Search This Blog

Wednesday, November 26, 2008

Some Brilliant Words About Economists and their Forecasts

Blown off course by butterflies
By John Kay Financial Times

Published: November 26 2008 02:00 | Last updated: November 26 2008 02:00

In the 1980s, it seemed that computers held the key to economic forecasting. With large models and sufficient processing power, predictions would become more and more accurate.

This dream did not last long. We now understand that economies are complex, dynamic, non-linear systems in which small differences to initial conditions can make large differences to final outcomes - the proverbial flapping of a butterfly's wings that causes a hurricane.

So economic crystal ball-gazing remains unscientific. The trend is the forecaster's friend. Extrapolation assumes that the future will be like the past, only more so. We project current preoccupations - the rise of China and India, global terror, climate change - with exaggerated speed and to an exaggerated degree.

We forget that our preoccupations change. The people who worry about these issues today would 20 years ago have worried about the coming economic hegemony of Japan and the cold war. These issues were resolved in ways that few predicted.

It is a safe prediction - and the only one I shall make - that the topics that grab our attention 20 years from now will differ from those that consume us today and, if anyone has guessed what they are, it is only by accident. The future is unknowable. As Karl Popper observed, to predict the creation of the wheel is to invent it. To anticipate a new political force or economic theory, or even a new product, is to take the main step in bringing it into being.

If extrapolation is the forecaster's friend, mean reversion is the forecaster's crutch. Much of the time, you can predict that next year's figure will be somewhere between this year's level and the long-run average. But mean reversion never anticipates anything out of the ordinary. Every few years, out-of-the-ordinary things happen. They just have.
Still, you might think there would be large rewards for those who succeed in anticipating these events. You would be wrong. People who worried before 2000 that the "new economy" was a bubble, or warned of the terrorist threat before September 11 2001, or saw that credit expansion was out of control in 2006, were not popular. They were killjoys.

Nor were they popular after these events. If these people had been right, then others had been blind or negligent, and the latter preferred to represent themselves as victims of unforeseeable events. As John Maynard Keynes observed, it is usually better to be conventionally wrong than unconventionally right

Wednesday, November 5, 2008

More on the Failure of the Quants and Their Models

The NYT had a great article today on the perils of financial models and how their failures contributed to the current crisis. The lesson is also relevant to individual’s portfolios both in not relying on hedge fund “genius managers” that use quantitative models which purport to provide “free alpha” i.e. increased return with no increase in risk. And it should be a cautionary note even in constructing portfolios of more conventional assets even using index instruments. Past performance and correlations of asset classes is not a prediction of future performance.

In Modeling Risk, the Human Factor Was Left Out
Today’s economic turmoil, it seems, is an implicit indictment of the arcane field of financial engineering — a blend of mathematics, statistics and computing. Its practitioners devised not only the exotic, mortgage-backed securities that proved so troublesome, but also the mathematical models of risk that suggested these securities were safe.
What happened?
The models, according to finance experts and economists, did fail to keep pace with the explosive growth in complex securities, the resulting intricate web of risk and the dimensions of the danger.
But the larger failure, they say, was human — in how the risk models were applied, understood and managed. Some respected quantitative finance analysts, or quants, as financial engineers are known, had begun pointing to warning signs years ago. But while markets were booming, the incentives on Wall Street were to keep chasing profits by trading more and more sophisticated securities, piling on more debt and making larger and larger bets.
“Complexity, transparency, liquidity and leverage have all played a huge role in this crisis,” said Leslie Rahl, president of Capital Market Risk Advisors, a risk-management consulting firm. “And these are things that are not generally modeled as a quantifiable risk.”….
….The miss by Wall Street analysts shows how models can be precise out to several decimal places, and yet be totally off base. The analysts, according to the Fed paper, doggedly clung to the optimists’ mantra that nominal housing prices in the United States had not declined in decades — even though house prices did fall nationally, adjusted for inflation, in the 1970s, and there are many sizable regional declines over the years.
Besides, the formation of a housing bubble was well under way. Until 2003, prices moved in line with employment, incomes and migration patterns, but then they departed from the economic fundamentals.
The Wall Street models, said Paul S. Willen, an economist at the Federal Reserve in Boston, included a lot of wishful thinking about house prices. But, he added, it is also true that asset price trends are difficult to predict. “The price of an asset, like a house or a stock, reflects not only your beliefs about the future, but you’re also betting on other people’s beliefs,” he observed. “It’s these hierarchies of beliefs — these behavioral factors — that are so hard to model.”
Indeed, the behavioral uncertainty added to the escalating complexity of financial markets help explain the failure in risk management. The quantitative models typically have their origins in academia and often the physical sciences. In academia, the focus is on problems that can be solved, proved and published — not messy, intractable challenges. In science, the models derive from particle flows in a liquid or a gas, which conform to the neat, crisp laws of physics.

Not so in financial modeling. Emanuel Derman is a physicist who became a managing director at Goldman Sachs, a quant whose name is on a few financial models and author of “My Life as a Quant — Reflections on Physics and Finance” (Wiley, 2004). In a paper that will be published next year in a professional journal, Mr. Derman writes, “To confuse the model with the world is to embrace a future disaster driven by the belief that humans obey mathematical rules.”…..
….Among quants, some recognized the gathering storm. Mr. Lo, the director of M.I.T. Laboratory for Financial Engineering, co-wrote a paper that he presented in October 2004 at a National Bureau of Economic Research conference. The research paper warned of the rising systemic risk to financial markets and particularly focused on the potential liquidity, leverage and counterparty risk from hedge funds.
Over the next two years, Mr. Lo also made presentations to Federal Reserve officials in New York and Washington, and before the European Central Bank in Brussels. Among economists and academics, he said, the research was well received. “On the industry side, it was dismissed,” he recalled.
The dismissive response, Mr. Lo said, was not really surprising because Wall Street was going to chase profits in the good times. The path to sensible restraint, he said, will include not only better risk models, but also more regulation. Like others, Mr. Lo recommends higher capital requirements for banks and the use of exchanges or clearinghouses for the trade of exotic securities, so that prices and risks are more visible. Any hedge fund with more than $1 billion in assets, he added, should be compelled to report its holdings to regulators.
Financial regulation, Mr. Lo said, should be seen as similar to fire safety rules in building codes. The chances of any building burning down are slight, but ceiling sprinklers, fire extinguishers and fire escapes are mandated by law.
“We’ve learned the hard way that the consequences can be catastrophic, even if statistically improbable,” he said.

One of my favorite authors Nassim Taleb, has been a constant critic of such models….and has made outsized returns as of late, as the wsj reported(below). His earlier book Fooled by Randomness is more directly relevant to finance than The Black Swan.

• NOVEMBER 3, 2008
October Pain Was 'Black Swan' Gain

or most of October, it seemed nearly everything that could go wrong with the markets did. But the rout turned into a jackpot for author and investor Nassim Nicholas Taleb.
Mr. Taleb last year published "The Black Swan," a best-selling book about the impact of extreme events on the world and the financial markets. He also helped start a hedge fund, Universa Investments L.P., which bases many of its strategies on themes in the book, including how to reap big rewards in a sharp market downturn. Like October's.

Separate funds in Universa's so-called Black Swan Protection Protocol were up by a range of 65% to 115% in October, according to a person close to the fund. "We're discovering the fragility of the financial system," said Mr. Taleb, who says he expects market volatility to continue as more hedge funds run into trouble.
A professor of mathematical finance at New York University, Mr. Taleb believes investors often ignore the risk of extreme moves in the market, especially when times are good and volatility is low, as it was for several years leading up to the current turmoil. "Black swan" alludes to the belief, once widespread, that all swans are white -- a notion that was proven false when European explorers discovered black swans in Australia. A black-swan event is something that is highly unexpected…..
To execute its strategy, Universa buys far-out-of-the-money "put" options on stocks and stock indexes. These are bets that the market will see a sharp, sudden downturn. They become extremely valuable in a market decline of 20% or more in a one-month period.
When times are good, such options are cheap and Universa gobbles them up, taking small losses along the way. When the market makes a quick, steep turn south, as it has recently, Universa's positions gain value as investors scramble to protect themselves in the downturn by buying puts. The strategy, which keeps more than 90% of assets in cash or cash equivalents such as Treasury bonds, either breaks even or loses small amounts in most months while waiting for periodic, infrequent spikes in volatility…..
While the black-swan strategy has paid off handsomely this year, it hasn't always. Mr. Taleb's previous fund, Empirica Capital, which used similar tactics, shut down in 2004 after several years of lackluster returns amid a period of low volatility. The strategy may face another test after the current bout of market turmoil.
The task for the fund's managers is to persuade clients to stick around after their big gains. Historically, such dramatic downturns have been rare events, occurring only once or twice a decade.