Asked if hes offended when people trash his investment
ideas, Harry Markowitz chuckles like a kindly uncle. The
founder of Modern Portfolio Theory replies that hes 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
My business has been brisk in explaining why Modern
Portfolio Theory is still correct, he says.
At 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 Dont 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
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 whove been saying, Well, thats
obsolete. Were going to do something new and
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
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 Yorkbased J.P.
Morgan Asset Managements 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
Theres 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 theres no herd mentality at work.
Last year all of those assumptions probably got violated
at the same time, says Gellers colleague Rumi
Masih, head of J.P. Morgan Asset Managements strategic
investment advisory group.
Thats 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
theorys growing up. So says Lisa Goldberg, executive
director of analytic initiatives and talent at New
Yorkbased MSCI Barra, which provides indexes, risk models
and portfolio analytics to asset managers and other
This so-called failed theory has a lot of brilliant
elements as well as material that needs revision or
rethinking, argues the Berkeley, Californiabased
Goldberg. By no means should it all be
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 doesnt 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,
Sharpes 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 dont tend to line
up exactly, you can shrink that risk through
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, Connecticutbased Zebra Capital
Markowitz says investors should know where their beta puts
them on the efficient frontier. But he admits that MPT
doesnt 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 youre 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 Diegos Rady
School of Management, Markowitz is co-founder and chief
architect of GuidedChoice, a Los Gatos, Californiabased
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.