Steve Lohr of the NYT reports that Wall Street’s Math Wizards Forgot a Few Variables:
In the aftermath of the great meltdown of 2008, Wall Street’s quants have been cast as the financial engineers of profit-driven innovation run amok. They, after all, invented the exotic securities that proved so troublesome.You have to hand it to the quants. Always looking to model the world by adding "more variables and more dimensions of uncertainty to predict waves of group behavior".
But the real failure, according to finance experts and economists, was in the quants’ mathematical models of risk that suggested the arcane stuff was safe.
The risk models proved myopic, they say, because they were too simple-minded. They focused mainly on figures like the expected returns and the default risk of financial instruments. What they didn’t sufficiently take into account was human behavior, specifically the potential for widespread panic. When lots of investors got too scared to buy or sell, markets seized up and the models failed.
That failure suggests new frontiers for financial engineering and risk management, including trying to model the mechanics of panic and the patterns of human behavior.
“What wasn’t recognized was the importance of a different species of risk — liquidity risk,” said Stephen Figlewski, a professor of finance at the Leonard N. Stern School of Business at New York University. “When trust in counterparties is lost, and markets freeze up so there are no prices,” he said, it “really showed how different the real world was from our models.”
In the future, experts say, models need to be opened up to accommodate more variables and more dimensions of uncertainty.
The drive to measure, model and perhaps even predict waves of group behavior is an emerging field of research that can be applied in fields well beyond finance.
Much of the early work has been done tracking online behavior. The Web provides researchers with vast data sets for tracking the spread of all manner of things — news stories, ideas, videos, music, slang and popular fads — through social networks. That research has potential applications in politics, public health, online advertising and Internet commerce. And it is being done by academics and researchers at Google, Microsoft, Yahoo and Facebook.
Financial markets, like online communities, are social networks. Researchers are looking at whether the mechanisms and models being developed to explore collective behavior on the Web can be applied to financial markets. A team of six economists, finance experts and computer scientists at Cornell was recently awarded a grant from the National Science Foundation to pursue that goal.
“The hope is to take this understanding of contagion and use it as a perspective on how rapid changes of behavior can spread through complex networks at work in financial markets,” explained Jon M. Kleinberg, a computer scientist and social network researcher at Cornell.
At the Massachusetts Institute of Technology, Andrew W. Lo, director of the Laboratory for Financial Engineering, is taking a different approach to incorporating human behavior into finance. His research focuses on applying insights from disciplines, including evolutionary biology and cognitive neuroscience, to create a new perspective on how financial markets work, which Mr. Lo calls “the adaptive-markets hypothesis.” It is a departure from the “efficient-market” theory, which asserts that financial markets always get asset prices right given the available information and that people always behave rationally.
Efficient-market theory, of course, has dominated finance and econometric modeling for decades, though it is being sharply questioned in the wake of the financial crisis. “It is not that efficient market theory is wrong, but it’s a very incomplete model,” Mr. Lo said.
Mr. Lo is confident that his adaptive-markets approach can help model and quantify liquidity crises in a way traditional models, with their narrow focus on expected returns and volatility, cannot. “We’re going to see three-dimensional financial modeling and eventually N-dimensional modeling,” he said.
J. Doyne Farmer, a former physicist at Los Alamos National Laboratory and a founder of a quantitative trading firm, finds the behavioral research intriguing but awfully ambitious, especially to build into usable models. Instead, Mr. Farmer, a professor at the interdisciplinary Sante Fe Institute, is doing research on models of markets, institutions and their complex interactions, applying a hybrid discipline called econophysics.
To explain, Mr. Farmer points to the huge buildup of the credit-default-swap market, to a peak of $60 trillion. And in 2006, the average leverage on mortgage securities increased to 16 to 1 (it is now 1.5 to 1). Put the two together, he said, and you have a serious problem.
“You don’t need a model of human psychology to see that there was a danger of impending disaster,” Mr. Farmer observed. “But economists have failed to make models that accurately model such phenomena and adequately address their couplings.”
When a bridge over a river collapses, the engineers who built the bridge have to take responsibility. But typically, critics call for improvement and smarter, better-trained engineers — not fewer of them. The same pattern seems to apply to financial engineers. At M.I.T., the Sloan School of Management is starting a one-year master’s in finance this fall because the field has become too complex to be adequately covered as part of a traditional M.B.A. program, and because of student demand. The new finance program, Mr. Lo noted, had 179 applicants for 25 places.
In the aftermath of the economic crisis, financial engineers, experts say, will probably shift more to risk management and econometric analysis and concentrate less on devising exotic new instruments. Still, the recent efforts by investment banks to create a trading market for “life settlements,” life insurance policies that the ill or elderly sell for cash, suggest that inventive sales people are browsing for new asset classes to securitize, bundle and trade.“Good or bad, moral or immoral, people are going to make markets and trade via computers, and this is a natural area of financial engineers,” says Emanuel Derman, a professor at Columbia University and a former Wall Street quant.
If this all sounds familiar that's because it's an old debate in social sciences that can be traced back to the Keynes Tinbergen debate. This is a classic debate which explores the problems of statistical inferences in modeling human behavior. I quote Keynes:
“the broad problem of the credit cycle is just about the worst case to select to which to apply the method, owing to its complexity, its variability, and the fact [that] there are such important influences which cannot be reduced to statistical form”Most of the problems Keynes raised were real and his warnings on the specific question of business cycle are still relevant today. Unfortunately, in the last fifty years, econometricians have done little to take the con out of econometrics. I quote Edward Leamer:
"The econometric art as it is practiced at the computer terminal involves fitting many, perhaps thousands, of statistical models. One or several that the researcher finds pleasing are selected for reporting purposes. This searching for a model is often well intentioned, but there can be no doubt that such a specification search invalidates the traditional theories of inference. The concepts of unbiasedness, consistency, efficiency, maximum-likelihood estimation, in fact, all the concepts of traditional theory, utterly lose their meaning by the time an applied researcher pulls from the bramble of computer output the one thorn of a model he likes best, the one he chooses to portray as a rose. The consuming public is hardly fooled by this chicanery."But the wizards of Wall Street remain undeterred. They will come up with new ways to model all risks, including systemic risk. Will the consuming public be fooled by their chicanery? I don't know about the consuming public, but I guarantee you that the pension parrots will be fooled by their chicanery.
This doctrinal thinking in finance is not limited to quants. One of the U.K. government’s panel of economic “wise men” under former British prime minister Tony Blair, Roger Bootle is critical of Alan Greenspan’s assertions during his tenure as U.S. Federal Reserve Chairman:
In order to help free markets back on their feet, central banks around the world need to take better account of economic bubbles before they burst, says Roger Bootle, managing director at Capital Economics.
"In my view the Greenspan doctrine is dead," the London-based economist said to a packed audience nestled into the British Columbia conference room at the Fairmont Royal York hotel in downtown Toronto.
One of the U.K. government's panel of economic "wise men" under former British prime minister Tony Blair, Mr. Bootle is critical of Alan Greenspan's assertions during his tenure as U.S. Federal Reserve chairman that bubbles are hard to recognize until they bust.
Mr. Greenspan argued that it was very difficult to discern whether an increase in asset prices was justified by economic fundamentals or the result of speculative activity and concluded that central banks should not try to target asset prices.
We should move towards a regime where bubbles are not tolerated as a key part of the main objective, Mr. Bootle said.
That means a more "variable" approach to inflation, with price stability to be the objective over the medium term. Instead of simply having inflation targets, he thinks more weight should be given to price-level targets to prevent major asset classes from inflating dramatically.
Too often ruled by greed above common sense in the decade leading up the financial crisis, Mr. Bootle says capitalism desperately needs to enter a new phase, where conscientious free markets are governed, not necessarily by more regulation, but better regulation.
"We should know now that greed is not good, and what's more, that the encouragement of it is downright stupid," he said. That's the lesson to be learned from these past few years, he said, but often we learn the wrong lesson. He remains worried that a massive wave of new regulation will render us ineffective in promoting long-term welfare.
Mr. Bootle listed several reasons for the failure of financial markets over the past two years, including inadequacy of capital and liquidity.
Until recently, he noted that some banks were lending out 40 times their capital, compared with just 20 times in the early 1990s and just six times at the beginning of the 20th century. The dramatic increase in bank leverage was exacerbated by inadequate knowledge and understanding by executives at the top of the global financial system and their inability to assess the excessive risks at hand.
Overseeing this was a regulatory system and monetary policy that failed on both fronts, largely due to its unwavering commitment to "efficient markets." In the case of Bernard Madoff, Mr. Bootle said the SEC was given countless indications of what was going on and chose to ignore them.
While the market can not be left alone entirely, Mr. Bootle thinks there are areas where the role of government needs to be reduced.
"In the U.K., there is a push to regulate and control everything," he said.
"What people don't seem to realize is that the aspect of the system that went badly wrong was in fact the most heavily regulated one. The banks were heavily regulated. They just happened to be incompetently regulated," he said. "So it is not obvious to me that the answer is to extend the thrust of regulation further, but make it better."
Mr. Bootle is right and he echoes the advice of George Soros. We do not need more regulation but better regulation. Quants can play a part in better regulating the system, but regulators also need to hire people who understand markets and can qualitatively assess the risks of the strategies and instruments being peddled. Believe it or not, quants do not hold a monopoly on wisdom.