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By Christine Benz | 10-18-2012 02:00 PM

Watch for These Hurdles When Investing in Alternatives

When buying into nontraditional assets, investors should monitor the risks of high correlations to equities, backward-looking data, and manager performance, says Vanguard's Fran Kinniry.

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Christine Benz: Hi. I'm Christine Benz for Morningstar.com. Ever since the bear market, investor interest in alternatives has increased dramatically. On a recent visit to Vanguard headquarters, I sat down with Fran Kinniry, a principal in Vanguard's investment strategy group, to discuss some recent research on the asset class.

Fran, thank you so much for being here.

Francis Kinniry: Thank you, Christine.

Benz: During the past decade or so investors have become much interested in adding nontraditional asset classes to their portfolios, and certainly some data support doing so. But you note that there are some practical hurdles to adding nontraditional asset classes. First, let's talk about the types of assets that people typically think of when they are thinking about that other portion of their portfolio.

Kinniry: Typically what we see as investors, the other part, would be beyond stocks, bonds and cash. They really come in two forms. One would be, what we would call betas, like different parts of the capital markets, and the other would be alpha, which would active managers either through hedge funds and private equity. They are very different, but that's what we've mostly seen, is trying to move out of the traditional asset classes of stocks, bonds, and cash and into some of these more exotic beta or alpha mandates. That's been a common theme, which I don't think is going to let up because of really the low-return environment.

Benz: Right. One thing that you found in analyzing some of these alternative asset classes is that oftentimes asset-allocation models are the most enthusiastic in their recommendations of alternative asset classes after they've already had a good performance runup.

Kinniry: Yeah, that's right. I mean with a traditional model portfolio, sometimes the more sophisticated you get, the more dangerous it can be. With the explosion in computing power and the speed at which computing power is, we can all go back to our desks and find a 20- or 30-year asset class that has outperformed on a risk-adjusted basis. And so, a lot of these model portfolios are formed through a technique known as mean variance optimization. You're trying to either increase the return with the same risk or lower the risk with the same return. The problem with all of that is, no matter how you do all of that, you're using backward-looking data.

So, you're using returns, risks, and correlations, and a lot of these asset classes may only have 10, 20, 30 years of history. And I want to remind everyone that we've been in one long super cycle of disinflation. So, we've had year-over-year lower interest rates and year-over-year lower inflation since 1977. So a lot of these models have not even seen different cycles. You'll see that no matter how you try to govern these, you're going to load on those asset classes that while looking great on a risk-adjusted basis they may be selling at some extreme valuations relative to their starting point.

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