The objective of asset allocation funds is to provide better than benchmark returns with (possibly) lower volatility through superior stock selection and/or successful market timing. The question for investors is: Are these funds likely to add value?
To answer this question, DK Malhotra and Elroi Hadad, authors of the study “Can Allocation Strategies Create Superior Alpha?” published in the June 2024 issue of Investment Journalevaluated the risk-adjusted performance of four types of US mutual funds that use asset allocation strategies – aggressive (typically 70%-90% equity allocation), moderate (50%-70% equity allocation), flexible ( 20%-80% capital allocation) and prudent (20%-50% capital allocation). They used a variety of asset pricing models, including the Fama-French three-factor model (beta, size, and value), the Carhart four-factor model (adding momentum), and the Fama-French five-factor model (beta, size, value, investment and profitability). They also compared the performance of mutual fund allocations against both the US stock market, represented by the Russell 3000 index, and global stock markets, represented by the FTSE All World Index. Using Morningstar's mutual fund database, they analyzed the performance of an equally weighted portfolio covering the period 2011-2021. Here is a summary of their key findings.
None of the allocation strategies outperformed the underlying US stock market index, either on a raw return basis or in terms of Sharp report (a measure of risk-adjusted performance). While each of the allocation strategies earned returns higher than the FTSE All-World Index, none produced a Sharpe ratio higher than the benchmark (and three of the four underperformed).
None of the allocation strategies produced statistically significant alpha as measured against the three-factor model, while the flexible and aggressive funds produced statistically significant negative monthly alphas (at the 5% confidence level) of -18bps and -16bps, respectively. The results were virtually identical when measured against the four- and five-factor models. Negative alphas suggest poor stock picking skills.
There was no evidence of successful market timing – mutual fund managers were unable to accurately predict future market movements to generate excess returns.
“Because the average monthly returns of these funds had a significantly high correlation with US and international stocks during the sample period (and this correlation increased significantly and reached near perfect positive levels (0.98) during the COVID-19 lockdowns) , the benefits of diversification were touted as a reason to invest in distribution mutual funds over standard mutual funds may not be realized.”
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Malhotra and Hadad's findings are consistent with previous research showing that active management, whether through stock selection, market timing or asset allocation strategies, is a losing game. While it is possible to win a loser's game (which is what keeps hope alive), the odds of doing so are so slim that it is imprudent to try. No one has invented a way to identify, in advance, a way to identify the small percentage of active managers who will outperform in the future. Many have tried, and even claimed success. However, out-of-sample studies have found this not to be the case. For example, Martijn Cremers and Antti Petajisto, authors of the 2009 study “How active is your fund manager: A new measure that predicts performance,” published in Review of Financial Studies, concluded: “Active Share predicts fund performance: funds with the highest active share significantly outperform their benchmarks, both before and after expenses, and they exhibit strong performance consistency.” Finding them gave hope.
Unfortunately, subsequent research has found problems with the conclusions drawn by Cremers and Petajisto. Using the same database they used, Andrea Frazzini, Jacques Friedman and Lukasz Pomorski reviewed the evidence and theoretical arguments for active participation as a predictor of performance and presented their findings and conclusions in the paper “Disable active sharing”, published in the March/April 2016 issue of Journal of Financial Analysts. The authors concluded that, controlling for benchmarks, equity has no predictive power for fund returns.
Providing even more dire evidence, Ananth Madhavan, Aleksander Sobczyk and Andrew Ang, authors of the 2016 study, “Estimating exposures to time-varying factors,” actually found that the asset share measure proposed by Cremers and Petajisto was negatively correlated (-0.75) with funding returns after controlling for factor loadings and other fund characteristics. Thus, they concluded that “it is not the case that managers with high beliefs perform better.”
And in their 2021 study “Unattractive separationMorningstar empirically showed that since 2011 investors in highly active equity funds in all Morningstar categories have paid higher fees, incurred greater risks and earned lower returns.
Thus, the key is to avoid active strategies that involve individual security selection and/or market timing.
Larry Swedroe is the author or co-author of 18 books on investing, including his latest, Enrich your future: the keys to a successful investment