CFA Institute Author Digests Source: Financial Analysts Journal, Vol. 58, No. 2 (Mar. - Apr., 2002), pp. 5-6+8+10+12-14 Published by: CFA Institute Stable URL: http://www.jstor.org/stable/4480374 . Accessed: 17/06/2014 06:22 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp . JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. . CFA Institute is collaborating with JSTOR to digitize, preserve and extend access to Financial Analysts Journal. http://www.jstor.org This content downloaded from 195.34.79.253 on Tue, 17 Jun 2014 06:22:46 AM All use subject to JSTOR Terms and Conditions
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.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact [email protected].
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Battle for Alphas: Hedge Funds versus Long-Only Portfolios page 16 Duen-Li Kao
The technology investing debacle, diminishing equity return expectations, and the inability of long-only portfolios to generate positive alphas have greatly contributed to institutional investors' recent interest in hedge-fund investments. The optionlike return pattem of hedge funds, however, is a challenge for investors in analyzing risk exposures. Single measures of risk and return always have the potential to be misleading, but they are especially inadequate in analyzing hedge-fund risk. Investors need to carefully examine the return patterns of a fund at times of various market conditions and consider the fund's exposure to various forms of systematic risk factors.
This article addresses two questions relevant to investor analysis of hedge-fund performance: First, do alphas from hedge funds and long-only portfolios have different return attributes? And second, do the sources of alpha for the two types of investments derive from different risk factors? Because investors can transfer alpha obtained from hedge funds to their traditional asset-class portfolios, a more appropriate way to evaluate hedge funds and long-only portfolios than simply comparing their returns is to compare their returns in excess of their respective benchmarks. The empirical findings presented here indicate that hedge funds, especially equity market-neutral strategies, provide more consistent transferable alpha than do long-only portfolios for both equity and bond asset classes and in various market environments. I assess, possible explanations of this performance difference from the standpoints of data reliability and differences between hedge funds and long-only funds in fees, manager incentives, investment constraints versus flexibility, and other structural factors.
Risk factors derived from asset prices in financial markets are timely and useful for hedge-fund risk analysis. Most relevant to hedge funds' risk profiles are exposure to the market-directional risk of standard asset classes and various volatility risks. I show that the way in which a hedge fund manages its exposures
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to implied volatilities in extreme market conditions may be the key to consistent performance. The results presented in the article highlight the importance of diversifying one's hedge-fund investments among different strategies-between funds and within a fund-for achieving consistent performance.
An analytical framework that incorporates multiple risk factors (rather than a single factor) gives investors a more complete picture of hedge-fund risk taking. Therefore, in the spirit of equity style analysis, which is so popular among practitioners, I evaluate common risk factors driving the performance of hedge funds and long-only portfolios. In this style-risk approach, various financial market risk indicators are categorized into (1) exposure to market risks (market-directional risk) and (2) exposure to volatility risk, which provides a concise assessment of risk exposures over time.
I also review another approach to analyzing hedge-fund risk-direct replication of the hedge fund's optionlike payoff profile, trading strategies, or arbitrage opportunities. Return series derived from this "mimicking" approach are particularly useful for studying the risk factors and performance attributes of hedge-fund investing. It also provides a promising direction for future research into hedge-fund asset pricing. ERl
Keywords: Alternative Investments: hedge funds; Portfolio Management: asset allocation
A Proposal for Quoting Money Market Rates page 38 Miles Livingston and Lei Zhou
Any observer of the U.S. market for money market instruments must be struck by the great number of ways of quoting money market interest rates. At least five different ways are frequently used to quote interest rates on zero-coupon money market instruments with maturities of less than six months. And additional methods are used to quote coupon-bearing money market instruments or money market instruments with maturities of between six months and one year.
Two instruments may have the same price or amount of loan, same coupon, and same par value, but the calculation of the interest rate differs. For example, suppose a 90-day noncoupon money market instrument has a par value of $100 and a price of $99. The quoted discount rate on the instrument is 4 percent, the add-on rate is 4.04 percent, the bond-equivalent yield is 4.10 percent, the semiannual yield is 4.12 percent, and the annual yield to maturity is 4.16 percent. This multiplicity of ways of quoting interest rates is a cause of constant confusion for novice analysts in the field of money market instruments and has no value for experts.
The reason for the multiplicity of interest rates appears to be historical accident. Before hand-held calculators, various money markets developed separately over time, but the ability to calculate rates easily was important, so each market developed an easy calculation. With the advent of hand-held calculators, calculation of any of these interest rates is no longer a problem.
Because long-term bonds in the United States are quoted in terms of semiannual yield to maturity (i.e., annualized semiannually compounded yield to maturity), the world of fixed-income analysis would be greatly simplified if all interest rates were stated this way. There would be no need to state interest rates on a particular debt instrument in different ways, and given the ease of calculating the semiannual yield to maturity, there is no reason to have any other interest rate. Therefore, we propose that the bond market use the semiannual yield for all bonds and money market instruments. 13
Keywords: Debt Investments: return or yield measures
Multiples Used to Estimate Corporate Value page 44 Erik Lie and Heidi J. Lie
Despite the importance of valuation in a variety of contexts, surprisingly few studies have examined the accuracy of various valuation techniques. Only the effect of the choice of matching companies on the valuation accuracy of P/E multiples and the usefulness of discounted cash flow and various multiples in valuing rather narrow subsets of companies, such as companies that operate in bankruptcy, have been addressed. The study reported here explicitly examined the overall performance of a variety of multiples used for valuation. The purpose was to examine the biases and valuation accuracy of multiples based on earnings, sales, or book value of assets for several categories of companies.
For the aggregate sample, we found that all multiples yield estimates that are somewhat negatively biased. That is, the mean valuation errors are slightly negative, whereas the median valuation errors are
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roughly zero. The ratio of market value to book value of assets yields the most accurate estimates. Adjusting the market and book values for the level of cash does not improve the accuracy, but using forecasted earnings in place of historical earnings improves the estimates based on the P/E multiple.
We partitioned the sample into financial and nonfinancial companies and, within those two groups, formed groups based on size and profitability. We also partitioned the companies into those with high (low) levels of intangible assets and research and development activities. We found that valuations are more precise for large companies. For all company sizes, the asset multiple performs the best and the sales multiple performs the worst. Valuations based on the asset multiple appear to be most precise for companies with mediocre or low earnings; they are roughly equally as precise as valuations based on other multiples for companies with high earnings. The bias for the measures as applied to companies grouped by earnings varies: For companies with high earnings, earnings-based multiples yield a positive valuation bias, but the asset multiple yields a negative bias-and vice versa for companies with low earnings.
The valuations tend to be more accurate for financial companies than for nonfinancial companies. Nevertheless, the trends regarding the performance of various multiples for groups based on size or profitability are similar for financial and nonfinancial companies.
When we assessed the performance of the multiples for companies with high intangible assets (i.e., either "dot-com" companies or companies with large levels of R&D), the valuation estimates became generally worse, especially for the dot-coms. We also found the estimates to be systematically lower than the actual values, presumably because the estimates do not fully capture the growth opportunities and other intangibles associated with these companies.
Our research is certainly relevant to practitioners, such as investment bankers and analysts, because they use multiples to value companies, but we believe it is also consequential to academic researchers. For instance, studies of the effect of corporate diversification on value use multiples to value individual segments of a company and then compare the estimated aggregate value to the market value to determine the "excess value" created by diversification. The results presented here may help such researchers choose multiples that minimize potential bias embedded in the value measures, especially if the companies or company segments exhibit certain irregularities. M
Keywords: Equity Investments: fundamental analysis and valuation models
Mutual Fund Age and Morningstar Ratings page 56 Matthew R. Morey
With the tremendous growth of privately managed retirement accounts and the more than 10,000 mutual funds now available to investors, mutual fund ratings have never been more in demand. One popular, if not the most popular, provider of mutual fund ratings today is Morningstar, Inc. Started in the mid-1980s, Morningstar has grown largely as a result of the success of its five-star rating system. Similar to the rating of hotels, movies, and restaurants, Morningstar rates mutual funds on a scale of one to five stars, where one star is the worst rating and five stars is the best.
The Morningstar rating system has become so popular that many people believe investment flows in and out of mutual funds are closely related to the Morningstar ratings. Moreover, the heavy use of Morningstar ratings in mutual fund advertising suggests that mutual fund firms believe investors care about Morningstar ratings.
The purpose of the study reported in this article was to document a methodological bias in the Morningstar ratings. The bias results from the way Morningstar treats funds of different "ages." Morningstar ratings are created by aggregating 3-year, 5-year, and 10-year star ratings for each fund. The ratings of young funds that do not have 5 years of return history are based solely on the 3-year ratings. The ratings for funds with 10 years or more of return history are based on a 20 percent weighting of the 3-year rating, a 30 percent weighting of the 5-year rating, and a 50 percent weighting of the 10-year rating. Therefore, the ratings of older funds are less likely to fall than those of younger funds. The result is that older funds tend to have higher ratings-not because of performance per se but because of the weighting system.
After illustrating this bias, I document that the bias emerges in the actual ratings. Upon examining each of the 37 quarterly Morningstar data disks from October 1991 to October 2000, I found that the average overall star rating of the seasoned (oldest) funds was greater than that of the young funds in 36 of the 37
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quarters. Moreover, in 26 of 37 cases, the seasoned funds' average rating was significantly higher. Finally, I found in robustness checks that these results are related to methodological bias, not survivorship bias.
Two implications of the results are particularly important. First, if investors do care about the ratings, then these results mean that investors should be careful in interpreting the overall ratings as signals of past performance, much less future performance. Investors need to look beyond the ratings when deciding which fund(s) to invest in. And to its credit, Morningstar gives similar advice.
Second, mutual fund rating services may want to use a single consistent time horizon to evaluate funds. Systems that use time horizons that depend on the age of the fund can lead to biases that make the ratings more subjective than objective. Again, to its credit, Morningstar has tried to address this issue by putting more emphasis on alternative ratings that use the same amount of information for each fund. R
What Risk Premium Is "Normal?" page 64 Robert D. Arnott and Peter L. Bernstein
The investment management industry thrives on the expedient of forecasting the future by extrapolating the past. As a consequence, U.S. investors have grown accustomed to the idea that stocks "normally" produce an 8 percent real return and a 5 percent risk premium over bonds compounded annually over many decades. Why? Because long-term historical returns have been in this range with impressive consistency. Because investors see these same long-term historical numbers year after year, these expectations are now embedded in the collective psyche of the investment community.
Both the 8 percent real return and the 5 percent risk premium assumptions are unrealistic in light of current market levels; more importantly, they have rarely been realistic in the past. As we demonstrate in this article, the long-term forward-looking risk premium is nowhere near the 5 percent level of the past; indeed, today, it may well be near zero, perhaps even negative.
The goal of this article is to estimate the objective forward-looking equity risk premium relative to bonds through history. For correct evaluation, such a complex topic requires several careful steps: To gauge the risk premium for stocks relative to bonds, we need an expected real stock return and an expected real bond return. To gauge the expected real stock return, we need both stock dividend yields and an estimate of expected real dividend growth. To gauge the expected real bond return, we need both bond yields and an estimate of expected inflation through history. Accordingly, we go through each of these steps.
We distinguish between observed historical return differences (that is, excess returns of the past) and the risk premium, which refers to expected future return differences. A critical component of our approach to the risk premium is to consider what investors could reasonably have been expecting at various points in the past. Using data from a variety of sources, we examine the history of U.S. bond returns, stock returns, return expectations, and economic, political/geopolitical, and demographic changes from 1802 to 2001.
We draw the following conclusions: * The observed real stock returns and the excess return for stocks relative to bonds in the past 75 years
have been extraordinary, largely as a result of important nonrecurring developments. * The investors of 75 years ago would not have had an objective basis for expecting the 8 percent real
returns or 5 percent excess returns that stocks subsequently delivered. * To shape future expectations based on extrapolating these lofty historical returns is dangerous. In so
doing, an investor is tacitly assuming that valuation levels that have doubled, tripled, and quadrupled, relative to underlying earnings and dividends, can be expected to do so again.
* The real internal growth that companies have generated for nearly 200 years in dividends and earnings is slower than the increase in real per capita GDP. This internal growth is far less than the consensus expectations for future earnings and dividend growth.
* The historical average equity risk premium, measured relative to 10-year government bonds, that investors might objectively have expected on their equity investments, is about 2.4 percent. The consensus that a normal risk premium is about 5 percent was shaped by deeply rooted naivete in
the investment community, where most participants have a career span reaching no farther back than the monumental 25-year bull market of 1975-1999. This kind of mind-set is a mirror image of the attitudes of the chronically bearish veterans of the 1930s. Today, investors are loathe to recall that the real total returns on stocks were negative for most 10-year spans during the two decades from 1963 to 1983 or that the excess return of stocks relative to long bonds was negative as recently as 10 years ago. When reminded of such
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experiences, today's investors tend to retreat behind the mantra "things will be different this time." No one, however, can kneel before the notion of the long run and at the same time deny that past circumstances will again occur in the decades ahead. Indeed, such crises are more probable than most of us would like to believe. Investors naive enough to expect a 5 percent risk premium and to sharply overweight equities accordingly may well be doomed to deep disappointments in the future. M
Keywords: Portfolio Management: asset allocation
Emerging Markets: When Are They Worth It? page 86 C. Mitchell Conover, Gerald R. Jensen, and Robert R. Johnson
The study we report reexamined the benefits to U.S. investors of investing in international equities, with a focus on emerging market stocks and on differences in returns and risks between periods of expansive U.S. monetary policy and periods of restrictive U.S. monetary policy. Several past studies have shown that international equities offer diversification benefits for U.S. investors, primarily because of the relatively low correlation of non-U.S. with U.S. stock returns. Emerging market equities have been shown to have particularly low correlations with the U.S. stock market. A troubling aspect of the past correlation findings, however, is that the correlations of non-U.S. and U.S. equity markets differ substantially over time. Of even more concern is the finding that the correlations tend to increase during periods when the markets are exhibiting the worst performance. Thus, the benefits of international diversification may be lowest when diversification is most needed.
Our analysis had two basic objectives: to quantify the overall benefit of investing in emerging markets and to determine whether the benefit fluctuates systematically with changes in U.S. monetary conditions. Based on recent evidence that shows stock market performance in developed countries to be systematically related to broad changes in monetary policy, we hypothesized that the benefits of international diversification may be related to changes in U.S. monetary conditions. In particular, previous findings confirm that, in the developed markets, equities perform much better (worse) than average during expansive (restrictive) monetary periods-perhaps because the monetary authorities in developed countries tend to cooperate in setting monetary policy. We argued, however, that the monetary policy decisions of developing country monetary authorities are less likely to coincide with their counterparts in developed countries. Thus, relative to the developed markets, emerging markets might provide a more effective hedge against the poor performance exhibited by U.S. equities during periods of restrictive U.S. monetary policy.
The sample used in this analysis compares favorably with past research, based on both breadth and length of time period covered. We considered returns to 20 emerging markets over a 24-year study period, whereas past studies relied on approximately half as many countries and a much shorter time frame. Therefore, our findings are less influenced by extreme observations that may have occurred in a particular time period or a particular country.
Our results indicate that adding emerging market equities to a portfolio that consists of developed country equities adds a net benefit of 1.5-2.0 percentage points (pps) a year to returns. This finding confirms the view that emerging market equities are an attractive diversification vehicle for U.S. investors. Furthermore, we found that emerging market equities represent a significant weight in both high-risk and low-risk efficient portfolios, which indicates that emerging market equities are beneficial even for equity investors with relatively high levels of risk aversion.
A more surprising result is that the benefit associated with investing in emerging market equities accrues almost entirely during periods of restrictive U.S. monetary policy; we found the net benefit to be more than 4 pps annually. During periods of expansive U.S. monetary policy, emerging markets added only a trivial improvement to portfolio performance (approximately 0.2 pps a year). This finding indicates that a necessary prerequisite to determining the appropriate allocation to international equities is to monitor U.S. monetary conditions. an
Keywords: Portfolio Management: asset allocation
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European Price Momentum and Analyst Behavior page 96 Ronald van Dijk and Fred Huibers
Price momentum refers to a tendency of stock prices to continue on the same path from one period to the next. The existence of such return continuation for periods up to a year has been documented for the U.S., European, and emerging equity markets in studies conducted by both academics and practitioners. The cause (or causes) of price momentum, however, is subject to much controversy. Some argue that it is a manifestation of slow reaction by analysts to earnings-related news. The study reported in this article provides empirical evidence, based on European data, of the validity of this hypothesis.
We used a comprehensive sample of all European stocks that had at least one earnings forecast in the I/B/E/S database spanning the period February 1987 and June 1999. We confirmed that price momentum strategies were profitable in the sample period. This finding is robust to corrections for size effects, value versus growth effects, estimated earnings-growth effects, and the effects of country-specific risk.
To test the underreaction hypothesis, we examined the relationships among earnings surprises, expectations for future earnings growth, earnings revisions, and the returns from momentum investing. The primary finding of this study is that a pessimism bias exists for portfolios composed of strong-price-momentum stocks and an optimism bias exists for portfolios consisting of weak-price-momen- tum stocks. The optimism bias is definitely more substantial than the pessimism bias; underreaction of analysts to earnings-related news is likely. We based this conclusion on the observation that earnings surprises are positive for strong-momentum stocks and negative for weak-momentum stocks. Moreover, just after an earnings announcement by a company, the expected growth in earnings is more overestimated for weak-momentum stocks than it is for strong-momentum stocks. The revisions were generally downward but were more downward for weak-momentum stocks.
Furthermore, we found that the widely documented value and size anomalies are distinct from the price momentum anomaly. An almost perfectly linear negative relationship exists between price momentum and the book-to-market ratio, whereas if the momentum and the book-to-market effects were the same phenomenon, we would expect a positive relationship. We found a relationship between market
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capitalization and momentum to be either absent or positive, which is inconsistent with the hypothesis that these two anomalies are the same phenomenon.
When we examined how robust the results are to some changes in sample selection and the method of portfolio construction, we found that the empirical results were not driven by one particular European country and were similar for the first and second halves of the sample period. In addition, the results are robust to alternative currency assumptions for the returns and to alternative methods of portfolio construction.
Based on our findings, price momentum strategies were profitable in the European markets in the period we studied, but these strategies may produce incremental returns only as long as underreaction to earnings information persists. Therefore, this study implies that to monitor the risks of using a price momentum strategy, investors should continuously observe analyst behavior and changes in behavior. Indicators for underreaction are earnings surprises within the price momentum portfolios and autocorrelations in earnings-forecast revisions. Whether price momentum strategies will continue to generate excess returns after a significant change in analyst behavior depends on the existence of other causes for price momentum-which calls for further research. 15
Wall Street People: True Stories of Today's Masters and Moguls page 106 Charles D. Ellis with James R. Vertin
This enjoyable and instructive book is a treasure trove for students of financial history-with sketches of luminaries and rascals, anecdotes, and descriptions of the sources of various financial products.
Keywords: The Profession: other
The Complete Investment and Finance Dictionary page 107 Howard Bryan Bonham
Designed as an investment guide as well as a lexicon, the author of this reference book defines and illustrates the use of various analytical tools and points out potential pitfalls in their applications.
Keywords: The Profession: investment industry; Quantitative Tools: other
No Bull: My Life In and Out of Markets page 108 Michael Steinhardt
This memoir of a hedge-fund manager provides not only insights into his investing strategy and successes but also a description of his personal life.
Keywords: The Profession: other
Complexity, Risk, and Financial Markets page 110 Edgar E. Peters
This philosophical approach to investing (reviewed together with Latticework) focuses on the need for investors to accept and deal with uncertainty and complexity.
Keywords: Financial Markets: other
Latticework: The New Investing page 11 0 Robert Hagstrom The solution offered in this book (reviewed together with Complexity, Risk, and Financial Markets) to the problem of complex and uncertain markets is to pursue interdisciplinary knowledge and creativity.
Keywords: Financial Markets: other
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