New research suggests that active fund investors are typically confusing “fake” alpha (i.e. outperformance that’s simply down to factor exposure) with “true” alpha (i.e. alpha produced through genuine skill).
It’s an expensive mistake to make, because passively managed factor funds are readily available at a fraction of the cost of traditional active funds.
The author of the study says investors’ failure to spot the difference between fake alpha and the real thing is costing them around $15 billion a year, as LARRY SWEDROE explains.
Jonathan Berk provided important insights into the issue of lack of persistence of performance of active managers even in the presence of skill.
In his 2005 paper The Five Myths of Active Portfolio Management, Berk suggested asking the following:
“Who gets money to manage? Since investors have access to databases that provide returns histories, and everyone wants to have their money managed by the best manager, money will flow to the best manager first.
“Eventually, the best manager will receive so much money that it will impact his ability to generate superior returns and his expected return will be driven down to the second best manager’s expected return.
“At that point investors will be indifferent to investing with either manager and 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 the benchmark expected return — the return investors can expect to receive by investing in a passive strategy of similar riskiness.
“At that point investors are indifferent between investing with active managers or just indexing and an equilibrium is achieved.”
Was Berk right?
Berk’s hypothesis is that the lack of return persistence is consistent with a model of rational investors competing for scarce skill and active funds subject to decreasing returns to scale. The hypothesis also predicts that managerial skill is matched with fund scale so that mutual funds earn zero expected alpha net of fees. However, this is hard to reconcile with the negative aggregate after-fee performance.
Yang Song contributes to the literature on the lack of persistence of performance of actively managed funds with his study The Mismatch Between Mutual Fund Scale and Skill, which was published in the October 2020 issue of The Journal of Finance. His fund sample is from the Center for Research in Security Prices (CRSP) survivorship-bias-free mutual fund database and covers the period 1984 to 2014.
Song began by noting that Berk’s hypothesis assumes that mutual fund investors are sophisticated in assessing fund manager skill. However, if they are not, certain funds would receive more assets than justified by their portfolio managers’ skill. The result would be that we would observe negative performance due to diminishing returns to scale. In other words, Berk’s equilibrium would not be achieved.
Song did find that skill and scale are significantly mismatched among actively managed equity mutual funds. The reason for the mismatch is that many naive mutual fund investors do not adjust for a fund’s exposure to common factors (such as size and value) when allocating capital among funds. The result is that actively managed funds with positive prior factor-related returns (FRRs) receive fund inflows, accumulating assets to the point that they significantly underperform appropriate risk-adjusted various benchmarks in the future.
To estimate a fund’s FRR, Song used the Fama-French-Carhart (FFC) four-factor (beta, size, value and momentum) model. In a test for robustness, the results were unchanged when augmenting the FFC model with the three industry factors of the model of Pástor and Stambaugh.
Song concluded: “In this sense, fund flows associated with FRRs are excessive and cannot be justified by managerial skill.”
He also demonstrated that “excess fund size, rather than total fund size, significantly predicts future performance. Controlling for fund size, mutual funds that have attracted flows through factor exposures significantly underperform benchmarks and other funds of the same size.”
Song also found the following:
— Funds that reach their current size because of positive prior FRRs significantly underperform various benchmarks and other funds despite having similar assets under management (AUM).
— Within each AUM quintile group, funds with top-tercile past FRRs underperformed bottom-tercile-FRR funds by around 300 to 400 basis points (bps) over the next year, depending on the benchmark.
— Across the five AUM quintiles, funds with top-tercile past FRRs had average negative future alphas of 230 to 250 bps per year. On the other hand, funds with middle-tercile FRRs had net alphas of about 20 bps, while funds with bottom-tercile FRRs had net average alphas of around 70 to 80 bps.
— The negative performance of active funds with positive prior FRRs is more significant among those funds that have higher trading costs — the return spreads between the low-trading-cost and high-trading-cost funds were about 180 bps per year and were significant at the 1% confidence level.
— Funds with high prior FRRs are positively exposed to styles that have experienced large aggregate mutual fund buying driven by uninformative fund flows.
— After controlling for the FFC factors, the top-third “crowded” styles observed abnormal returns of about 4% per year as non-fundamental price pressure dissipated eventually, while the one-third of styles with the most flow-induced selling observed significantly positive future alphas. This flow-driven style effect explained around 20% to 25% of the negative performance of funds with positive FRRs.
Investors confuse fake and true alpha
Song demonstrated that retail fund investors fail to distinguish between return components due to managerial skill, such as processing private information and discovering mispriced stocks, from components due to factor exposures. In other words, they over-invest in funds when they confuse a mutual fund’s “fake” alpha (exposure to common factors) with its “true” alpha.
The result is that investor behaviour leads to actively managed funds with positive prior FRRs accumulating so many assets that they have negative expected true alphas in the future. Sadly, many retail investors fail to recognise that these factor exposures can be obtained in lower-cost, more tax-efficient, passively managed funds (such as index funds and ETFs) that have fund construction rules that are systematic and transparent.
Song also showed how expensive a mistake this is. By not accounting for factor exposures, he calculated that investors lost around $15 billion per year on average over the sample period!
Song had one other interesting finding that merits discussion: funds with middle-tercile FRRs had net alphas of about 20 bps, while funds with bottom-tercile FRRs had net average alphas of around 70 to 80 bps.
The conclusion one might draw is that there appear to be active managers with sufficient skill to generate persistent alpha — as long as their AUM remains at low levels. The problem is that once their skill is uncovered, their success contains the seeds of their destruction, as cash flows will lead to diseconomies of scale.
Important Disclosure: The analysis in this article is for information and educational purposes only and should not be construed as specific investment, accounting, tax, or legal advice. By clicking on any of the links above, you acknowledge that they are solely for your convenience, and do not necessarily imply any affiliations, sponsorships, endorsements or representations whatsoever by us regarding third-party websites. We are not responsible for the content, availability or privacy policies of these sites, and shall not be responsible or liable for any information, opinions, advice, products or services available on or through them. The opinions expressed by featured authors are their own and may not accurately reflect those of the Buckingham Strategic Wealth®. R-20-1406
LARRY SWEDROE is Chief Research Officer at Buckingham Strategic Wealth and the author of numerous books on investing.
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