Tuesday, September 8, 2009

Economists Finally See The Light About Their Crappy Math

I am totally sorry that the text below is unformatted, but you can thank the WSJ for that. In order for me to report the full story, you would have to pay for a subscription so I grabbed it on my Blackberry for you.

Here is the gist. On January 22,2009 in an article entitled "Who Knows What Is Going To Happen To The Economy?" I questioned the math that all the idiots have used to predict financial futures. Here's the nugget: Nobel Prize winner Markowitz thirty years ago entirely absorbed the Gaussian curve...and that's what won him the (dubious) prize. Yet as I wrote on February 25, 2009, "Why I Hate Economists," I explained that their math was horrific and I pointed you to Mr. Mandelbrot's work which I have studied extensively.

Finally, on May 4, 2009 I displayed that Buffett and Munger had disdain for all this "high-order math." In another installment I will display my utter distaste for Mr. Buffett's achievements and intellectual capacity but that will have to wait. In the meantime, please read the junk that follows, courtesy of my Blackberry.


John A.

SEPTEMBER 8, 2009 Some Funds Stop Grading on the Curve Yahoo! Buzz By ELEANOR LAISE Last year, a typical investment portfolio of 60% stocks and 40% bonds lost roughly a fifth of its value. Standard portfolio-construction tools assume that will happen only once every 111 years. With once-in-a-century floods seemingly occurring every few years, financial-services firms ranging from J.P. Morgan Chase & Co. to MSCI Inc.'s MSCI Barra are concocting new ways to protect investors from such steep losses. The shift comes from increasing recognition that conventional assumptions about market behavior are off the mark, substantially underestimating risk. Mark Brewer Though mathematicians and many investors have long known market behavior isn't a pretty picture, standard portfolio construction assumes returns fall along a tidy, bell-curve-shaped distribution. With that approach, a 5% or 6% stock-market return would fall toward the fat middle of the curve, indicating it happens fairly often, while a 2008-type decline would fall near the skinny left tail, indicating its rarity. Recent history would suggest such meltdowns aren't so rare. In a little more than two decades, investors have been buffeted by the 1987 market crash, the implosion of hedge fund Long-Term Capital Management, the bursting of the tech-stock bubble and other crises. Investors using standard asset-allocation approaches have been hammered. Last year, all their supposedly diversified investments plummeted in unison. In short, the underlying assumptions failed. "We got blindsided by some developments that weren't accounted for by the models we were using," says Clark McKinley, a spokesman for the giant pension fund California Public Employees' Retirement System, or Calpers. As a result, the fund is looking at incorporating an extreme-events model into its risk-management approach. Many of Wall Street's new tools assume market returns fall along a "fat-tailed" distribution, where, say, last year's nearly 40% stock-market decline would be more common than previously thought. Fat-tailed distributions are nothing new. Mathematician Benoit Mandelbrot recognized their relevance to finance in the 1960s. But they were never widely used in portfolio-building tools, partly because the math was so unwieldy. Morningstar's Ibbotson Associates unit in recent months built fat-tailed assumptions into its Monte Carlo simulations, which estimate the odds of reaching retirement financial goals. More than nine million individual retirement-plan participants have access to Ibbotson's Monte Carlo tool. The new assumptions present a far different picture of risk. Consider the 60% stock, 40% bond portfolio that fell about 20% last year. Under the fat-tailed distribution now used in Ibbotson's tool, that should occur once every 40 years, not once every 111 years as assumed under a bell-curve-type distribution. (The last year as bad as 2008 was 1931.) Insulation from extreme market events doesn't come cheap. Allianz SE's Pacific Investment Management Co., or Pimco, which systematically hedges against extreme market events in several mutual funds launched last year, says the hedges may cost investors 0.5% to 1% of fund assets a year. Pimco uses a variety of derivatives and other strategies to hedge the funds. "You're spending some of your upside to buy the insurance" against catastrophic losses, says Vineer Bhansali, a Pimco managing director. Among the Pimco products applying the hedges are target-date funds, aimed at retirement savers. The firm plans to launch more funds that employ the approach in the next few years, Mr. Bhansali says. Another potential pitfall: Number-crunchers have a smaller supply of historical observations to construct models focused on rare events. "Data are intrinsically sparse," says Lisa Goldberg, executive director of analytic initiatives at MSCI Barra. Even so, the firm this year offered pension plans and other large clients a beta, or prerelease, version of its new risk-management model, which seeks to account for more extreme market events. The company plans to include the model in risk-management products to be released next year. As Wall Street relies on ever-more-complex mathematical models to manage money, a new breed of uber-wonks is gaining influence. Pimco's Mr. Bhansali, for example, holds a doctorate in theoretical particle physics from Harvard University and runs 50-mile to 100-mile super-marathons. And MSCI's Ms. Goldberg, an inventor of the firm's credit-risk and extreme-risk models, is also a professor at the University of California, Berkeley and has a penchant for the "beautiful mathematical subject" of extreme value statistics. The fat-tailed assumptions sometimes lead to quite conservative portfolios that cushion investors on the downside but also sharply curtail the upside. Smart Portfolios LLC last year launched the Aston Dynamic Allocation Fund, which uses fat-tailed distributions and other complex formulas to assume more-frequent occurrence of market shocks. In the 12 months ending Sept. 4, the fund is down 0.5%, compared with a 16% decline for the Standard & Poor's 500-stock index, thanks to hefty allocations to Treasurys and cash. But as markets have rallied in the past three months, it has risen only 4%, compared with 8% for the S&P. In times of upheaval, "we don't sit there and take it like a man. We run for the hills," says Bryce James, the firm's president. Many of the new tools also limit the role of conventional risk measures. Standard deviation, proposed as a risk measure by Nobel Prize-winning economist Harry Markowitz in the 1950s, can be used to gauge how much an investment's returns vary over time. But it is equally affected by upside and downside moves, whereas many investors fear losses much more than they value gains. And it doesn't fully gauge risk in a fat-tailed world. A newer measure that gained prominence in recent decades ignores potential gains and looks at downside risk. That measure, called "value at risk," might tell you that you have a 5% chance of losing 3% or more in a single day, but doesn't home in on the worst downside scenarios. To focus on extreme risk, many firms have begun using a measure called "conditional value at risk," which is the expected portfolio loss when value at risk has been breached. In other words, if value at risk says you have a 5% chance of losing 3% or more in a single day, but you have lost 4% before lunch, conditional value at risk helps estimate your expected loss on this very bad day. Firms such as J.P. Morgan and MSCI Barra are employing the measure. Pimco's Mr. Bhansali is unimpressed. Since it is so difficult to forecast extreme events, investors should focus on their potential consequences rather than the probability they will occur, Mr. Bhansali says. As for comprehensive measures of risk, he says, "they fail you in many cases when you need them the most." Write to Eleanor Laise at eleanor.laise@wsj.com

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