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.
Financial planners and advisors increasingly recognize that human capital must be taken into account when building optimal portfolios for individual investors. But human capital is not simply another pre-endowed asset class; it contains a unique mortality risk in the form of the loss of future income and wages in the event of the wage earner's death. Life insurance hedges this mortality risk, so human capital affects both optimal asset allocation and demand for life insurance. Yet, historically, asset allocation and life insurance decisions have been analyzed separately. This article develops a unified framework based on human capital that enables individual investors to make these decisions jointly.
The Morningstar Rating™ for load-waived versions of the class A shares of mutual funds and other load-waived statistics better reflect the investor experience for those individuals who do not pay the fund's front-end sales load, such as retirement-plan participants.
This study measures historical equity returns over 42 years on the Japanese market by a supply-side approach using accounting data for 24 industries. It also demonstrates a method of constructing expected returns for the future. Equity return is generated from two fundamental sources: growth of shareholders’ equity and dividend payments.
A number of risk-adjusted performance measures have been developed to address the shortcomings of the information ratio when active-return strategies are non-normal. These include the Sortino ratio, Omega, and the Stutzer index. The various risk-adjusted performance measures differ in theoretical motivation and mathematical form and can result in different rankings for non-normal distributions. However, they are more closely related to each other than is apparent. In this paper we unify all of these measures into a single family and expand on it.
The Black-Litterman model enables investors to combine their unique views regarding the performance of various assets with the market equilibrium in a manner that results in intuitive, diversified portfolios. This paper consolidates insights from the relatively few works on the model and provides step-by-step instructions that enable the reader to implement this complex model. A new method for controlling the tilts and the final portfolio weights caused by views is introduced.
During retirement, investors need to decide how to invest their savings among asset classes and possibly fixed payout annuities. The author explores retirement income solutions in a simple setting to illustrate the trade-offs that retired investors face regarding how much income they can generate, how much short-term risk they are exposed to, how large an estate they can expect to leave, and how likely they are not to run out of assets before dying (the “success” probability).
Morningstar uses the historical monthly total returns for the appropriate time period (one-, three-, five-, 10-, 15-, and 20-year) to calculate the monthly standard deviation for stocks, open-end mutual funds, closed-end funds, exchange-traded funds, indexes, separate accounts, variable annuity underlying funds, and variable annuity sub-accounts.
The Morningstar Tax Cost Ratio measures how much a fund’s annualized return is reduced by the taxes investors pay on distributions. In this paper we discuss how this is calculated.
Morningstar calculates potential capital gain exposure to give investors some idea of the potential tax consequences of their investment in a fund. PCGE estimates how much the fund’s assets have appreciated, and it measures the gains that have not yet been distributed to shareholders or taxed.
Morningstar® Indexes were created to provide investors with accurate benchmarks for performance measurement, as well as offering discrete building blocks for portfolio construction. These indexes provide an accurate, comprehensive depiction of the performance and fundamental characteristics of U.S. equity markets.
This paper assesses the investment value of the CBOE S&P 500 BuyWrite (BXM) Index and its covered call investment strategy to an investor from the total portfolio perspective. Additionally, we compare standard investor portfolios to portfolios where BXM has been substituted for large cap assets and find significant risk-adjusted performance improvement.
The Sortino Ratio and the more recently developed Omega statistic are conceptually related “downside” risk-adjusted return measures, but appear distinct mathematically. We show that each of these measures is a special case of Kappa, a generalized risk-adjusted performance measure. A single parameter of Kappa determines whether the Sortino Ratio, Omega, or another risk-adjusted return measure is generated.
The Morningstar Style Box™, sometimes referred to as the Equity Style Box, is a nine-square grid that classifies securities by size along the vertical axis and by value and growth characteristics along the horizontal axis.
Little academic research has been conducted that empirically and systematically compares the two most common approaches to assessing a mutual fund’s investment style, i.e., portfolio-based (fundamental) style analysis and returns-based style analysis. Each method has its proponents and detractors, yet fundamental questions about the accuracy of each approach remain open. This paper clarifies the debate over style analysis and completes the literature with an empirical analysis of the accuracy of the two methods, with respect to an actual set of open-end mutual funds.
This paper examines the role that style (growth vs. value) plays in the risk and return characteristics of equities. Ibbotson Associates, with the help of the Center for Research in Security Prices (CRSP®), has created a set of style indices going back to 1969 that are both comprehensive and mutually exclusive. This paper discusses the construction methodology of these indices, presents an analysis of the results, and provides samples of raw data.
The Morningstar Rating™ for separate accounts is a quantitative assessment of past performance--both return and risk--as measured from 1 to 5 stars. The Morningstar Rating, often referred to as the "star rating," is a familiar tool that helps investors evaluate the risk-adjusted returns of separate account composites.
There are two main approaches to style analysis: holdings-based and returns-based. This study compares these methods by (1) developing a method to display the style plot points generated by the two methods, and (2) comparing the style plot points generated by the two methods over a large set of U.S. equity funds. We highlight where the results are similar and where they significantly differ. Where there are significant differences, we explore some of the possible reasons. Users of style analysis should find this study helpful in determining which, if either, method is appropriate for their applications.
This paper examines the constant and variable liquidity direct real estate price indexes of Fisher, Galtzaff, Geltner, and Haurin  and use them in asset allocation exercises. Review of these indexes suggests they provide improved measures of direct real estate performance that do much to remedy problems resulting from the appraisal-induced smoothing of the NCREIF property index.
The Markowitz mean-variance model is widely accepted as the gold standard for asset allocation on the way to retirement. Unfortunately, this framework only considers the risk and return tradeoff in the financial market, neglecting the longevity risk people face during retirement. To fill this gap, our paper revisits the importance of longevity insurance (while discussing the problems with fixed payout annuities) and then addresses the proper asset allocation between conventional financial assets and variable payout annuity products.
This article introduces the Morningstar U.S. Style Indexes as a new generation of equity indexes. It shows using several measures how the Morningstar indexes are more style pure than other style index families.
Traditionally, measuring industry risk has been a qualitative analysis and subject to the judgment of the appraiser. To address the problems inherent in this type of subjective approach, Ibbotson has developed industry risk premia for use in the buildup model using a method that is more quantitative and objective in nature. This paper explores its calculation and methodology.
This study estimates the forward-looking long-term equity risk premium by extrapolating the way it has participated in the real economy. The authors decomposed the 1926–2000 historical equity returns into supply factors—inflation, earnings, dividends, the P/E, the dividend-payout ratio, book value, return on equity, and GDP per capita.
Data of domestic equity mutual funds indicates that winning funds, as defined by appropriate benchmarks, do repeat good performance, and that the strongest persistence is exhibited by funds with the highest returns over a stylized benchmark. This paper examines the relevance of this trend.
When designing investment portfolios within a long-term strategic asset allocation context, this paper maintains that direct energy investments (diversified portfolio of producing oil and gas properties) should be evaluated as a separate, distinct asset class. The authors demonstrate that direct energy investments offer potentially significant diversification benefits and relatively low correlation with other traditional asset classes, establishing them as a viable asset class to be considered when constructing a long-term asset allocation policy.
In this paper, the authors collect individual stock prices for NYSE stocks over the period 1815 to 1925 and individual dividend data over the period 1825 to 1870. They use monthly price and dividend information on more than 600 individual securities over the period to estimate a stock price index and total return series that extends virtually to the beginning of the New York Stock Exchange. This data is used to estimate the power of past returns and dividend yields to forecast future long-horizon returns.
The curious title of this note refers to Lewis et al., "The Ibbostson-Sinquefield Simulation Made Easy," Journal of Business, 1980,. In that paper, the authors use a lognormal model of asset returns to proxy the Ibbotson-Sinquefield (1976) simulations, making the Ibbotson-Sinquefield forecasts easy to do. Unfortunately, their paper is not easy to read. This is a condensation of its basic ideas.
Disagreement over the importance of asset allocation policy stems from asking different questions. We used balanced mutual fund and pension fund data to answer the three relevant questions. We found that about 90 percent of the variability in returns of a typical fund across time is explained by policy, about 40 percent of the variation of returns among funds is explained by policy, and on average about 100 percent of the return level is explained by the policy return level.
TIPS (Treasury Inflation-Protection Securities) possess unique characteristics that are not directly available through other investment vehicles. The authors demonstrate that TIPS offer potentially significant diversification benefits, establishing them as a viable asset class to be considered when constructing a long-term asset allocation policy.
In this paper we describe a method for selecting portfolios of managers or mutual funds to implement a target asset allocation. Our goal is to maximize alpha for each level of tracking error. Furthermore, the routine is designed to meet manager imposed minimum investment requirements by utilizing discrete optimization techniques. A step-by-step example illustrates the practical use of the methods we have developed.
When small-cap stocks underperform large-cap stocks, does this mean there is no size premium? This paper examines data for small-cap stocks from 1977-96, against longer term findings.
In this article, its authors first present some support for the argument that the market is assigning a high degree of belief that the Euro will take hold in 1999. Then we consider the position of the long-term investor. In terms of historical performance and optimal asset allocation, what are the implications of the disappearance of eleven currencies and the appearance of a new one?
This paper deals with a selection of investment judgment biases, and discusses errors of preference, which arise either from mistakes that people make in assigning values to future outcomes or from improper combinations of probabilities and values. In both cases, each bias is introduced with a question that illustrates the bias and conclude with recommendations for financial advisors to help mitigate the harmful effects of these biases. The article concludes with a checklist that advisors can use to measure their effectiveness at dealing with these biases.