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BAM Intelligence

Short-Term Performance and Mutual Fund Size

Javier Vidal-García, author of the June 2016 paper Short-Term Performance and Mutual Fund Size, contributes to the literature on mutual fund performance by examining the relationship between short-term mutual fund results and fund size around the world.

Using a large sample (more than 16,000 worldwide equity funds, from 35 countries, with the United States making up about 40% of the sample) that represents more than 90% of global market capitalization and covers the period from 1990 through 2015, he found that fund size shows a significantly negative coefficient (overall, the funds in the smallest quintile present better performance than funds in the largest one) using both net returns and Carhart four-factor alphas (beta, size, value, and momentum) as dependent variables.

His findings were both robust to various tests and statistically significant at the 5% level (and even the 1% level in most cases). The finding on diminishing returns to scale in the fund industry is consistent with both prior research and theory. Vidal-García concluded that his “study of mutual fund performance and fund size confirms the evidence that total net assets value influence fund performance.”

Let’s examine the theory behind the diseconomies of scale. Jonathan Berk, a professor at the University of California, Berkeley, in his “must-read” paper, Five Myths of Active Portfolio Management, suggested the following thought process: “Who gets money to manage? Well, as investors know who the skilled managers are, money will flow to the best manager first. Eventually, this manager will receive so much money that it will impact the manager’s ability to generate superior returns, and expected return will be driven down to the second-best manager’s expected return. At that point, investors will be indifferent between investing with either manager, so funds will flow to both managers until their expected returns are driven down to the third-best manager. This process will continue until the expected return of investing with any manager is driven down to the expected return investors can expect to receive by investing in a passive strategy of similar riskiness (the benchmark expected return). At this point, investors are indifferent between investing with active managers or just indexing, and an equilibrium is achieved.”

Berk went on to point out that the manager with the most skill ends up with the most money. He then added, “When capital is supplied competitively by investors but ability is scarce, only participants with the skill in short supply can earn economic rents. Investors who choose to invest with active managers cannot expect to receive positive excess returns on a risk-adjusted basis.” If they did, “there would be an excess supply of capital” to those managers.

This is an important insight. Just as the efficient markets hypothesis explains why investors cannot use publicly available information to beat the market (because all investors have access to that information and, therefore, it is already incorporated in prices), the same is true of active managers. Investors shouldn’t expect to outperform the market through the use of publicly available information to select active managers. Any excess return will go to the active manager (in the form of higher expenses).

As Berk explains, the process is simple. Investors observe benchmark-beating results and funds flow into the top performers. The investment inflow eliminates return persistence because fund managers face diminishing returns to scale.

Roger Edelen, Richard Evans, and Gregory Kadlec, who authored the 2007 study Scale Effects in Mutual Fund Performance: The Role of Trading Costs, provided evidence supporting the logic of Berk’s theory. They examined the role of trading costs as a source of diseconomies of scale for mutual funds. They studied the annual trading costs for 1,706 U.S. equity funds during the period from 1995 through 2005 and found:

  • Trading costs for mutual funds are, on average, even greater in magnitude than the expense ratio.
  • The variation in returns is related to fund trade size.
  • Annual trading costs bear a statistically significant negative relationship to performance.
  • Trading has an increasingly detrimental impact on performance as a fund’s relative trade size increases.
  • Trading fails to recover its costs—$1 in trading costs reduced fund assets by $0.41. However, while trading does not adversely impact performance at funds with a relatively small average trade size, trading costs decrease fund assets by roughly $0.80 for funds with a relatively large average trade size.
  • Flow-driven trades are shown to be significantly more costly than discretionary trades. This nondiscretionary trade motive partially—but not fully—explains the negative impact of trading on performance.
  • Relative trade size subsumes fund size in regressions of fund returns. Thus, trading costs are likely to be the primary source of diseconomies of scale for funds.

The authors concluded: “Our evidence directly establishes scale effects in trading as a source of diminishing returns to scale from active management.”

There is, however, another reason successful active management sows the seeds of its own destruction. As a fund’s assets grow, either trading costs will rise or the fund will have to diversify across additional securities to limit trading costs. The more a fund diversifies, the more it looks and performs like its benchmark index. It becomes what is known as a closet index fund. If it chooses this alternative, then the fund’s higher total costs have to be spread across a smaller amount of differentiated holdings, increasing the hurdle of outperformance.

The Bottom Line

The bottom line for investors? There’s a good reason for the SEC warning about using past performance as an indicator of future results. Even if you identify the skilled managers by observing good past performance, other investors are also making the same observation. Cash flows follow performance, sowing the seeds for the future likelihood of a lack of persistence in delivering alpha. By the time there is sufficient data to justify the belief in skilled management, it’s likely too late to act, as cash flows increase the hurdles to outperformance. Forewarned is forearmed.

This commentary originally appeared July 20 on MutualFunds.com

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The opinions expressed by featured authors are their own and may not accurately reflect those of the BAM ALLIANCE. This article is for general information only and is not intended to serve as specific financial, accounting or tax advice.

© 2016, The BAM ALLIANCE

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Chief Research Officer

Larry Swedroe is Chief Research Officer for the BAM ALLIANCE.

Previously, Larry was vice chairman of Prudential Home Mortgage. Larry holds an MBA in finance and investment from NYU, and a bachelor’s degree in finance from Baruch College.

To help inform investors about the evidence-based investing approach, he was among the first authors to publish a book that explained evidence-based investing in layman’s terms — The Only Guide to a Winning Investment Strategy You’ll Ever Need. He has authored 15 more books:

What Wall Street Doesn’t Want You to Know (2001)
Rational Investing in Irrational Times (2002)
The Successful Investor Today (2003)
Wise Investing Made Simple (2007)
Wise Investing Made Simpler (2010)
The Quest for Alpha (2011)
Think, Act and Invest Like Warren Buffett (2012)
The Incredible Shrinking Alpha (2015)
Your Complete Guide to Factor-Based Investing (2016)
Reducing the Risk of Black Swans (2018)
Your Complete Guide to a Successful & Secure Retirement (2019)

He also co-authored four books: The Only Guide to a Winning Bond Strategy You’ll Ever Need (2006), The Only Guide to Alternative Investments You’ll Ever Need (2008), The Only Guide You’ll Ever Need for the Right Financial Plan (2010) and Investment Mistakes Even Smart Investors Make and How to Avoid Them (2012). Larry also writes blogs for MutualFunds.com and Index Investor Corner on ETF.com.

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