Updated Tuesday, May 21, 2013 as of 4:31 AM ET
Goodbye, Old Theory
Thursday, September 1, 2011
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Since early this year, I've been arranging the sessions for my upcoming Business & Wealth Management Forum, coordinating presentations by industry heavyweights Bill Bengen, Harold Evensky, Don Phillips, Michael Kitces, Mark Tibergien and-well, you get the idea. The goal is to get all of these deep thinkers to go a little deeper than you typically see at these gatherings and explore topics you don't hear enough about. Along the way, I've found there's still a lot of unexplored terrain in our professional body of knowledge.

For instance? Investing, where modern portfolio theory is not very different in the way we apply it than it was when Dwight Eisenhower occupied the White House. How is that possible? Unlike Harry Markowitz when he was writing his seminal research, advisors today live in the Information Age. We know things Markowitz only suspected: that during normal markets, correlations among assets tend to move around unpredictably within a surprisingly tight spectrum of numbers, and then behave very differently whenever investors are paralyzed with fear or excited. Interestingly, the same is true about measures of investment volatility.

We also now know that there is a significant connection between current valuations and long-term future returns. As Roger Gibson (profiled on page 57) has shown, future performance has been much less exciting when we invest during a period when P/E ratios are high than when they are low. When people bravely invested during periods when the S&P 500's P/E10 (the normalized price/earnings ratio over the past 10 years) was below 12, their average annual return over the next 10 years was a princely 14.88%. Investors who put their money into the index when its P/E10 was more than 20 received an average of just 4.68% a year over the ensuing decade. The initial P/E ratio seems to be telling us a lot more about expected returns than the historical averages.

But how do we capitalize on this information? One of the conference presenters I've been talking to, Jerry Miccolis of Brinton Eaton Wealth Advisors, spent 25 years working at Towers Perrin before he moved into the financial services world. As a consultant to business managers, he routinely used the mathematics of something called enterprise risk management, which is the corporate management equivalent of modern portfolio theory. In fact, enterprise risk management was created from the work by Markowitz. Today, it's used by corporate managers and consultants to evaluate the real-world riskiness of "portfolios" of a company's divisions or product lines. But unlike modern portfolio theory, enterprise risk management has been evolving along with new computer systems and mathematical tools.

As an example, Miccolis says no corporate manager would measure risk as a single static measure in a dynamic marketplace. "In the corporate world," he says, "there is broad understanding that the degree of risk and the nature of the risks change as the marketplace changes. And when you look at investments, what do you find?" he asks rhetorically. "Exactly the same thing."

He was taken aback when told a single number normally describes the correlation of price movements between, say, large-cap U.S. stocks and emerging-market bonds. Why would modern portfolio theory inputs use single numbers for all the correlations when they clearly move around, and converge when markets do what they did in 2008? A corporate manager with enterprise risk management training is naturally curious about how the correlations between different product lines will change over time, and what market conditions have, in the past, caused which kinds of changes.

Miccolis is attempting to translate enterprise risk management mathematics into a more sophisticated version of modern portfolio theory and discovering that our investing world has developed a lot of strange taboos. "In the investment markets, we are learning that when volatility rises, it tends to stay high-what they call volatility clustering," he says. "If portfolios are entering a period of high volatility, one might respond by taking some risk off the table." In the enterprise risk management world, that is common sense. In the investment world, such behavior is labeled market timing.

Miccolis believes we can do a better job of forecasting expected equity and bond performance, and create modern portfolio theory models that use a spectrum of numbers rather than a single expected return. For our volatility and correlation inputs, we can use models instead of numbers, and the models would distinguish between normal markets and periods like the fall of 2008, when everybody is trying to unload their investments in a panic. The goal is to build sturdier portfolios, and also make constant adjustments, just the way a corporate manager or consultant would.


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