Wealth Manager

The idea wasn’t new in 2003, although—
due in part to the timing—Bernstein’s
counsel was provocative. The U.S. stock
market had just come through one of its
deepest and longest corrections in history.
Meanwhile, here was a high-profile, widely
respected financial analyst and historian
challenging what some—perhaps many—
considered conventional wisdom.
In fact, the choice of dynamic or static
asset allocation probably has not made
a huge difference one way or the other in
recent years. Midway through last year, all
the broad asset classes—equities, bonds,
commodities, REITs and most of their
subdivisions—were in the fifth year of an
extraordinary bull run that left almost
nothing behind. Fixed and active asset allocation
strategies alike had ample chance
to shine. So it goes when almost everything
is virtually flying, year after year.

No one will confuse the bull run between
2002 and 2007 with what has been
unfolding over the last 12 months or so.
Higher volatility and red ink are again harassing
investment strategies, elevating
the relevance of asset allocation along the
way. Although there’s always likely to be a
bull market somewhere, the expectation
of tidy gains in almost everything is probably
history. That raises the stakes for the
gritty work of picking asset class weights
and deciding when and how to adjust
those weights.

Bernstein’s five-year-old counsel may
face the acid test in the months and years
ahead—arguably for the first time since
his 2003 essay appeared. Why? The case for
a relatively active approach to asset allocation
looks timely for 2008 and beyond.
The reasoning boils down to a belief that
actively managed asset allocation is well
suited in a world of divergent and evolving
expectations for risk and return.

In fact, the conviction is supported by
a growing body of academic research that
has been piling up empirical evidence on
the side of dynamic strategies. A crucial
finding: Securities markets appear to be at
least partially predictable after all.

Professors Robert Shiller (Yale), Ken
French (University of Chicago) and scores
of others have documented what many
investors have known (or suspected) all
along: Markets go to extremes from time
to time. That’s another way of saying that
expected returns vary through time, which
inspires active asset allocation.

Yes, the S&P 500’s annualized return
is 10 percent over the past 80 years, but
even if that holds for the future, no one
should expect 10 percent year in and year
out, as the chart below reminds us.
Expected return rises and falls in
connection with changing prices
and valuations. And as academic studies
strongly suggest, when expected returns
are relatively high, the weight of the asset
class should also be relatively lofty, and
vice versa.

Sound familiar? The concept is at the
heart of Graham and Dodd’s Security Analysis,
the 1934 classic that formalized value
investing, or buying securities at a discount
to their estimated intrinsic value.
The book focuses on individual securities
rather than markets. But embedded in
the strategy is the belief that the relationship
between market price and intrinsic
value is forever in flux, which means that
expected return fluctuates, too. For those
who agree, the intellectual leap to active
asset allocation is only natural.

Academics are inclined to agree in the
21st century, but not without rethinking
certain aspects of modern portfolio theory
as some have used it in the past. Notably,
the intellectual evolution that now
favors active asset allocation conflicts
with the random walk theory (RWT), a
particular version of the efficient market
hypothesis (EMH).

RWT, which helped spawn the indexing
revolution, asserts that returns are 1) independent—
meaning that yesterday’s return
has no effect on today’s or tomorrow’s;
and 2) returns are “normally” distributed
over time, as per a gently sloping bell
curve. Assuming the two assertions accurately
describe market behavior provides
statistical aid and comfort for fixed-asset
allocation strategies premised on the idea
that expected return is fairly stable.

In fact, returns don’t strictly follow a
random walk. So-called “fat-tail” distributions
prevail, meaning that large price
changes occur in the real world with far
more frequency than a normal distribution
predicts. That has been clear since
at least Benoit Mandelbrot’s research in
the 1960s, and over time the literature has
only confirmed the point. The message is
periodically repeated, often to deaf ears.
Eugene Fama, who coined the term “efficient
markets,” recognized the case for
non-random distributions in his landmark
1965 paper that helped launch EMH. More
recently, financial scold Bill Jahnke argued
that a proper reading of finance literature
leads to the conclusion that “the policy
portfolio deserves to be buried” (The Investment
Think Tank, Bloomberg, 2004).

Indeed, the academic bibliography is
now flush with 20-plus years of empirical
studies showing that fundamental data
(dividend yields, interest rates, etc.) offers
a richer source for predicting returns than
what was thought possible via the early
conceptions of EMH that focused on price
alone. For example, one line of research
shows that returns are mean reverting
in the medium to longer term, which implies
predictability, and so asset allocation
weights should change. Such notions clash
with the random walk account of EMH.

A modest degree of return predictability
may be respectable in academic circles,
but debate still rages about the underlying
cause. One camp says irrational investors
drive valuations to extremes. A competing
view sees markets through the prism of an
updated EMH: Expected returns vary in order
to compensate for risk associated with the
business cycle—a recession beta, if you will.

Either way, the lesson is that some degree
of dynamic asset allocation is warranted in
a world where expected return cycles.

How can active asset allocation coexist
with notions of an efficient market? Economist
Paul Samuelson, one of the intellectual
fathers of EMH, has bridged the chasm
by observing that markets can be microefficient
and still be macroinefficient.

In fact, the seeds of active asset allocation
in the context of modern portfolio
theory were planted long ago. After all,
MPT’s founding document (Markowitz’s
1952 paper on optimal portfolios) allows
for asset classes—“aggregates,” as he
calls them—in portfolio construction.
Meanwhile, the Capital Asset Pricing
Model—the theoretical foundation for capitalization-
weighted indexing—assumes
shifting weights for assets, as per Mr. Market’s
incessant repricing. And in the 1970s,
some of the pioneers of the original index
funds—Bill Fouse, for one—took the original
but overlooked MPT ideas to heart and
developed so-called tactical asset allocation,
which eschews the principle of the
policy portfolio.

The chief inspiration for accepting
some form of dynamic asset allocation
is the market, suggests Bill Reichenstein,
CFA and professor of investments
at Baylor University. In a recent interview,
he discusses an example drawn
from the then-current market condition
of the S&P 500—off roughly 14 percent
from its high of last October. “From this
point forward,” Reichenstein explains,
“the risk premium that’s embedded in
stocks is higher than the risk premium
of a few months ago. There’s nothing inefficient
about that. That doesn’t mean
that the next three months are going to
deliver well above average returns. What
it means is that over the next five or 10
years, stocks will do a lot better than they
would have if you would have started out
three months ago.”

Market excess becomes conspicuous
from time to time, says William Bernstein,
author of The Four Pillars of Investing. That
was true in 1990, for example, when “a lot
of people saw all the BS in the Japanese
market,” which was trading at astonishing
nosebleed valuations, he recalls.

The past, of course, never fails to offer
trustworthy guidance about what you
should have done. Handicapping the future
in real time is the challenge. Yes, the
academics now counsel that returns are
somewhat predictable, but at best it’s still
only a partial solution because forecasting
still entails risk.

“The level of predictability [in equity returns]
tends to be 25 percent, 35 percent,”
says Reichenstein. That suggests that
asset allocation strategies should be only
partially dynamic—such as allowing for
shifts in equity weights within a modest
range without betting the farm on predictions,
he advises. Even then, adding value
to the portfolio assumes the strategist has
the talent to correctly read the market’s
signals and make portfolio adjustments at
opportune moments. Nonetheless, while
the academic literature shows that there
is opportunity for generating alpha with
dynamic asset allocation relative to a fixed
policy, there are no guarantees. Expected
returns vary, but that doesn’t mean everyone
will profit from the trend.

Perhaps, then, it’s no surprise to learn
that even advocates of dynamic asset allocation
recognize that the policy portfolio is
still useful—even if it’s theoretically inferior.
A fixed asset allocation can capture “a
big part” of the results generated by a more
active strategy, says Jim King, president and
chief investment officer of National Penn
Investors Trust Co., which manages money
for high-net-worth clients.

Bill Bernstein, too, says static asset allocation
“isn’t a bad idea,” although he
favors a dynamic approach for his client
portfolios. Active asset allocation demands
“industrial amounts of discipline,”
he reminds. Taking advantage of higher
expected returns and then pulling back
when the outlook is less alluring is inherently
a contrarian philosophy. “You have
to buy when everyone else is selling.”
Yes, mustering the discipline to buck
the crowd can reap big rewards. One has
only to consider Warren Buffett, Ben Graham
and George Soros for inspiration. But
such names tend to be the exceptions. Mediocrity
or worse is still the likely result in
money management generally. And that
leads us back to the bedrock principle
that was quantified all those years ago by
Markowitz and his intellectual heirs: Risk
and return are joined at the hip.

Some things remain the same no matter
what the academics say.