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Research by Russ Wermers
 Knowing
how the best mutual fund managers are choosing their portfolios
can be valuable information for investors, if stocks picked
by skilled fund managers really outperform those picked by unskilled
managers. But it has been difficult to test this hypothesis,
since it is not clear how to use fund holdings to pick stocks.
Russ Wermers, associate professor of finance, with co-authors
Tong Yao, University of Arizona, and Jane Zhao, PanAgora Asset
Management, developed a statistical model that predicts the
future performance of individual stocks based on how heavily
they are held or purchased by both successful and unsuccessful
fund managers.
Rather than just looking at the results of winning funds,
Wermers and his co-authors examined good, average and bad funds
to see what highly skilled—and thus very successful—fund managers
were buying in common, and what underperforming fund managers
were not buying. The model uses a weighted average alpha to
determine the outlook for a stock at the beginning of a given
year, consisting of the portfolio weight on a stock multiplied
by a manager’s past alpha, summed across all managers who held
that stock at the beginning of that month.
“You can’t just consider how many winning funds bought the
stock, you have to weight how much of it they purchased, and
you also have to put some weight on the skill of the manager,”
says Wermers. “We considered the performance of every fund manager
and use it as the main factor in the weighting of the outlook
for a stock.”
The result is a much more accurate prediction of stock returns
than any previous model, and significantly better returns result
even when adjusted for risk, beating previous methods by as
much as 6 percent to 8 percent per year.
“Even controlling for all the risk factors that are already
known in finance, this model seems to provide an independent
source for stock-picks,” says Wermers. “People have been poring
over stock returns for decades now, trying to find a new angle,
a new way to make money. We didn’t expect to find something
this big. Hedge funds in particular have shown interest in this
research because they need an independent source of stock returns,
above what is already known by the masses.”
The model uses three stock alpha estimators to extract information
about the future alphas of stocks from portfolio data for the
cross-section of mutual funds. The net returns and portfolio
holdings of actively managed U.S. domestic equity funds from
1980 to 2002 are used to show that that these three stock alpha
estimators consistently predict cross-sectional stock returns
over the following year. Wermers and his co-authors also developed
conditional stock alphas by taking into account stock characteristics
and fund characteristics, and found that these characteristics
helped to further improve the model. They found that smaller
and older funds, and funds with lower expense ratios, higher
turnover and higher industry concentration of portfolio holdings
were more likely to exhibit persistent skills.
Because mutual funds only disclose portfolio holdings information
on a quarterly basis, and because the funds have a 60-day grace
period to file their holdings with the SEC, investors interested
in using this model to predict stock returns are limited by
the time lag in receiving information about what mutual fund
managers are holding. Mutual fund disclosures are also staggered,
so it isn’t easy to obtain the information—for instance, some
funds report their holdings in December, while others report
in October. Wermers used a multitude of datasets to create the
holdings data and returns data used in the study.
Wermers is interested in using this technology to develop
stock signals for European and Asian stocks in the international
stock arena. “We think there is a lot of potential in non-U.S.
markets because those fund managers are more likely to have
inside information, which is perfectly legal in some of those
countries,” says Wermers. “We’re trying to find a source of
reliable fund holdings in order to examine this data.”
“The Investment Value of Mutual Fund Disclosure” won the
Best Paper award at the annual conference of Inquire-Europe,
an international consortium of investment companies dedicated
to bringing academic research into the public arena. For more
information about this research, contact
rwermers@rhsmith.umd.edu.
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