Morningstar Ratings Research Articles

Fund Rating Model Based on Finite Normal Mixture Distribution

This paper proposes a new method of fund rating based on the cross-sectional distribution of fund performance measured by alpha. This distribution-based fund rating model is more flexible and provides more interesting results than current commercial fund rating method used by Morningstar. Unlike Morningstar's rating, this method does not use preset percentiles to rate funds. It is the distribution of alpha that dictates the number of performance groups in a given fund category and time period. The framework is based on the crucial assumption that the expected fund performance may be different, and the difference of the expected fund performance arises from the segmented market information and/or the differentiated ability of mangers to acquire and analyze information. The multimodal shape and formal normality tests prompt us to model the distribution of alpha by finite normal mixture model. We introduce the parametric bootstrap procedure to determine the number of performance groups in the model. We then employ expectation and maximization (EM) algorithm to estimate the model. Based on the estimated posterior probabilities of the fund, we assign the rating to funds. Our empirical results show that the number of performance groups is not fixed and varies across time and fund categories. We observe a clear tendency of the merging of information sets, which implies that the fund market has become gradually more efficient over time as information was well transmitted and analyzed.

The value of Morningstar ratings: evidence using stochastic data envelopment analysis

PurposeThis paper aims to contribute the existing finance literature by examining whether the ratings of Morningstar in Australia provide useful information for an investor by way of investigating the efficiency of domestic Australian equity funds that received a rating as at November 2005.Design/methodology/approachThis paper proposes the application of a simulation approach to stochastic data envelopment analysis (SDEA) based on Excel/@RISK, which was first proposed by Premachandra et al. in 1998. The analysis provides a variety of informative statistical information about the stochastic properties of the efficiency figure. Efficiency is measured by looking at fund performance, fund cost, fund risk exposure and manager ability over the period December 1990‐November 2005.FindingsThe introduction to portfolio performance evaluation of a new tool for evaluating fund performance (namely, the efficiency rating) is recommended. From a sample of Australian domestic equity managed funds we find that evidence exists to suggest that efficient funds are likely to receive an upgrade in rating in the medium to long term.Practical implicationsThe benefit of the present paper for investors and fund managers is the improved efficiency of managed funds in terms of expense and risk.Originality/valueThe present paper further contributes to the literature by reinforcing the importance of SDEA as a tool for measuring the efficiency of decision‐making units within investment fund markets.

How Much Does Size Erode Mutual Fund Performance? A Regression Discontinuity Approach

The level of diseconomies of scale in asset management has important implications for tests of manager skill and the expected level of performance persistence. To identify the causal impact of fund size on future returns, we exploit the fact that small differences in returns can cause discrete changes in Morningstar ratings that, in turn, generate discrete differences in size. Despite robust evidence that Morningstar ratings increase fund size, our regression discontinuity estimates yield little evidence that fund size erodes returns. Consequently, any downward bias in standard estimates of performance persistence due to diseconomies of scale is likely to be small.

From Rising Stars and Falling Angels: On the Relationship Between the Performance and Ratings of German Mutual Funds

The aim of this article is to analyze the relationship between a fund’s Morningstar rating and 1) its subsequent performance and 2) its rating and subsequent inflows or outflows of funds. The authors distinguish between actual and expected predictability as perceived by investors. This study is the first to analyze a prolonged investment period on the German market after Morningstar implemented essential changes in its rating methodology in 2002. The empirical findings suggest that the Morningstar rating has a limited ability to predict future fund quality for the German fund market and that the Sharpe ratio may be a better forecasting tool than the Morningstar rating, although neither is ultimately reliable. Furthermore, the fund flow performance relationship strongly depends on overall market movements. Highly rated funds suffered much greater outflows than lower-rated funds, especially during bear markets. An event study reveals, however, that investors do perceive rating changes as new information. German investors seem to react later than American investors, suggesting they are less influenced by Morningstar ratings in their allocation decisions. <b>TOPICS:</b>Mutual funds/passive investing/indexing, developed, information providers/credit ratings, performance measurement

Mutual Funds: Portfolio Structures, Analysis, Management, and Stewardship

Mutual Funds: Portfolio Structures, Analysis, Management, and Stewardship

The predictive power of fund ratings with a novel approach using uncertainty measures to analyzing risk

Using two approaches to panel data, Granger causality analysis with semi-asymptotic tests, and a structural approach based on entropies measured on sequences of multiperiod ratings and returns, we specify the relationship between a fund’s performance and both Morningstar and Europerformance ratings. We conclude on the Europerformance agency’s forecasting ability for the Luxembourg funds, and the Morningstar agency for the French funds. Indeed, we find two groups of funds depending on their domiciliation and appropriated rating. The results of this paper have implications for the management of fund portfolios, and the structural approach, more robust to our data, must be a first process for forecast models on the basis of similar funds, minor uncertainty or risk measure, and appropriated rating.

On the Role of Risk in the Morningstar Rating for Mutual Funds

In the mutual funds industry the rating process is very important, and Morningstar is surely the most influential international rating agency. In this work we consider the problem of evaluating if the risk component is adequately accounted for in the Morningstar rating. To face this problem we compare the ratings produced giving different weights to the risk component. The focus of the analysis is on testing the hypothesis that two similar rating procedures with different risk parameters (or, in statistical terms, two raters) are equivalent. To that end, first the notion of beta-equivalence is introduced and then a Monte Carlo test for the hypothesis of beta-equivalence is described. Finally, to answer the question on the role of risk in the Morningstar rating, we analyze 1763 monthly return time series of US mutual funds. Results show that the current Morningstar classification, based on a risk-adjusted measure, only marginally accounts for risk and that if we want that risk really matters, the risk parameter should be increased.

Selectivity, Market Timing and the Morningstar Star-Rating System

This paper evaluates the Morningstar mutual fund ranking system. We find that indeed higher Morningstar ratings are associated with higher returns on the portfolios including respectively five-, four-, three-, two- and one-star funds only (STAR5 to STAR1). We then perform an unconditional and conditional portfolio performance evaluation. In both cases the evidence suggests that the better performance of the STAR3, STAR4 and STAR5 categories reflects superior stock selection rather than market timing abilities. Overall, the implication for the Morningstar ranking system is that this is most effective in identifying the worst-performing funds (STAR1 or STAR2) rather than the best-performing ones.

Do Mutual Fund Media Recommendations Hold Value? An Empirical Analysis of the Wall Street Journal's SmartMoney Fund Screen

We examine the mutual funds that appeared in the Wall Street Journal’s SmartMoney Fund Screen column from September 2004 through July 2009. We find that the majority of funds listed do not have Morningstar’s highest five star rating. Regardless of Morningstar rating, the average prepublication performance of the funds is significantly higher than the benchmarks used to measure performance. Post publication, fund performance declines, and the decline is statistically significant across our performance measures. However, additional tests indicate that the SmartMoney funds which have a three or four star rating from Morningstar are better investment values than corresponding five star Morningstar funds with the same prospectus objective and expense ratio.

The effect of distribution channels on mutual fund flows

The Morningstar fund rating has been reported to affect mutual fund flows in the US markets. This paper finds that flow patterns in Finnish bank-managed funds are significantly different from the patterns in the US. Specifically, non-bank funds attract flows in a manner similar to the US markets, that is Morningstar ratings affect fund flows. In contrast, Finnish bank-managed funds do not exhibit the same relationship between star ratings and flows. The results suggest that in Finland, five-star Morningstar ratings are not regarded as highly as in the US, where good performance attracts significantly higher flows. More significantly, our findings demonstrate the importance of banks' distribution channels in the Finnish financial market.

Rating mutual funds: Construction and information content of an investor-cost based rating of Danish mutual funds

We develop a new rating of mutual funds: the atpRating. The atpRating assigns crowns to each individual mutual fund based upon the costs an investor pays when investing in the fund in relation to what it would cost to invest in the fund's peers. Within each investment category, the rating assigns five crowns to funds with the lowest costs and one crown to funds with the highest costs. We investigate the ability of the atpRating to predict the future performance of a fund. We find that an investor who has invested in the funds with the lowest costs within an investment category would have obtained a risk-adjusted excess return that is approximately 3–4 percentage points higher per annum than if the funds with the highest costs had been invested in. We compare the atpRating with the Morningstar Rating. We show that one reason why the atpRating and the Morningstar Rating contain different information is that the returns Morningstar uses as inputs when rating funds are highly volatile whereas the costs the atpRating uses as inputs when rating funds are highly persistent. In other words, a fund that has low costs one year will most likely also have low costs the following year, whereas the return of a fund in a certain year generally contains only little information about the future return that the fund will generate. Finally, we have information on the investments in different mutual funds made by a small subgroup of investors known to have been exposed to both the atpRating and the Morningstar Rating. We find that investors have clear preferences for funds rated high by both the atpRating and the Morningstar Rating.

Characteristics and Performance of U.S. Bond Funds in Index Investing

This abstract was created post-production by the JFI Editorial Board. A well-diversified portfolio should contain bonds. This study has identified all bond index funds and ETFs currently available as avenues to diversify portfolios. The authors of this study find the "almost" index funds identified by Ferri (2002) tum out to be gems: they have low expense ratios and the lowest turnover, while exhibiting mostly the lowest risk and highest riskadjusted returns. Pure index funds, with low expense ratios and turnover, have performed well in the past ten years based on Morningstar's ratings, but below average in the past three years. Enhanced index funds have the highest expense ratios, extremely high turnover, average or high risk and always the lowest risk-adjusted returns. As newcomers, bond ETFs have the lowest expense ratios and comparable returns, but they underperformed "almost" and pure index funds in the areas of turnover, risks and risk-adjusted returns.

Morningstar Mutual Fund Ratings Redux

We perform an extensive examination of how the new Morningstar rating system, introduced in June 2002, predicts future fund performance. Specifically, we examine all domestic equity funds that were rated by Morningstar as of June 30, 2002. We then examine the performance of these funds over the next three years, July 2002-June 2005. Using four different performance metrics, adjustments for loads, and three different methodologies for dealing with survivorship bias, we find widespread support for the notion that the new Morningstar rating system can predict future performance, at least within the first three years out-of-sample. Specifically, we find that higher rated funds, for the most part, significantly outperform lower rated funds. Moreover, the effect is relatively monotonic as even the next to lowest rated funds (2-star funds) significantly outperform the lowest rated funds (1-star funds). These results are quite different from those of Blake and Morey (2000) and Morey (2002b) which show that the older Morningstar rating system did not predict future performance well.

Ranking Properties of Morningstar Risk-Adjusted Ratings

A study of its ranking properties finds the Morningstar risk-adjusted ratings (RAR) for the decade ending 2001 and the excess return from a CAPM regression yield similar star ratings, but there are systematic differences between the RAR star ratings and the excess return estimated according to the Fama-French three-factor model. Over three-quarters of domestic equity funds with a ten-year five-star Morningstar rating do not keep their five stars under the null hypothesis of the Fama-French model. An explanation of this discrepancy provides support for the extensive modification of the Morningstar rating system made in July 2002.

Relative benchmark rating and persistence analysis: Evidence from Italian equity funds

The recent introduction into the Italian mutual fund market of Morningstar performance rating of private institutions gives rise to the question of what is the relation between this relative benchmark measure and the other traditional performance measures. This paper provides a comprehensive analysis of the relative benchmark performance measure (Morningstar rating) applied to Italian equity funds. It is found that this performance measure is highly correlated with the classical performance measures (Sharpe ratio, Sortino ratio and Treynor ratio) and poorly correlated with the customized benchmark measure (Information ratio). Furthermore, performing a persistence analysis, using non-parametric methods Cross-product Ratio and Chi-squared test, it is observed that only the Morningstar rating measure generates a strong degree of persistence. These results deviate from most European studies, which argue that Italian mutual funds display weak persistence.

Reading the Stars: Age Bias in Morningstar Ratings

Comparisons of Morningstar ratings may be affected by fund age and market conditions during the evaluation period.

The Ranking Properties of the Morningstar Risk-Adjusted Rating

The study examines the ranking properties of the Morningstar risk-adjusted rating (RAR). We find that the RAR and the excess return from the CAPM regression yield similar star ratings. In contrast, we document systematic differences between the star ratings produced by the RAR and the excess return estimated from the Fama-French [1993] three factor model. Approximately 77% of domestic equity funds with a ten-year five-star Morningstar rating do not maintain their five stars under the null hypothesis of the Fama-French three factor model. The study concludes that the sole reliance upon the Morningstar star rating to select U.S. equity funds may not result in an optimal allocation across style categories for a multi-fund portfolio.

Mutual Fund Age and Morningstar Ratings

The study reported here identified an age bias in the Morningstar mutual fund ratings. I found that the average overall star ratings of seasoned funds are consistently—and in many cases, significantly—higher than the average overall star ratings of younger funds. This bias is not the result of a survivorship bias but of the methodology Morningstar uses to calculate the ratings. If star ratings affect fund flows, then this age bias in the Morningstar ratings is of significance to the mutual fund industry and to investors.

Improve Your Morningstar Rating Using Options

The author demonstrates that equity mutual fund managers can be confident of improving their Morningstar ratings by overwriting call options on portions of their portfolios. A look at the Morningstar rating system in detail helps us understand why this kind of enhancement is possible.

Star Power: The Effect of Morningstar Ratings on Mutual Fund Flows

We apply an event-study methodology on over 10,000 Morningstar star rating changes and find that Morningstar has substantial independent influence on the investment allocation decisions of retail mutual fund investors. It is the discrete change in the star rating itself, and not the change in the underlying performance measures that drives flow. We document economically and statistically significant positive abnormal flow following rating upgrades, and negative abnormal flow following rating downgrades. In contrast to the cross-sectional flow-performance literature, we find evidence of investor punishment of performance declines, some of which is evident immediately in the month of the rating change.