The Morningstar Analyst Rating TM has done a good job in helping predict funds’ future risk-adjusted returns, with higher-rated funds generally outperforming lower-rated funds, according to a recent Morningstar study. That said, the study also identified areas where there’s opportunity to improve the way that analysts assign ratings.
Launched globally in November 2011, the Analyst Rating is a forward-looking assessment of a fund’s ability to outperform its peer group or a relevant benchmark over a market cycle, after accounting for risk and expenses. The Analyst Rating takes the form of Gold, Silver, Bronze, Neutral, or Negative, with Morningstar Medalist ratings reserved for funds the analysts have higher conviction in.
How we studied the Analyst Rating’s performance
We analyzed the returns of more than 4,500 unique open-end funds globally that were assigned Analyst Ratings between November 2011 and April 2017, including dead funds. (We tracked subsequent returns of rated funds through Oct. 31, 2017.) We evaluated rated funds’ performance using two techniques: a cross-sectional regression and an “event-study” framework. For more details on our analysis and findings, read the full research paper.
Our analysis shows that the Analyst Rating exhibited certain predictive abilities during our sample period, though the strength varied between asset class. Using the regression technique, we found the Analyst Rating was most predictive during the sample period among equity and allocation funds, where Gold-, Silver-, and Bronze-rated funds significantly outperformed Neutral-rated funds after accounting for expenses and common risk-factor exposures.
Our findings were similar under the event-study method: The average Gold-rated fund in the study produced 0.76% per year in alpha (versus a relevant category index) over a 60-month event horizon whereas the average Neutral- and Negative-rated fund in the study earned negative 0.04% and 0.22% of alpha per year, respectively. Taken as a whole, we found in the study that the Analyst Ratings effectively sorted funds based on their average future risk-adjusted returns
Opportunities we see to improve the Analyst Rating
One of the main reasons we conduct performance studies like these is to transparently assess how well our ratings have done and to help identify strengths and weaknesses that we believe we can build upon. In that spirit, it behooves us to reflect on where the opportunities are to improve.
First, we would like to improve our risk- un adjusted performance. For example, the average Silver- and Bronze-rated fund suffered negative excess returns versus the category index. We also need to better identify underperforming funds in advance, as the average Neutral- and Negative-rated funds achieved positive excess returns compared with the category average. The Analyst Rating’s performance strengthened once we accounted for risk, but we realize that some investors may define success as outperforming an index before risk.
Second, at times, we observed that Silver- and Bronze-rated funds did not perform much better than lower-rated funds, on average. To meet its objective, the Analyst Rating should predict differences in future performance, with high-rated funds outperforming low-rated funds monotonically. We need to determine ways to achieve better separation between ratings rungs.
Finally, while the Analyst Ratings of U.S. funds generally met its objective in sorting funds based on future risk-adjusted performance, this was less evident when measuring based on future excess returns, especially among stock and bond funds. To be sure, market conditions have been challenging for some types of active funds, and this in turn has likely weighed on ratings efficacy. But it’s important that we seek to achieve greater separation and slope across the rated universe.
Predictive Power
Despite these shortcomings, the findings are encouraging. It’s important to remember that the Analyst Rating has yet to perform through a full market cycle. But on balance, the rating appears to have met their objective in sorting funds based on future excess returns, though its predictive ability varied depending on the event horizon, asset class, or measurement technique used. The findings reveal areas of weakness, and those insights will help animate future efforts to continually innovate and improve the Analyst Rating.
You can also read about the information provided in the Morningstar Quantitative Rating.
This blog post is adapted from an article that originally appeared in the February/March 2018 issue of Morningstar magazine. Read the full article.
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