From Research Affiliates:
Factors are becoming so numerous and exotic that John Cochrane referred to the collection as a zoo.1 While
the concept is entertaining, the proliferation of factors is deeply
troubling. The sheer number of factors suggests that it’s better to have
more factors than less, but how can investors determine how to use
factors in their equity portfolios? The options are endless,
particularly given the smart beta movement under way today. We believe
one cannot make intelligent choices regarding smart betas without first
understanding factors and their role in investment portfolios. Luckily
for investors, most so-called factors can be ignored.
Factor Proliferation
When
we were in the Ph.D. program at UCLA, we were taught the four-factor
model in our asset pricing class. The world was simple; there were the
market risk factor and the value, small-cap, and momentum return
factors.2 The three non-market factors carried juicy return premia that could be had by inve
stors willing to diversify into non-market exposures and exploit retail investors’ behavioral biases.
Fifteen
years later, we are shocked to learn that some quant shops now use an
81-factor model to build equity portfolios. This inflation in factors
has certainly made us feel inadequate and has potentially eroded the
real value of our paper diploma. Understandably, we are concerned with
the relentless onslaught of shiny, exciting, and sexy new factors
introduced by bright-eyed, bushy-tailed young financial engineers.3
Frankly,
we expected the number of “accepted” factors to decrease rather than
explode over time. We expected that at least one of the three documented
anomalies would be revealed as a fluke—a data artifact that would
disappear with better quality international data and with additional
decades of out-of-sample data following the original discovery.
Indeed, that is what we have seen. The small-cap anomaly has not been observed in the United States since the early 1980s and does not exist outside the U.S. dataset (Table 1).
This lack of “robustness” out-of-sample led Tyler Shumway and Vincent
Warther to re-examine the small-cap anomaly; they concluded that it was
likely driven by a mistake in how researchers treated missing data for
delisted stocks. Apparently, missing returns for delisted stocks in the
CRSP database created a systematic bias in the computed returns for
small stocks, which are more likely to face delisting. When this bias is
adjusted for, the small-cap anomaly is no longer observed (Shumway and
Warther, 1999).
Oddly,
the nullification of the small-cap anomaly has received scant notice.
At the same time, between academia and the investment industry, the
mining of new equity anomalies has yielded a great many new return
factors that offer exotic and diversifying premia. Today, quantitative
managers and smart beta solution providers peddle breathtaking Sharpe
ratios from back-tested equity portfolios, which optimally hold
uncorrelated “pure” factors. As providers rush to outdo each other, the
number of shiny new factors and the resulting portfolio Sharpe ratios
have both grown improbably large.
We
can completely understand the providers’ incentive to
“factor-proliferate.” Equally, we can sympathize with the investors’
desire to believe that there might really be 81 unique factors which can
be combined to provide an equity portfolio with a Sharpe ratio of 2. We
have seen this very same phenomenon in the “alpha” space. Managers,
consultants, and investors alike dream that lush dream of combining
diversifying alpha portfolios to create an equity core with an
information ratio of 2. For those of us who are skeptical of “alphas,”
this is our chance to dream that same dream in the smart beta space.
Except, of course, we get to invoke the arbitrage pricing theory (APT)
framework and throw around big words like multi-factors and
optimization, which gives our version an added air of intellectual rigor
and authority....MORE
HT: Barron's
Focus on Funds
