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Asked if he’s offended when people trash his investment ideas, Harry Markowitz chuckles like a kindly uncle. The founder of Modern Portfolio Theory replies that he’s in the videoconferencing business. From his San Diego office, he delivers lectures around the globe for $15,000 a pop. Markowitz lets audiences choose from a handful of nontechnical topics — among them, whether his influential blueprint for portfolio construction stopped working during the crash of 2008.

“My business has been brisk in explaining why Modern Portfolio Theory is still correct,” he says.

Harry MarkowitzAt 82, Markowitz is still dining out on the slim 1952 paper that changed finance forever — and won him a Nobel Memorial Prize in Economic Sciences. Written when Markowitz was a graduate student at the University of Chicago, this document contains a formula for building a diversified portfolio that delivers the best return for a certain amount of risk. A mathematical expression of the old adage “Don’t put all your eggs in one basket,” Modern Portfolio Theory, or MPT, is still widely used almost 60 years later because the logic behind it makes so much sense.

As Markowitz admits, though, MPT has taken plenty of knocks along the way: “For years — maybe almost from the beginning of [Modern] Portfolio Theory — there have been people who’ve been saying, ‘Well, that’s obsolete. We’re going to do something new and better.’”

This chorus has grown louder since 2008. According to critics, diversification offers little protection against markets plunging in lockstep. It may be the right thing to do in normal conditions, they say, but it fails exactly when you need it the most, during times of crisis.

Institutions ostensibly using MPT in 2008 got omelet on their faces. According to the Commonfund Institute of Wilton, Connecticut, and the Washington-based National Association of College and University Business Officers, U.S. college and university endowments lost, on average, 18.7 percent for the year ended June 30, 2009. Many of these funds followed the so-called Yale model of portfolio construction, which advocates diversification through significant exposure to alternative asset classes like hedge funds and private equity. When these illiquid investments stopped throwing off cash — alternatives plummeted, on average, 17.8 percent between July 2008 and June 2009 — endowments had trouble meeting their commitments.

In the end, this problem was more about liquidity than portfolio theory. Correlations head toward 1 in every bear market, says Jeffrey Geller, CIO of New York–based J.P. Morgan Asset Management’s U.S. global multiasset group. But three things combined to make 2008 a different animal: The credit markets all but froze, there was widespread deleveraging, and liquidity rapidly declined.

“People underestimated the risk they had in their portfolio vis-à-vis their demands and requirements for liquidity,” Geller says. “It was felt across all institutional portfolios, but perhaps most across endowments that typically hold larger allocations to alternatives.”

There’s no doubt that markets are far more complex and volatile than they were in 1952. In this changed world, which presents more challenges and more opportunities, MPT could use a makeover just to hold down a job. The recent meltdown was a powerful reminder to stop blindly obeying B-school axioms, including the models of Markowitz and his intellectual descendants. As sound as it may be academically, MPT is vulnerable to big market moves and ripe for misuse. In response, practitioners have built portfolio construction tools that they hope better reflect how markets actually behave. These efforts include fresh takes on optimization, a computer-assisted method of generating portfolios. They also involve making portfolios more resilient to turbulence by building in some recognition that the relationship between risk and return changes over time.

Like many theories, MPT makes a host of simplifying assumptions. One of them is that the market is perfectly liquid. MPT also assumes that there are no transaction costs, that investors can take a position of any size in any security they want and that there’s no herd mentality at work. “Last year all of those assumptions probably got violated at the same time,” says Geller’s colleague Rumi Masih, head of J.P. Morgan Asset Management’s strategic investment advisory group.

That’s reason to be more circumspect about MPT, but not to toss it aside like a quaint relic. With understanding of market dynamics still in its infancy, testing is part of the theory’s growing up. So says Lisa Goldberg, executive director of analytic initiatives and talent at New York–based MSCI Barra, which provides indexes, risk models and portfolio analytics to asset managers and other clients.

“This so-called failed theory has a lot of brilliant elements as well as material that needs revision or rethinking,” argues the Berkeley, California–based Goldberg. “By no means should it all be discarded.”

Much of the debate swirling around MPT concerns optimization. Traditionally, that has meant Markowitz mean-variance optimization, whereby investors generate the most efficient portfolio from a basket of assets. First, they use statistical methods to estimate expected returns, volatilities and covariances (that is, how the assets will move in relation to one another during a certain period).

All of this information gets plugged into a piece of software called an optimizer. The optimizer then sifts through every possible combination of assets and produces a graph showing a curve called an efficient frontier. Ranged along it are a series of optimal portfolios, from the lowest risk and return to the highest.

While the benefits of diversification are tough to dismiss, mean-variance optimization doesn’t stand up so well, for a couple of reasons. It can produce questionable portfolios, and it makes no allowance for fat tails — returns that fall far outside historical norms. Also known as “black swans,” these unexpected and dramatic price changes can ripple through the entire system, as they did in 2008.

For some practitioners, relying on MPT is simply too dangerous. Svetlozar (Zari) Rachev — chief scientist at FinAnalytica, a risk management and portfolio construction consulting firm based in New York, London and Sofia, Bulgaria — compares it to living beneath an avalanche-prone mountain. “The correlations that are embedded as the main assumption — the normality of returns — are telling you the chance of an avalanche affecting everybody in the village below is zero,” he says.

Also, according to Rachev, Markowitz never intended to create a universal model that works for any portfolio. “He did MPT for one type of problem: quiet markets, constant volatility, constant correlation,” Rachev says. “The world now is not such. We need different solutions.”

Then again, people should have known better than to apply MPT naively. In the lead-up to 2008, they took on too much risk, foolishly betting that the avalanche would never come. MPT “did not fail,” Markowitz says. “Some financial advisers, but certainly some people on the sell side, sold things without a proper analysis of how they affected the portfolio as a whole.”

Markowitz hangs his defense of MPT on the simplified version of the theory laid out in 1964 by longtime Stanford University finance professor William Sharpe, who at the time was teaching at the University of Washington (see timeline, page 68). Now known as the capital asset pricing model, or CAPM, Sharpe’s “one-factor” theory assumes that all assets in a portfolio share systematic, or market, risk. The source of beta returns, this common risk factor is impossible to diversify away. Each security, however, also has an unsystematic, or idiosyncratic, risk, which generates alpha. Because the returns on different assets don’t tend to line up exactly, you can shrink that risk through diversification.

But in a crisis, market risk swamps idiosyncratic risk. As a result, Markowitz explains, everyone moves downward — but not the same distance. Just like MPT says, the more beta you have, the farther you fall.

Besides, diversification actually worked in 2008. Roger Ibbotson, a finance professor at the Yale School of Management, notes that high-quality bonds were up while equity markets fell 40 percent overall. Although beta, or volatility, risks are the key drivers of stock returns, Ibbotson adds, the role of liquidity has often been ignored. “That liquidity component of what affects returns is every bit as important as the risk component,” says Ibbotson, who is also chairman and CIO of Milford, Connecticut–based Zebra Capital Management.

Markowitz says investors should know where their beta puts them on the efficient frontier. But he admits that MPT doesn’t make sophisticated assumptions about probability distributions — a big problem for highly leveraged investments that get marked to market daily. “There are ways of acting where you’re exposing yourself to model risk in a very major way,” says Markowitz.

The solution is to make estimates that reflect future uncertainty. In addition to being an adjunct professor of finance at the University of California, San Diego’s Rady School of Management, Markowitz is co-founder and chief architect of GuidedChoice, a Los Gatos, California–based 401(k) adviser. He says GuidedChoice favors volatility and return estimates that are, respectively, at least as high as and slightly lower than the historical average. This cautious outlook encourages clients to settle on a portfolio of, say, 60 percent stocks and 40 percent bonds, rather than leveraging highly on dubious assumptions.

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