"What Marty is mathematically showing is that you get a more efficient portfolio by moving alpha to the core and beta as the swing asset," said Michael Litt, partner and portfolio strategist for FrontPoint Partners LLC, a Greenwich, Conn.-based absolute return manager.
"Barton Waring of BGI and Kurt Winkelmann of Goldman Sachs, Ray Dalio of Bridgewater and Cliff Asness of AQR have written extensively on asset-liability management and on the separation of alpha and beta (as have others). Marty Leibowitz ties these thoughts together in his own, unique mathematical framework, and I think the implications of all of these ideas are both profound and are indeed revolutionary," wrote Michael Rosen, principal at Angeles Investment Advisors LLC, Santa Monica, Calif., in an e-mail to Pensions & Investments.
Mr. Leibowitz has been developing his thinking in a series of research notes and papers over the past year. In an interview, he noted the proliferation of sub-asset classes.
"What I began to feel over the course of the year (is) you're losing a handle on what the risk profile is. You're seeing a proliferation of too much data and not enough information," Mr. Leibowitz said.
One of his critical findings: 90% or more of the volatility of U.S. institutional portfolios is tied to domestic equities, despite the growing array of allocations to different asset classes.
This embedded beta means that nearly all U.S. institutional investors have volatility in a narrow range of 9.5% to 11.5% of the size of the fund. And, despite widely varying asset mixes, pension funds' "structural betas" — what their betas, measured against U.S. equities, really are once the underlying betas are sniffed out — are not only higher than expected, but range in a narrow band of 0.55% to 0.65% (where 1% equals a 100% correlation).
"All of sudden, (you) put these numbers together, and they're pretty shocking," Mr. Leibowitz said.
Jason Hsu, director of research and investment management at Research Affiliates LLC, Pasadena, Calif., concurred, saying: "You really need to look at the asset exposures you have. The fact that you have moved out of a 60/40 (equity/bond mix) doesn't mean you have reduced your equity factor exposure by as much as you think you have."
Part of the problem is that investors "torture" the results from their optimizers, Mr. Leibowitz said. If unconstrained, traditional mean/variance optimizers would lead investors to very high allocations to alternative asset classes that are deemed to be efficient on a risk-adjusted basis. But few investors would be happy with a 100% allocation to venture capital, so they cap allocations to alternative asset classes.
Then he puts forward a truly heretical notion, from a Morgan Stanley note from Jan. 7. Mr. Leibowitz, one of the great quantitative investment thinkers, suggests putting aside the black-box optimizer and instead relying on intuition.
"The underlying philosophy here is that any set of market assumptions is inherently imprecise — at best! Therefore, it is far better to develop approximate guidelines than to become enmeshed in complex methodology that promises theoretically refined solutions, but obscures the role that should be played by intuition, judgment and common sense," he wrote.
Mr. Leibowitz proposes that instead of pouring buckets of data and assumptions into the black box, institutional investors should decide the maximum amount of assets they are willing to put into a new "alpha core," whose main benefit would be to enhance returns.
Investors could then decide how much they would allocate to different parts of the core. Those assets could include international equity, real estate, emerging market equity, private equity, venture capital and hedge funds, he wrote. Once assembled, the alpha core could be described in terms of its aggregate alpha return, an alpha volatility and a beta value.
The rest of the portfolio would be invested in swing assets of U.S. stocks, bonds and cash, depending on the levels of expected returns and volatility the investor desires.
Of course, there are limits on how much money can be invested in the alpha core. Limits include regulatory or organizational constraints, difficulty in finding suitable managers, high transaction costs, troubling fee structures, liquidity issues, peer-based standards, "headline risk" and inadequate performance data, Mr. Leibowitz wrote.