Swedroe: Scale’s Effect On Active Performance

January 18, 2017

There is a large body of overwhelming evidence that past performance is at best a poor predictor of active managers’ future performance. That is why the SEC requires that common and familiar disclaimer.

There are many explanations for the difficulty that active managers face in delivering persistent outperformance. Among them is that there are well-documented diseconomies of scale in terms of trading costs (and problems associated with closet indexing for managers who seek to minimize trading costs), which sow the seeds of destruction for even successful active managers as their performance brings in new assets.

Campbell Harvey and Yan Liu contribute to the literature with their November 2016 study “Does Scale Impact Skill?” One of their contributions is that their model controlled for both the size of the individual fund (total assets under management) and the size of the overall fund industry. The authors note: “Intuitively, a $100 million fund in 1991 should be treated differently from a $100 million fund in 2011 given the mutual fund industry has grown substantially during this period.”

Their data sample covered domestic equity funds over the period 1991 through 2011. They required funds to have AUM above $10 million and more than 80% of their holdings in stocks. The authors’ sample covered 3,623 mutual funds. To determine a fund’s alpha, they used the Carhart four-factor (market beta, size, value and momentum) model.

The Impact Of Scale
Their first major finding was that, consistent with prior research, scale has a large impact at the individual fund level. They observe: “In particular, for an average fund in the cross-section that doubles its size in one year, its alpha drops by around 20bp per annum. The impact of scale is significant both statistically and economically.”

Importantly, they noted that there is a decreasing impact of scale as fund size increases. Thus, larger funds imply a milder response than smaller funds to changes in industry-level scale.

For example, they found that the impact for very small funds (i.e., the bottom 20% by fund size) is almost double the impact for very large funds (i.e., the top 20% by fund size). This is intuitive, as they explain. Small funds often trade illiquid stocks and, given the limited supply of small and illiquid stocks, it becomes more difficult to invest in such stocks. The result is a decline in alpha.

In contrast, for large funds, the impact is less. Even if they also grow by 100%, the market has a larger capacity for large and liquid stocks. As a result, large funds aren’t impacted as negatively by an increase in assets under management (unless they are trading in small-cap stocks).

This led Harvey and Liu to conclude that their findings lend considerable support to the model proposed by Jonathan Berk and Richard Green in their 2004 paper “Mutual Fund Flows and Performance in Rational Markets.”


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