A better method for measuring alpha returns

ITHACA, N.Y. – Doppler radar, the Consumer Price Index, quarterback rating – these and many other measuring tools have refined the way performance is both documented and predicted in weather, the economy and sports.

Likewise, Cornell University researchers have developed a new method to better understanding mutual fund returns, which could impact both performance rankings and fund managers’ career trajectories.

Scott Stewart is a clinical professor of finance and accounting in Cornell’s Samuel Curtis Johnson Graduate School of Management. Along with three of his former students, Stewart has co-authored “Improving Equity Fund Alpha Estimates with a Second Size Factor,” which published in the Journal of Portfolio Management.

For 30 years, the gold standard for predicting mutual fund performance has been the Fama-French Model, developed by Nobel laureate Eugene Fama and researcher Kenneth French, which expanded on the capital asset pricing model by adding size and value risk factors to the previously used market risk factor.

However, Fama-French method only compares big versus small companies and doesn’t factor in mid-cap companies, valued between $2 billion and $10 billion and considered prime candidates for growth.

The Stewart group proposes that company size should be broken into two parts: big vs. mid-cap and mid-cap vs. small.

“Big, small and mid-size companies don’t move in lock step,” Stewart said. “This is especially important for understanding mutual fund returns – and manager outperformance, which is defined as ‘alpha.’”

While Fama-French is easy to implement, by breaking company size into two metrics, Stewart’s team was able to produce more finely tuned measurements.

The researchers conducted statistical tests on 1,000’s of active U.S. equity mutual funds, from 1984 through 2020. Funds had to exhibit no less than eight months of returns, represent asset sizes greater than $5 million and be in existence for no less than five years prior to the end of the sample period.

The researchers confirmed that this supplemental measure is superior to the standard Fama-French approach, resulting in significant improvement in more than 75% of fund analyses.

“It’s not just that it’s a better technique, but it actually has practical implications,” Stewart said. “If you’re a fund manager, it may move you from being below average to above average, or vice versa.”

For additional information, see this Cornell Chronicle story.

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