Close the Gap Between Complexity and Communication
About the Quantitative Rating: The Quantitative Rating consists of a series of seven individual models working in unison that were designed to provide a best approximation for the Analyst Rating on the global universe of open-end funds and ETFs. Visually, you can think of the estimation as a two-step process. First, we estimate the pillar ratings for each fund, and then we estimate the overall rating. To estimate the pillar ratings, we chose a machine-learning algorithm known as a "random forest" to fit a relationship between the fund’s pillar ratings and its attributes. After the pillar ratings are estimated, we needed to aggregate them into an overall fund rating. To do this, we apply the analyst ratings framework. The result is the Morningstar Quantitative Rating™ for funds.
MQR Analysis generates opinion-based text (not automated text)
We derive analyst-like opinions from data by assigning a pillar score and creating a thesis. Analysts then choose between mental modes that support their thesis.
The opinions of the MQR Analysis are that of the Morningstar Quantitative Rating model. MQR applies analyst-written content wherever possible. With MQR Analysis, the Morningstar Quantitative Rating system offers the same core elements as the Morningstar Analyst Rating, helping investors make sense of what’s driving our quantitatively-derived ratings.
Source: Morningstar Quantitative Rating Three-Year Event Study, Data as of Dec 31, 2020.
MQR is a good predictor of excess returns
In short, the Morningstar Quantitative Rating is very effective at predicting future overperformance (or underperformance). In a three-year event study, funds initially rated gold outperformed similar funds during a full market cycle. When MQR does not recommend a fund (negative or neutral), there is a high likelihood of underperforming.
The Morningstar Analyst Rating and The Morningstar Quantitative Rating have a proven track-record of effectively identifying managed investments that will outperform or underperform their peers.
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