A Way to Select Outperforming Mutual Funds
Technology has made it possible for us to walk on the moon once again, yet academic research has failed to find a way to identify outperforming mutual funds. But a new study shows that may be possible.
An overwhelming body of academic research demonstrates that the past performance of actively managed mutual funds does not provide useful information as to future risk-adjusted performance, and (as the annual SPIVA Persistence Scorecards regularly report) there is less persistence of outperformance than randomly expected. Thus, while active management underperforms in aggregate, and the majority of active funds underperform every year (the percentage that underperform increases with the time horizon studied), if an investor were able to identify the few future winners by utilizing some metric, active management could be the winning strategy.
Given the potential rewards, it’s not surprising that numerous attempts have been made to find that holy grail – the metric that will identify future outperformers. Believers in active management were offered hope with the 2009 study by Martijn Cremers and Antti Petajisto, “How Active Is Your Fund Manager: A New Measure That Predicts Performance.” The authors concluded: “Active share (a measure of how much a fund’s holdings deviate from its benchmark index) predicts fund performance: funds with the highest active share significantly outperform their benchmarks, both before and after expenses, and they exhibit strong performance persistence.” Unfortunately, later research, including the 2016 studies “Deactivating Active Share” and “Estimating Time-Varying Factor Exposures,” the 2017 study “Defining Activeness: Active Share, Risk Share & Factor Share,” the 2021 study “Is Active Share Unattractive?,” and the 2022 studies “Fund Concentration: A Magnifier of Manager Skill” and “Active Share and the Predictability of the Performance of Separate Accounts,” all demonstrated that it is extremely difficult to make the case that active share – either as a standalone metric or in combination with other metrics such as past performance – has any predictive value in terms of future risk-adjusted outperformance of actively managed mutual funds.
The search goes on.
Academic studies of actively managed mutual funds tend to focus on risk-adjusted performance, not on risk alone. When risk is directly considered, it is typically measured as volatility or beta (a measure of risk/volatility relative to the risk of the overall market). However, volatility is not the only measure of risk used by practitioners. Another frequently used metric, maximum drawdown (a measure of the largest decline in a fund’s value from peak to trough), which focuses on downside risk, is simple to understand and is reported by Morningstar as part of their risk analysis.