Ten years ago, an abrupt meltdown in quantitative equity funds worldwide shook the burgeoning industry, spurring an exodus of investors. Goldman Sachs Group Inc. was among the worst hit, shedding three-quarters of its $165 billion in quant investments by 2012. Gary Chropuvka, one of two partners leading the Quantitative Investment Strategies team at Goldman in New York, sweated those hot August days in 2007 that he says he’ll never forget. Rather than losing faith in quant investing, the group began to rebuild the strategies with less leverage and more diversity.
The phrase “it’s different this time” has a bad reputation in financial circles. It’s often the tag line for bullish investors who dismiss stock-market warning signals to their own detriment. Take the late 1990s, the critics will say. Many believed then that the internet would change the world. It did, sure. But the sector still had just as many losers as winners. Investors dismissed sky-high valuations—it really isdifferent this time, they said—only to see the market crash in 2000. The phrase, however, or at least its context, is misplaced, argues economist and author Andrew Lo. It is indeed different this time, he says—things are likely worse than history would belie.
By almost any measure, U.S. stocks are expensive—but this can remain the case for years to come because of an ever growing appetite for equities by retirement funds, according to economist and author Andrew Lo. Lo is a leading authority on behavioral finance, having provided some of the most definitive explanations for the financial crisis in 2007-08. After the crisis, Lo helped set up the new Office of Financial Research under the U.S. Treasury Department, which aims to provide better data and insights about the industry.
A longstanding academic theory for describing how markets work has finally died. Its impact on investment theory and practice was enormous, but has also led to some risks. The so-called efficient market hypothesis (EMH), which basically assumes that investors are rational and that it's impossible to beat the market because prices reflect all available information, has been under fire for years. And MIT's Andrew Lo, who Time Magazine named as one of the 100 most influential people in the world in 2012, finally put an end to it in his new book, “Adaptive Markets: Financial Evolution at the Speed of Thought.”
Ever since I was a graduate student in economics, I’ve been struggling with the uncomfortable observation that economic theories often don’t seem to work in practice. That goes for that most influential economic theory, the Efficient Markets Hypothesis, which holds that investors are rational decision makers and market prices fully reflect all available information, that is, the “wisdom of crowds.”
Build a better mousetrap, the saying goes, and the world will beat a path to your door. Find a way to beat the stockmarket and they will construct a high-speed railway. As investors try to achieve this goal, they draw on the work of academics. But in doing so, they are both changing the markets and the way academics understand them.
Bloomberg View columnist Barry Ritholtz interviews Andrew Lo, director of the Laboratory for Financial Engineering and the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management. Lo holds a bachelor’s degree in economics from Yale University and a doctorate in economics from Harvard University. This commentary aired on Bloomberg Radio.
Early in January in a Chicago hotel, Campbell Harvey gave a rip-snorting presidential address to the American Finance Association, the world’s leading society for research on financial economics. To get published in journals, he said, there’s a powerful temptation to torture the data until it confesses—that is, to conduct round after round of tests in search of a finding that can be claimed to be statistically significant. Said Harvey, a professor at Duke University’s Fuqua School of Business: “Unfortunately, our standard testing methods are often ill-equipped to answer the questions that we pose.” He exhorted the group: “We are not salespeople. We are scientists!”
It was a typical New York summer day, the kind where arriving at Goldman Sachs’ perfectly air-conditioned offices in downtown Manhattan was a blissful release from the humid weather outside. But for Gary Chropuvka it proved to be one of the worst days of his life. Mr Chropuvka worked at Goldman’s money management arm, specifically at Quantitative Investment Strategies, a division staffed by mathematicians, computer scientists and physicists. Even at Goldman, the QIS employees were considered intellectual superstars. Their prowess at decoding the signals of financial markets meant the unit managed $165bn at its peak — more than any hedge fund group. But on August 6 2007, everything unravelled. As soon as US markets started trading, the previously wildly successful automated investment algorithms coded by the QIS brainiacs went horribly awry, and losses mounted at a frightening pace.
Andrew W. Lo of the Massachusetts Institute of Technology was named winner of the top $2,500 prize in the Bernstein Fabozzi/Jacobs Levy Awards. Mr. Lo, a professor of finance at the Sloan School of Management and director of the MIT Laboratory for Financial Engineering, was honored for his article “What is an Index?”