, after the markets closed, he went out to hit a thousand backhands on the tennis court." Taleb is Greek-Orthodox Lebanese and his first language was French, and in his pronunciation the name Niederhoffer comes out as the slightly more exotic Nieder hoffer. "Here was a guy living in a mansion with thousands of books, and that was my dream as a child," Taleb went on. "He was part chevalier, part scholar. My respect for him was intense." There was just one problem, however, and it is the key to understanding the strange path that Nassim Taleb has chosen, and the position he now holds as Wall Street's principal dissident. Despite his envy and admiration, he did not want to be Victor Niederhoffer -- not then, not now, and not even for a moment in between. For when he looked around him, at the books and the tennis court and the folk art on the walls -- when he contemplated the countless millions that Niederhoffer had made over the years -- he could not escape the thought that it might all have been the result of sheer, dumb luck.

Taleb knew how heretical that thought was. Wall Street was dedicated to the principle that when it came to playing the markets there was such a thing as expertise, that skill and insight mattered in investing just as skill and insight mattered in surgery and golf and flying fighter jets. Those who had the foresight to grasp the role that software would play in the modern world bought Microsoft in 1985, and made a fortune. Those who understood the psychology of investment bubbles sold their tech stocks at the end of 1999 and escaped the Nasdaq crash. Warren Buffett was known as the "sage of Omaha" because it seemed incontrovertible that if you started with nothing and ended up with billions then you had to be smarter than everyone else: Buffett was successful for a reason. Yet how could you know, Taleb wondered, whether that reason was responsible for someone's success, or simply a rationalization invented after the fact? George Soros seemed to be successful for a reason, too. He used to say that he followed something called "the theory of reflexivity." But then, later, Soros wrote that in most situations his theory "is so feeble that it can be safely ignored." An old trading partner of Taleb's, a man named Jean-Manuel Rozan, once spent an entire afternoon arguing about the stock market with Soros. Soros was vehemently bearish, and he had an elaborate theory to explain why, which turned out to be entirely wrong. The stock market boomed. Two years later, Rozan ran into Soros at a tennis tournament. "Do you remember our conversation?" Rozan asked. "I recall it very well," Soros replied. "I changed my mind, and made an absolute fortune." He changed his mind! The truest thing about Soros seemed to be what his son Robert had once said:

My father will sit down and give you theories to explain why he does this or that. But I remember seeing it as a kid and thinking, Jesus Christ, at least half of this is bullshit. I mean, you know the reason he changes his position on the market or whatever is because his back starts killing him. It has nothing to do with reason. He literally goes into a spasm, and it?s this early warning sign.

For Taleb, then, the question why someone was a success in the financial marketplace was vexing. Taleb could do the arithmetic in his head. Suppose that there were ten thousand investment managers out there, which is not an outlandish number, and that every year half of them, entirely by chance, made money and half of them, entirely by chance, lost money. And suppose that every year the losers were tossed out, and the game replayed with those who remained. At the end of five years, there would be three hundred and thirteen people who had made money in every one of those years, and after ten years there would be nine people who had made money every single year in a row, all out of pure luck. Niederhoffer, like Buffett and Soros, was a brilliant man. He had a Ph.D. in economics from the University of Chicago. He had pioneered the idea that through close mathematical analysis of patterns in the market an investor could identify profitable anomalies. But who was to say that he wasn't one of those lucky nine? And who was to say that in the eleventh year Niederhoffer would be one of the unlucky ones, who suddenly lost it all, who suddenly, as they say on Wall Street, "blew up"?

Taleb remembered his childhood in Lebanon and watching his country turn, as he puts it, from "paradise to hell" in six months. His family once owned vast tracts of land in northern Lebanon. All of that was gone. He remembered his grandfather, the former Deputy Prime Minister of Lebanon and the son of a Deputy Prime Minister of Lebanon and a man of great personal dignity, living out his days in a dowdy apartment in Athens. That was the problem with a world in which there was so much uncertainty about why things ended up the way they did: you never knew whether one day your luck would turn and it would all be washed away.

So here is what Taleb took from Niederhoffer. He saw that Niederhoffer was a serious athlete, and he decided that he would be, too. He would bicycle to work and exercise in the gym. Niederhoffer was a staunch empiricist, who turned to Taleb that day in Connecticut and said to him sternly, "Everything that can be tested must be tested," and so when Taleb started his own hedge fund, a few years later, he called it Empirica. But that is where it stopped. Nassim Taleb decided that he could not pursue an investment strategy that had any chance of blowing up.

Nassim Taleb is a tall, muscular man in his early forties, with a salt-and-pepper beard and a balding head. His eyebrows are heavy and his nose is long. His skin has the olive hue of the Levant. He is a man of moods, and when his world turns dark the eyebrows come together and the eyes narrow and it is as if he were giving off an electrical charge. It is said, by some of his friends, that he looks like Salman Rushdie, although at his office his staff have pinned to the bulletin board a photograph of a mullah they swear is Taleb's long-lost twin, while Taleb himself maintains, wholly implausibly, that he resembles Sean Connery. He lives in a four-bedroom Tudor with twenty-six Russian Orthodox icons, nineteen Roman heads, and four thousand books, and he rises at dawn to spend an hour writing. He is the author of two books, the first a technical and highly regarded work on derivatives, and the second a treatise entitled "Fooled by Randomness," which was published last year and is to conventional Wall Street wisdom approximately what Martin Luther's ninety-five theses were to the Catholic Church. Some afternoons, he drives into the city and attends a philosophy lecture at City University. During the school year, in the evenings, he teaches a graduate course in finance at New York University, after which he can often be found at the bar at Odeon Café in Tribeca, holding forth, say, on the finer points of stochastic volatility or his veneration of the Greek poet C. P. Cavafy.

Taleb runs Empirica Capital out of an anonymous, concrete office park somewhere in the woods outside Greenwich, Connecticut. His offices consist, principally, of a trading floor about the size of a Manhattan studio apartment. Taleb sits in one corner, in front of a laptop, surrounded by the rest of his team -- Mark Spitznagel, the chief trader, another trader named Danny Tosto, a programmer named Winn Martin, and a graduate student named Pallop Angsupun. Mark Spitznagel is perhaps thirty. Win, Danny, and Pallop look as if they belonged in high school. The room has an overstuffed bookshelf in one corner, and a television muted and tuned to CNBC. There are two ancient Greek heads, one next to Taleb's computer and the other, somewhat bafflingly, on the floor, next to the door, as if it were being set out for the trash. There is almost nothing on the walls, except for a slightly battered poster for an exhibition of Greek artifacts, the snapshot of the mullah, and a small pen-and-ink drawing of the patron saint of Empirica Capital, the philosopher Karl Popper.

On a recent spring morning, the staff of Empirica were concerned with solving a thorny problem, having to do with the square root of n, where n is a given number of random set of observations, and what relation n might have to a speculator's confidence in his estimations. Taleb was up at a whiteboard by the door, his marker squeaking furiously as he scribbled possible solutions. Spitznagel and Pallop looked on intently. Spitznagel is blond and from the Midwest and does yoga: in contrast to Taleb, he exudes a certain laconic levelheadedness. In a bar, Taleb would pick a fight. Spitznagel would break it up. Pallop is of Thai extraction and is doing a Ph.D. in financial mathematics at Princeton. He has longish black hair, and a slightly quizzical air. "Pallop is very lazy," Taleb will remark, to no one in particular, several times over the course of the day, although this is said with such affection that it suggests that "laziness," in the Talebian nomenclature, is a synonym for genius. Pallop's computer was untouched and he often turned his chair around, so that he faced completely away from his desk. He was reading a book by the cognitive psychologists Amos Tversky and Daniel Kahneman, whose arguments, he said a bit disappointedly, were "not really quantifiable." The three argued back and forth about the solution. It appeared that Taleb might be wrong, but before the matter could be resolved the markets opened. Taleb returned to his desk and began to bicker with Spitznagel about what exactly would be put on the company boom box. Spitznagel plays the piano and the French horn and has appointed himself the Empirica d.j. He wanted to play Mahler, and Taleb does not like Mahler. "Mahler is not good for volatility," Taleb complained. "Bach is good. St. Matthew's Passion!" Taleb gestured toward Spitznagel, who was wearing a gray woollen turtleneck. "Look at him. He wants to be like von Karajan, like someone who wants to live in a castle. Technically superior to the rest of us. No chitchatting. Top skier. That's Mark!" As Spitznagel rolled his eyes, a man whom Taleb refers to, somewhat mysteriously, as Dr. Wu wandered in. Dr. Wu works for another hedge fund, down the hall, and is said to be brilliant. He is thin and squints through black-rimmed glasses. He was asked his opinion on the square root of n but declined to answer. "Dr. Wu comes here for intellectual kicks and to borrow books and to talk music with Mark," Taleb explained after their visitor had drifted away. He added darkly, "Dr. Wu is a Mahlerian."

Empirica follows a very particular investment strategy. It trades options, which is to say that it deals not in stocks and bonds but with bets on stocks and bonds. Imagine, for example, that General Motors stock is trading at fifty dollars, and imagine that you are a major investor on Wall Street. An options trader comes up to you with a proposition. What if, within the next three months, he decides to sell you a share of G.M. at forty-five dollars? How much would you charge for agreeing to buy it at that price? You would look at the history of G.M. and see that in a three-month period it has rarely dropped ten per cent, and obviously the trader is only going to make you buy his G.M. at forty-five dollars if the stock drops below that point. So you say you'll make that promise, or sell that option, for a relatively small fee, say, a dime. You are betting on the high probability that G.M. stock will stay relatively calm over the next three months, and if you are right you'll pocket the dime as pure profit. The trader, on the other hand, is betting on the unlikely event that G.M. stock will drop a lot, and if that happens his profits are potentially huge. If the trader bought a million options from you at a dime each and G.M. drops to thirty-five dollars, he'll buy a million shares at thirty-five dollars and turn around and force you to buy them at forty-five dollars, making himself suddenly very rich and you substantially poorer.

That particular transaction is called, in the argot of Wall Street, an "out-of-the-money option." But an option can be configured in a vast number of ways. You could sell the trader a G.M. option at thirty dollars, or, if you wanted to bet against G.M. stock going up, you could sell a G.M. option at sixty dollars. You could sell or buy options on bonds, on the S. & P. index, on foreign currencies or on mortgages, or on the relationship among any number of financial instruments of your choice; you can bet on the market booming, or the market crashing, or the market staying the same. Options allow investors to gamble heavily and turn one dollar into ten. They also allow investors to hedge their risk. The reason your pension fund may not be wiped out in the next crash is that it has protected itself by buying options. What drives the options game is the notion that the risks represented by all of these bets can be quantified; that by looking at the past behavior of G.M. you can figure out the exact chance of G.M. hitting forty-five dollars in the next three months, and whether at a dollar that option is a good or a bad investment. The process is a lot like the way insurance companies analyze actuarial statistics in order to figure out how much to charge for a life-insurance premium, and to make those calculations every investment bank has, on staff, a team of Ph.D.s, physicists from Russia, applied mathematicians from China, computer scientists from India. On Wall Street, those Ph.D.s are called "quants."

Nassim Taleb and his team at Empirica are quants. But they reject the quant orthodoxy, because they don't believe that things like the stock market behave in the way that physical phenomena like mortality statistics do. Physical events, whether death rates or poker games, are the predictable function of a limited and stable set of factors, and tend to follow what statisticians call a "normal distribution," a bell curve. But do the ups and downs of the market follow a bell curve? The economist Eugene Fama once studied stock prices and pointed out that if they followed a normal distribution you'd expect a really big jump, what he specified as a movement five standard deviations from the mean, once every seven thousand years. In fact, jumps of that magnitude happen in the stock market every three or four years, because investors don't behave with any kind of statistical orderliness. They change their mind. They do stupid things. They copy each other. They panic. Fama concluded that if you charted the ups and downs of the stock market the graph would have a "fat tail,"meaning that at the upper and lower ends of the distribution there would be many more outlying events than statisticians used to modelling the physical world would have imagined.

In the summer of 1997, Taleb predicted that hedge funds like Long Term Capital Management were headed for trouble, because they did not understand this notion of fat tails. Just a year later, L.T.C.M. sold an extraordinary number of options, because its computer models told it that the markets ought to be calming down. And what happened? The Russian government defaulted on its bonds; the markets went crazy; and in a matter of weeks L.T.C.M. was finished. Spitznagel, Taleb's head trader, says that he recently heard one of the former top executives of L.T.C.M. give a lecture in which he defended the gamble that the fund had made. "What he said was, Look, when I drive home every night in the fall I see all these leaves scattered around the base of the trees,?" Spitznagel recounts. "There is a statistical distribution that governs the way they fall, and I can be pretty accurate in figuring out what that distribution is going to be. But one day I came home and the leaves were in little piles. Does that falsify my theory that there are statistical rules governing how leaves fall? No. It was a man-made event." In other words, the Russians, by defaulting on their bonds, did something that they were not supposed to do, a once-in-a-lifetime, rule-breaking event. But this, to Taleb, is just the point: in the markets, unlike in the physical universe, the rules of the game can be changed. Central banks can decide to default on government-backed securities.

One of Taleb's earliest Wall Street mentors was a short-tempered Frenchman named Jean-Patrice, who dressed like a peacock and had an almost neurotic obsession with risk. Jean-Patrice would call Taleb from Regine's at three in the morning, or take a meeting in a Paris nightclub, sipping champagne and surrounded by scantily clad women, and once Jean-Patrice asked Taleb what would happen to his positions if a plane crashed into his building. Taleb was young then and brushed him aside. It seemed absurd. But nothing, Taleb soon realized, is absurd. Taleb likes to quote David Hume: "No amount of observations of white swans can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion." Because L.T.C.M. had never seen a black swan in Russia, it thought no Russian black swans existed. Taleb, by contrast, has constructed a trading philosophy predicated entirely on the existence of black swans. on the possibility of some random, unexpected event sweeping the markets. He never sells options, then. He only buys them. He's never the one who can lose a great deal of money if G.M. stock suddenly plunges. Nor does he ever bet on the market moving in one direction or another. That would require Taleb to assume that he understands the market, and he doesn't. He hasn't Warren Buffett's confidence. So he buys options on both sides, on the possibility of the market moving both up and down. And he doesn't bet on minor fluctuations in the market. Why bother? If everyone else is vastly underestimating the possibility of rare events, then an option on G.M. at, say, forty dollars is going to be undervalued. So Taleb buys out-of-the-money options by the truckload. He buys them for hundreds of different stocks, and if they expire before he gets to use them he simply buys more. Taleb doesn't even invest in stocks, not for Empirica and not for his own personal account. Buying a stock, unlike buying an option, is a gamble that the future will represent an improved version of the past. And who knows whether that will be true? So all of Taleb's personal wealth, and the hundreds of millions that Empirica has in reserve, is in Treasury bills. Few on Wall Street have taken the practice of buying options to such extremes. But if anything completely out of the ordinary happens to the stock market, if some random event sends a jolt through all of Wall Street and pushes G.M. to, say, twenty dollars, Nassim Taleb will not end up in a dowdy apartment in Athens. He will be rich.

Not long ago, Taleb went to a dinner in a French restaurant just north of Wall Street. The people at the dinner were all quants: men with bulging pockets and open-collared shirts and the serene and slightly detached air of those who daydream in numbers. Taleb sat at the end of the table, drinking pastis and discussing French literature. There was a chess grand master at the table, with a shock of white hair, who had once been one of Anatoly Karpov's teachers, and another man who over the course of his career had worked, in order, at Stanford University, Exxon, Los Alamos National Laboratory, Morgan Stanley, and a boutique French investment bank. They talked about mathematics and chess and fretted about one of their party who had not yet arrived and who had the reputation, as one of the quants worriedly said, of "not being able to find the bathroom." When the check came, it was given to a man who worked in risk management at a big Wall Street bank, and he stared at it for a long time, with a slight mixture of perplexity and amusement, as if he could not remember what it was like to deal with a mathematical problem of such banality. The men at the table were in a business that was formally about mathematics but was really about epistemology, because to sell or to buy an option requires each party to confront the question of what it is he truly knows. Taleb buys options because he is certain that, at root, he knows nothing, or, more precisely, that other people believe they know more than they do. But there were plenty of people around that table who sold options, who thought that if you were smart enough to set the price of the option properly you could win so many of those one-dollar bets on General Motors that, even if the stock ever did dip below forty-five dollars, you'd still come out far ahead. They believe that the world is a place where, at the end of the day, leaves fall more or less in a predictable pattern.

The distinction between these two sides is the divide that emerged between Taleb and Niederhoffer all those years ago in Connecticut. Niederhoffer's hero is the nineteenth-century scientist Francis Galton. Niederhoffer called his eldest daughter Galt, and there is a full-length portrait of Galton in his library. Galton was a statistician and a social scientist (and a geneticist and a meteorologist), and if he was your hero you believed that by marshalling empirical evidence, by aggregating data points, you could learn whatever it was you needed to know. Taleb's hero, on the other hand, is Karl Popper, who said that you could not know with any certainty that a proposition was true; you could only know that it was not true. Taleb makes much of what he learned from Niederhoffer, but Niederhoffer insists that his example was wasted on Taleb. "In one of his cases, Rumpole of the Bailey talked about being tried by the bishop who doesn't believe in God," Niederhoffer says. "Nassim is the empiricist who doesn't believe in empiricism." What is it that you claim to learn from experience, if you believe that experience cannot be trusted? Today, Niederhoffer makes a lot of his money selling options, and more often than not the person who he sells those options to is Nassim Taleb. If one of them is up a dollar one day, in other words, that dollar is likely to have come from the other. The teacher and pupil have become predator and prey.

Years ago, Nassim Taleb worked at the investment bank First Boston, and one of the things that puzzled him was what he saw as the mindless industry of the trading floor. A trader was supposed to come in every morning and buy and sell things, and on the basis of how much money he made buying and selling he was given a bonus. If he went too many weeks without showing a profit, his peers would start to look at him funny, and if he went too many months without showing a profit he would be gone. The traders were often well educated, and wore Savile Row suits and Ferragamo ties. They dove into the markets with a frantic urgency. They read the Wall Street Journal closely and gathered around the television to catch breaking news. "The Fed did this, the Prime Minister of Spain did that," Taleb recalls. "The Italian Finance Minister says there will be no competitive devaluation, this number is higher than expected, Abby Cohen just said this." It was a scene that Taleb did not understand.

"He was always so conceptual about what he was doing," says Howard Savery, who was Taleb?s assistant at the French bank Indosuez in the nineteen-eighties. "He used to drive our floor trader (his name was Tim) crazy. Floor traders are used to precision: "Sell a hundred futures at eighty-seven." Nassim would pick up the phone and say, "Tim, sell some." And Tim would say, "How many?" And he would say, "Oh, a social amount." It was like saying, "I don't have a number in mind, I just know I want to sell." There would be these heated arguments in French, screaming arguments. Then everyone would go out to dinner and have fun. Nassim and his group had this attitude that we're not interested in knowing what the new trade number is. When everyone else was leaning over their desks, listening closely to the latest figures, Nassim would make a big scene of walking out of the room."

At Empirica, then, there are no Wall Street Journals to be found. There is very little active trading, because the options that the fund owns are selected by computer. Most of those options will be useful only if the market does something dramatic, and, of course, on most days the market doesn't. So the job of Taleb and his team is to wait and to think. They analyze the company's trading policies, back-test various strategies, and construct ever-more sophisticated computer models of options pricing. Danny, in the corner, occasionally types things into the computer. Pallop looks dreamily off into the distance. Spitznagel takes calls from traders, and toggles back and forth between screens on his computer. Taleb answers e-mails and calls one of the firm's brokers in Chicago, affecting, as he does, the kind of Brooklyn accent that people from Brooklyn would have if they were actually from northern Lebanon: "Howyoudoin?" It is closer to a classroom than to a trading floor.

"Pallop, did you introspect?" Taleb calls out as he wanders back in from lunch. Pallop is asked what his Ph.D. is about. "Pretty much this," he says, waving a languid hand around the room."It looks like we will have to write it for him," Taleb chimes in, "because Pollop is very lazy."

What Empirica has done is to invert the traditional psychology of investing. You and I, if we invest conventionally in the market, have a fairly large chance of making a small amount of money in a given day from dividends or interest or the general upward trend of the market. We have almost no chance of making a large amount of money in one day, and there is a very small, but real, possibility that if the market collapses we could blow up. We accept that distribution of risks because, for fundamental reasons, it feels right. In the book that Pallop was reading by Kahneman and Tversky, for example, there is a description of a simple experiment, where a group of people were told to imagine that they had three hundred dollars. They were then given a choice between (a) receiving another hundred dollars or (b) tossing a coin, where if they won they got two hundred dollars and if they lost they got nothing. Most of us, it turns out, prefer (a) to (b). But then Kahneman and Tversky did a second experiment. They told people to imagine that they had five hundred dollars, and then asked them if they would rather (c) give up a hundred dollars or (d) toss a coin and pay two hundred dollars if they lost and nothing at all if they won. Most of us now prefer (d) to (c). What is interesting about those four choices is that, from a probabilistic standpoint, they are identical. They all yield an expected outcome of four hundred dollars. Nonetheless, we have strong preferences among them. Why? Because we're more willing to gamble when it comes to losses, but are risk averse when it comes to our gains. That's why we like small daily winnings in the stock market, even if that requires that we risk losing everything in a crash.

At Empirica, by contrast, every day brings a small but real possibility that they'll make a huge amount of money in a day; no chance that they'll blow up; and a very large possibility that they'll lose a small amount of money. All those dollar, and fifty-cent, and nickel options that Empirica has accumulated, few of which will ever be used, soon begin to add up. By looking at a particular column on the computer screens showing Empirica's positions, anyone at the firm can tell you precisely how much money Empirica has lost or made so far that day. At 11:30 A.M., for instance, they had recovered just twenty-eight percent of the money they had spent that day on options. By 12:30, they had recovered forty per cent, meaning that the day was not yet half over and Empirica was already in the red to the tune of several hundred thousand dollars. The day before that, it had made back eighty-five per cent of its money; the day before that, forty-eight per cent; the day before that, sixty-five per cent; and the day before that also sixty-five per cent; and, in fact-with a few notable exceptions, like the few days when the market reopened after September 11th -- Empirica has done nothing but lose money since last April. "We cannot blow up, we can only bleed to death," Taleb says, and bleeding to death, absorbing the pain of steady losses, is precisely what human beings are hardwired to avoid. "Say you've got a guy who is long on Russian bonds," Savery says. "He's making money every day. One day, lightning strikes and he loses five times what he made. Still, on three hundred and sixty-four out of three hundred and sixty-five days he was very happily making money. It's much harder to be the other guy, the guy losing money three hundred and sixty-four days out of three hundred and sixty-five, because you start questioning yourself. Am I ever going to make it back? Am I really right? What if it takes ten years? Will I even be sane ten years from now?" What the normal trader gets from his daily winnings is feedback, the pleasing illusion of progress. At Empirica, there is no feedback. "It's like you're playing the piano for ten years and you still can't play chopsticks," Spitznagel say, "and the only thing you have to keep you going is the belief that one day you'll wake up and play like Rachmaninoff." Was it easy knowing that Niederhoffer -- who represented everything they thought was wrong -- was out there getting rich while they were bleeding away? Of course it wasn't . If you watched Taleb closely that day, you could see the little ways in which the steady drip of losses takes a toll. He glanced a bit too much at the Bloomberg. He leaned forward a bit too often to see the daily loss count. He succumbs to an array of superstitious tics. If the going is good, he parks in the same space every day; he turned against Mahler because he associates Mahler with the last year's long dry spell. "Nassim says all the time that he needs me there, and I believe him," Spitznagel says. He is there to remind Taleb that there is a point to waiting, to help Taleb resist the very human impulse to abandon everything and stanch the pain of losing. "Mark is my cop," Taleb says. So is Pallop: he is there to remind Taleb that Empirica has the intellectual edge.

"The key is not having the ideas but having the recipe to deal with your ideas," Taleb says. "We don't need moralizing. We need a set of tricks." His trick is a protocol that stipulates precisely what has to be done in every situation. "We built the protocol, and the reason we did was to tell the guys, Don't listen to me, listen to the protocol. Now, I have the right to change the protocol, but there is a protocol to changing the protocol. We have to be hard on ourselves to do what we do. The bias we see in Niederhoffer we see in ourselves." At the quant dinner, Taleb devoured his roll, and as the busboy came around with more rolls Taleb shouted out "No, no!" and blocked his plate. It was a never-ending struggle, this battle between head and heart. When the waiter came around with wine, he hastily covered the glass with his hand. When the time came to order, he asked for steak frites -- without the frites, please! -- and then immediately tried to hedge his choice by negotiating with the person next to him for a fraction of his frites.

The psychologist Walter Mischel has done a series of experiments where he puts a young child in a room and places two cookies in front of him, one small and one large. The child is told that if he wants the small cookie he need only ring a bell and the experimenter will come back into the room and give it to him. If he wants the better treat, though, he has to wait until the experimenter returns on his own, which might be anytime in the next twenty minutes. Mischel has videotapes of six-year-olds, sitting in the room by themselves, staring at the cookies, trying to persuade themselves to wait. One girl starts to sing to herself. She whispers what seems to be the instructions -- that she can have the big cookie if she can only wait. She closes her eyes. Then she turns her back on the cookies. Another little boy swings his legs violently back and forth, and then picks up the bell and examines it, trying to do anything but think about the cookie he could get by ringing it. The tapes document the beginnings of discipline and self-control -- the techniques we learn to keep our impulses in check -- and to watch all the children desperately distracting themselves is to experience the shock of recognition: that's Nassim Taleb!

There is something else as well that helps to explain Taleb's resolve -- more than the tics and the systems and the self-denying ordinances. It happened a year or so before he went to see Niederhoffer. Taleb had been working as a trader at the Chicago Mercantile Exchange, and developed a persistently hoarse throat. At first, he thought nothing of it: a hoarse throat was an occupational hazard of spending every day in the pit. Finally, when he moved back to New York, he went to see a doctor, in one of those Upper East Side prewar buildings with a glamorous façade. Taleb sat in the office, staring out at the plain brick of the courtyard, reading the medical diplomas on the wall over and over, waiting and waiting for the verdict. The doctor returned and spoke in a low, grave voice: "I got the pathology report. It's not as bad as it sounds ?" But, of course, it was: he had throat cancer. Taleb's mind shut down. He left the office. It was raining outside. He walked and walked and ended up at a medical library. There he read frantically about his disease, the rainwater forming a puddle under his feet. It made no sense. Throat cancer was the disease of someone who has spent a lifetime smoking heavily. But Taleb was young, and he barely smoked at all. His risk of getting throat cancer was something like one in a hundred thousand, almost unimaginably small. He was a black swan! The cancer is now beaten, but the memory of it is also Taleb's secret, because once you have been a black swan -- not just seen one, but lived and faced death as one -- it becomes easier to imagine another on the horizon.

As the day came to an end, Taleb and his team turned their attention once again to the problem of the square root of n. Taleb was back at the whiteboard. Spitznagel was looking on. Pallop was idly peeling a banana. Outside, the sun was beginning to settle behind the trees. "You do a conversion to p1 and p2," Taleb said. His marker was once again squeaking across the whiteboard. "We say we have a Gaussian distribution, and you have the market switching from a low-volume regime to a high-volume. P21. P22. You have your igon value." He frowned and stared at his handiwork. The markets were now closed. Empirica had lost money, which meant that somewhere off in the woods of Connecticut Niederhoffer had no doubt made money. That hurt, but if you steeled yourself, and thought about the problem at hand, and kept in mind that someday the market would do something utterly unexpected because in the world we live in something utterly unexpected always happens, then the hurt was not so bad. Taleb eyed his equations on the whiteboard, and arched an eyebrow. It was a very difficult problem. "Where is Dr. Wu? Should we call in Dr. Wu?"

A year after Nassim Taleb came to visit him, Victor Niederhoffer blew up. He sold a very large number of options on the S. & P. index, taking millions of dollars from other traders in exchange for promising to buy a basket of stocks from them at current prices, if the market ever fell. It was an unhedged bet, or what was called on Wall Street a "naked put," meaning that he bet everyone on one outcome: he bet in favor of the large probability of making a small amount of money, and against the small probability of losing a large amount of money-and he lost. On October 27, 1997, the market plummeted eight per cent, and all of the many, many people who had bought those options from Niederhoffer came calling all at once, demanding that he buy back their stocks at pre-crash prices. He ran through a hundred and thirty million dollars -- his cash reserves, his savings, his other stocks -- and when his broker came and asked for still more he didn't have it. In a day, one of the most successful hedge funds in America was wiped out. Niederhoffer had to shut down his firm. He had to mortgage his house. He had to borrow money from his children. He had to call Sotheby's and sell his prized silver collection -- the massive nineteenth-century Brazilian "sculptural group of victory" made for the Visconde De Figueirdeo, the massive silver bowl designed in 1887 by Tiffany & Company for the James Gordon Bennet Cup yacht race, and on and on. He stayed away from the auction. He couldn't bear to watch.

"It was one of the worst things that has ever happened to me in my life, right up there with the death of those closest to me," Niederhoffer said recently. It was a Saturday in March, and he was in the library of his enormous house. Two weary-looking dogs wandered in and out. He is a tall man, an athlete, thick through the upper body and trunk, with a long, imposing face and baleful, hooded eyes. He was shoeless. One collar on his shirt was twisted inward, and he looked away as he talked. "I let down my friends. I lost my business. I was a major money manager. Now I pretty much have had to start from ground zero." He paused. "Five years have passed. The beaver builds a dam. The river washes it away, so he tries to build a better foundation, and I think I have. But I'm always mindful of the possibility of more failures." In the distance, there was a knock on the door. It was a man named Milton Bond, an artist who had come to present Niederhoffer with a painting he had done of Moby Dick ramming the Pequod. It was in the folk-art style that Niederhoffer likes so much, and he went to meet Bond in the foyer, kneeling down in front of the painting as Bond unwrapped it. Niederhoffer has other paintings of the Pequod in his house, and paintings of the Essex, the ship on which Melville's story was based. In his office, on a prominent wall, is a painting of the Titanic. They were, he said, his way of staying humble. "One of the reasons I've paid lots of attention to the Essex is that it turns out that the captain of the Essex, as soon as he got back to Nantucket, was given another job," Niederhoffer said. "They thought he did a good job in getting back after the ship was rammed. The captain was asked, `How could people give you another ship?' And he said, `I guess on the theory that lightning doesn't strike twice.' It was a fairly random thing. But then he was given the other ship, and that one foundered, too. Got stuck in the ice. At that time, he was a lost man. He wouldn't even let them save him. They had to forcibly remove him from the ship. He spent the rest of his life as a janitor in Nantucket. He became what on Wall Street they call a ghost." Niederhoffer was back in his study now, his lanky body stretched out, his feet up on the table, his eyes a little rheumy. "You see? I can't afford to fail a second time. Then I'll be a total washout. That's the significance of the Pequod."

A month or so before he blew up, Taleb had dinner with Niederhoffer at a restaurant in Westport, and Niederhoffer told him that he had been selling naked puts. You can imagine the two of them across the table from each other, Niederhoffer explaining that his bet was an acceptable risk, that the odds of the market going down so heavily that he would be wiped out were minuscule, and Taleb listening and shaking his head, and thinking about black swans. "I was depressed when I left him," Taleb said. "Here is a guy who goes out and hits a thousand backhands. He plays chess like his life depends on it. Here is a guy who, whatever he wants to do when he wakes up in the morning, he ends up better than anyone else. Whatever he wakes up in the morning and decides to do, he did better than anyone else. I was talking to my hero . . ." This was the reason Taleb didn't want to be Niederhoffer when Niederhoffer was at his height -- the reason he didn't want the silver and the house and the tennis matches with George Soros. He could see all too clearly where it all might end up. In his mind's eye, he could envision Niederhoffer borrowing money from his children, and selling off his silver, and talking in a hollow voice about letting down his friends, and Taleb did not know if he had the strength to live with that possibility. Unlike Niederhoffer, Taleb never thought he was invincible. You couldn't if you had watched your homeland blow up, and had been the one person in a hundred thousand who gets throat cancer, and so for Taleb there was never any alternative to the painful process of insuring himself against catastrophe.

This kind of caution does not seem heroic, of course. It seems like the joyless prudence of the accountant and the Sunday-school teacher. The truth is that we are drawn to the Niederhoffers of this world because we are all, at heart, like Niederhoffer: we associate the willingness to risk great failure -- and the ability to climb back from catastrophe--with courage. But in this we are wrong. That is the lesson of Taleb and Niederhoffer, and also the lesson of our volatile times. There is more courage and heroism in defying the human impulse, in taking the purposeful and painful steps to prepare for the unimaginable.

Last fall, Niederhoffer sold a large number of options, betting that the markets would be quiet, and they were, until out of nowhere two planes crashed into the World Trade Center. "I was exposed. It was nip and tuck." Niederhoffer shook his head, because there was no way to have anticipated September 11th. "That was a totally unexpected event."


Belief in Efficient Valuation Yields Ground to Role of Irrational Investors;

Mr. Thaler Takes on Mr. Fama

Jon E. Hilsenrath.

The Wall Street Journal. New York, N.Y.: Oct 18, 2004. pg. A.1

For forty years, economist Eugene Fama argued that financial markets were highly efficient in reflecting the underlying value of stocks. His long-time intellectual nemesis, Richard Thaler, a member of the "behaviorist" school of economic thought, contended that markets can veer off course when individuals make stupid decisions.

In May, 116 eminent economists and business executives gathered at the University of Chicago Graduate School of Business for a conference in Mr. Fama's honor. There, Mr. Fama surprised some in the audience. A paper he presented, co-authored with a colleague, made the case that poorly informed investors could theoretically lead the market astray. Stock prices, the paper said, could become "somewhat irrational."

Coming from the 65-year-old Mr. Fama, the intellectual father of the theory known as the "efficient-market hypothesis," it struck some as an unexpected concession. For years, efficient market theories were dominant, but here was a suggestion that the behaviorists' ideas had become mainstream.

"I guess we're all behaviorists now," Mr. Thaler, 59, recalls saying after he heard Mr. Fama's presentation.

Roger Ibbotson, a Yale University professor and founder of Ibbotson Associates Inc., an investment advisory firm, says his reaction was that Mr. Fama had "changed his thinking on the subject" and adds: "There is a shift that is taking place. People are recognizing that markets are less efficient than we thought." Mr. Fama says he has been consistent.

The shift in this long-running argument has big implications for real-life problems, ranging from the privatization of Social Security to the regulation of financial markets to the way corporate boards are run. Mr. Fama's ideas helped foster the free-market theories of the 1980s and spawned the $1 trillion index-fund industry. Mr. Thaler's theory suggests policy makers have an important role to play in guiding markets and individuals where they're prone to fail.

Take, for example, the debate about Social Security. Amid a tight election battle, President Bush has set a goal of partially privatizing Social Security by allowing younger workers to put some of their payroll taxes into private savings accounts for their retirements.

In a study of Sweden's efforts to privatize its retirement system, Mr. Thaler found that Swedish investors tended to pile into risky technology stocks and invested too heavily in domestic stocks. Investors had too many options, which limited their ability to make good decisions, Mr. Thaler concluded. He thinks U.S. reform, if it happens, should be less flexible. "If you give people 456 mutual funds to choose from, they're not going to make great choices," he says.

If markets are sometimes inefficient, and stock prices a flawed measure of value, corporate boards and management teams would have to rethink the way they compensate executives and judge their performance. Michael Jensen, a retired Harvard economist who worked on efficient-market theory earlier in his career, notes a big lesson from the 1990s was that overpriced stocks could lead executives into bad decisions, such as massive overinvestment in telecommunications during the technology boom.

Even in an efficient market, bad investments occur. But in an inefficient market where prices can be driven way out of whack, the problem is acute. The solution, Mr. Jensen says, is "a major shift in the belief systems" of corporate boards and changes in compensation that would make executives less focused on stock price movements.

Few think the swing toward the behaviorist camp will reverse the global emphasis on open economies and free markets, despite the increasing academic focus on market breakdowns. Moreover, while Mr. Fama seems to have softened his thinking over time, he says his essential views haven't changed.

A product of Milton Friedman's Chicago School of thought, which stresses the virtues of unfettered markets, Mr. Fama rose to prominence at the University of Chicago's Graduate School of Business. He's an avid tennis player, known for his disciplined style of play. Mr. Thaler, a Chicago professor whose office is on the same floor as Mr. Fama's, also plays tennis but takes riskier shots that sometimes land him in trouble. The two men have stakes in investment funds that run according to their rival economic theories.

Neither shies from tossing about highbrow insults. Mr. Fama says behavioral economists like Mr. Thaler "haven't really established anything" in more than 20 years of research. Mr. Thaler says Mr. Fama "is the only guy on earth who doesn't think there was a bubble in Nasdaq in 2000."

In its purest form, efficient-market theory holds that markets distill new information with lightning speed and provide the best possible estimate of the underlying value of listed companies. As a result, trying to beat the market, even in the long term, is an exercise in futility because it adjusts so quickly to new information.

Behavioral economists argue that markets are imperfect because people often stray from rational decisions. They believe this behavior creates market breakdowns and also buying opportunities for savvy investors. Mr. Thaler, for example, says stocks can under-react to good news because investors are wedded to old views about struggling companies.

For Messrs. Thaler and Fama, this is more than just an academic debate. Mr. Fama's research helped to spawn the idea of passive money management and index funds. He's a director at Dimensional Fund Advisers, a private investment management company with $56 billion in assets under management. Assuming the market can't be beaten, it invests in broad areas rather than picking individual stocks. Average annual returns over the past decade for its biggest fund -- one that invests in small, undervalued stocks -- have been about 16%, four percentage points better than the S&P 500, according to Morningstar Inc., a mutual-fund research company.

Mr. Thaler, meanwhile, is a principal at Fuller & Thaler, a fund management company with $2.4 billion under management. Its asset managers spend their time trying to pick stocks and outfox the market. The company's main growth fund, which invests in stocks that are expected to produce strong earnings growth, has delivered average annual returns of 6% since its inception in 1997, three percentage points better than the S&P 500.

Mr. Fama came to his views as an undergraduate student in the late 1950s at Tufts University when a professor hired him to work on a market-forecasting newsletter. There, he discovered that strategies designed to beat the market didn't work well in practice. By the time he enrolled at Chicago in 1960, economists were viewing individuals as rational, calculating machines whose behavior could be predicted with mathematical models. Markets distilled these differing views with unique precision, they argued.

"In an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value," Mr. Fama wrote in a 1965 paper titled "Random Walks in Stock Market Prices." Stock movements were like "random walks" because investors could never predict what new information might arise to change a stock's price. In 1973, Princeton economist Burton Malkiel published a popularized discussion of the hypothesis, "A Random Walk Down Wall Street," which sold more than one million copies.

Mr. Fama's writings underpinned the Chicago School's faith in the functioning of markets. Its approach, which opposed government intervention in markets, helped reshape the 1980s and 1990s by encouraging policy makers to open their economies to market forces. Ronald Reagan and Margaret Thatcher ushered in an era of deregulation and later Bill Clinton declared an end to big government. After the collapse of Communist central planning in Russia and Eastern Europe, many countries embraced these ideas.

As a young assistant professor in Rochester in the mid-1970s, Mr. Thaler had his doubts about market efficiency. People, he suspected, were not nearly as rational as economists assumed.

Mr. Thaler started collecting evidence to demonstrate his point, which he published in a series of papers. One associate kept playing tennis even though he had a bad elbow because he didn't want to waste $300 on tennis club fees. Another wouldn't part with an expensive bottle of wine even though he wasn't an avid drinker. Mr. Thaler says he caught economists bingeing on cashews in his office and asking for the nuts to be taken away because they couldn't control their own appetites.

Mr. Thaler decided that people had systematic biases that weren't rational, such as a lack of self-control. Most economists dismissed his writings as a collection of quirky anecdotes, so Mr. Thaler decided the best approach was to debunk the most efficient market of them all -- the stock market.

Even before the late 1990s, Mr. Thaler and a growing legion of behavioral finance experts were finding small anomalies that seemed to fly in the face of efficient-market theory. For example, researchers found that value stocks, companies that appear undervalued relative to their profits or assets, tended to outperform growth stocks, ones that are perceived as likely to increase profits rapidly. If the market was efficient and impossible to beat, why would one asset class outperform another? (Mr. Fama says there's a rational explanation: Value stocks come with hidden risks and investors are rewarded for those risks with higher returns.)

Moreover, in a rational world, share prices should move only when new information hit the market. But with more than one billion shares a day changing hands on the New York Stock Exchange, the market appears overrun with traders making bets all the time.

Robert Shiller, a Yale University economist, has long argued that efficient-market theorists made one huge mistake: Just because markets are unpredictable doesn't mean they are efficient. The leap in logic, he wrote in the 1980s, was one of "the most remarkable errors in the history of economic thought." Mr. Fama says behavioral economists made the same mistake in reverse: The fact that some individuals might be irrational doesn't mean the market is inefficient.

Shortly after the stock market swooned, Mr. Thaler presented a new paper at the University of Chicago's business school. Shares of handheld-device maker Palm Inc. -- which later split into two separate companies -- soared after some of its shares were sold in an initial public offering by its parent, 3Com Corp., in 2000, he noted. The market gave Palm a value nearly twice that of its parent even though 3Com still owned 94% of Palm. That in effect assigned a negative value to 3Com's other assets. Mr. Thaler titled the paper, "Can the Market Add and Subtract?" It was an unsubtle shot across Mr. Fama's bow. Mr. Fama dismissed Mr. Thaler's paper, suggesting it was just an isolated anomaly. "Is this the tip of an iceberg, or the whole iceberg?" he asked Mr. Thaler in an open discussion after the presentation, both men recall.

Mr. Thaler's views have seeped into the mainstream through the support of a number of prominent economists who have devised similar theories about how markets operate. In 2001, the American Economics Association awarded its highest honor for young economists -- the John Bates Clark Medal -- to an economist named Matthew Rabin who devised mathematical models for behavioral theories. In 2002, Daniel Kahneman won a Nobel Prize for pioneering research in the field of behavioral economics. Even Federal Reserve Chairman Alan Greenspan, a firm believer in the benefits of free markets, famously adopted the term "irrational exuberance" in 1996.

Andrew Lo, an economist at the Massachusetts Institute of Technology's Sloan School of Management, says efficient-market theory was the norm when he was a doctoral student at Harvard and MIT in the 1980s. "It was drilled into us that markets are efficient. It took me five to 10 years to change my views." In 1999, he wrote a book titled, "A Non-Random Walk Down Wall Street."

In 1991, Mr. Fama's theories seemed to soften. In a paper called "Efficient Capital Markets: II," he said that market efficiency in its most extreme form -- the idea that markets reflect all available information so that not even corporate insiders can beat it -- was "surely false." Mr. Fama's more recent paper also tips its hand to what behavioral economists have been arguing for years -- that poorly informed investors could distort stock prices.

But Mr. Fama says his views haven't changed. He says he's never believed in the pure form of the efficient-market theory. As for the recent paper, co-authored with longtime collaborator Kenneth French, it "just provides a framework" for thinking about some of the issues raised by behaviorists, he says in an e-mail. "It takes no stance on the empirical importance of these issues."

The 1990s Internet investment craze, Mr. Fama argues, wouldn't have looked so crazy if it had produced just one or two blockbuster companies, which he says was a reasonable expectation at the time. Moreover, he says, market crashes confirm a central tenet of efficient market theory -- that stock-price movements are unpredictable. Findings of other less significant anomalies, he says, have grown out of "shoddy" research.

Defending efficient markets has gotten harder, but it's probably too soon for Mr. Thaler to declare victory. He concedes that most of his retirement assets are held in index funds, the very industry that Mr. Fama's research helped to launch. And despite his research on market inefficiencies, he also concedes that "it is not easy to beat the market, and most people don't."

Top of Form


Kolbert, Elizabeth

New Yorker; 2/25/2008, Vol. 84 Issue 2, p77-79, 3p

The latest reasoning about our irrational ways.

A couple of months ago, I went on-line to order a book. The book had a list price of twenty-four dollars; Amazon was offering it for eighteen. I clicked to add it to my "shopping cart" and a message popped up on the screen. "Wait!" it admonished me. "Add $7.00 to your order to qualify for FREE Super Saver Shipping!" I was ordering the book for work; still, I hesitated. I thought about whether there were other books that I might need, or want. I couldn't think of any, so I got up from my desk, went into the living room, and asked my nine-year-old twins. They wanted a Tintin book. Since they already own a large stack of Tintins, it was hard to find one that they didn't have. They scrolled through the possibilities. After much discussion, they picked a three-in-one volume containing two adventures they had previously read. I clicked it into the shopping cart and checked out. By the time I was done, I had saved The New Yorker $3.99 in shipping charges. Meanwhile, I had cost myself $12.91.

Why do people do things like this? From the perspective of neoclassical economics, self-punishing decisions are difficult to explain. Rational calculators are supposed to consider their options, then pick the one that maximizes the benefit to them. Yet actual economic life, as opposed to the theoretical version, is full of miscalculations, from the gallon jar of mayonnaise purchased at spectacular savings to the billions of dollars Americans will spend this year to service their credit-card debt. The real mystery, it could be argued, isn't why we make so many poor economic choices but why we persist in accepting economic theory.

In "Predictably Irrational: The Hidden Forces That Shape Our Decisions" (Harper; $25.95), Dan Ariely, a professor at M.I.T., offers a taxonomy of financial folly. His approach is empirical rather than historical or theoretical. In pursuit of his research, Ariely has served beer laced with vinegar, left plates full of dollar bills in dorm refrigerators, and asked undergraduates to fill out surveys while masturbating. He claims that his experiments, and others like them, reveal the underlying logic to our illogic. "Our irrational behaviors are neither random nor senseless -- they are systematic," he writes. "We all make the same types of mistakes over and over." So attached are we to certain kinds of errors, he contends, that we are incapable even of recognizing them as errors. Offered FREE shipping, we take it, even when it costs us.

As an academic discipline, Ariely's field -- behavioral economics -- is roughly twenty-five years old. It emerged largely in response to work done in the nineteen-seventies by the Israeli-American psychologists Amos Tversky and Daniel Kahneman. (Ariely, too, grew up in Israel.) When they examined how people deal with uncertainty, Tversky and Kahneman found that there were consistent biases to the responses, and that these biases could be traced to mental shortcuts, or what they called "heuristics." Some of these heuristics were pretty obvious -- people tend to make inferences from their own experiences, so if they've recently seen a traffic accident they will overestimate the danger of dying in a car crash -- but others were more surprising, even downright wacky. For instance, Tversky and Kahneman asked subjects to estimate what proportion of African nations were members of the United Nations. They discovered that they could influence the subjects' responses by spinning a wheel of fortune in front of them to generate a random number: when a big number turned up, the estimates suddenly swelled.

Though Tversky and Kahneman's research had no direct bearing on economics, its implications for the field were disruptive. Can you really regard people as rational calculators if their decisions are influenced by random numbers? (In 2002, Kahneman was awarded a Nobel Prize -- Tversky had died in 1996 -- for having "integrated insights from psychology into economics, thereby laying the foundation for a new field of research.")

Over the years, Tversky and Kahneman's initial discoveries have been confirmed and extended in dozens of experiments. In one example, Ariely and a colleague asked students at M.I.T.'s Sloan School of Management to write the last two digits of their Social Security number at the top of a piece of paper. They then told the students to record, on the same paper, whether they would be willing to pay that many dollars for a fancy bottle of wine, a not-so-fancy bottle of wine, a book, or a box of chocolates. Finally, the students were told to write down the maximum figure they would be willing to spend for each item. Once they had finished, Ariely asked them whether they thought that their Social Security numbers had had any influence on their bids. The students dismissed this idea, but when Ariely tabulated the results he found that they were kidding themselves. The students whose Social Security number ended with the lowest figures -- 00 to 19 -- were the lowest bidders. For all the items combined, they were willing to offer, on average, sixty-seven dollars. The students in the second-lowest group -- 20 to 39 -- were somewhat more free-spending, offering, on average, a hundred and two dollars. The pattern continued up to the highest group -- 80 to 99 -- whose members were willing to spend an average of a hundred and ninety-eight dollars, or three times as much as those in the lowest group, for the same items.

This effect is called "anchoring," and, as Ariely points out, it punches a pretty big hole in microeconomics. When you walk into Starbucks, the prices on the board are supposed to have been determined by the supply of, say, Double Chocolaty Frappuccinos, on the one hand, and the demand for them, on the other. But what if the numbers on the board are influencing your sense of what a Double Chocolaty Frappuccino is worth? In that case, price is not being determined by the interplay of supply and demand; price is, in a sense, determining itself.

Another challenge to standard economic thinking arises from what has become known as the "endowment effect." To probe this effect, Ariely, who earned one of his two Ph.D.s at Duke, exploited the school's passion for basketball. Blue Devils fans who had just won tickets to a big game through a lottery were asked the minimum amount that they would accept in exchange for them. Fans who had failed to win tickets through the same lottery were asked the maximum amount that they would be willing to offer for them.

"From a rational perspective, both the ticket holders and the non-ticket holders should have thought of the game in exactly the same way," Ariely observes. Thus, one might have expected that there would be opportunities for some of the lucky and some of the unlucky to strike deals. But whether or not a lottery entrant had been "endowed" with a ticket turned out to powerfully affect his or her sense of its value. One of the winners Ariely contacted, identified only as Joseph, said that he wouldn't sell his ticket for any price. "Everyone has a price," Ariely claims to have told him. O.K., Joseph responded, how about three grand? On average, the amount that winners were willing to accept for their tickets was twenty-four hundred dollars. On average, the amount that losers were willing to offer was only a hundred and seventy-five dollars. Out of a hundred fans, Ariely reports, not a single ticket holder would sell for a price that a non-ticket holder would pay.

Whatever else it accomplishes, "Predictably Irrational" demonstrates that behavioral economists are willing to experiment on just about anybody. One of the more compelling studies described in the book involved trick-or-treaters. A few Halloweens ago, Ariely laid in a supply of Hershey's Kisses and two kinds of Snickers -- regular two-ounce bars and one-ounce miniatures. When the first children came to his door, he handed each of them three Kisses, then offered to make a deal. If they wanted to, the kids could trade one Kiss for a mini-Snickers or two Kisses for a full-sized bar. Almost all of them took the deal and, proving their skills as sugar maximizers, opted for the two-Kiss trade. At some point, Ariely shifted the terms: kids could now trade one of their three Kisses for the larger bar or get a mini-Snickers without giving up anything. In terms of sheer chocolatiness, the trade for the larger bar was still by far the better deal. But, faced with the prospect of getting a mini-Snickers for nothing, the trick-or-treaters could no longer reckon properly. Most of them refused the trade, even though it cost them candy. Ariely speculates that behind the kids' miscalculation was anxiety. As he puts it, "There's no visible possibility of loss when we choose a FREE! item (it's free)." Tellingly, when Ariely performed a similar experiment on adults, they made the same mistake. "If I were to distill one main lesson from the research described in this book, it is that we are all pawns in a game whose forces we largely fail to comprehend," he writes.

A few weeks ago, the Bureau of Economic Analysis released its figures for 2007. They showed that Americans had collectively amassed ten trillion one hundred and eighty-four billion dollars in disposable income and spent very nearly all of it -- ten trillion one hundred and thirty-two billion dollars. This rate of spending was somewhat lower than the rate in 2006, when Americans spent all but thirty-nine billion dollars of their total disposable income.

According to standard economic theory, the U.S. savings rate also represents rational choice: Americans, having reviewed their options, have collectively resolved to spend virtually all the money that they have. According to behavioral economists, the low savings rate has a more immediate explanation: it proves -- yet again -- that people have trouble acting in their own best interests. It's worth noting that Americans, even as they continue to spend, say that they should be putting more money away; one study of participants in 401(k) plans found that more than two-thirds believed their savings rate to be "too low."

In the forthcoming "Nudge: Improving Decisions About Health, Wealth, and Happiness" (Yale; $25), Richard H. Thaler and Cass R. Sunstein follow behavioral economics out of the realm of experiment and into the realm of social policy. Thaler and Sunstein both teach at the University of Chicago, Thaler in the graduate school of business and Sunstein at the law school. They share with Ariely the belief that, faced with certain options, people will consistently make the wrong choice.Therefore, they argue, people should be offered options that work with, rather than against, their unreasoning tendencies. These foolish-proof choices they label "nudges." (A "nudge," they note with scholarly care, should not be confused with a "noodge.")

A typical "nudge" is a scheme that Thaler and Sunstein call "Save More Tomorrow." One of the reasons people have such a hard time putting money away, the authors say, is that they are loss-averse. They are pained by any reduction in their take-home pay -- even when it's going toward their own retirement. Under "Save More Tomorrow," employees commit to contributing a greater proportion of their paychecks to their retirement over time, but the increases are scheduled to coincide with their annual raises, so their paychecks never shrink. (The "Save More Tomorrow" scheme was developed by Thaler and the U.C.L.A. economist Shlomo Benartzi, back in 1996, and has already been implemented by several thousand retirement plans.)

People aren't just loss-averse; they are also effort-averse. They hate having to go to the benefits office, pick up a bunch of forms, fill them out, and bring them all the way back. As a consequence, many eligible employees fail to enroll in their companies' retirement plans, or delay doing so for years. (This is the case, research has shown, even at companies where no employee contribution is required.) Thaler and Sunstein propose putting this sort of inertia to use by inverting the choice that's presented. Instead of having to make the trip to the benefits office to opt in, employees should have to make that trip only if they want to opt out. The same basic argument holds whenever a so-called default option is provided. For instance, most states in the U.S. require that those who want to become organ donors register their consent; in this way, many potential donors are lost. An alternative -- used, for example, in Austria -- is to make consent the default option, and put the burden of registering on those who do not wish to be donors. (It has been estimated that if every state in the U.S. simply switched from an "explicit consent" to a "presumed consent" system several thousand lives would be saved each year.)

"Nudges" could also involve disclosure requirements. To discourage credit-card debt, for instance, Thaler and Sunstein recommend that cardholders receive annual statements detailing how much they have already squandered in late fees and interest. To encourage energy conservation, they propose that new cars come with stickers showing how many dollars' worth of gasoline they are likely to burn through in five years of driving.

Many of the suggestions in "Nudge" seem like good ideas, and even, as with "Save More Tomorrow," practical ones. The whole project, though, as Thaler and Sunstein acknowledge, raises some pretty awkward questions. If the "nudgee" can't be depended on to recognize his own best interests, why stop at a nudge? Why not offer a "push," or perhaps even a "shove"? And if people can't be trusted to make the right choices for themselves how can they possibly be trusted to make the right decisions for the rest of us?

Like neoclassical economics, much democratic theory rests on the assumption that people are rational. Here, too, empirical evidence suggests otherwise. Voters, it has been demonstrated, are influenced by factors ranging from how names are placed on a ballot to the jut of a politician's jaw. A 2004 study of New York City primary-election results put the advantage of being listed first on the ballot for a local office at more than three per cent -- enough of a boost to turn many races. (For statewide office, the advantage was around two per cent.) A 2005 study, conducted by psychologists at Princeton, showed that it was possible to predict the results of congressional contests by using photographs. Researchers presented subjects with fleeting images of candidates' faces. Those candidates who, in the subjects' opinion, looked more "competent" won about seventy per cent of the time.

When it comes to public-policy decisions, people exhibit curious -- but, once again, predictable -- biases. They value a service (say, upgrading fire equipment) more when it is described in isolation than when it is presented as part of a larger good (say, improving disaster preparedness). They are keen on tax "bonuses" but dislike tax "penalties," even though the two are functionally equivalent. They are more inclined to favor a public policy when it is labelled the status quo. In assessing a policy's benefits, they tend to ignore whole orders of magnitude. In an experiment demonstrating this last effect, sometimes called "scope insensitivity," subjects were told that migrating birds were drowning in ponds of oil. They were then asked how much they would pay to prevent the deaths by erecting nets. To save two thousand birds, the subjects were willing to pay, on average, eighty dollars. To save twenty thousand birds, they were willing to pay only seventy-eight dollars, and to save two hundred thousand birds they were willing to pay eighty-eight dollars.

What is to be done with information like this? We can try to become more aware of the patterns governing our blunders, as "Predictably Irrational" urges. Or we can try to prod people toward more rational choices, as "Nudge" suggests. But if we really are wired to make certain kinds of mistakes, as Thaler and Sunstein and Ariely all argue, we will, it seems safe to predict, keep finding new ways to make them. (Ariely confesses that he recently bought a thirty-thousand-dollar car after reading an ad offering FREE oil changes for the next three years.)

If there is any consolation to take from behavioral economics -- and this impulse itself probably counts as irrational -- it is that irrationality is not always altogether a bad thing. What we most value in other people, after all, has little to do with the values of economics. (Who wants a friend or a lover who is too precise a calculator?) Some of the same experiments that demonstrate people's weak-mindedness also reveal, to use a quaint term, their humanity. One study that Ariely relates explored people's willingness to perform a task for different levels of compensation. Subjects were willing to help out -- moving a couch, performing a tedious exercise on a computer -- when they were offered a reasonable wage. When they were offered less, they were less likely to make an effort, but when they were asked to contribute their labor for nothing they started trying again. People, it turns out, want to be generous and they want to retain their dignity -- even when it doesn't really make sense.


Lanchester, John New Yorker; 6/1/2009, Vol. 85 Issue 16, p83-87,

High finance vs. human nature

The world of banking, it's becoming clear, operates according to different norms from those of the rest of the business world. Take the offsite corporate weekend. Normal behavior on these occasions consists of punishing the minibar and nursing consequent hangovers, hitting on long-fancied colleagues, and putting embarrassing items, ideally pornographic videos, on one another's hotel bills. For form's sake, a few new ideas are cooked up, and then gradually allowed to die a natural death when everyone is back at work and liver-function levels have stabilized. In June, 1994, when a team from J. P. Morgan went on an off-site weekend to Boca Raton, they conformed to normative behavior in certain respects. Binge drinking occurred; a senior colleague's nose was broken; somebody charged a trashed Jet Ski and many cheeseburgers to somebody else's account. Where the J. P. Morgan team broke with tradition was in coming up with a real idea -- an idea that changed the entire nature of modern banking, with consequences that are currently rocking the planet.

The new idea was based on an old one, that of the swap. Say you're in the grocery business, and feel gloomy about your prospects. Your immediate neighbor is in the stationery business, and he feels gloomy about his prospects, less so about yours. You get to talking, and one of you hits on a brilliant idea: why not just swap revenues? You take his earnings for the year, and he takes yours. The actual business doesn't change hands, making the swap, in banking terminology, "synthetic." The first currency swap took place in 1981, and allowed I.B.M. to trade surplus Swiss francs and Deutsche marks for dollars held by the World Bank. The two institutions exchanged their obligations to bondholders and their bond earnings without actually exchanging the bonds. The deal, brokered by Salomon Brothers, was worth two hundred and ten million dollars over ten years and ushered in a whole new field of finance. As Gillian Tett tells it in her book "Fool's Gold" (Free Press; $26), by the time of the Boca Raton off-site, swaps had become a roaringly successful feature of the banking world: the volume of such interest-rate and currency derivatives was worth twelve trillion dollars, more than the entire U.S. economy.

But competition was making those swap deals less profitable. The quest was for a new, and therefore newly lucrative, product to sell. What got the J. P. Morgan team rolling was this thought: instead of swapping bonds or currency or interest rates, why not swap the risk of default? In effect, it could sell the risk that a borrower won't be able to pay back his debt. Since banking is based on making loans to customers, the risk of default by those customers is a crucial part of the business. A product that made it possible to reduce that risk -- by selling it to somebody else -- had the potential to create a gigantic new market.

The broad outline of the financial crash is becoming well known. The value of Gillian Tett's book is in the level of detail with which she tells the story, concentrating on the specific sequence of inventions and innovations that made it possible. Tett, a Financial Times reporter who covered the credit markets, was one of the few people to have seen the implosion coming. A critical factor was that she has a Ph.D. in social anthropology -- a "hippie" background, as one banker told her, intending no compliment. It helped her focus on what she calls "social silences" in the world of banking. It's not always what people say that contains the most important information; often, it's what they take for granted. To Tett, it was obvious that the banking sector was running irresponsibly large risks in the overexpansion of credit and the overingenuity of its financial engineering. So she was perfectly placed to follow the story as it happened, and to pull together the story of how we got here. There are a number of different ways of peeling this particular onion; Tett does so through the J. P. Morgan team that helped create the new credit derivatives. These lie at the heart of the current crisis, and Tett's account of their invention and dispersal makes "Fool's Gold" a gripping and indispensable book.

The Boca Raton meeting first bore fruit when Exxon needed to open a line of credit to cover potential damages of five billion dollars resulting from the 1989 Exxon Valdez oil spill. J. P. Morgan was reluctant to turn down Exxon, which was an old client, but the deal would tie up a lot of reserve cash to provide for the risk of the loans going bad. The so-called Basel rules, named for the town in Switzerland where they were formulated, required that the banks hold eight per cent of their capital in reserve against the risk of outstanding loans. That limited the amount of lending bankers could do, the amount of risk they could take on, and therefore the amount of profit they could make. But, if the risk of the loans could be sold, it logically followed that the loans were now risk-free; and, if that were the case, what would have been the reserve cash could now be freely loaned out. No need to suck up useful capital.

In late 1994, Blythe Masters, a member of the J. P. Morgan swaps team, pitched the idea of selling the credit risk to the European Bank of Reconstruction and Development. So, if Exxon defaulted, the E.B.R.D. would be on the hook for it -- and, in return for taking on the risk, would receive a fee from J. P. Morgan. Exxon would get its credit line, and J. P. Morgan would get to honor its client relationship but also to keep its credit lines intact for sexier activities. The deal was so new that it didn't even have a name: eventually, the one settled on was "credit-default swap."

So far, so good for J. P. Morgan. But the deal had been laborious and time-consuming, and the bank wouldn't be able to make real money out of credit-default swaps until the process became streamlined and industrialized. The invention that allowed all this to happen was securitization. Traditionally, banking involves a case-by-case assessment of the risk of every loan, and it's hard to industrialize that process. What securitization did was bundle together a package of these loans, and then rely on safety in numbers and the law of averages: even if some loans did default, the others wouldn't, and would keep the stream of revenue going, thereby diffusing and minimizing the risk of default. So there would be two sources of revenue: one from the sale of the loans, and another from the steady flow of repayments. Then someone had the idea of dividing up the securities into different levels of risk -- a technique called tranching -- and selling them off accordingly, so that riskier tranches of debt would pay a higher rate of interest than safer ones. Bill Demchak, a "structured finance" star at J. P. Morgan, took the lead in creating bundles of credit-default swaps -- insurance against default -- and selling them to investors. The investors would get the streams of revenue, according to the risk-and-reward level they chose; the bank would get insurance against its loans, and fees for setting up the deal.

There was one final component to the J. P. Morgan team's invention. The team set up a kind of offshore shell company, called a Special Purpose Vehicle, to fulfill the role supplied by the European Bank for Reconstruction and Development in the first credit-default swap. The shell company would assume $9.7 billion of J. P. Morgan's risk (in this case, outstanding loans that the bank had made to some three hundred companies) and sell off that risk to investors, in the form of securities paying differing rates of interest. According to J. P. Morgan's calculations, the underlying loans were so safe that it needed to collect only seven hundred million dollars in order to cover the $9.7-billion debt. In 1997, the credit agency Moodys agreed, and a whole new era in banking dawned. J. P. Morgan had found a way to shift risk off its books while simultaneously generating income from that risk, and freeing up capital to lend elsewhere. It was magic. The only thing wrong with it was the name, BISTRO, for Broad Index Secured Trust Offering, which made the new rocket-science financial instrument sound like a place you went to for steak frites. The market came to prefer a different term: "synthetic collateralized debt obligations."

Inevitably, J. P. Morgan's innovation was taken up by more aggressive and less cautious banks. Mortgage-based versions of collateralized debt obligations were especially profitable. These C.D.O.s involved the techniques that the J. P. Morgan team had developed, but their underlying assets were pools of mortgages -- many of them based on the most lucrative mortgages, the now notorious subprime loans, which paid higher than usual rates of interest. (These new instruments could be pretty exotic: some consisted of C.D.O.s of C.D.O.s, pools of pools of debt.) J. P. Morgan was wary of them, as it happens, because it didn't see how the risks were being engineered down to a safe level. But institutions like Citigroup, U.B.S., and Merrill Lynch plunged in.

The new financial instruments, as clever as they were, had an unfortunate side effect: they broke banking. At its heart, banking is a simple business. Customers deposit money at a bank, in return for interest; the bank lends that money to other people, at a higher rate of interest. This isn't glamorous or interesting, but banking is not supposed to resemble skydiving or hip-hop; what recommends it is that it's a good way of making steady money (and of creating credit in the economy), as long as the bank is careful about whom it lends money to. The quality of the loans is critical, because those loans are the bank's earning assets.

This isn't some incidental issue; it's the very core of what banking is. But the model of packaging plus securitization spurned the principle that a bank had to individually assess and monitor every loan. The mathematics of valuation models -- horrendously complex equations to assess probabilities and correlations, cooked up in mad-scientist style by the firms' "quants" -- took on the burden of assessing statistical risk. The idea that a banker looks a borrower in the eye and takes a view on whether he can trust him came to seem laughably nineteenth-century. As for the risks? Well, as Lawrence Summers said when he was Deputy Secretary of the Treasury, "The parties to these kinds of contract are largely sophisticated financial institutions that would appear to be eminently capable of protecting themselves from fraud and counterparty insolvencies."

Alas, Richard A. Posner, a judge on the U.S. Court of Appeals for the Seventh Circuit, observes with pointed restraint, "That turned out not to be true." The result has been, in the title phrase of Posner's new book, "A Failure of Capitalism" (Harvard; $23.95). He argues that we are now in a bona-fide depression, which he defines as "a steep reduction in output that causes or threatens to cause deflation and creates widespread public anxiety and, among the political and economic elites, a sense of crisis that evokes extremely costly efforts at remediation." His book is an attempt to write "a concise, constructive, jargon- and acronym-free, non-technical, unsensational, light-on-anecdote, analytical examination of the major facets of the biggest U.S. economic disaster in my lifetime and that of most people living today."

Accounts of the banking-and-credit crisis tend to focus their explanations, which usually also means their blame, on one or more of the following four factors: greed, stupidity, government, and the banks. The process resembles a children's game in which you spin an arrow and it lands on a word. Tett spins twice, and lands on greed and the banks; Posner suggests that he doesn't know what the word "greed" means, and his spin lands firmly on government. "We are learning from it that we need a more active and intelligent government to keep our model of a capitalist economy from running off the rails," he writes. "The movement to deregulate the financial industry went too far by exaggerating the resilience -- the self-healing powers -- of laissez-faire capitalism."

This isn't an original conclusion, but the way Posner arrives at it is new and bracing. His first claim to fame was as one of the founders of a school of thought that takes economic ideas and techniques and applies them to the law, as well as to life more generally. He has published nearly twenty books in just the past decade, a superhuman rate of productivity, bearing in mind that Posner is also a practicing judge, a senior lecturer at the University of Chicago, and an energetic blogger (in association with the Nobel Prize-winning economist Gary Becker). He has the rare kind of mind that is a pure pleasure to watch in action, regardless of the subject and the argument being made.

"A Failure of Capitalism" argues that the risks taken by the banks were rational, for two main reasons. First, it's only with the benefit of hindsight that we can know that a bubble in prices was taking place. Bankers had to assign a probability to the prospect that there was a bubble, and, second, to the prospect that, if there was a bubble and it burst, house prices would fall by twenty per cent or more -- this being the decline that precipitated the general crisis of bank insolvency. Now, suppose that the risk of both things happening was one per cent. Whether an event with that likelihood is worth worrying about depends on what its consequences will be. From the larger point of view, the consequences included systemic meltdown; but Posner invites us to focus our attention on what they looked like for individual bankers. They had strong incentives for taking the maximum amount of risks in their lending, since risks are correlated with rewards, and the bankers were so well paid that they didn't really have to worry about being laid off. "The greater the gains are from taking risks that enable very high short-term profits, and the better cushioned the executive is by his severance package against the cost of losing his job, the more risks he rationally will take," Posner notes. Besides, if a bank avoids these risks, and its competitors don't and therefore make more money during the boom, the cautious bank risks going out of business anyway, because its clients will walk away.

People taking out what now look like crazily risky mortgage loans were being rational, too, because they were acting on the widespread assumption that house prices would continue rising. If house prices fell, well, tough luck, they'd walk away from the loan and go bankrupt -- but they probably had lousy credit ratings anyway. "Thus the downside of the home buyer's speculative investment is truncated, making his 'reckless' behavior not only rational but also consistent with his being well informed about the risks," Posner writes. The conclusion: "Risky behavior of the sort I have been describing was individually rational during the bubble. But it was collectively irrational." As for the idea that the bankers were dumb to get so carried away: "I am skeptical that readily avoidable mistakes, failures of rationality, or the intellectual deficiencies of financial managers whose IQs exceed my own were major factors in the economic collapse. Had the mistakes that brought down the banking industry been readily avoidable, they would have been avoided."

This is a familiar place for these arguments to end up: economists often find that apparently erratic behavior is, at heart, rational. It helps that the definition of rationality can be stretched to include emotion, which "is not necessarily or even typically irrational," Posner argues. Reckless greed, incompetent assessments of probability, blindness to the inevitability of downturns, failure to hedge risks so big that they threaten a firm's very existence: all are rational.

It seems a pity that a man as unflinching as Posner didn't put his ideas under more pressure from the specifics of what the bankers did. He is willing to criticize those who have criticized bankers -- "the distinguished economist Paul Krugman," for instance, "who should know better" -- but no banker is named and blamed. One can regret that Posner didn't get the chance to read Tett's book, which offers the opportunity to assess in detail the kind of risks that the bankers were taking.

Blythe Masters, who was in charge of the Exxon Valdez deal, and of selling the very first BISTRO notes, and thus one of the creators of the entire credit-default-swap industry, was among those baffled by the C.D.O. boom. "How are the other banks doing it?" she asked. "How are they making so much money?" The answer, Tett says, is that "she was so steeped in the ways of J. P. Morgan that it never occurred to her that the other banks might simply ignore all the risk controls J. P. Morgan had adhered to. That they might do so was simply outside her cognitive map."

In particular, those banks had accumulated huge amounts of super-senior debt. In the first BISTRO, remember, only seven hundred million dollars was reserved to cover $9.7 billion of risk. The remainder of the debt was regarded as marvellously safe. Bankers call that kind of debt "super-senior," i.e., better than AAA grade, safer than U.S. Treasury bills, so secure that it didn't need to be insured. So what to do with it? Some banks simply let the super-senior debt accumulate on their balance sheets. The amount of this debt "was a closely guarded secret, even within the banks themselves," Tett writes, and the collapse in their value helped bring down the big banks. It would be interesting to read Posner's analysis of these specific actions, which to the layman seem, as they seemed to so many of the J. P. Morgan team, insanely reckless.

A common mistake of very smart people is to assume that other people's minds work in the same way that theirs do. This is a particular problem in economics. Its mathematically based models and assumptions of rational conduct can appear, to non-economists, like toys, entertaining but, by definition, of limited utility. Even Posner, who spent years extending the purview of economic thought, thinks that "the depression is a wake-up call to the economics profession." It's no surprise to find the Yale economist Robert J. Shiller as one of the first respondents to that call. Shiller -- not content with having predicted the bursting of the dot-com bubble in his book "Irrational Exuberance"; co-creating the standard measure for tracking house prices, the Case-Shiller index; going on the record with worries about the housing bubble as early as 2003; and writing one of the first books on the crash, "The Subprime Solution," in 2008 -- has now, with George A. Akerlof, the 2001 Nobel winner in economics, co-written a book on the influence of emotions on economics. "Animal Spirits: How Human Psychology Drives the Economy, and Why It Matters for Global Capitalism" (Princeton; $24.95) takes its title from John Maynard Keynes, who, in a famous passage of his 1936 treatise "The General Theory of Employment, Interest and Money," mused about how businessmen manage to make decisions, given the level of uncertainty about the future. "Our basis of knowledge for estimating the yield ten years hence of a railway, a copper mine, a textile factory, the goodwill of a patent medicine, an Atlantic liner, a building in the City of London amounts to little and sometimes to nothing," he wrote. We can't know the future, and therefore our inclination to act, to do things, "can only be taken as a result of animal spirits -- of a spontaneous urge to action rather than inaction." Akerlof and Shiller extrapolate from this an idea of animal spirits encompassing "noneconomic motives and irrational behaviors," a slightly broader idea than Keynes's usage, but one that allows them to study a range of negative impulses as well as the basic urge to optimism about which Keynes was talking.

"Animal Spirits" is addressed to a general reader, but it's hard not to feel that the book's real audience is among economists. The general reader needs no persuading about the influence of non-rational, non-economic forces on economic thinking. Within the economic profession, however, the subject of strict rationality is the occasion of a permanent pitched battle. (Posner: "The very existence of warring schools within a field is a clue that the field is weak, however brilliant its practitioners.") "Animal Spirits," like "A Failure of Capitalism," is a campaigning maneuver in this ongoing struggle.

Akerlof and Shiller have a set of specific proposals for how the animal spirits might be incorporated into their science. They set out a framework of factors -- Confidence (and the lack thereof), Fairness, Corruption and Bad Faith, Money Illusion (the failure to understand the impact of inflation), and Stories -- and then apply their ideas to a series of specific questions. Some of this is very timely, such as a chapter on "The Current Financial Crisis" and one asking "Why Are Financial Prices and Corporate Investments So Volatile?" But it's clear that the great white whale of modern economics, a thing that would appease the descendants of both Milton Friedman and John Maynard Keynes, is a quantifiable, evidence-based theory of how bubbles are formed, and, hence, how to forestall them. Bubbles are irrefutably clear in hindsight; but an economist who found a way of proving their presence with foresight would be doing humanity a profound favor.

We aren't there yet, though Akerlof and Shiller's book does give the profession some suggestions for the search. There is barely a page of "Animal Spirits" without a fascinating fact or insight, and by no means all from a reflexively liberal viewpoint. One of their culprits for the crisis is Andrew Cuomo, who, as Secretary of Housing and Urban Development, sharply increased the mandated lending to underserved communities by Fannie Mae and Freddie Mac, and in the process lowered credit standards, thus making it "easy for mortgage lenders to justify loosening their own lending standards." Despite the various ideological and methodological differences with Richard Posner, Akerlof and Shiller's fundamental view of how capitalism should work is similar: "What allows capitalism to function is the regulations," they write. This should be an enduring lesson of the crisis -- an understanding that the rules governing the operating of markets were not handed down on stone tablets but are made by men, and are in constant need of revision, supervision, and active, imaginative enforcement. All these books coincide on this point: human beings make markets. A general recognition of that fact, led by the economic profession and taken to heart by politicians, would be a step so important as to be almost worth what it has cost to be reminded of it.


Jonathan Lewellen, Jonathan Tuck Forum Winter 2007

Forty years ago, economist William Sharpe rattled Wall Street when he balanced risks and rewards mathematically. At first seen as heretical and later as "commanding," his capital asset pricing model (CAPM) earned him the Nobel prize in 1990. Succeeding generations of distinguished scholars have continued to tweak the model and debate it, among them Tuck Professor Jonathan Lewellen. "The CAPM," explains Lewellen, "is a way to measure risk, and, in some ways, it's the right way. The underlying intuition for it is exactly right." In Sharpe's model, a stock's beta shows how a particular stock affects a portfolio and provides risk an investor can't diversify away. "That use of CAPM is very elegant," says Lewellen.

But not so fast! It seems that CAPM doesn't perfectly match reality. "On the basis of the CAPM, stocks with a high beta should pay a risk premium," says Lewellen, "but their actual rates of return have not been as high as the CAPM predicts. And key data patterns dealing with 'value' and 'momentum' effects

are inconsistent with the model: stocks that are 'cheap,' as measured, for example, by a low market-to book ratio, do much better than they should. And 'winner' stocks that do very well one year continue their momentum into the next despite having the same beta as losers." If investors are rational, Lewellen concludes, the CAPM is missing some component of risk. "Or, alternatively, CAPM is a complete measure of risk, but stocks are mispriced."

To explain CAPM's failings, several high-profile theorists have proposed a conditional CAPM in which beta varies over time and anomalies disappear-at least according to proponents. In their recent research, Lewellen and Stefan Nagel of Stanford investigated what kind of job the new, conditional model does. The short answer: not so good.

Lewellen and Nagel analyzed portfolios of common stocks from 1964 to 2001. Rather than calculating a stock's risk once over the 40-year span, they found beta for each quarter. "We were looking for new, simple, and intuitive tests-and we came up with vastly different conclusions," Lewellen says. "It turns out beta does vary, but not nearly enough to explain these anomalies." The magnitude of value and momentum effects is what matters.

For the value effect, variations in beta could explain an additional return of 1 percent annually, but the real difference is 7 to 8 percent (the historical difference between value stocks and growth stocks). The momentum effect is a staggering 10 to 15 percent. "None of that could be explained by a change in beta," Lewellen says.

"Beta has to be very volatile, and it has to co-vary with the risk premium. If that's not true, then you may as well assume beta is constant. You may be wrong. But assuming a changing beta can't significantly affect your conclusions."

CAPM may be missing something, but it still plays an important role in capital budgeting and portfolio analysis. For corporations, it can assess a project's risk or judge the work of a mutual fund manager. Says Lewellen, "The CAPM is still useful for all these things even if it's not a perfectly accurate description of the way the world works."


Malkiel. Burton G. The Wall Street Journal Oct 13, 2008. pg. A.19

As the world economy reels under the weight of the worst financial crisis since the Great Depression, we have been left with a broken financial system. Financial institutions around the world have suffered life-threatening, self-inflicted wounds by purchasing over a trillion dollars of complex mortgage-backed securities backed by dodgy loans based on inflated real-estate values. These assets have been financed with enormous leverage and with short-term debt. Just prior to its "rescue," Bear Stearns had a debt to equity ratio of over 30 to 1, making it susceptible to a "run on the bank," although Bear was not a commercial bank but rather part of the "shadow banking system" built on derivatives.

The long-run solution to the present crisis must involve substantial deleveraging and a recapitalization of our financial institutions. In the meantime, credit has been essentially frozen and a world-wide recession seems almost inevitable.

But just because stock markets have panicked, investors should not. The best position for investors today is not "fetal and 100% in cash." We are not going to have a depression, and we have survived financial crises before. A century of investing experience, as well as insights from the field of behavioral finance, suggest that investors who bail out of equities during times like these are almost always making the wrong decision.

It is very tempting to try to time the market. We all have 20/20 hindsight. It is clear that selling stocks a year ago would have been an excellent strategy. But neither individuals nor investment professionals can consistently time the market. The herd instinct is extraordinarily powerful. When the economy and the stock market were booming in early 2000, investors could easily convince themselves that prosperity would continue without interruption and that stocks catering to the "New Economy" were surefire tickets to wealth. Individuals poured more money into equity mutual-funds during the last quarter of 1999 and the first quarter of 2000 than ever before. And not only was the timing wrong but so was the selection of funds. The money flow was directed to the hot Internet funds. Investors liquidated "value" funds that owned less exciting businesses, whose stocks sold at only modest multiples of their earnings and book values.

The herd instinct works exactly the same way in bear markets. Nervous investors convince themselves that every "light at the end of the tunnel" is a train coming in the opposite direction. Panic is just as infectious as blind optimism. During the third quarter of 2002, which turned out to be the bottom of a punishing bear market, investors redeemed their mutual funds in droves. My own calculations show that in the aggregate, investors who moved money in and out of equity mutual-funds underperformed the buy-and-hold investors by almost three percentage points per year during the 1995-2007 period.

Look at history: The market eventually bounded back from the damaging stagflation of the 1970s and the savings-and-loan crisis of the early 1990s, when a whole industry had to be rescued. Stocks also recovered from the Asian crisis of the late 1990s. Similarly, investors who held on after the more than 20% one-day stock-market decline in 1987 were eventually well rewarded.

So what should investors do? By all means, young 401(k) investors, and those in their prime earnings years, who are stashing away funds from every monthly paycheck, should stay the course. If you decide to eschew equities during periods of ubiquitous pessimism, you will lose all of the advantage of "dollar cost" averaging (buying more shares when prices are low than when they are high). Asset allocations should be shifted to safer securities over time as the investor ages, but only gradually and on a set schedule as through a "target maturity fund."

If you are now approaching retirement and failed to move to a more conservative asset allocation, you should not do so now in response to a time of panic. If anything, well diversified investors should, at the end of each year, consider rebalancing to ensure that your portfolio composition remains consistent with the risk level appropriate for your financial circumstances and tolerance for risk. But this is likely to mean shifting into equities and not out of them.

Suppose you started the year with a portfolio of half stocks and half Treasury bonds. You are likely to find that the value of your bonds has gone up, as Treasury yields have fallen, and your stock portfolio has declined. Suppose the allocation at rebalancing time is two-thirds bonds and one-third stocks. The appropriate strategy is then to sell safe bonds and buy more equities to bring the stock/bond ratio back to 50%. Over the past decade, rebalancing a 50-50 portfolio each year has added to investors' returns and reduced risk.

We will have a serious recession now, but a 1930s-style depression is highly unlikely. We will not let the money supply decline by 25%, as we did in the '30s, and automatic stabilizers (like unemployment insurance) are now a significant element of fiscal policy. Don't forget that the U.S. economy is still the most flexible in the world and our "innovation machine" is alive and well.

No one has consistently made money by selling America short, and I am confident the same lesson is true today.



Mann, Charles C. Investment Vision Oct/Nov 1991

"Investor pornography!" erupts Eugene Fama, a wiry man in a knit shirt and khaki pants, Fama is flipping through a pile of investment newsletters that has been slipped onto his desk. Outside, it is a bright, baking hot Chicago morning; young people desultorily knock balls back and forth on a nearby tennis court.

Inside, it is air-conditioned, and people are briskly knocking ideas back and forth-ideas about playing the markets, and whether the tipsheets on Fama's desk, chockablock with charts and graphs. can help do it.

For more than 25 years, Eugene Fama, a cheerfully contentious man, has sat in his office and thought about the stock market. What makes Fama different from the securities analysts on Wall Street is that he doesn't think about the market in order to make money—or, at any rate, not exclusively to make money. Fama is an economist at the University of Chicago Graduate School of Business, and what he wants to know is how the blessed thing works.

Economists have been fascinated by markets for decades. The stock, bond, and commodity markets have always seemed the epitome of capitalism with their roar and hubbub, their ceaseless activity, their violent unpredictability. Capitalism being the reigning interest of most economists, it is unsurprising that many great practitioners of the dismal science have taken a crack at explaining Wall Street. Fama, perhaps the most important living theoretician of the stock market, has devoted his entire career to studying the questions that puzzled his predecessors: Why do stock prices rise and fall so erratically? Do investors make rational decisions? Can a trading system be designed that would outperform the simple strategy of buying and holding many different stocks? In the language of contemporary economics, these boil down to a single query: Is the market efficient?

Fama devoted his 1964 thesis and many later articles to these matters. But it was not until 1970 that the world outside academia sat up and took notice. In that year, Fama published an article in The Journal of Finance that both defined the term "efficient capital market" and examined whether the stock market was one. 1n an efficient capital market the prices of securities fully reflect all available data. And yes, he concluded, the stock exchange, along with its brethren in bonds and commodities, is overwhelmingly efficient. The concept was far from purely theoretical, for when security prices reflect all available data, nobody can consistently find under- or overpriced stocks to exploit for profit. Which means that no investor can reliably do better than the market as a whole. Which means, in turn, that the securities industry is based on a chimera.

Fama gave his article the dull academic-sounding title, "Efficient Capital Markets: A Review of Theory and Empirical Work." He never expected the level of reaction it would provoke. Forbes and Fortune wrote lengthy pieces reviewing the theory; a drawing of his curly head appeared in The Wall Street Journal. Lauded by his colleagues, Fama found himself discussed on TV talk shows. "Insofar as you can become famous for writing an article for an academic journal," he says dryly, "I became famous."

On the other hand, professional investors paid little attention to the rumblings from academe. And, in a sense, they may have been right. Since Fama's first paper, many economists have turned up evidence that stock market movements are far from random. If the market is efficient, some say, how could Black Monday have happened? Indeed, the picture has changed so much that Fama has prepared a sequel to his 1970 article. Soon to be published by the Journal of Finance, the new paper has already stirred heated argument.

For the investor, Fama has some good news and some bad news. The good news is that, contrary to what he originally thought, the stock market is somewhat predictable. The bad news is that you still can't beat it.

Historians say that the careful study of the question of whether individuals can beat the market began in 1900 when Louis Bachelier, a brilliant French mathematician, wrote his dissertation on the price of government bonds. Bachelier's findings can be simply put: The rise of the price of a bond on Monday tells you nothing about whether it will rise on Tuesday. The lack of serial correlation-the failure to show that one movement has anything to do with the movement before or after--defines what mathematicians call a "random walk." And the salient feature of a random walk is that you can guess where it's going only by accident.

Unfortunately, Bachelier's work on bonds was almost entirely ignored, as was his near simultaneous description of Brownian motion. (Discovered by British botanist Robert Brown, Brownian motion is the slight erratic motion of particles in suspension, like grains of pollen on water.) Bachelier's work on Brownian motion was independently rediscovered five years later by Albert Einstein; the random walk theory had to wait more than half a century for its turn, until 1953, when Maurice Kendall, a British researcher, examined the weekly changes in 19 stock indexes on the London exchange and tried to find a pattern in the price movement. He couldn't. Indeed, Kendall reported, his charts of stock prices looked "almost as if ... the Demon of Chance drew a random number ... and added it to the current price to determine the next week's price."

The implications of the random walk theory are profound. Random walks occur, economists argue, because stock market prices adjust rapidly to every bit of new information that affects the value of a company. A merger is announced, and the company's share price soars. Investors hear that winter freezes might hit in Florida and sell orange futures in droves. Because these events occur sporadically, and the adjustments happen fast, it is impossible for most people to take advantage of them. Thus stock prices change randomly, skittering like a drop of water on a hot frying pan.

Such randomness means that nobody can beat the market except by luck or inside information. An investor may have along run of success, but that is no more than the "millionth monkey effect"-the likelihood that, just as one of a million monkeys at a million typewriters will write out Macbeth, or that one of a million would-be financial wizards at computer consoles will make a fortune. But in the end, the theory says, no trader can beat the market consistently; anyone who says otherwise is either a fool, a knave, or Ivan Boesky.

Throughout the 1960s, economists tinkered with the random walk model. But still the investment industry rejected it. The market, in Wall Street's view, is not efficient. It is not a random walk. One investor can get better information, beat other investors to the punch, make more money, and do so consistently. Sure, money managers said, the capital markets are mostly efficient. That's obvious. But the investment business is devoted to exploiting the holes in that efficiency, and feels it does it very well, thank you.

Economists smile at such self-interested claims. As Charles Nelson of the University of Washington has said, Wall Street is not littered with huge stock bargains for the very same reason that it is not littered with $20 bills. If money is lying around, somebody picks it up. In other words, any new information is immediately figured into the price of a stock.

"The prevailing belief held by money managers," says Andrei Schleifer, an economist at Harvard University, "is that most other money managers are idiots, and they alone see through the market. It's a curious situation on Wall Street-a huge industry full of economics majors, which operates based on beliefs that professional economists think are silly. The only way to resolve the question is, of course, to look at actual evidence, and that's what Fama did so well, first in 1970 and now again."

In 1970 Fama was a full professor at the University of Chicago. He looked at the hodgepodge of arguments about stock market predictability, and grasped that, beyond self interest, the issue boiled down to the not-so-obvious question of efficiency. In his "Efficient Capital Markets," he began by observing that stock markets could never be shown to be perfectly efficient-that would be, he said, proving a null hypothesis, an empirical impossibility. The real question was the degree of inefficiency, and whether it was large enough to be useful to investors (since inefficient capital markets offer the only hope of doing better than the market as a whole).

Using the mainframes that had recently been made available to universities, Fama and others picked through reams of data on stock market trades. Much like Bachelier before them, they tried to observe whether the change in the price of a stock on one day was linked to the change in its price, say, one week later. Testing on intervals of from one day to two weeks, Fama discovered that the predictability of stock price movements in the Dow Jones Industrial Average was considerably less than 3%-- "real", he says now, "but not big enough to be worth bothering with."

One implication was clear: Professional investment managers were as unlikely as ordinary investors to outperform the market. "And that," Fama says, smiling, "leads to an interesting puzzle. You say the stock market is a random walk because investors are smart enough to absorb the meaning of all new information quickly. And the randomness of the random walk means that you can't beat the market. Well, how come those same smart investors are spending fortunes on analysts and newsletters like these, which according to the random walk model are entirely unproductive?"

Within the realm of economics, Fama's argument for capital market efficiency became the classic treatment of the subject. He continued to work on understanding the stock market, now using the University of Chicago's Center for Research in Security Prices (CRSP), a department that keeps computerized records of New York, OTC, and American Stock Exchange transactions. Meanwhile, his "Efficient Capital Markets” was subjected to the treatment meted out to all classic academic texts: It was attacked, sometimes vehemently.

Fama ignored the scoffs from Wall Street as merely the noise of people who had a vested interest in the existence of market inefficiencies. Bur more substantive criticism came from researchers using the CRSP data banks. Poring over this vast store of transactions, economists plucked out statistical anomalies that seemed to contradict the notion that stock movements were patternless. Returns on Monday are consistently lower than those on other days of the week, for example. Average returns are greater on the last day of the month, the day before a holiday, and at the beginning of every day. Most surprising is the so-called "January effect" -that small stocks routinely rise in value during the last trading day of December and the first five trading days of January. These effects are, minor, to be sure, but could their existence be reconciled with the notion that stock market movements are random?

Yes, backers of the efficient market said. To them, these phenomena were the offspring of "data-mining." Imagine all the possible ways that researchers can comb for regular, seasonal bumps in stock returns. You could check each day of the week, the fifth day of every month, the day after holidays, the summer doldrums, and so on. Now, given all these various ways of hunting for correlation, what is the chance that you won't find that on some days investors are more likely to do better? Close to zero. To most economists, such regularities are no more meaningful than the discovery that a group of five or six people who live near each other have similar types of cancer.

"What is the likelihood that in the entire country you'll find such clusters if you look for them?" Fama says. "Very large, I think, which is why people who understand statistics tear their hair out when reporters make a big thing of them. Anomalous patterns in the stock market are the same. They exist, but aren't necessarily anything more than chance."

In Fama’s view, the more interesting aberrations are the long-term serial correlations uncovered by himself and Kenneth French, also of the University of Chicago, in 1988. They were stimulated by the idea of a colleague, Lawrence Summers, now at the World Bank, that stock market averages might be predictable over longer periods and that Fama's short, two week tests might have missed this effect. Markets could have "fads"-irrational rises and falls-that last for weeks or months, only slowly returning to normal levels. The implication is that, a la Fama, you can't foresee next week's stock returns, but you might be able to get a handle on next year's. Fama and French were intrigued. Going back to the CRSP data, they found that over two- to ten-year periods, returns were indeed strikingly predictable.

Fama thought the results were "dramatic" enough to draft a sequel to his 1970 article, "Efficient Capital Markets: II." "I was astounded at first," Fama concedes. "But then, later, I realized that of course we hadn't found the key to all wealth." He made two points. First, many of the long-term patterns disappeared if data from the Depression were thrown out. In other words, the Fama-French regularities are due to a sort of huge "blip"-the 1930s.

Second, and most important, market predictability does not necessarily conflict with market efficiency. For example, stock markets must, on average, give players extra benefits, or they will demand safer investments. Because Treasury bills are safe and always available, the return from them is like a zero point-the money someone can make without risking anything. Because investors can lose their shirts in the stock market, they won't be persuaded to put their cash into it unless they can make extra profit (a premium, in the jargon). The expected return fluctuates with economic conditions. But when all variations are accounted for, the premium demanded for investment in the stock market is reliable in the long run.

As a result, investors face a kind of ladder of premiums. At the bottom are T-bills, which have the lowest returns. Next are corporate bonds, which are riskier, and therefore must pay more interest. And above them are stocks, or equities, riskier still. When business conditions change, expected stock market returns may fall. Investors will then look into bonds. With more investors in the bond market, expected bond returns drop; meanwhile, companies with public stock may lure investors with extra cash, in the form of dividends. Over time, the equity premium is maintained through the ups and downs of business conditions. The stock market may seem to sag and jump irrationally, but in the long run, it maintains the ladder of premiums. It's part of a larger efficient market.

Unfortunately for investors, Fama says, it is extremely difficult to take advantage of these regularities. ''To some extent, the market is predictable. But what it's predicting is that you can't beat it. It is saying spread your wealth over a wide range of stocks, hold onto them for a long time, and you'll almost certainly win. But you won't win more than anyone else, unless you're the millionth monkey."

This is not necessarily bad news for money managers. Surveys of equity mutual funds have shown that as a whole they perform close to market average. True, a few funds consistently outperform it, but this is no more than would be expected. Since investors can do just as well on their own, why do they go into the funds? "They can provide something," Fama says. Investors pay for the convenience of not having to handle their own money, and for the security of knowing they are unlikely to lose more than everybody else. Of course, money managers actually promise financial, not emotional rewards-a claim that makes Fama scoff. "Just think about it," he says, picking up a newsletter at random. "Why do these things exist? To tell you that certain stocks are over or underpriced, right? In other words, the prices don't reflect their true value, and you should buy or sell to take advantage of that.

"But when you go to the supermarket, you don't say, 'Hey, the price of these heads of lettuce doesn't reflect their true value.' You say, 'Gee, this lettuce is expensive.' Then you buy or you don't buy, depending on how much you want lettuce. It's mystifying to me why people think prices at the stock market are different from prices at the supermarket."

Fama shakes his head. Sunlight glares from behind the shades in his office.

"You know what people would say if you went out and claimed you'd consistently beat the supermarket? They'd say, 'You're crazy!' But you know what they say if you tell them you've beat the stock market? They say 'Let me give you my savings.'"

Markets and Morality

Or Arbitragers Get No Respect

Markowitz, Harry M. Wall Street Journal: May 14, 1991. pg. A.2

Usually the only thing I lecture on lately is portfolio theory, but this time I think it best if I make an exception. I have decided, instead, to discuss questions of right and wrong, especially as applied to participants in financial markets. Now, you know as much as I do about right and wrong. So, this afternoon I will be an equal opportunity speaker: I will explore a subject on which the audience knows as much as the speaker.

There are many obvious ways in which a society's rules of right and wrong influence its quality of life. Where littering is not frowned upon, all live in a world of litter. Where "excuse me" and "thank you" are passe, all live in a rude world.

The consequences of rules of right and wrong are sometimes subtler. A few years ago a friend asked me to have dinner with him and a Russian emigre mathematician. I was disturbed to hear the mathematician predict that the Gorbachev reforms would not succeed. "The basic problem is the Russian people's attitude toward profit," he explained. "If there are goods one place that are needed someplace else and someone makes a profit moving these goods from the one place to the other, he is considered greedy and evil."

In fact, the Gorbachev reforms did not succeed. When economic collapse had proceeded far enough, Mikhail Gorbachev froze bank accounts, causing much distress among those who had managed to save anything. The purpose was to frustrate those Mr. Gorbachev said were the true culprits: the blackmarketeers. Thus in Mr. Gorbachev's mind, or at least in his words to the Soviet people, the source of the Soviet ill was the greedy, evil people who seek to benefit from the misfortunes of others by moving goods from where they are to where they are needed, not out of altruism but out of avarice.

My own views are much closer to the gospel according to Adam Smith. The invisible hand is clumsy, heartless and unfair, but it is ever so much more deft and impartial than a central planning committee. Consequently, I am troubled by the indiscriminate way many Americans use "greed" as an explanation of economic events. For example, the cover of "Liar's Poker," a book about Salomon Brothers, shows a dollar bill with a picture of John Gutfreund, head of Salomon. Inscriptions on the dollar include "In Gutfreund We Trust" and "Wall Street Greed." The back cover of "The Predators' Ball," about Drexel Burnham Lambert and Michael Milken, contains part of a New York Times review, which says the book "dramatically captures the philosophy of greed that has dominated Wall Street in the 1980s."

The blanket condemnation of the "greedies" of the 1980s fails to distinguish between the complaint that too many people sought to maximize their own well being, as Adam Smith would have us all do, legally, and the complaint that too much leverage was used in the 1980s. If the latter is the true complaint, the blanket condemnation of "the greedies" fails to ask whether the reason for excess leverage was the fact that slick salesmen disguised the true risks of the junk bonds they sold. Or was it that unwise laws structured institutions so that they were induced, and sometimes compelled, to take high risks?

The blanket condemnation of the greedies of the 1980s blurs other important distinctions. It lumps together people who were remarkably stingy with those who were remarkably generous, either with public donations to good causes or with quiet private help to others in need. It lumps together those whose sole interest in life was the winning of the finance game, as measured by their accumulating wealth, and those who played the game well, accumulated fortunes, but found time for other interests. It lumps together those who committed well-defined crimes and deserved the punishment they got, and perhaps more, with those who were arrested conspicuously, left waiting for the next round of charges, then had their cases dropped as a big mistake; and those whose crimes had been civil offenses before, but now were elevated to criminal offenses.

I'd like to examine some of these distinctions more closely, but before that I'd like to correct two misimpressions I may be giving. First, you may think that I think that maximizing well-being is the same as maximizing wealth. But I believe that most people find that once some moderate needs for food and shelter are satisfied, it depends more on how you spend your time than on how much money you make.

Second, since I have emphasized the efficacy of markets as compared to bureaucrats, you may think I think that markets can run themselves. This is not the case. Laws and law enforcement are needed to assure me that the meal I buy is not poisoned and the airplane I fly on is well maintained; that those who manufacture things for my use pay their full costs, including the costs of cleaning up the mess they make; that if I deposit money with a bank or pay a premium to an insurance company the banker or insurer will not go to Las Vegas to gamble with my money.

These two things now said, let's return to the alleged greedies of the 1980s. I would like to organize my remarks around two product areas of major importance in the 1980s. One is mortgage bond products as pioneered at Salomon Brothers; the other is junk bonds -- that is, high-yield, high-risk bonds, whose market was dominated by Mr. Milken at Drexel.

"Liar's Poker" is the story of Salomon Brothers as told by Michael Lewis, who entered the firm early in 1985 as a young trainee and left it three years later when he decided making that much money wasn't that important. When he speaks generally, he speaks of the greed that permeated and dominated Salomon Brothers. When he describes specific individuals and actions we find that some are mean and some kind, some are stingy and others generous, some you can trust and some you cannot. The individuals seem no more nor less than human.

Mr. Lewis considers his to be a tale of greed. I view the same events and find in them the triumph of two great ideas: Adam Smith's invisible hand at its clumsy but beneficent best; and option-pricing theory as applied and enhanced by the "rocket scientists" whom Salomon Brothers had gathered.

The mortgage-backed bond did not become a great source of profit for Salomon Brothers until the 1980s, but its cause was championed within Salomon Brothers by Bob Dall as early as 1977. By February 1979, Lewie Ranieri, who had started in the mailroom, was officially placed in charge of mortgage operations. Eventually the mortgage bond business blossomed, thanks in part to a tax break passed in 1981 that made it highly desirable for savings and loans to sell their old mortgages and use the proceeds for other investments, even the mortgages sold by other S&Ls.

In the following years the market grew. It also changed character. Mr. Lewis quotes Samuel Sachs, longtime mortgage bond salesman, as saying: "They wheeled in the rocket scientists, who started to carve up mortgages into itty-bitty pieces. The market became more than the five things that Lewie {Ranieri} could hold in his brain at any one time."

Mr. Lewis contrasts the refinement of analysis that lay behind some mortgage products with the crudeness of some of the traders who bought and sold these products. My own view is that the fact that the invisible hand could work its magic through mere humans is an essential part of Adam Smith's insight. Not many thousands of years ago, men like this would have clubbed each other over hunting rights. A few hundreds of years ago they would have hacked each other with axes and swords. Now they yelled at trainees while they brought together the supply and demand of home mortgages on a world-wide scale.

At first, Salomon Brothers had a great advantage over other investment banks in the mortgage product area. This advantage was temporary. Bright young people could see that they were bringing millions of dollars of profit to Salomon Brothers, and felt that their annual bonuses should reflect this. This conflicted with Salomon caps on bonuses as a function of how long the person had been there. But other investment banks were delighted to bid away many of Salomon Brothers' young stars. As other investment banks built their own capabilities, customers gained the ability to shop around. In short, I take the story of mortgage products at Salomon as an example of Adam Smith's thesis that individuals seeking their own self-interest through the marketplace will promote the common good, even if some of them are crude.

Now let us turn to the junk bond market under Michael Milken at Drexel. I find Connie Bruck's detailed account in "The Predators' Ball" quite plausible and will use it as my principal source. In the 1980s Michael Milken engaged in illegal and near-illegal behavior as a regular part of doing business. Part of this behavior had as its purpose the suppression of competition in the junk-bond business.

For example, in 1985 the board of Wickes decided to do a debt underwriting through Salomon Brothers, which had been trying to break into the junk-bond business. After Mr. Milken learned of the forthcoming underwriting, Saul Steinberg, a close Milken associate, accumulated 10.4% of Wickes's stock, and duly reported this to the SEC. Then Mr. Milken had a Saturday breakfast meeting with Sandy Sigoloff, president of Wickes. According to a Wickes director, "Mike told Sandy what Saul held, what Drexel held, and how, when you combined that with whatever other pockets Mike might have placed stock in, it meant they would have control of the company." In the next few days Drexel became co-manager and then sole manager of the Wickes underwriting.

Ms. Bruck notes that if Mr. Steinberg, Drexel and perhaps "other pockets" did plan to act in concert, they were in violation of securities laws by not filing with the SEC as a group. Ms. Bruck also provides other examples of "the brass knuckles, threatening, market manipulating Cosa Nostra of the securities world."

A small part of Mr. Milken's illegal or near illegal activities involved his association with Ivan Boesky. My dictionary defines greed as "excessive or reprehensible acquisitiveness." The word is so overworked that I hesitate to use it. But it does seem that Mr. Milken was as excessively acquisitive as one could get, and Mr. Boesky about as reprehensible. Since Mr. Boesky is usually associated with the words "greed," "insider trading" and "arbitrager" I cannot resist saying a few words in defense of the perfectly respectable business of doing arbitrage. This is in part self-defense since, for three years, I was in the arbitrage business.

In index arbitrage, the arbitrager looks for moments in time when the price of a futures contract for a stock index is out of line with the appropriate sum of prices of the individual stocks that make up the index. The arbitrager then buys the one and shorts the other. This would tend to keep prices in line. Admittedly, this may seem like a rather fussy fine tuning of the price system; but it seems, at least to me, to be a good thing rather than a bad one to have prices of related things be closely linked.

Ivan Boesky practiced merger arbitrage or risk arbitrage. A simplified example will serve to illustrate. Suppose that Company A agrees to buy Company B, and B agrees to be bought. A agrees to exchange one share of its $150 stock for each share of B's $100 stock. Upon the announcement of the deal, let us assume that A's stock stays at $150 while B's rises to $140. If you owned neither stock, and you were sure that the deal would go through, you could assure yourself a $10 profit by shorting (that is, selling) one share of A at $150 and buying one share of B at $140. This procedure would be safer than just buying a share of B, since the price of both A and B might fall.

But there is one risk: Sometimes deals do not go through. Thus inside information is very valuable to the merger arbitrager, but it is not legal to act upon. It is much less likely that any kind of inside information would be of value to other sorts of arbitragers.

The proposition "inside information is especially useful to merger arbitragers" does not imply the proposition "all merger arbitragers use inside information." For a reduced sentence Ivan Boesky implicated Marty Siegel among others, and Marty Siegel implicated three arbitragers in prominent positions. The three were arrested with great fanfare, one being led away in tears and handcuffs.

One of the three was eventually convicted of having learned that a merger might not go through for which he had an arbitrage, and acting on this information. This was indeed a crime, or at least a securities law violation, and deserved some kind of punishment. But it was not a pattern of buying and selling inside information as with Messrs. Boesky, Siegel and Levine. As for the other two arbitragers arrested, after much delay it was decided that no charges would be brought, that there had been a miscommunication between Mr. Siegel and the prosecutors. I agree with those who feel that if the prosecutor had been less politically motivated he would have prepared his case first and made his arrests second.

Returning to Michael Milken and the junk market, as we noted already Mr. Milken engaged in illegal activities, in part to maintain a near monopoly in junk bonds. One use of this monopoly was to obtain high fees for junk-bond underwritings. Implicitly, part of the fee was in the form of warrants -- the right to buy the issuing company's stock at a fixed price, which would prove highly valuable if the stock price rose. Frequently Drexel insisted that the warrants were needed to induce prospective buyers to buy the bonds. In fact, most warrants went to Drexel employees, favored clients, and investment partnerships controlled by Mr. Milken.

But the chief complaint about junk bonds was not that Drexel charged too much for them but that they were used for destructive purposes, that they weakened the American economy. I believe this to be true, but there are exceptions.

Only a small minority of companies command investment-grade ratings from the bond-rating services. The junk-bond market provides a major source of capital for the rest. Clearly this market serves a useful purpose in bringing together supply and demand for such higher-risk and therefore higher-yield securities.

The chief complaint about junk bonds is that they were used to finance highly leveraged deals -- management buy-outs or hostile takeovers. The extent of the leverage is illustrated by Ms. Bruck's description of Nelson Peltz's 1985 hostile takeover of National Can, financed by Mr. Milken's junk bonds: "Five hundred sixty-five million dollars was a towering debt load for $100 million of equity to carry. And Peltz pointed out that even the $70 million from Triangle, at the equity base, came from its earlier offering of junk. . . . `We called it equity here, but it was debt over here. Do you understand the leverage in this deal? It was eleven to one!'"

Part of the standard takeover strategy is to attempt to reduce the debt once the target firm is acquired. In some hostile takeovers the stock of the company is sufficiently undervalued as compared with the underlying assets that a corporate raider can buy the company at a high price (compared with the stock's recent market price), sell off pieces of the firm, pay off most of the debt and thus acquire the core business for almost nothing.

In general in such situations, either the market has set an irrationally low value on the company or, as corporate raiders often contend, the market reflects the poor way entrenched management uses resources. This point is well taken. Such raids, and the threats of such raids, tend to put a boundary on how inefficient management can become in corporations where no individual or small group considers itself the company's owner. But in highly leveraged deals such as Mr. Peltz's takeover of National Can, the sale of inessential assets still leaves the company highly in debt.

Another source of debt reduction is the company's cash flow. To increase the cash flow the raider, now owner of the company, reduces research, employment and maintenance. Sometimes, some of this makes the firm more efficient. But based on the levels of debt that had to be paid down, I imagine that the raiders, now owners, of the highly leveraged companies had to cut back research, maintenance and staff to the point where firm value fell.

If so, then somebody had to lose. Who? Not the old stockholders, since they were bought out at a favorable price. Not Drexel or Michael Milken, since they received large fees plus warrants. Not the raider, since he took a highly advantageous gamble. If things went well, his bet would have a high payoff. If it went poorly, for the most part it was not his own money that was at stake; and, in the meantime, he enjoyed the perks of his large enterprise.

Old bondholders lost as the firm became more risky, since the quality and therefore the price of their old bonds fell. Perhaps better bond covenants could protect bondholders against such increases in firm risk at their expense. The people who were laid off lost. But it is hard to see how to protect them without passing laws that generally restrict firms' abilities to lay off workers. In the long run it would lead to a rigid and less productive economy -- therefore a much smaller pie for all to share.

What about the investors in the junk bonds? Were they winners or losers? Here we must distinguish between those who chose to invest in junk bonds and those who had their funds put at risk in these bonds without their knowledge or consent. If people invest in a high-yield investment fund, they have little or no cause to complain if they lose. But Mr. Milken's vast sources of funds were not such investment trusts; they were pension plans, S&Ls and certain kinds of insurers.

The S&L structure encouraged gambling by S&L managements with S&L funds. The risks they took were in real estate and junk bonds. The game was structured so that if bets were won on average, then the S&L and its management gained; if they lost, then the U.S. taxpayer lost.

A similar game was available to some insurance companies. A good example is Fred Carr's First Executive Corp. As Ms. Bruck tells us in "The Predators' Ball," Mr. Carr was one of Mr. Milken's best customers. The money with which Mr. Carr bought junk bonds was mostly the reserves of insurance policyholders. As with S&Ls, Fred Carr bore little of the risk of the junk bonds. The risk was principally borne by the policyholders, who were not warned of this risk. They were provided no notice saying: "This policy is backed by risky investments. It may or may not pay off in full."

This situation raises regulatory and moral questions. On the regulatory side, we should try to eliminate situations where one party makes the decisions and reaps the gains while someone else pays the costs or suffers the losses. The individual needs protection against such financial risk, as he needs protection against bad food and unsafe planes.

The moral question is this: Suppose you can legally gain the reward and stick other people with the risk. It is easy enough for me to tell you not to do it. But will it change your action? Perhaps you should weigh this in your decision: Someday people you put at risk without comparable reward may seek retribution. Even if what you did to them was legal, some regulator or prosecutor may look at everything else you did to see if anything can be used to embarrass or punish you. Is it worth it?

Crimes were committed in the financial industries during the 1980s. But I know of no study that shows that, per person with comparable opportunity, the financial industries of the 1980s had more lawbreakers than other industries or other times. It is also true that members of the financial communities have been the victims of overzealous prosecutors. It is this that makes me feel that the blanket condemnation of the greedies of the 1980s is not just silly, but destructive.

The chief complaint about Wall Street in the 1980s was not about lawbreaking, but about highly leveraged hostile takeovers. I now hold the hypothesis that excesses in this area were primarily due to the availability of large pools of money whose ultimate owners or guarantors could be stuck with risk with little or none of the reward, without their knowledge or consent. Without these pools the junk bond would mostly be a vehicle for bringing together those who need funds, but do not have an investment-grade rating, with those who seek higher return, understanding that it comes with higher risk.

Top of Form

Why Students Of Prof. El Karoui Are In Demand;

French Math Teacher Covers Structure Of Derivatives;

Banks Clamor for 'Quants';

A Lesson on 'Smile Risk'

Mollenkamp, Carrick and Fleming, Charles. Wall Street Journal : Mar 9, 2006. pg. A.1

When Xavier Charvet applies for a job at an investment bank next year, he thinks he'll have an advantage. The 24-year-old French student's resume begins with the phrase: "DEA d'El Karoui."

That stands for the postgraduate degree he is studying for under Nicole El Karoui, a math professor in Paris. She teaches skills required to create and price derivatives, the complex financial instruments based on stocks, bonds or loans. "When I talk about El Karoui's master's, everyone knows" about the degree, says Mr. Charvet.

As derivatives have become one of the hottest areas for the world's biggest banks, Ms. El Karoui, 61 years old, has become an unlikely player in the business. Her courses at the prestigious Ecole Polytechnique and a state university, in such rarefied subjects as stochastic calculus, have become an incubator for experts in the field. A resume with her name on it "is a shortcut because you don't need to train the person on the basics of derivatives," says Rachid Bouzouba, a former student who is now head of European equity trading at the London office of Lehman Brothers Holdings Inc.

The derivatives departments at banking giants J.P. Morgan Chase & Co., Deutsche Bank AG, Dresdner Kleinwort Wasserstein, and France's BNP Paribas SA and Societe Generale SA include many of her proteges.

The high demand for her students reflects big changes in the global banking industry. Investment banks used to make much of their money from underwriting and trading stocks and bonds, or providing mergers- and-acquisitions advice. They hired people with a wide range of academic experience, including liberal-arts and science graduates.

In recent years, profits from trading and selling derivatives have come to rival those from stocks and bonds at many banks. On average, revenue from derivatives based on stocks now accounts for about 30% of an investment bank's total revenue from stock-related businesses, according to a Citigroup Inc. report issued in January.

As a result, banks are hiring an increasing number of recruits who understand derivatives. Inside banks, they are known as "quantitative analysts," or "quants" for short. They are able to marry stochastic calculus -- the study of the impact of random variation over time -- with the realities of financial trading.

Derivatives are financial contracts, often exotic, whose values are derived from the performance of an underlying asset to which they are linked. Companies use them to help mitigate risk. For example, a company that stands to lose money on fixed-rate loans if rates rise can mitigate that risk by buying derivatives that increase in value as rates rise. Increasingly, investors are also using derivatives to make big bets on, say, the direction that interest rates will move. That carries the possibility of large returns, but also the possibility of large losses.

The 75 or so students who take Ms. El Karoui's "Probability and Finance" course each year are avidly sought by recruiters. Three years ago, Joanna Cohen, a specialist in quant recruitment at Huxley Associates in London traveled to Paris to meet Ms. El Karoui to ensure her search firm was in the loop when students hit the job market. Today, Ms. Cohen says she carefully checks resumes with Ms. El Karoui's name to make sure applicants aren't overstating their interaction with the professor.

"French quant candidates know that Nicole El Karoui's name has real clout, so many of them put her name on their [curriculum vitae] even if they've just taken one course with her. They want to give the impression that she has supervised their Ph.D.," Ms. Cohen says. "It'd be impossible for any one person to supervise the number of students who put her name on their CV."

Rama Cont, a former student and now a research fellow at the Ecole Polytechnique, describes a degree with Ms. El Karoui's name on it as "the magic word that opened doors for young people."

Headhunters say Ms. El Karoui's graduates can expect to earn up to about $140,000 a year in their first job, including a bonus, once they complete an internship that constitutes part of her course. After five years, they could be earning at least three times as much.

In BNP Paribas's offices in London, the fixed-income interest rates derivatives research team, which totals six, includes three of her former students. On a recent day, Fahd Belfatmi, who took Ms. El Karoui's course in 2003, was working at the bank on a model to predict long-term interest rates. For help, he keeps handy a beat-up, paperback copy of Ms. El Karoui's French-language textbook, "Stochastic Models in Finance."

Ms. El Karoui's only hands-on banking experience in her 38-year career was a six-month stint about two decades ago at a French retail bank. "I'm still a theoretician. My knowledge of markets is patchy and I've never spent a year in a trading room," she says. "On many counts, I probably have a fairly naive vision of things."

But she was one of the first in the world to carve out an academic niche studying the underpinnings of derivatives transactions, starting courses in the late 1980s. About two dozen universities have moved into that field, setting up their own mathematical-finance departments, including Stanford University, Carnegie Mellon University and the Massachusetts Institute of Technology.

One of eight children in a middle-class family, Ms. El Karoui grew up a Protestant in a predominantly Catholic town in eastern France. Today she attributes her nonconformity to that background. "Protestants are rebels by nature," she says. Though her mother thought France's elite colleges were better suited for boys, her father, an engineer, encouraged her to take the tough entrance exams for Ecole Nationale Superieure, where she was accepted to study math. In 1968, around the time she was protesting the Vietnam War, she married a Muslim Tunisian economics professor, Faycal El Karoui.

"If you'd told the left-winger that I was then that I was going to end up working in finance, I'd never have believed it," Ms. El Karoui says.

France, the land of Descartes and Fermat, has a storied tradition in the study of math. Over the years, its engineering schools, including Ecole Polytechnique, a 212-year-old institution transformed by Napoleon into a military academy, have produced a steady stream of math students. Louis Bachelier's work in 1900 at the Sorbonne is considered the earliest effort to grasp how the markets work.

Ms. El Karoui first branched into finance in 1987. The government had just closed down the elite Ecole Normale Superieure in Paris, where she had been teaching. She took a six-month sabbatical to work in the research department of consumer credit bank Compagnie Bancaire.

At the time, many French mathematicians tended to deem the world of finance beneath them. "Finance meant selling your soul to the devil," she says. Her break with the French math establishment "took a lot of courage," says Marek Musiela, a leading figure in financial mathematics and the global head of fixed-income quant research at BNP Paribas.

At first, Ms. El Karoui felt out of her depth. "I didn't even know what a bond is. I took a dictionary to look up the financial words," she recalls.

But she soon realized that employees on the bank's newly formed derivatives desk were facing problems similar to those of stochastics scholars in trying to build models to predict the impact of interest- rate changes.

After her time at the bank, she took a post teaching at the Paris VI, officially known as the University of Pierre and Marie Curie. She and another academic, Helyette Geman, launched a postgraduate mathematical-finance course. Demand for know-how in derivatives was growing rapidly among banks at that time, sparked by the development of specialized exchanges that could trade derivative products, such as futures.

"I said 'That's beautiful mathematics and it's teachable as a theoretical course,' " Ms. El Karoui says.

Amine Belhadj, head of BNP Paribas's U.S. equity and derivatives department in New York, says Ms. El Karoui played a crucial role in finding interns when the bank began handling derivatives for clients in 1989. "There was nobody on the options desk with a mathematical- financial background," he says. "Having someone like Nicole who was making a specialty of it was pretty timely."

Today, four of her five children have pursued careers in math and sciences, two as academics and two still as students. In her spare time, Ms. El Karoui plays classical piano, with a preference for Brahms sonatas.

She earns about 80,000 euros, or about $95,000, a year as a professor, plus a smaller amount for consulting fees -- a fraction of what her students can make. She drives around Paris in a small Renault.

Lately, Ms. El Karoui has been vocal in warning students to use derivatives carefully. She says she is perturbed that an instrument that began primarily as a hedge for banks and financial firms against market risk is increasingly being used as a way to make a profit. Investors can profit, for example, by betting that the prices of stocks or bonds will increase. Ms. El Karoui worries that those looking for quick speculative gains could ramp up their bets on derivatives, but lose sight of the underlying financial instruments on which they're based, actually increasing their risk exposure.

"Some clients aren't mature enough to understand the risks of products that are too complex," she says. "It's better to do business with those people responsibly, either taking the time to teach them or selling them a less complex product."

Some big banks are being criticized for selling derivatives to institutions that may not understand the risks. Last year, for instance, Bank of America Corp. and Barclays PLC of the United Kingdom each agreed to settle claims that they had missold or mismanaged derivatives that were purchased by smaller banks in Italy and Germany. The banks said the matters were settled amicably.

One recent afternoon in her classroom, Ms. El Karoui ran through a series of dense formulas designed to price derivatives. In class were about 50 students studying for the DEA, or "Diplome d'Etudes Approfondies," as a French master's degree leading to a doctorate is known.

Ms. El Karoui talked softly toward the blackboard as much as she faced her students. There were few questions. Only near the end of the two-hour class did she raise a faint titter as she gestured to a full page of equations headed "General Pricing Formula." "There might be some of you brave enough to go through this," she said, then continued on, breezing through arcane jargon such as "smile risk," "volatility of volatility" and "Vega hedging."

To some, Ms. El Karoui has been almost too successful in placing her students in top international banks. Ryan Taylor, a headhunter specializing in quantitative-finance candidates at Napier Scott Executive Search Ltd. in London, says some investment bankers are now starting to question how many French-trained quants are in the field. "France has got what borders on a monopoly of quant candidate production and we'd love to hear from quants in other countries," he says.


Scott Patterson. Wall Street Journal. New York, N.Y.: Feb 23, 2009. pg. C.1

The financial engineers are at it again. Critics may complain that these math wizards started the trouble in the first place by designing securities that couldn't withstand the market's turbulence. But they also may have the expertise to help fix the problem.

"Airplanes fail, too," says Peter Cotton, founder of Julius Finance, a structured-finance firm in New York. "That doesn't mean you don't fix them."

Mr. Cotton is one of many such engineers trying to solve a seemingly intractable problem before the government: how to design a system for buying up assets shunted into a massive "bad bank." The government doesn't want to pay too much and banks don't want to sell for too little.

How big are these spreads? Last week, a triple-A student-loan auction-rate security was offered for 95 cents on the dollar by its owner. The highest bid: 50 cents.

For years, Mr. Cotton worked on Morgan Stanley's structured-finance desk, often designing collateralized-debt obligations, large pools of loans that are one of the prime culprits in the banking collapse. A longtime critic of credit models, he left Morgan in early 2007 to start his own company.

Mr. Cotton says the models most banks and ratings firms used to price CDOs were poorly designed. "They are superficial," he says, and "often spit out prices that don't capture the underlying value of the assets."

Using those same failed models now, says Mr. Cotton, most banks are "essentially just making up numbers."

At Julius, he has been designing new systems that dig deeper into the underlying loans of CDOs. The models use a variety of data points crucial to valuing these assets, such as the relationships between underlying slices of debt with different maturities in the assets.

For instance, a CDO containing many slices of corporate debt, or derivatives tied to that debt, can be priced by looking at where a large number of baskets containing these assets are trading and implying the behavior of the slices from these prices. The resulting CDO price closely matches similar assets changing hands on the open market. The model most banks use today is calibrated to a small subset of available data points.

Other financial engineers are working on new methods to price troubled assets. Richard Field, managing director of structured-finance firm TYI, has designed a system that provides real-time loan-performance data investors can consult to more accurately price the securities.

If investors can peer into the underlying loan-performance of their assets on a daily basis, they'll have a much better idea of their present value, Mr. Field argues. Now, investors usually have to rely on stale loan-performance data that's often updated on a monthly basis.

Getting a better idea of the value of these securities will also go a long way toward understanding the value of the institutions holding them. "Without real time transparency on which to base independent valuations, the market can't determine if the banks are adequately capitalized," says Mr. Field.

More broadly, financial engineers are struggling to reorient themselves to a world that shuns mathematical gizmos. It's a worthy goal. First, they need to focus on cleaning up the problems their gizmos left behind


Soros, George Wall Street Journal: Mar 24, 2009. pg. A.17

In all the uproar over AIG, the most important lesson has been ignored. AIG failed because it sold large amounts of credit default swaps (CDS) without properly offsetting or covering their positions. What we must take away from this is that CDS are toxic instruments whose use ought to be strictly regulated: Only those who own the underlying bonds ought to be allowed to buy them. Instituting this rule would tame a destructive force and cut the price of the swaps. It would also save the U.S. Treasury a lot of money by reducing the loss on AIG's outstanding positions without abrogating any contracts.

CDS came into existence as a way of providing insurance on bonds against default. Since they are tradable instruments, they became bear-market warrants for speculating on deteriorating conditions in a company or country. What makes them toxic is that such speculation can be self-validating.

Up until the crash of 2008, the prevailing view -- called the efficient market hypothesis -- was that the prices of financial instruments accurately reflect all the available information (i.e. the underlying reality). But this is not true. Financial markets don't deal with the current reality, but with the future -- a matter of anticipation, not knowledge. Thus, we must understand financial markets through a new paradigm which recognizes that they always provide a biased view of the future, and that the distortion of prices in financial markets may affect the underlying reality that those prices are supposed to reflect. (I call this feedback mechanism "reflexivity.")

With the help of this new paradigm, the poisonous nature of CDS can be demonstrated in a three-step argument. The first step is to acknowledge that being long and selling short in the stock market has an asymmetric risk/reward profile. Losing on a long position reduces one's risk exposure, while losing on a short position increases it. As a result, one can be more patient being long and wrong than being short and wrong. This asymmetry discourages short-selling.

The second step is to recognize that the CDS market offers a convenient way of shorting bonds, but the risk/reward asymmetry works in the opposite way. Going short on bonds by buying a CDS contract carries limited risk but almost unlimited profit potential. By contrast, selling CDS offers limited profits but practically unlimited risks. This asymmetry encourages speculating on the short side, which in turn exerts a downward pressure on the underlying bonds. The negative effect is reinforced by the fact that CDS are tradable and therefore tend to be priced as warrants, which can be sold at anytime, not as options, which would require an actual default to be cashed in. People buy them not because they expect an eventual default, but because they expect the CDS to appreciate in response to adverse developments.

AIG thought it was selling insurance on bonds, and as such, they considered CDS outrageously overpriced. In fact, it was selling bear-market warrants and it severely underestimated the risk.

The third step is to recognize reflexivity, which means that the mispricing of financial instruments can affect the fundamentals that market prices are supposed to reflect. Nowhere is this phenomenon more pronounced than in the case of financial institutions, whose ability to do business is so dependent on trust. A decline in their share and bond prices can increase their financing costs. That means that bear raids on financial institutions can be self-validating.

Taking these three considerations together, it's clear that AIG, Bear Stearns, Lehman Brothers and others were destroyed by bear raids in which the shorting of stocks and buying CDS mutually amplified and reinforced each other. The unlimited shorting of stocks was made possible by the abolition of the uptick rule, which would have hindered bear raids by allowing short selling only when prices were rising. The unlimited shorting of bonds was facilitated by the CDS market. The two made a lethal combination. And AIG failed to understand this.

Many argue now that CDS ought to be traded on regulated exchanges. I believe that they are toxic and should only be allowed to be used by those who own the bonds, not by others who want to speculate against countries or companies.

Under this rule -- which would require international agreement and federal legislation -- the buying pressure on CDS would greatly diminish, and all outstanding CDS would drop in price. As a collateral benefit, the U.S. Treasury would save a great deal of money on its exposure to AIG.


Surowiecki, James New Yorker; 11/12/2007, Vol. 83 Issue 35, p34-34, 1p

The havoc on Wall Street following the collapse of the subprime-mortgage market boils down to a simple truth: for years, lots of very smart people took lots of very foolish risks, betting borrowed billions on dubious mortgage derivatives, and eventually the odds caught up with them. But behind that simple truth is a more surprising one: the financial whizzes made bad decisions in part because that's what they were paid to do.

Not literally, of course. The way that hedge-fund managers and investment-bank C.E.O.s get paid is supposed to make them perform better for the investors they serve. Hedge-fund managers, for instance, typically are paid "2 and 20": they get two per cent of total assets as a management fee, and they keep twenty per cent of their investment gains (above some agreed-upon benchmark). Letting hedge-fund managers keep a chunk of their winnings gives them an incentive to do well for their clients: in theory, they get rich only if their clients do.

In practice, though, things don't always work that way. Fund managers get bonuses at the end of each year, and they keep those performance fees even if the fund eventually goes south. So if a billion-dollar hedge fund rises twenty per cent in its first year and falls twenty per cent in its second, its investors will have lost money, while the fund's manager might earn forty million dollars in performance fees. Hedge funds do have a rule that's meant to deal with this problem: when a fund loses money, it yields no performance bonus until investors get back to even. The catch is that nothing prevents a hedge-fund manager from simply shutting down after a bad year and walking away with the fees he's already accrued. Sometimes this happens out of necessity: the two subprime-focussed funds at Bear Stearns whose closure precipitated this summer's market mayhem had seen their assets annihilated. But sometimes it happens because a manager has no incentive to keep supervising a fund that won't generate a decent performance fee. In either case, the managers keep what they've earned and investors are left holding the bag. In short, a hedge-fund manager can do a lousy job and still become very wealthy.

Because fund managers reap large rewards on the upside without a correspondingly punitive downside, they have a much greater incentive to take big risks than ordinary investors do. Hedge funds generally leverage their bets with large amounts of borrowed cash - one Bear Stearns fund, for instance, borrowed ten times its capital - which makes it possible for them to turn small gains into enormous ones. Of course, leverage can also turn small losses into enormous ones. That helps explain why bad bets by hedge funds have been at the heart of the biggest financial-market meltdowns of the past decade.

A similar tendency to underplay risk is at work in parts of corporate America, thanks to the ubiquity of stock options. Options, which give executives the opportunity to buy company stock at a predetermined "strike price" within a certain period, seem like an ideal tool for insuring that a C.E.O. cares as much about the company's stock price as his shareholders do. The problem is that if a company's stock price is below the options' strike price when they expire those options become valueless - and they're just as valueless whether the stock price is a dollar below the strike price or fifteen dollars below it. To a shareholder, the difference between a stock that's at thirty dollars and a stock that's at twenty means a lot. But to a C.E.O. who has a pile of options with a strike price of thirty-one dollars, the difference means much less. As a result, that C.E.O. is likely to embrace projects that promise big rewards, even if they also entail a significant chance of failure.

Not surprisingly, a recent study of almost a thousand companies by the management professors W. Gerard Sanders and Donald Hambrick found that C.E.O.s whose compensation was made up mostly of stock options tended to "swing for the fences," making investments and acquisitions that were riskier than those made by other executives. As a result, the performance of the companies run by the risk-takers was far more volatile, and not for the good of the companies: the risky strategies were more likely to end in a big failure than a big gain. Generous options grants may also encourage fraud; the business professors Jared Harris and Philip Bromiley, who have made a study of hundreds of firms forced to restate earnings after accounting irregularities, found that companies that paid out most of their compensation in stock options were far more likely to end up restating earnings. And, as with hedge funds, the perverse effects of performance pay are exacerbated by the fact that big bonuses are often based on short-term performance. Stanley O'Neal, who was recently forced to resign as the C.E.O. of Merrill Lynch, made eighty-four million dollars in 2005 and 2006, a figure based in part on the huge profits that Merrill booked as a result of its forays into the subprime market. Last week, thanks to those same forays, Merrill announced giant losses and writedowns that obliterated most of those profits. O'Neal, however, won't be giving any money back.

One lesson of the current market chaos, then, is that it's hard to get incentives right. Investors, after all, want fund managers and corporate executives to take reasonable risks - that's the only way to make money - and many of them do just that. But, in trying to reward reasonable risks, we've encouraged unreasonable ones as well. And when you make it rational for people to bet the house, you may end up without a roof over your head.


Van Horne, James C., Financial Management and Policy, Prentice-Hall 1974.

In this [course], we assume that the objective of the firm is to maximize its value to its shareholders.  Value is represented by the market price of the company’s common stock which, in turn, is a reflection of the firm’s investment, financing, and dividend decisions.

Profit Maximization vs. Wealth Maximization

Frequently, maximization of profits is regarded as the proper objective of the firm, but it is not as inclusive a goal as that of maximizing shareholder wealth.  For one thing, total profits are not as important as earnings per share.  A firm could always raise total profits by issuing stock and using the proceeds to invest in Treasury bills.  Even maximization of earnings per share, however, is not a fully appropriate objective, partly because it does not specify the timing or duration of expected returns.  Is the investment project that will produce $100,000 return 5 years from now more valuable than the project that will produce annual returns of $15,000 in each of the next 5 years?  An answer to this question depends upon the time value of money to the firm and to investors at the margin.  Few existing stockholders would think favorably of a project that promised its first return in 100 years. We must take into account the time pattern of returns in our analysis.

Another shortcoming of the objective of maximizing earnings per share is that it does not consider the risk or uncertainty of the prospective earnings stream.  Some investment projects are far more risky than others.  As a result, the prospective stream of earnings per share would be more uncertain if these projects were undertaken.  In addition, a company will be more or less risky depending upon the amount of debt in relation to equity in its capital structure.  This risk is known as financial risk; and it, too, contributes to the uncertainty of the prospective stream of earnings per share.  Two companies may have the same expected future earnings per share, but if the earnings stream of one is subject to considerably more uncertainty than the earnings stream of the other, the market price per share of its stock may be less.

For the reasons above, an objective of maximizing earnings per share may not be the same as maximizing market price per share.  The market price of a firm’s stock represents the focal judgment of all market participants as to what the value is of the particular firm.  It takes into account present and prospective future earnings per share, the timing, duration, and risk of these earnings, and any other factors that bear upon the market price of stock. The market price serves as a performance index or report card of the firm’s progress; it indicates how well management is doing in behalf of its stockholders.

Management vs. Stockholders

In certain situations the objectives of management may differ from those of the firm's stockholders.  In a large corporation whose stock is widely held, stockholders exert very little control or influence over the operations of the company.  When the control of a company is separate from its ownership, management may not always act in the best interests of the stockholders [Agency Theory].  [Managers] sometimes are said to be "satisficers" rather than "maximizers"; they may be content to "play it safe" and seek an acceptable level of growth, being more concerned with perpetuating their own existence than with maximizing the value of the firm to its shareholders.  The most important goal to a management [team]of this sort may be its own survival.  As a result, it may be unwilling to take reasonable risks for fear of making a mistake, thereby becoming conspicuous to the outside suppliers of capital. In turn, these suppliers may pose a threat to management’s survival.

It is true that in order to survive over the long run, management may have to behave in a manner that is reasonably consistent with maximizing shareholder wealth.  Nevertheless, the goals of the two parties do not necessarily have to be the same.  Maximization of shareholder wealth, then, is an appropriate guide for how a firm should act.  When management does not act in a manner consistent with this objective, we must recognize this as a constraint and determine the opportunity cost.  This cost is measurable only if we determine what the outcome would have been had the firm attempted to maximize shareholder wealth.

A Normative Goal

Because the principal of maximization of shareholder wealth provides a rational guide for running a business and for the efficient allocation of resources in society, we use it as our assumed objective in considering how financial decisions should be made. The purpose of capital markets is to efficiently allocate savings in an economy from ultimate savers to ultimate users of funds who invest in real assets. If savings are to be channeled to the most promising investment opportunities, a rational economic criteria must exist that governs their flow. By and large, the allocation of savings in an economy occurs on the basis of expected return and risk. The market value of a firm’s stock embodies both of these factors. It therefore reflects the market’s tradeoff between risk and return. If decisions are made in keeping with the likely effect upon the market value of its stock, a firm will attract capital only when its investment opportunities justify the use of that capital in the overall economy.

Put another way, the equilibration process by which savings are allocated in an economy occurs on the basis of expected return and risk.  Holding risk constant, those economic units (business firms, households, financial institutions, or governments) willing to pay the highest yield are the ones entitled to the use of funds.  If rationality prevails, the economic units bidding the highest yields will be the ones with the most promising investment opportunities.  As a result, savings will tend to be allocated to the most efficient users.  Maximization of shareholder wealth then embodies the risk-return tradeoff of the market and is the focal point by which funds should be allocated within and among business firms.  Any other objective is likely to result in the suboptimal allocation of funds and therefore lead to less than optimal level of economic want satisfaction.

This is not to say that management should ignore the question of social responsibility.  As related to business firms, social responsibility concerns such things as protecting the consumer, paying fair wages to employees, maintaining fair hiring practices, supporting education, and becoming actively involved in environmental issues like clean air and water.  Many people feel that a firm has no choice but to act in socially responsible ways; they argue that shareholder wealth and, perhaps, the corporations vary existence depends upon its being socially responsible.  However, the criteria for social responsibility are not clearly defined, making formulation of a consistent objective function difficult.

Moreover, social responsibility creates certain problems for the firm.  One is that it falls unevenly on different corporations.  Another is that it sometimes conflicts with the objective of wealth maximization.  Certain social actions, from a long-range point of view, unmistakably are in the best interests of stockholders, and there is little question that they should be undertaken.  Other actions are less clear, and to engage in them may result in a decline of profits and in shareholder wealth in the long run.  From the standpoint of society, this decline may produce a conflict.  What is gained in having a socially desirable goal achieved may be offset in whole or part by an accompanying less efficient allocation of resources in society.  The latter will result in a less than optimal growth of the economy and a lower total level of economic want satisfaction.  In an era of unfilled wants and scarcity, the allocation process is extremely important.

Many people feel that management should not be called upon to resolve the conflict posed above. Rather, society, with its broad general perspective, should make the decisions necessary in this area.  Only society, acting through Congress and other representative governmental bodies, can judge the relative tradeoff between the achievement of a social goal and the sacrifice in the efficiency of apportioning resources that may accompany realization of the goal.  With these decisions made, corporations can engage in wealth maximization and thereby efficiently allocate resources, subject, of course, to certain governmental constraints.  Under such a system, corporations can be viewed as producing both private and social goods, and the maximization of shareholder wealth remains a viable corporate objective.

A Portfolio of Nobel Laureates: Markowitz, Miller and Sharpe

Varian, Hal. Journal of Economic Perspectives—Volume 7, Number 1—Winter 1993

Finance is one of the great success stories of quantitative economics. A recent ad in The Economist for a "mathematical economist" described an "excellent opportunity for numerate individual with background in capital markets." In today's market, numeracy pays.

But it was not always so. According to Robert Merton (1990):

“As recently as a generation ago, finance theory was still little more than a collection of anecdotes, rules of thumb, and manipulations of accounting data. The most sophisticated tool of analysis was discounted value and the central intellectual controversy centered on whether to use present value or internal rate of return to rank corporate investments. The subsequent evolution from this conceptual potpourri to a rigorous economic theory subjected to scientific empirical examination was, of course, the work of many, but most observers would agree that Arrow, Debreu, Lintner, Markowitz, Miller, Modigliani, Samuelson, Sharpe, and Tobin were the early pioneers in this transformation.”

Three of these pioneers of quantitative finance have now been justly honored: Harry Markowitz, Merton Miller and William Sharpe received the Nobel Prize in Economic Science in 1990.

From today's perspective it is hard to understand what finance was like before portfolio theory. Risk and return are such fundamental concepts of finance courses that it is hard to realize that these were once a novelty. But these esoteric theories of the last generation form the basic content of MBA courses today.

The history of the quantitative revolution in finance has recently been summarized in Bernstein (1992). Here I attempt to provide a very brief history of this enterprise, drawing upon the work of Bernstein and the accounts of the Nobel laureates in Markowitz (1991), Miller (1991) and Sharpe (1991). Readers interested in more detailed accounts of the development of modern financial theory should consult these works.

Harry Markowitz

Harry Markowitz was born in 1927 in Chicago. He attended the University of Chicago and majored in economics. He found the subject appealing enough to go on to graduate school and eventually arrived at the thesis stage. While waiting to see Jacob Marschak he struck up a conversation with a stockbroker who suggested that he might write a thesis about the stock market. Markowitz was excited by this idea and started to read in the area.

One of his first books was The Theory of Investment Value by John Burr Williams, (1938). Williams argued that the value of a stock should be the present value of its dividends—which was then a novel theory. Markowitz quickly recognized the problem with this theory: future dividends are not known for certain—they are random variables. This observation led Markowitz to make the natural extension of the Williams' theory: the value of a stock should be the expected present value of its dividend stream.

But if an investor wants to maximize the expected value of portfolio of stocks he owns, then it is obvious that he should buy only one stock—the one that has the highest expected return. To Markowitz, this was patently unrealistic. It was clear to him that investors must care not only about the expected return of their wealth, but also about the risk. He was then naturally led to examine the problem of finding the portfolio with the maximum expected return for a given level of risk.

The fact that investors should care about both the risk and the return of their investments is so commonplace today that it is hard to believe that this view was not appreciated in 1952. Even Keynes (1939) said, "To suppose that safety-first consists in having a small gamble in a large number of different [companies]... strikes me as a travesty of investment policy." Luckily, Keynes was not held in high repute in Chicago, even in those days, and Markowitz was not deterred from his investigations.

Markowitz posed the problem of minimizing the variance of a portfolio taking as a constraint a required expected return. This way of posing the problem contained two significant insights. First, Markowitz realized that the mathematics could not pick out a single optimal portfolio, but rather, could only identify a set of efficient portfolios—the set of portfolios that had the lowest possible risk for each possible expected return. Secondly, Markowitz recognized that the appropriate risk facing an investor was portfolio risk—how much his entire portfolio of risky assets would fluctuate.

Today, we pose the problem of portfolio selection as a quadratic programming problem. The choice variables are the fractions of wealth invested in each of the available risky assets, the quadratic objective function is the variance of return on the resulting portfolio, and the linear constraint is that the expected return of the portfolio achieve some target value. Variables may be subjected to nonnegativity constraints or not, depending on whether short sales are feasible.

The first-order conditions for this quadratic programming problem require that the marginal increase in variance from investing a bit more in a given asset should be proportional to the expected return of that asset. The key insight that arises from this first-order condition is that the marginal increase in variance depends on both the variance of a given asset's return plus the co-variance of the asset return with all other asset returns in the portfolio.

Markowitz's formulation of portfolio optimization leads quickly to the fundamental point that the riskiness of a stock should not be measured just by the variance of the stock, but also by the covariance. In fact, if a portfolio is highly diversified, so that the amount invested in any given asset is "small," and the returns on the stocks are highly correlated, then most of the marginal risk from increasing the fraction of a given asset in a portfolio is due to this covariance effect.

This was, perhaps, the central insight of Markowitz's contribution to finance. But it is far from the end of the story. As every graduate student knows, the first-order conditions are only the first step in solving an optimization problem. In 1952, linear programming was in its infancy and quadratic programming was not widely known. Nevertheless, Markowitz succeeded in developing practical methods to determine the "critical line" describing mean-variance efficient portfolios. The initial work in his thesis was described in two papers Markowitz (1952, 1956) and culminated in his classic book (Markowitz, 1959).

When Markowitz defended his dissertation at the University of Chicago, Milton Friedman gave him a hard time, arguing that portfolio theory was not a part of economics, and therefore that Markowitz should not receive a Ph.D. in economics. Markowitz (1991) says, "... this point I am now willing to concede: at the time I defended my dissertation, portfolio theory was not part of Economics. But now it is."

William Sharpe

Markowitz's model of portfolio selection focused only on the choice of risky assets. Tobin (1958), motivated by Keynes' theory of liquidity preference, extended the model to include. 3 riskless asset. In doing so, he discovered a surprising fact. The set of efficient risk-return combinations turned out to be a straight line!

The logic of Tobin's discovery can be seen with simple geometry. The hyperbola in Figure 1 depicts the combination of mean returns and standard deviation of returns that can be achieved by the various portfolios of risky assets. Each set of risky assets will generate some such hyperbola depicting the feasible combinations of risk and return.

The risk-free return has a standard deviation of zero, so it can be represented by a point on the vertical axis, (0, R0). Now make the following geometric construction: draw a line through the point (0, R0) and rotate it clockwise until it just touches the set of efficient portfolios.

Figure 1


Efficient portfolios of risky assets

Expected Return

Efficient portfolios with risky and risk-free assets

Standard Deviation

Call the point where it touches this line (am, Rm) Now observe that every efficient portfolio consisting of risky assets and the riskless asset can be achieved by combining only two portfolios—one portfolio consisting only of the risk free asset, and one consisting of the portfolio that yields the risk-return combination (crm, Rm~).

For example, if you want an expected return and standard deviation that is halfway between (0, R0) and (crm, Rm), just put half of your wealth in the risk-free asset and half in the risky portfolio. Points to the right of the risky portfolio can be achieved by leverage: borrow money at the rate R0 and invest it in the risky portfolio.

Tobin's discovery dramatically simplified portfolio selection: his analysis showed the same portfolio of risky assets is appropriate for everyone. All that varies is how much money you choose to put in risky assets and how much you choose to put in die riskless asset. Each investor can limit his investment choices to two "mutual funds:'' a money market fund that invests only in the riskless asset (e.g., Treasury bills) and another fund that invests only in the magical portfolio that yields (am, Rm~),

But one still needs to determine just which stocks, and which proportions of stocks, comprise the magic portfolio m—and that is a difficult and costly computation. The next contribution to portfolio theory was a simplified way to perform this computation. William Sharpe was a doctoral student at UCLA, one of the first students there to take courses in both economics and finance. When it came time to write a thesis, Fred Weston suggested that he talk with Harry Markowitz, who was then at RAND. Markowitz became Sharpe's unofficial diesis advisor and put him to work trying to simplify the computational aspects of portfolio theory.

Sharpe explored an approach -now known as the "market model" or the "single factor" model. It .assumes that the return on each security is linearly related to a single index, usually taken to be the return on some stock market index such as the S&P500. Thus the (random) return on asset a, at time t can be written as

where Rmt is the return on the S&P 500, say, and sat is an error term with expected value of zero. In this equation c is the expected return of the asset if the market is expected to have a zero return, while the parameter b measures the sensitivity of the asset to "market conditions." A stock that has b = 1 is just as risky as the market index: if the S&P index increases by 10 percent in a given year, we would expect this stock to increase by c + 10 percent. A stock that has b < 1 is less volatile than the market index, while one with b > 1 is more volatile. Sharpe's motivation in formulating this model was empirical: most stocks move together, most of the time. Hence, it is natural to think that a single factor (or small number of factors) determines most of the cross-sectional variation in returns.

This linear relationship can easily be estimated by ordinary least squares, and the estimated coefficients can be used to construct co-variances, which, in turn, can be used to construct optimal portfolios. Sharpe's approach reduced the dimensionality of the portfolio problem dramatically and made it much simpler to compute efficient portfolios. Problems that took 33 minutes of computer time using the Markowitz model took only 30 seconds with Sharpe's model. This work led to Sharpe (1963) and a Ph.D. thesis.

Later, while teaching at the University of Washington, Sharpe turned his attention to equilibrium theory in capital markets. Up until this point portfolio theory was a theory of individual behavior — how an individual might choose his investments given the set of available assets.

What would happen, Sharpe asked, if everyone behaved like Markowitz portfolio optimizers? Tobin had shown that everyone would hold the same portfolio of risky assets. If Mr. A had 5 percent of his stock market wealth invested in IBM, then Ms. B should invest 5 percent of her stock portfolio in IBM. Of course, they might have different amounts of money invested in the stock market, but each would choose the same portfolio of risky assets. But Sharpe then realized that if everyone held the same portfolio of risky assets, then it would be easy to measure that portfolio: you just need to look at the total wealth invested in IBM, say, and divide that by the total wealth in the stock market. The portfolio of risky assets that was optimal for each individual would just be the portfolio of risky assets held by the market.

This insight gave Sharpe an empirical proxy for the risky portfolio in the Tobin analysis: in equilibrium it would simply be the market portfolio.' This observation has the important implication that the market portfolio is mean-variance efficient — that is, it lies on the frontier of the efficient set, and therefore satisfies the first-order conditions for efficiency.

Some simple1 manipulations of those first-order conditions then yield the celebrated Capital Asset Pricing Model (CAPM):

In words, the expected return on any asset a is the risk-free rate plus the risk premium. The risk premium is the "beta" of the asset a times the expected excess return on the market portfolio.

The "beta" of an asset turns out to be the covariance of that asset's return with the market return divided by the variance of the market return. This is simply the theoretical regression coefficient between the return on asset a and the market return, a result remarkably consistent with the single-factor model proposed in Sharpe's thesis.

Meanwhile, back on the east coast, Jack Treynor and John Lintner were independently discovering the same fundamental pricing equation of the CAPM. Treynor's work was never published; Sharpe (1964) and Lintner (1965) remain the classical citations for the CAPM.

The Capital Asset Pricing Model was truly a revolutionary discovery for financial economics. It is a prime example of how to take a theory of individual optimizing behavior and aggregate it to determine equilibrium pricing relationships. Furthermore, since the demand for an asset inevitably depends on the prices of all assets, due to the nature of the portfolio optimization problem, it is inherently a general equilibrium theory.

Sharpe's two major contributions, the single factor model and the CAPM, are often confused. The first is a "supply side" model of how returns are generated; the second is a "demand side" model. The models can hold independently, or separately, and both are used in practice.

Subsequent research has relaxed many of the conditions of the original CAPM (like unlimited short sales) and provided some qualifications about the empirical observables of the model. Sharpe (1991) provides a brief review of these points. Despite these qualifications, the CAPM still reigns as one of the fundamental achievements of financial economics, taught in every finance textbook and intermediate microeconomics texts.2

'Sharpe's proof of the CAPM was given in a footnote.2 Or at least, the good ones.

Merton Miller

In 1990 Merton Miller was named a Distinguished Fellow of the American Economic Association in honor of his many contributions. He has worked on a variety of topics in economics and finance, but the idea singled out by the Nobel Committee was one of his early papers on corporate finance. Portfolio theory and the CAPM focus on the behavior of the demanders of securities—the individual investors. Corporate finance focuses on the suppliers of the securities—the corporations that issue stocks and bonds.

Merton Miller joined Carnegie, Tech in 1952 to teach economic history and public finance. In 1956, the dean Basked Miller to teach corporate finance in the business school. At first Miller wasn't interested, since finance was then viewed as being a bit too grubby for an economist to dabble in. But after appropriate inducements, Miller sat in on the corporate finance class in the fall and started to teach it the following term,

One of the major issues in corporate finance, then and now, was how to raise capital in the best way. Broadly speaking a firm can issue new equity or new debt to raise money. Each has its advantages and disadvantages: issuing debt increases the fixed costs of the firm, while issuing equity dilutes the shares of the existing shareholders. There were lots of rules of thumb about when to do one and when to do the other. Miller started to look at some data to see if he could determine how corporate financial structure affected firms' values.

He found, much to his surprise, that there was no particular relationship between financial structure and firm value. Some firms had a lot of debt; some had a lot of equity, but there didn't appear to be much of a pattern in terms of how the debt-equity ratio affected market value.

It has been seriously suggested that there should be a Journal of Negative Results which could contain reports of all those regressions with insignificant regression coefficients and abysmal R-squares. If such a journal had existed, Miller might well have published his findings there. But there was no such journal, so Miller had to think about why there might be no relationship between capital structure and firm value.

Franco Modigliani, whose office was next to Miller's, had been working on some of the same issues from the theoretical side. He was concerned with providing microeconomic foundations for Keynesian models of investment. Building on previous work .by Durand (1952), Modigliani had sketched out some models of financial structure that seemed to imply that there was no preferred capital structure. Miller and Modigliani joined forces, and the world of corporate finance has never been the same.

Miller and Modigliani considered a simple world without taxes or transactions costs and showed that in such a world, the value of a firm would be independent of its capital structure. Their argument was a novel application of the arbitrage principle, or the law of one price. Since the MM theorem has been described at least twice in this journal (Miller, 1988; Varian, 1987), I will give only a very brief outline of the theorem.

The easiest way to think about the MM theorem, in my view, is that it is a consequence of value additivity. Consider any portfolio of assets. Then value additivity says that the value of the portfolio must be the sum of the values of the assets that make it up. At first, this principal seems to contradict the insights of Markowitz about portfolio diversification: certainly an asset should be worth more combined in a portfolio with other assets than it is standing alone due to the benefits of diversification.

But the point is that asset values in a well-functioning securities market already reflect the value achievable by portfolio optimization. This is the chief insight of the Capital Asset Pricing Model: the equilibrium value of an asset depends on how it co-varies with other assets, not on its risk as a stand-alone investment.

In any event, the principal of value additivity is even more fundamental than the Capital Asset Pricing Model, since it rests solely on arbitrage considerations. If a slice of bread and a piece of ham were worth more together as a sandwich than separately, everyone would buy bread and ham and make sandwiches—for a free lunch! The excess demand for bread and ham would push up the price of each, restoring the equilibrium relationship that the value of the whole has to be the sum of the value of the parts.

From this observation, the MM theorem follows quickly. The value of the firm is defined to be the sum of the values of its debt and its equity. If the firm could increase its value by changing how much of its cash flow is paid to bondholders and how much to stockholders, any individual investor could construct a free lunch. The investor would buy a fraction / of the outstanding stocks and the same fraction / of the outstanding bonds, which would give him a fraction / of the total cash flow. He could then repackage this cash flow in the same way as the firm could, thereby increasing the value of the total portfolio—and violating value additivity.

This sort of "home-made leverage" argument is one way to prove the MM theorem. But it is a particularly powerful way since it doesn't appeal to a particular model of consumer or-firm behavior. It rests solely on the principle of arbitrage—there can be no free lunches in equilibrium.

The theory of the MM proposition is solidly established. The controversies all arise from the assumption of a frictionless world: in particular, no costs to bankruptcy, no asymmetric information, and no taxes. The latter is probably more important than the former. In the United States, at least, interest payments on debt are tax deductible while dividends to shareholders are taxed at both the corporate and individual level.

Since the MM proposition showed that debt and equity were perfect substitutes in the absence of taxes, the favorable tax treatment given to debt should imply that all firms are 100 percent debt-financed. This is contrary to fact—although for a while in the 1980s it looked as though it might come true. Miller (1988), and the comments on this article by Bhattacharya, Modigliani, Ross, and Stiglitz, describe the current state of research on the MM theorem. Suffice it to say that there is still doubt about exactly which frictions are the most relevant ones.

I happened to have lunch with Merton Miller in October 1990, the weekend before the Nobel prize winners were announced. Part of the lunchtime conversation was devoted to speculation about who might win the Nobel Prize in Economics that year. Mert thought that someone from Chicago might well receive the prize that year, and he suggested a few worthy possibilities—his own name not among them, of course. He was awarded the Nobel Prize two days later. His 1990 forecast was a bit like the MM theorem itself—it was right in principle, but the details were a little off!


In reviewing the work of these three economists, we see a common thread of theory and empiricism running through their research. It isn't enough just to formulate a theory of portfolio choice—you've got to find a feasible way to compute optimal portfolios as well. It isn't enough to formulate a theory of capital market equilibrium—the theory should be estimated and tested. It isn't enough just to look at a scatter plot of firm values and debt-equity ratios—w« need a theory for why there should or should not be a relationship among these variables.

Financial economics has been so successful because of this fruitful relationship between theory and data. Many of the same people who formulated the theories also collected and analyzed the data. This is a model that the rest of the economics profession would do well to emulate.


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