Methodology Documents

This paper lists the various categories into which we sort Europe and Asian investments.

The Morningstar Manager Benchmarks contain three distinct series of benchmarks based on key peer grouping factors such as Morningstar Institutional Category, equity style, investment strategy, and market capitalization. Each series has a unique set of construction rules to determine constituency, so that peer grouping is a precise combination of Morningstar Institutional Category and fund attribute data.

This paper outlines our method of calculating the Fixed-Income Ownership Zone, which is where the duration range and the credit quality range intersect in the Morningstar Style Box.

Morningstar® Investor Return™ (also known as dollar-weighted return) measures how the average investor fared in a fund over a period of time. Investor return incorporates the impact of cash inflows and outflows from purchases and sales and the growth in fund assets.

It is well known that the normal distribution model fails to describe the fat tails of markets. The Lévy stable distribution model, meanwhile, has fat tails but leads to an infinite variance, thus complicating risk estimation. This study introduces truncated Lévy flight (TLF) — a better distribution model that has fat tails, finite variance, and more importantly, scaling properties. The paper uses TLF to estimate the downside risk of a variety of asset classes.

This article explains why the air is coming out of the argument that fundamental indexing is a revolutionary innovation.

The importance of asset allocation has been the subject of considerable debate and misunderstanding. What seems like an easy question or topic on the surface is actually quite complicated and filled with nuance. In an article written by Thomas Idzorek, James Xiong, Roger Ibbotson, and Peng Chen, “The Equal Importance of Asset Allocation and Active Management” for the Financial Analysts Journal, they pinpoint one of the primary sources of confusion surrounding the importance of asset allocation. This article presents that paper's key insights.

The 2011 Industry Survey updates much of the data from the 2010 edition while providing new features on asset allocation, performance attribution, and portfolio composition — particularly among retirement-income funds, the terminal funds in many target-date series.

This paper provides a brief summary on the importance of asset allocation, while noting that nowhere near 90 percent of the variation in returns is caused by the specific asset allocation mix. It highlights that most time-series variation comes from general market movement, with active management having about the same impact on performance as a fund’s specific asset allocation policy.

What is the relative importance of asset allocation policy versus active portfolio management in explaining variability in performance? This paper shows that, with market movements removed, asset allocation and active management assume equal importance in determining portfolio return differences within a peer group. It also examines period-by-period cross-sectional results to reveal why researchers using the same regression technique can get widely different results.

A model called the Truncated Lévy Flight builds on Benoit Mandelbrot’s stable hypothesis to accurately capture the market’s fat tails.

We investigate the impact of mean-conditional value-at-risk (M-CVaR) optimizations that take into account fat tails and skewness on optimal asset allocation. In a series of controlled optimizations, we compare optimal asset allocation weights obtained from the traditional mean-variance optimizations with those from M-CVaR. The study provides useful insights for designing optimal asset allocation mixes when investor preferences go beyond mean and variance.

This paper studies a variety of asset allocation issues associated with deferred variable annuities with guaranteed minimum withdrawal benefits for life (VA+GMWB) with the goal of developing a framework for the construction of optimal retirement portfolios.

The idea of an economic moat refers to how likely companies are to keep competitors at bay for an extended period. Morningstar calculates an average economic moat score for mutual funds by using the economic moat ratings assigned to the fund’s stock holdings. Economic moat is calculated for all universes.

This article discusses the level of overlap among style index providers, and the implications for investors using style-based indexes. It explores the differences in performance within style families and the serious ramifications for investors’ portfolio building activities. It explains the potential for indexes and index funds to help investors by laying the basis for performance attribution, portfolio construction, and better manager evaluation.

In August 2017, Morningstar will begin calculating many of its category percentile ranks and category averages using fractional weighting.

After another market crash, advisors question whether Modern Portfolio Theory is the best way to tackle asset allocation. We asked two experts to debate its merits.

This document describes the rationale for, and the formulas and procedures used in, calculating the Morningstar Rating™ (star rating) for funds domiciled or available for sale in Europe, Hong Kong, Singapore, Taiwan, and the United States.The Morningstar Rating has the following key characteristics: 1) The peer group for each fund’s rating is its Morningstar Category™; 2) ratings are based on funds’ risk-adjusted returns.

This survey measures the experiences of mutual fund investors in 16 countries in North America, Europe, and Asia. Aiming to promote best practices for investors, we rated companies across six categories—Investor Protection, Transparency in Prospectus and Shareholder Reports, Transparency in Sales Practices and Media, Taxation, Fees and Expenses, and Distribution/Choice—and added the cumulative category scores to produce an overall country grade.

When risk models fall short, advisors need to look no further than the historical record to plan for the next 100-year flood.

As investors awaken to the risks of investing, our distinguished economics panel debates the value of current risk models.

This paper studies the role of infrastructure in a strategic asset allocation. It addresses two critical questions: is infrastructure an asset class; and if so, what might be an appropriate asset allocation range. Though adding infrastructure to a diversified portfolio led to only a marginal improvement in the efficient frontier, unconstrained historical and forward-looking optimizations resulted in significant infrastructure allocations.

This document covers the Morningstar Rating methodology for for three variable products: variable annuity, variable life, and variable universal life.

This document is a supplement to the main methodology, presenting how the holdings weights of the portfolio and the benchmark are calculated under various exception cases. This paper expands on the single period definition described in the Morningstar® Equity Performance Attribution Methodology document to accommodate for user-specified time periods that may not begin on a date that has holdings data.

This paper studies the impact of liability-driven investing on asset allocation policy with an emphasis on U.S commercial real estate and Non-U.S. commercial real estate allocations. This study consists of two parts – a historical analysis and a forward-looking analysis. It uses a relatively robust opportunity set of 14 asset classes that is indicative of the type of opportunity set used by a sophisticated investor.

Morningstar undertook an initiative to incorporate the effect of short positions and derivatives in a portfolio's descriptive statistics. This involved recalculating current and historical portfolio statistics to better capture the exposures provided by these instruments. This document describes how the portfolio statistics changed and gives examples of the types of funds affected.

Traditional, long-only commodity indexes only tell half the story. Why a momentum-based long/short approach makes a better benchmark.

Although MVO is widely accepted in academic and finance circles as the golden standard for developing asset allocations, its effectiveness in retirement-income planning is inherently limited. To more effectively evaluate the risk-reward trade-off of retirement-income patterns generated by different portfolios, we developed a new retirement-income efficient frontier framework to complement the traditional MVO framework. In this new setting, we can fully examine a portfolio’s sustainable income levels and the risks of it coming up short.

Morningstar has been building its own hedge fund database since 2004, and acquired other hedge fund databases along the way. Although hedge funds present certain challenges because they are not subject to regulation, we have the necessary expertise in tracking and analyzing pooled investment vehicles.

This paper promotes an enhanced understanding of human capital's role in the market portfolio, and how liability-driven investing is relevant for individuals. Providing a rich theoretical framework, it answers how and why equity-bond glide paths, as well as intra-stock and intra-bond splits, should evolve over time.

The Morningstar® 1000SM Hedge Fund Index is a rules-based, equal-weighted, non-investable index designed to capture the performance and behavior of the hedge fund universe in as representative a fashion as possible.

Some proponents of fundamental indexation claim that the strategy is based on a new theory in which market prices of stocks deviate from fair values. A key assumption in this approach is that fundamental weights are unbiased estimators of fair value weights that are statistically independent of market values. This article demonstrates that, except in trivial cases, this assumption is internally inconsistent because the sources of the “errors” are also determinants of market values. The article shows under what conditions fundamental weights are better—or worse—estimators of fair value weights than are market value weights, thereby demonstrating that the new theory is merely a conjecture. A formula is developed for the value bias inherent in fundamental weighting, and two approaches to combining fundamental and market values are discussed.

The Morningstar Stewardship Grade℠ for mutual funds is designed to help investors further research, identify, and compare fund managers and fund companies that do a good job--or a poor job--of aligning their interest with those of fund shareholders. The Stewardship Grade beyond the usual analysis of strategy, risk, and return.

This paper studies the role of U.S. Private Equity and Non-U.S. Private Equity in a strategic asset allocation. There is relatively little guidance in the literature on how much investors should allocate to private equity in a strategic asset allocation setting because of confusion between the private equity asset class and private equity funds, and considerable debate over historical returns.

We measure how much serial correlation there is in mutual fund returns.

Using from January 1995 to November 2006, this paper studies the relationship between performance and fund flow and the relationship between performance and asset size for funds of hedge funds. The findings confirmed that funds of hedge funds that have better performance experience greater capital inflows. This paper also finds that funds with more assets tend to produce higher returns at lower levels of volatility resulting in superior risk-adjusted performance.

Morningstar Rating for stocks represents our opinion, on a risk-adjusted basis, of the firm's intrinsic value relative to its market price. There are three components to the Morningstar Rating for stocks: our analysts' estimate of the stock's fair value; our assessment of the firm's business risk; and the stock's current market price.

Morningstar® Stewardship Rating for Stocks represents our assessment of management's stewardship of shareholder capital, with particular emphasis on capital allocation decisions.

This paper presents an equity index weighting scheme that combines features of market-cap and fundamental weighting that we call "collared" weighting. We use market-capitalization to assign initial individual security weights and fundamental factors used to control those weights The final security weights are allowed to fluctuate within a band established by a multiple based on a combination of fundamental factors. One of the features of our approach is that like fundamental weighting, it limits the effects of market bubbles. However, it maintains the desirable features of market weighting such as low turnover during normal market conditions.

In this book for The Research Foundation of CFA Institute, we review the traditional investment advice model for individual investors, briefly introduce three additional factors that investors need to consider when making investment decisions, and propose a new framework for developing lifetime investment advice for individual investors that expands the traditional advice model to include the additional factors that we discuss in the chapter.

How to measure how much a hedge fund hedges and how much alpha it provides.

This study creates savings guidelines for typical individuals with different ages, income levels, and initial accumulated wealth so the public can more easily determine how much to save for retirement. It also creates benchmarks for how much capital an individual would have accumulated based on their income and age. The study calculates retirement income as a percent of net pre-retirement income, and uses Monte Carlo simulations and Ibbotson Associates’ forecasted returns to calculate capital required for retirement.

Many professionals use only one method of style analysis, and researchers at Morningstar wanted to determine if the holdings-based and returns-based methods were fair substitutes for each other. Two separate Morningstar studies evaluated results and assumptions of each approach.

This paper studies the yearly returns of U.S. real-estate for the period starting in 1978. The best performing category was business real estate. All categories of real estate, as well as stock, bond, and commodity markets, outperformed the inflation rate during this period. The real-estate market statistics in this paper will help investors, speculators, and hedgers develop strategies and analyze the potentials of trading schemes and risk-reduction strategies.

The Morningstar Rating for collective investment trusts uses the same methodology as the Morningstar Rating for funds. Ratings are based on risk-adjusted returns for the three-, five-, and 10-year time periods, and then the overall rating is a weighted average of the available time-period ratings.

Commercial real estate equity has become an increasingly popular and accessible asset class for investment in the United States over the last 10 years, due in large part to the proliferation and success of real estate investment trusts (REITs). The introduction and growth of REITs and listed real estate stocks worldwide has created new investment opportunities for strategic asset allocation policy makers. This paper analyzes the historical performance of six traditional asset classes plus North American, European, and Asian real estate from 1990 to 2005.

Morningstar calculates investor returns for open-end mutual funds and exchange-traded funds to capture how the average investor fared in a fund over a period of time. Investor return incorporates the impact of cash inflows and outflows from purchases and sales and the growth in fund assets.

This study examines the extent to which investors are protected by share class limits, and how financial advisors who seek to fulfill their fiduciary and suitability obligations to their clients can determine which share class is suitable given the client’s investment horizon and wealth.

This paper studies the role of commodities in a strategic asset allocation. There are several methods of obtaining exposure to commodities. This paper focuses on the type of exposure to commodities produced by a fully collateralized total return commodity index. To study the historical return characteristics of commodities, we formed an equally weighted, monthly rebalanced composite of four commodity indexes.

The Morningstar Ownership ZoneSM complements the style box to provide an additional layer of detail about an equity portfolio’s investment style.