quality ranking whitepaper final

Standard & Poor’s Quality RankingsPortfolio Performance, Risk, and Fundamental Analysis

October 2005

Standard & Poor’sQuality Rankings

Portfolio Performance, Risk,

and Fundamental Analysis

October 2005

TThhiiss rreeppoorrtt wwaass pprreeppaarreedd bbyy::Massimo SanticchiaDirector(212) 438-3934

Philip G. Murphy, CFADirector(212) 438-1368

Acknowledgements:Jim BranscomeDavid BlitzerRoger BosJim DunnMichael FinkJoshua HarariJacqueline MezianiJohn SchemitschKen Shea

October 2005 / Standard & Poor’s Quality Rankings: Portfolio Performance, Risk, and Fundamental AnalysisAdvisors must distribute this document to clients in its entirety. An advisor can not comment on Standard & Poor’s investment methodology.

This report is published by Standard & Poor’s, 55 Water Street, New York, NY 10041. Copyright © 2005. First Edition.Standard & Poor’s (S&P) is a division of The McGraw-Hill Companies, Inc. All rights reserved. Standard & Poor’sdoes not undertake to advise of changes in the information in this document. Standard & Poor’s has used informa-tion available in the public domain to produce this report.

I. Executive Summary

� Standard & Poor’s has provided Earnings and Dividend Rankings, commonly referred to as QualityRankings, on common stocks since 1956. Quality Rankings reflects the long-term growth and stability of acompany’s earnings and dividends.

� Portfolios of stocks with high Quality Rankings outperformed the S&P 500 Index and substantially outper-formed portfolios of stocks with low Quality Rankings over the 1986-2004 period. The portfolio with thehighest quality (A+) outperformed the S&P 500 by about 110 basis points.

� Portfolio risk is lower for companies with higher Quality Rankings. On a risk-adjusted basis, the all-A port-folio outperformed the all-B portfolio by almost 300 basis points.

� Fundamental risk is lower in portfolios of stocks with high Quality Rankings. The portfolios exhibit stableand persistent earnings, high returns on equity, stable and wide profit margins, and low debt levels.

� Companies with high Quality Rankings appear less likely to engage in accounting manipulations. Over the1986-2004 time frame, these companies reported significantly lower non-recurring items. They also havehigher quality of earnings as defined by Standard & Poor’s Core Earnings methodology.

� Portfolios of stocks with high Quality Rankings provide downside protection. Over the 1986-2004 period,these portfolios significantly outperformed the S&P 500 and portfolios of companies with low QualityRankings in times of earnings deceleration and increasing credit risk.

� Earnings growth for companies with high Quality Rankings is not correlated with overall corporate earn-ings and credit cycles. Conversely, earnings growth for companies with low Quality Rankings is highlydependent on earnings and credit cycles.

� Stock selection strategies based on Quality Rankings can be executed with little market impact, as stockswith high Quality Rankings exhibit high liquidity, and portfolio turnover is low.



TABLE OF CONTENTS

SECTION I. 1.0 INTRODUCTION 3

SECTION II. 2.0 DESCRIPTION OF THE STANDARD & POOR’S QUALITY RANKINGS SYSTEM 5

SECTION III. 3.0 RISK AND RETURN ANALYSIS OF QUALITY RANKINGS PORTFOLIOS 6

3.1 Methodology 6

3.2 Risk and Return Analysis 7

3.3 Downside Risk Analysis 8

SECTION IV. 4.0 FUNDAMENTAL ANALYSIS OF QUALITY RANKINGS PORTFOLIOS 11

4.1 Size, Leverage, and Profitability 11

4.2 Growth and Profitability Analysis 12

4.3 Performance of Quality Rankings Portfolios in Earnings and Credit Cycles 14

SECTION V. 5.0 QUALITY OF EARNINGS 18

5.1 Quality Rankings and Standard & Poor’s Core Earnings 18

5.2 Quality Rankings and Special and Extraordinary Items 18

5.3 Quality Rankings and Dispersion in Analyst Forecasts 18

SECTION VI. 6.0 PORTFOLIO CHARACTERISTICS OF RECENT AND HISTORICAL

QUALITY RANKINGS PORTFOLIOS 22

6.1 Quality Rankings Portfolio Characteristics and Composition 22

6.2 Quality Rankings Sector Makeup 24

6.3 Quality Rankings, Capitalization, and Growth-Value Split Analysis 26

6.4 Valuation Multiples Analysis 28

SECTION VII. 7.0 CONCLUSION 30

Table 1 Quality Rankings Classification

Table 2 Market-Weighted Annual Returns for Quality Rankings Portfolios

Table 3 Equal-Weighted Annual Returns for Quality Rankings Portfolios

Table 4 Size, Leverage and Profitability at Different Points in Time

Table 5 Mean Values and Volatility of Profitability Metrics for the Period 1985-2004

Table 6 Quality Rankings: Number and Percent of Total Ranked Stocks

Table 7 Price, Market Value and Turnover by Quality Rankings

Table 8 Transitional Probabilities Matrix for Quality Rankings

Table 9 Growth-Value Split of High-Quality (A+, A and A-) As of June 2005

Figure 1 Value of $10,000 Invested in All-A and All-B, C & D Portfolios — Market-Weighted Returns

Figure 2 Value of $10,000 Invested in All-A and All-B, C & D Portfolios — Equal-Weighted Returns

Figure 3 Market Betas of Quality Rankings Portfolios in Up and Down Markets

Figure 4 Average Monthly Returns in Up and Down Markets

Figure 5 Growth and Profitability Metrics over Time

Figure 6 Corporate Earnings Cycle and Performance of Quality Rankings Portfolios

Figure 7 Percentage of Companies with S&P Credit Rating of A- or Better

Figure 8 Impact of Interest Rate on Interest Coverage Ratio of High- and Low-Quality Companies

Figure 9 Median Percentage Difference Between Core Earnings and As-Reported Earnings

Figure 10 Special and Extraordinary Items and Discontinued Operations As a Percentage of Operating Income

for Quality Rankings Portfolios

Figure 11 Analysts’ Growth Forecast Consensus and Dispersion As of December 2004

Figure 12 High-to-Low Quality Ratio Over Time

Figure 13 Current Breakdown of and Trend in S&P 1500 Sector Composition of All-A Portfolio

Figure 14 Quality Rankings Distribution by Index

Figure 15 All-A Companies Classified As Growth or Value As a Percentage of Total

Figure 16 Price-to-Book and Price-to-Sales Ratios for Quality Rankings Portfolios

Figure 17 Earnings Yield for A+ and B Quality Rankings Portfolios

LIST OF EXHIBITS



4

“A statement of actual earnings, over a period of years, with a reasonable expectation thatthese will be approximated in the future. The record must cover a number of years, firstbecause a continued or repeated performance is always more impressive than a singleoccurrence, and secondly because the average of a fairly long period will tend to absorband equalize, the distorting influences of the business cycle.”1

—Graham and Dodd on sustainable earnings power

Standard & Poor’s has provided Earnings and Dividend Rankings, also known as Quality Rankings, on com-mon stocks since 1956. These Quality Rankings capture Graham and Dodd’s definition of sustainable earn-ings power, are used in portfolio management as prudent investments, and are commonly employed ininvestment litigation to determine the prudence of stock investments. A long history of Quality Rankings isavailable, and several academic and practitioner studies have examined their informativeness and reliability2.

This paper analyzes whether the prudent investment suggested by Quality Rankings is a wise investment aswell. In particular, after briefly describing the mechanics of Quality Rankings, we analyze the following ques-tions: What are the risk and return characteristics of portfolios based on Quality Rankings? How do higher-quality portfolios perform in times of distress? What are the fundamental risk characteristics of differentQuality Ranking portfolios? How do the fundamental characteristics of different Quality Rankings portfoliosvary in different phases of the corporate profit and credit cycles?2

After analyzing the risk, return, and fundamental characteristics of Quality Rankings portfolios, we examinethe relationship between Quality Rankings and several other measures of earnings quality. We show thatearnings growth of higher-quality firms, as defined by Quality Rankings, is more predictable than that oflower-quality firms. We also show that companies with higher Quality Rankings appear less likely to engagein accounting manipulations. Companies with high Quality Rankings also have higher quality of earnings asdefined by the Standard & Poor’s Core Earnings methodology.

Next, we briefly examine whether high-quality stocks are “glamour” stocks. Our analysis shows that high-quality stocks indeed have generally traded at higher multiples. Our analysis of fundamentals, however,shows that the premium in multiples for the higher-quality portfolio is justified by better fundamentals. Thus,our results show that higher-quality stocks command higher multiples and deliver higher returns. Theseresults are different from the conventional wisdom established by previous studies on risk factors in the U.S.equity markets, and provide a new insight into the risk and return characteristics of U.S. stocks.

Finally, we report characteristics of current and historical Quality Rankings portfolios. Our results show thathigh-quality stocks generally have greater liquidity, higher average price per share, and larger market value.In addition, Quality Rankings exhibit high stability over time. This implies that portfolio strategies based onQuality Rankings can be executed in practice.

I. Introduction

1 Graham and Dodd (1934), p. 429.2 Stevenson (1966), Haugen (1979), Muller, Fielitz and Greene (1983,1984), Muller and Fielitz (1987), Del Guercio (1995), Fernando,

Gatchev and Spindt (2003).


II. Description of the Standard & Poor’s Quality Rankings System3

The Quality Rankings System attempts to capture the growth and stability of earnings and dividends recordin a single symbol. In assessing Quality Rankings, Standard & Poor’s recognizes that earnings and dividendperformance is the end result of the interplay of various factors such as products and industry position, cor-porate resources and financial policy. Over the long run, the record of earnings and dividend performancehas a considerable bearing on the relative quality of stocks. The rankings, however, do not profess to reflectall of the factors, tangible or intangible, that bear on stock quality.

The rankings are generated by a computerized system and are based on per-share earnings and dividendrecords of the most recent 10 years – a period long enough to measure significant secular growth, captureindications of basic change in trend as they develop, encompass the full peak-to-peak range of the businesscycle, and include a bull and a bear market. Basic scores are computed for earnings and dividends, and thenadjusted as indicated by a set of predetermined modifiers for change in the rate of growth, stability withinlong-term trend, and cyclicality. Adjusted scores for earnings and dividends are then combined to yield afinal ranking.

The ranking system makes allowance for the fact that corporate size generally imparts certain advantagesfrom an investment standpoint. Conversely, minimum size limits (in sales volume) are set for the various rank-ings. However, the system provides for making exceptions where the score reflects an outstanding earningsand dividend record. Table 1 shows the letter classifications and brief descriptions of Quality Rankings.

The ranking system grants some exceptions to the pure quantitative ranking. Thus, if a company has not paidany dividend over the past 10 years, it is very unlikely that it will rank higher than A-. In addition, companiesmay receive a bonus score based on their sales volume. If a company omits a dividend on preferred stock,it will receive a rank of no better than C that year. If a company pays a dividend on the common stock, it ishighly unlikely that the rank will be below B-, even if it has incurred losses. In addition, if a company files forbankruptcy, the model’s rank is automatically changed to D.

5

TABLE 1: QUALITY RANKINGS CLASSIFICATION

LETTER DESCRIPTION

A+ HighestA HighA- Above AverageB+ AverageB Below AverageB- LowerC LowestD In ReorganizationLIQ Liquidation

3 Based on the description provided in the Standard & Poor’s Stock Guide.


6

III. Risk and Return Analysis of Quality Rankings Portfolios

In this section we present an analysis of the risk-return performance of different Quality Rankings portfolios.Our analysis provides significant insight into the value of using the rankings in a portfolio management context.

3.1 Methodology4

Our sample includes all common stocks that are listed on NYSE/AMEX/NASDAQ that have Quality Rankingsdata available in the S&P Compustat annual files. Our sample period begins in December 1985 and ends inDecember 2004, and extends previous studies.5 Section 6 provides a detailed description of sample size,number of companies, and sector composition of each of the Quality Rankings portfolios.

We construct seven portfolios based on Quality Rankings, ranging from A+ to D. We also construct two addi-tional portfolios, the “All-A”, comprised of stocks with A+, A, or A- rankings, and the “All-B, C & D”, com-prised of stocks with B+, B, B-, C & D rankings. We exclude stocks with prices lower than $1 to avoid theinfluence of extreme returns on portfolio performance. We compute portfolio returns on both equal-weight-ed and market-weighted bases and rebalance the portfolios monthly. When S&P Compustat stops reportingmonthly data on a stock, we rebalance the market capitalization invested in the stock among the remainingstocks in the Quality Rankings portfolio.

The market-weighted portfolios methodology conforms to the academic practice, but we also present equal-weighted returns for comparison. The Market-weighted approach of calculating portfolio returns may bemore realistic, as portfolio managers generally hold stocks in proportion to their market capitalizations.6 Inaddition, market weighting alleviates the potential bias that a few small, illiquid stocks with large returnshave on portfolio returns.

4 In the February 2003 report we rebalanced the portfolios only once a year and start calculating returns in April 1986. In this reportwe rebalance the portfolios on a monthly basis and we calculate returns starting in January 1985. We believe monthly rebalance ismore appropriate, as it captures the monthly quality ranking drift. For example, 10% of the S&P 500 ranked companies changed qual-ity ranking between December 2003 and December 2004.

5 Haugen (1979) analyzes risk characteristics of quality rankings for the period 1956-1971; Muller, Fielitz and Greene (1987) study therisk and return characteristics of quality rankings for the period 1970-1984.

6 A number of studies over the last decade provide evidence that institutions tilt portfolios towards larger-capitalization stocks. Thestudies include Badrinath, Gay and Kale (1989), Del Guercio (1995), and Gompers and Metrick (2001).



7

3.2 Risk and Return Analysis7

Table 2 and Figure 1 show that high-quality portfolios have the best overall performance on both return andrisk-adjusted bases. The risk-adjusted returns, as measured by the ratio of return to standard deviation or byrealized returns in excess of returns on a similar market beta portfolio, are higher for the high-quality portfolios.

The A+ Quality Rankings portfolio outperformed the S&P 500 by 110 basis points annually over the 19-yearsample period. The portfolio of All-A ranked stocks outperformed the S&P 500 and the portfolio of All-B, C &D ranked stocks by 70 basis points and 100 basis points, respectively. On a risk-adjusted basis, the perform-ance of the all-A portfolio compares even more favorably, as it has lower risk than the S&P 500 and the all-B, C & D portfolio. Over the period of analysis, the annualized standard deviation of the all-A portfolio is14.1%, compared to 15.6% for the S&P 500 and 17.6% for the all-B, C & D portfolio. The market beta of the all-A portfolio is lower than 1, at 0.87, whereas the market beta of all-B, C & D portfolio is higher than 1, at 1.08.As a result of higher return and lower risk, the all-A portfolio outperformed the all-B, C & D portfolio by almost300 basis points annually on a risk-adjusted basis.

7 This and the following sections focus on the market-weighted portfolio results.


8


TABLE 2: MARKET-WEIGHTED ANNUAL RETURNS FOR QUALITY RANKINGS PORTFOLIOS

ALLYEAR A+ A A- B+ B B- C & D ALL-A B, C & D S&P 500

1986 16.9% 22.7% 19.5% 19.1% 14.7% 3.3% -8.5% 19.6% 14.2% 18.7%1987 3.5% 3.0% 1.9% 1.3% 9.6% 10.4% 7.3% 2.9% 5.5% 5.2%1988 15.4% 16.5% 18.9% 16.5% 20.4% 17.5% 29.3% 16.8% 18.9% 16.6%1989 26.2% 33.3% 38.0% 22.5% 25.1% 23.4% 30.5% 32.5% 24.1% 31.6%1990 6.3% 2.1% -4.5% -13.6% -14.1% -15.6% -27.6% 0.8% -14.5% -3.1%1991 49.8% 25.6% 23.6% 36.6% 25.2% 22.0% 36.2% 32.6% 30.1% 30.4%1992 1.9% 7.2% 8.4% 10.1% 17.4% 17.7% 16.1% 5.6% 13.9% 7.6%1993 -2.2% 2.1% 12.5% 11.2% 27.6% 27.1% 25.1% 3.7% 20.4% 10.1%1994 3.5% 3.5% -0.3% -1.6% -0.3% 0.1% -3.9% 2.3% -0.9% 1.3%1995 42.6% 34.0% 35.5% 34.6% 37.6% 32.4% 29.9% 37.9% 34.8% 37.5%1996 23.3% 22.4% 22.0% 23.6% 25.2% 23.0% 0.0% 22.8% 23.4% 22.9%1997 37.9% 41.9% 37.4% 29.4% 25.8% 24.3% 13.1% 39.1% 26.9% 33.4%1998 32.9% 17.2% 21.6% 27.5% 23.6% 4.8% 54.7% 24.6% 23.4% 28.6%1999 16.6% 0.3% 14.5% 28.7% 33.8% 27.1% 102.0% 10.6% 32.5% 21.0%2000 4.9% 1.9% -0.5% -5.0% -7.0% -16.3% -22.8% 2.2% -8.5% -9.1%2001 -9.0% -4.0% -1.7% -15.9% -11.9% -3.3% -28.1% -5.3% -13.4% -11.9%2002 -20.3% -19.6% -8.4% -17.9% -26.0% -23.5% -44.2% -16.7% -23.2% -22.1%2003 19.5% 35.3% 24.5% 29.5% 34.7% 40.6% 58.8% 24.6% 35.2% 28.7%2004 9.1% 3.0% 15.6% 11.6% 17.3% 16.2% 4.6% 9.5% 13.5% 10.9%

$$1100,,000000 IInnvveesstteedd 108,158 85,528 116,818 81,944 104,494 69,496 53,876 101,976 86,375 90,785 CCoommppoouunndd RReettuurrnn 13.4% 12.0% 13.8% 11.7% 13.1% 10.7% 9.3% 13.0% 12.0% 12.3%SSttaannddaarrdd DDeevviiaattiioonn 15.8% 14.6% 13.8% 16.8% 17.9% 19.7% 29.3% 14.1% 17.6% 15.6%RReettuurrnn//RRiisskk 0.85 0.82 1.00 0.70 0.73 0.55 0.32 0.93 0.68 0.79BBeettaa 0.92 0.87 0.81 1.03 1.08 1.11 1.37 0.87 1.08AAllpphhaa 2.01% 1.25% 3.51% -0.74% 0.19% -2.09% -4.43% 2.09% -0.88%SSkkeewwnneessss -0.42 -0.63 -0.74 -1.05 -1.00 -1.22 -0.16 -0.67 -1.11 -0.84

FIGURE 1: VALUE OF $10,000 INVESTED IN ALL-A AND ALL-B, C & D PORTFOLIOS — MARKET-WEIGHTED RETURNS

$120,000

$100,000

$80,000

$60,000

$40,000

$20,000

$-

$101,976$90,785$86,375

A+, A & A-B+, B, B-, C & DS&P 500

85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04



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TABLE 3: EQUAL-WEIGHTED ANNUAL RETURNS FOR QUALITY RANKINGS PORTFOLIOS

ALLYEAR A+ A A- B+ B B- C & D ALL-A B, C & D

1986 20.8% 18.1% 19.4% 11.9% 9.5% 8.0% -0.1% 19.3% 7.9%1987 1.2% -0.8% -0.2% -2.0% -4.3% -6.6% -10.0% -0.1% -5.6%1988 19.6% 20.1% 25.6% 27.1% 32.5% 28.3% 17.4% 22.5% 26.6%1989 24.2% 23.8% 26.8% 15.8% 16.7% 9.5% 5.1% 25.2% 11.9%1990 -6.9% -10.2% -7.0% -14.2% -19.4% -23.9% -32.9% -8.1% -22.2%1991 44.1% 39.1% 39.7% 41.0% 41.9% 42.9% 37.1% 40.4% 40.8%1992 12.2% 17.3% 19.9% 18.1% 21.5% 31.1% 28.6% 17.4% 24.9%1993 2.1% 5.8% 12.2% 16.3% 21.1% 23.1% 30.8% 8.0% 22.9%1994 1.8% -1.6% -1.9% -0.5% 1.9% 2.8% -2.9% -1.1% 0.7%1995 34.0% 27.5% 29.9% 28.0% 33.6% 29.9% 35.8% 29.8% 31.7%1996 24.0% 21.2% 21.2% 19.9% 25.1% 21.7% 11.0% 21.7% 20.1%1997 42.8% 44.7% 42.0% 35.7% 29.9% 24.9% 8.8% 43.2% 25.3%1998 20.7% 9.7% 8.3% 3.5% 0.7% -5.3% -11.7% 10.9% -3.2%1999 -1.9% -7.9% -1.8% 3.7% 14.1% 25.3% 59.8% -3.9% 24.1%2000 21.2% 16.3% 17.4% 12.1% 11.4% 1.7% -10.5% 17.6% 4.6%2001 7.0% 17.7% 17.3% 23.0% 24.4% 26.5% 11.8% 15.7% 21.7%2002 -5.0% 1.6% 3.3% -0.8% -4.0% -7.3% -23.4% 1.4% -9.5%2003 29.2% 32.0% 34.5% 39.2% 48.8% 66.2% 100.5% 32.8% 65.3%2004 14.6% 19.6% 19.6% 19.8% 24.5% 28.4% 25.4% 18.9% 25.0%

$$1100,,000000 IInnvveesstteedd 145,217 131,684 177,014 136,075 170,591 152,646 74,433 155,234 138,599 CCoommppoouunndd RReettuurrnn 15.1% 14.5% 16.3% 14.7% 16.1% 15.4% 11.1% 15.5% 14.8%SSttaannddaarrdd DDeevviiaattiioonn 14.5% 13.3% 12.8% 14.3% 16.4% 18.7% 25.7% 13.1% 18.0%RReettuurrnn//RRiisskk 1.04 1.10 1.27 1.03 0.98 0.82 0.43 1.18 0.82SSkkeewwnneessss -0.74 -1.00 -1.30 -1.60 -1.54 -1.15 -0.29 -1.12 -1.22

FIGURE 2: VALUE OF $10,000 INVESTED IN ALL-A AND ALL-B, C & D PORTFOLIOS — EQUAL -WEIGHTED RETURNS

$180,000

$160,000

$140,000

$120,000

$100,000

$80,000

$60,000

$40,000

$20,000

$-

$155,234$147,518$138,599

A+, A & A-B+, B, B-, C & DBenchmark

85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04


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3.3 Downside Risk Analysis

As an alternative view of the sensitivity of our results to different phases of the market, we analyze the per-formance of Quality Rankings Portfolios in up and down markets. This analysis reveals some interestingresults on downside protection that high-quality portfolios provide.

Table 2 shows that S&P 500 performance was negative in 4 of the 19 years in our sample period. In each ofthese years, the all-A portfolio outperformed the S&P 500. However, the all-B, C & D portfolio underper-formed the S&P 500 in 3 years out of 4. S&P 500 performance was positive in 15 of the 19 years in our sam-ple period. In these up years, the all-A portfolio outperformed the S&P 500 and the all-B, C & D portfolio in 7of the 15 years. It is clear that historically low-quality stocks have frequently outperformed high-qualitystocks in up markets. As may be surmised from the relative returns of the All-A portfolio and as we will fur-ther show below, much of the value and most of the historical alpha of the All-A portfolio has been generat-ed in down markets. This is not surprising as the Quality Rankings are a measure of the persistence and sta-bility of earnings and dividends; i.e., a measure of fundamental risk. A high rank ought therefore to corre-spond to low fundamental risk.

We analyze monthly returns data to further characterize the performance of Quality Rankings portfolios indifferent market cycles. Figure 3 shows the sensitivity, as measured by market beta based on monthlyreturns, of Quality Rankings Portfolios in up and down markets. Figure 3 shows that the A+ portfolio is theonly Quality Rankings portfolio with a systematic risk (beta) greater than 1.0 in up markets and less than 1.0in down markets.

FIGURE 3: MARKET BETAS OF QUALITY PORTFOLIOS IN UP AND DOWN MARKETS

2.0

1.0

0.0

Down Markets

A+ A A- B+ B B- C & D All-A All-B, C & D

Up Markets



The portfolio of A+ rated stocks is also the portfolio with the highest systematic risk among the QualityRankings portfolios in up markets. Higher systematic risk in up markets is positive as it implies that the A+portfolio provides full or higher participation in the up movements. Equally important, in down markets, the A+portfolio has a low beta. This implies that in down markets, the A+ portfolio does not go down as much as themarket does.

This “switching beta” characteristic of A+ Quality Rankings portfolios is highly desirable from a risk per-spective. Indeed, portfolio managers often attempt to reduce portfolio volatility in down markets andincrease it in up markets. A market-weighted portfolio of A+ stocks delivers this desired changing exposureto the market without demanding a forecast of future returns. This asymmetric behavior of high-qualitystocks during up and down markets is in sharp contrast to the behavior of low-quality stocks. In decliningmarkets, low-quality stocks decline more than the market, and in rising markets, they rise less.

Figure 4 shows that when the market declines, low-quality portfolios perform significantly worse than high-quality portfolios. Thus, when monthly losses on the S&P 500 Index are larger than 8%, the S&P 500 indexdrops an average of 11.2% and the all-B, C & D portfolio falls on average of 12.5%, while the decline of theall-A portfolio is less at an average of 9.4%.

The risk-return analysis of Quality Rankings portfolios shows that high-quality portfolios exhibit a favorablerisk-return profile for long-term investors, as they provide above-market absolute and risk-adjusted returnsover the entire period and sub-periods under study. In addition, high-quality portfolios mitigate downsiderisk. High-quality portfolios, over time, achieve superior returns by losing less in down markets and, in thecase of the A+ portfolio, by gaining more in up markets.

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FIGURE 4: AVERAGE MONTHLY RETURNS IN UP AND DOWN MARKETS

12%

7%

2%

-3%

-8%

-13%

-18%

All-B, C & D

S&P 500

<-8% -8% to -4% -4% to 0% 0 to 4% +4% to +8% >8%

All-A

S&P 500 Returns


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IV. Fundamental Analysis of Quality Rankings Portfolios

4.0 Fundamental Analysis of Quality Rankings Portfolios

The analysis of the risk-return profile of Quality Rankings portfolios in Section 3 showed that high-qualityportfolios earned higher risk-adjusted returns over the period under study. In addition, high-quality portfoliosmitigate downside risk. Section 4 analyzes the sensitivity of Quality Rankings portfolios to the phases of cred-it and corporate earnings cycles. The results show that high-quality portfolios tend to provide higher returnsthan both low-quality portfolios and the market index during periods of increasing credit risk and decelerat-ing corporate earnings growth. This is probably because high-quality companies deliver stable earningsgrowth, whereas low-quality companies deliver unstable earnings growth. Earnings of low-quality compa-nies plummet when overall corporate earnings growth declines. The analysis in Section 4 sheds further lighton relative performance of high-quality and low-quality portfolios, especially periods when low-quality port-folios outperform, as they periodically do.

Sections 4.1 and 4.2 analyze fundamental characteristics that enable high-quality companies to deliver sta-ble growth in earnings and dividends. It then provides details on the stability of earnings and dividends forthe Quality Rankings Portfolios. During the sample period, despite carrying lower financial leverage, high-quality companies provided high and stable profitability.

Section 4.3 examines the consequences of stable profitability growth and low leverage in detail. In particu-lar, we examine the sensitivities of the growth in earnings for Quality Rankings portfolios over credit andaggregate profit cycles.

4.1 Size, Leverage, and Profitability

Table 4 presents statistics on the size, leverage, and profitability of different Quality Rankings portfolios forfour different periods. High-quality portfolios, on average, contain larger firms in terms of sales, total assetsand total capital. In particular, A+ companies have become progressively larger than those in the other port-folios. In fact, in 2004, average sales for the A+ companies were more than 4.5 times the average sales forthe A companies. The long-term debt to total assets ratio shows that low-quality companies tend to be moreleveraged than high-quality companies. Despite lower leverage, return on equity for high-quality companiesis well above that of low-quality companies.

TABLE 4.: SIZE, LEVERAGE AND PROFITABILITY OF QUALITY RANKINGS PORTFOLIOS AT DIFFERENT POINTS IN TIME

QUALITY SALES ($ MILLIONS) LONG-TERM DEBT/TOTAL ASSETS6 RETURN ON EQUITYRANKING 1985 1993 2001 2004 1985 1993 2001 2004 1985 1993 2001 2004

A+ 3,837 6,529 13,434 19,270 14.3% 14.6% 16.3% 15.9% 16.0% 20.5% 20.8% 18.3%A 2,659 2,877 5,829 4,095 14.4% 14.7% 23.4% 17.8% 12.8% 12.8% 14.7% 17.1%A- 1,910 2,995 5,782 4,975 19.8% 19.1% 20.2% 17.4% 11.0% 12.1% 15.0% 16.3%B+ 840 1,867 3.399 3,811 17.5% 18.2% 24.1% 19.7% 8.3% 11.7% 10.2% 15.2%B 969 1,508 3,196 3,687 12.3% 18.7% 28.4% 29.0% 5.8% 6.5% 2.1% 11.7%B- 364 1,057 897 1,264 21.1% 18.1% 25.4% 25.2% 5.9% 9.9% -2.9% 6.2%C 285 406 256 568 30.8% 25.5% 34.5% 31.7% -24.0% -4.5% -145.0% -5.1%

* Excludes Financials and General Electric Co. due to its large financial business



4.2 Growth and Profitability Analysis

Table 5 and Figure 5 provide details for the entire sample period on various profitability metrics. Table 5 pro-vides summary statistics for gross and net margin, return on equity, and five-year compound annualizedgrowth rate of earnings and dividend. Figure 4 graphically depicts annual values for net profit margin, returnon equity, and five-year compound annualized growth rate of earnings and dividends.

High-quality companies have higher and more stable gross and net margins. Companies with A+ QualityRankings have an average gross margin of 37.7% and average net margin of 7.9%. Moreover, high-qualitycompanies exhibit remarkable stability in their gross and net margin levels. The standard deviation of grossand net margins is 1.5% and 0.9%, respectively, for companies with A+ Quality Rankings. In contrast, lower-quality companies have lower and unstable margins. Net margins for the companies with B- QualityRankings are 2.0%, with a standard deviation of 2.2%. Our analysis, available upon request, shows that thehigh-quality companies also deliver steadier sales growth than low-quality companies.

Steadier sales growth and high and stable profit margins result in higher return on equity for high-qualitycompanies. In addition to the low standard deviation of return on equity, the fundamental risk of return onequity is lower for high-quality companies, as they carry lower leverage on average.

These higher and more stable levels of profitability bring about greater and more stable earnings and divi-dend growth for the higher-quality companies. Figure 5 shows that low-quality companies display a lowergrowth rate in dividends and a higher variability of dividends. We also looked at the dividend coverage, theratio between income before extraordinary items and dividend paid out, by Quality Ranking. The dividendcoverage is a measure of the “safety of the dividend.” It gives the investor an idea of how likely it is that thecompany will be able to generate enough profits to keep paying the dividend. High-quality stocks coveredtheir dividends quite comfortably over 1985-2004. Higher growth rate and stability of dividends indicates thatthe quality of future dividends is higher for high-quality companies.

13

TABLE 5: MEAN VALUES AND VOLATILITY OF PROFITABILITY METRICS FOR THE PERIOD 1985-2004

55 YYRR.. CCAAGGRR OOFF S&P GGRROOSSSS MMAARRGGIINN NNEETT MMAARRGGIINN RREETTUURRNN OONN EEQQUUIITTYY 55 YYRR.. CCAAGGRR OOFF EEAARRNNIINNGGSS DDIIVVIIDDEENNDDSS PPEERR SSHHAARREEQUALITYRANKING AVERAGE ST. DEV. AVERAGE ST. DEV. AVERAGE ST. DEV. AVERAGE ST. DEV. AVERAGE ST. DEV.

A+ 37.7% 1.5% 7.9% 0.9% 20.1% 2.1% 12.1% 2.0% 13.3% 13.3%A 38.0% 5.3% 7.5% 1.7% 15.2% 2.4% 7.5% 3.8% 10.2% 10.2%A- 34.2% 3.1% 7.0% 1.7% 14.0% 2.2% 5.8% 5.7% 6.9% 6.9%B+ 29.5% 3.1% 5.1% 1.5% 12.1% 2.6% 5.6% 6.5% 6.1% 6.1%B 26.3% 3.5% 3.9% 1.5% 9.6% 3.6% 4.5% 14.1% 2.4% 2.4%B- 24.9% 2.8% 2.0% 2.2% 5.9% 5.5% NM NM 1.5% 1.5%C 26.4% 3.9% -7.5% 13.5% -27.0% 40.5% NM NM -14.6% -14.6%


14


The dividend coverage trend mimics earnings growth for both low-quality and high-quality companies. Aswe noted earlier in this section, low-quality companies tend to be more leveraged. The next section exam-ines whether the high-quality companies’ ability to grow earnings steadily despite a low leverage allowsthem to weather the corporate earnings and credit cycles better. Our analysis shows that for low-qualitycompanies, during periods of earnings decelerations, the interest expense burden becomes a large portionof earnings, their cash flows contract, and dividend payments come under pressure. However, high-qualitycompanies’ earnings growth has a low correlation with overall corporate earnings and, therefore, their earn-ings and dividends are more insulated from profit recessions.

4.3 Performance of Quality Rankings Portfolios in Earnings and Credit Cycles

The analysis of risk and return of Quality Rankings portfolios shows that high-quality companies outperformlow-quality companies when S&P 500 return is negative. The analysis of fundamental characteristics showsthat high-quality companies deliver high and stable return on equity despite their low leverage. This sectionanalyzes the return, profitability, and creditworthiness of Quality Rankings portfolios in detail and in relationto each other.

FIGURE 5: GROWTH AND PROFITABILITY METRICS OVER TIME

NET PROFIT MARGIN

A+10%9%8%7%6%5%4%3%2%1%0%

B+

BS&P 500

RETURN ON EQUITY

A+

25%

20%

15%

10%

5%

0%

B+

BS&P 500

5-YEAR CAGR OF DIVIDENDS

A+

32%

22%

12%

2%

-8%

-18%

B+

B

S&P 500

5-YEAR CAGR OF EARNINGS

A+40%30%20%10%0%

-10%-20%-30%-40%

B+

B

S&P 500

85 87 89 91 93 95 97 99 01 03 04

85 87 89 91 93 95 97 99 01 03 04

85 87 89 91 93 95 97 99 01 03 04

85 87 89 91 93 95 97 99 01 03 04



A study of the relationship of Quality Rankings portfolios to the corporate earnings and credit cycles shedssome additional light on the drivers of relative performance of high- and low-quality stocks. In Figure 6 wegraph trailing four quarters earnings growth for the overall S&P 500 on the left vertical axis. An increase inthe height of the bars means that corporate earnings growth is accelerating. On the right vertical axis wereported the price index ratio between All-A and All-B, C & D stocks. When the line rises, it means that All-A stocks are outperforming the All-B, C & D stocks. The most important piece of information we take fromthe chart is that the highest-quality portfolio returns appear to be negatively correlated with the overall prof-it cycle. The reverse is true for low-quality portfolio returns.8

This is not surprising in light of our fundamental analysis findings that high-quality stocks tend to generate sta-ble earnings growth over time and are less susceptible to fluctuations in general economic activity (Figure 5).Our analysis also shows that higher-quality companies’ earnings growth has a low correlation to overall cor-porate earnings growth as represented by the S&P 500. Conversely, lower-quality companies’ earningsgrowth is highly correlated to the overall market. Over the sample period, A+ companies’ annual earningsgrowth has a correlation of about zero with earnings growth of the S&P 500; annual earnings growth of B+, B,B- and C companies have a high and positive correlation with earnings growth of the S&P 500. Our analysisalso shows that there is positive correlation between the credit downgrade/upgrade ratio and the perform-ance of high-quality stocks in relation to the performance of low-quality stocks. High-quality stocks outper-form in deteriorating credit cycles and low-quality stocks outperform in ebullient phases of credit cycles.

8 2004 proved to be an exception in the record of the link between the rate of earnings growth and the relative performance of highvs. low quality stocks. In fact, despite earnings deceleration, high quality stocks underperformed low quality stocks.

15

FIGURE 6: CORPORATE EARNINGS CYCLE AND PERFORMANCE OF QUALITY RANKINGS PORTFOLIOS

100%

80%

60%

40%

20%

0%

-20%

-40%

-60%

1.8

1.6

1.4

1.2

1.0

0.8

0.6

0.4

0.2

0.086 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

EPS Growth

Relative Performance

S&P

500

Quar

terly

Tra

iling

12

Mon

ths

GAAP

EPS

Gro

wth

Rela

tive

Perfo

rman

ce o

f All-

A Vs

. All-

B St

ocks

The explanation for the difference in performances of low- and high-quality stocks through the earnings andcredit cycles requires a further examination of credit markets’ impact on companies’ operations. Changingcredit market conditions have very different effects on low- and high-quality companies’ business and finan-cial risks, and profitability. Our analysis in Section 4.1 shows that low-quality companies are generally moreleveraged as indicated by the debt-to-total assets ratio. Although greater leverage allows low-quality compa-nies to be more profitable during times of low interest rates and earnings growth, it also makes their profitsmore vulnerable to tightening monetary policy and corporate earnings deceleration. The high leverage and vul-nerability of low-quality companies to credit and interest rate cycles are also reflected in their credit ratings.

Figure 7 shows the percent of companies with a Standard & Poor’s Credit Rating of A- or better on seniordebt.9 Generally, as one would expect, companies with high quality of earnings tend to also have high cred-it quality. Thus, low fundamental risk is consistent with high credit rating. However, we notice that evenamong high-quality companies there has been a decline in credit quality. Changes in financial policy and inthe business environment have been identified as the most significant drivers of the declining credit qualityof the U.S. corporations.10


16


9 The Standard & Poor’s Credit Rating represents the opinion of an issuer’s overall creditworthiness, apart from its ability to repayindividual obligations. This opinion focuses on the obligor’s capacity and willingness to meet its long-term financial commitments asthey come due. A credit rating of A- to AAA indicates strong capacity to meet financial commitments.

10 See the report “The Decline and Fall of the ‘AAA’ Rated Company”, CreditWeek, March 16 2005.

FIGURE 7: PERCENTAGE OF COMPANIES WITH S&P CREDIT RATING OF A- OR BETTER

70%

60%

50%

40%

30%

20%

10%

0%

A+

S&P 500

AA-

All-B, C & D

85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05


To analyze the interaction between creditworthiness and profit cycles, Figure 8 graphs the ratio betweeninterest expense and the sum of after-tax earnings and interest expense for high- and low-quality rankingportfolios11. A rising line indicates that interest cost is becoming a higher percentage of after-tax earnings.The sum of interest expense and after-tax earnings is effectively the total income available to providers ofcapital. Thus, this ratio can also be interpreted as the percent of total income going to satisfy the debthold-ers. For bondholders, the interest coverage ratio is a sort of safety gauge, since it provides a sense of howfar a company’s earnings can fall before it will start defaulting on its bond payments.

We notice that as we move from high- to low-quality companies, the level and volatility of the ratio increase.Changes in interest rates imply a larger impact on the interest expense burden of low-quality companies, whichin turn implies a larger negative impact on their future earnings and cash flows. Low-quality companies tend tohave more limited access to capital markets and tend to use more bank loans. Low-quality firms generally do nothave the same ability to raise external funds and, as a consequence, are more adversely affected by lower liq-uidity and higher short-term interest rates. Thus, during periods of increasing interest rates, low-quality compa-nies’ balance sheets weaken as net worth declines and higher interest costs reduce operating cash flows.

The effects of the corporate cash-flow squeeze on companies’ operations depend largely on companies’ability to smooth the drop in cash flows by borrowing. High-quality firms are more likely to have far greateraccess to commercial paper markets and other sources of low-cost short-term credit, and to respond to anunanticipated decline in cash flows by increasing their short-term borrowing. Conversely, because low-qual-ity firms do not have the same accessibility to short-term credit markets, they respond to the cash-flowsqueeze principally by selling off inventories through price discounting and by slashing production.

17


11 We actually chose to plot the inverse of the interest coverage ratio for clarity of representation. The interest coverage ratio meas-ures the immediate effect of increasing interest costs on profitability.

FIGURE 8: IMPACT OF INTEREST RATE ON INTEREST COVERAGE RATIO OF HIGH- AND LOW-QUALITY COMPANIES

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

10%

9%

8%

7%

6%

5%

4%

3%

2%

1%

0%85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

Low Quality (B) (left axis)

FedFund Rate (right axis)

High Quality (A+) (left-axis)


18


This conjecture is confirmed by our analysis showing that high-quality companies have progressivelyincreased the short-term debt portion of their total debt. For example, recently, A+ companies had, on average,a 58% short-term debt to total debt ratio, versus 27% for B companies. This is likely due to high-quality compa-nies’ recourse to the commercial paper market. Commercial paper is an unsecured form of short-term debtused primarily by large, well-established corporations for short-term borrowing needs. It is attractive becauseit usually carries an interest rate lower than those on a longer-term loan or an equivalent bank borrowing.Commercial paper issuance is restricted to companies with strong balance sheets and high cash flows.

In Figure 8 we also graphed the Fed Funds rate. It is evident from the graph that the trend in interest cover-age ratio for low-quality companies is dramatically different from that in high-quality companies and that itfollows the interest rate cycle. High-quality companies’ coverage ratio seems to be immune to interest ratemovements. In effect, A+ companies have been steadily improving their coverage ratios between 1985 and2004. For low-quality companies the story is radically different, as profits and cash flows decline followingan increase in interest rates. In fact, higher interest rates directly decrease corporate profits. After anincrease in interest rates, low-quality companies’ corporate profits tend to fall more quickly than costs,which tend to be quasi-fixed in nature. Both of these factors lead to a significant corporate cash squeezeduring a period of monetary tightening.

To summarize, since low-quality firms have more volatile businesses and more limited access to credit mar-kets, they tend to be affected more by credit constraints. In particular, it is precisely during recessions thatcredit constraints are more binding for low-quality companies. As interest rates rise and credit markets tight-en, low-quality companies’ balance sheets deteriorate and their cash flows decrease because of the high-er interest expense burden. Additionally, as higher interest rates decrease the overall demand in the econ-omy, low-quality companies’ revenues, profits and cash flows diminish further. Furthermore, since tighter liq-uidity reduces the amount of funds that banks can lend, low-quality companies, which are heavily depend-ent on bank loans, are impacted by tighter credit. This higher exposure of low-quality companies’ earningsand cash flows to tighter credit markets increases their business and financial risk and their probability ofcredit default. This translates into a higher risk during recessions for low-quality companies.

This asymmetric behavior of high- and low-quality companies through the profit and credit cycles helps toexplain why, in a period of worsening credit conditions characterized by higher short-term interest rates andhigher default premia, low-quality companies’ stocks become riskier and investors move into larger, better-collateralized, higher-quality companies.

5.0 Quality of Earnings

“While the problem of earnings management is not new, it has swelled in a market that isunforgiving of companies that miss their estimates. I believe that almost everyone in thefinancial community shares responsibility for fostering a climate in which earnings man-agement is on the rise and the quality of financial reporting is on the decline.”

—Arthur Levitt, speech on September 28, 1998

The term “quality of earnings” has been used with different interpretations in a variety of contexts. For exam-ple, in the bull market of the late 1990s, investors rewarded higher valuations to the companies that theythought provided high-quality earnings — companies that systematically, quarter after quarter, met or “beat”estimates. However, consistent and positive earnings surprises and earnings growth over a short time peri-od may reflect aggressive accounting, earnings management and poor quality of earnings.

As earnings growth is an important factor in the determination of Quality Rankings, an examination ofwhether there is any correspondence between Quality Rankings and quality of earnings is necessary. Ouranalysis confirms the prudence of Quality Rankings System. The Quality Rankings reflect earnings and divi-dend growth over a long time period over which it is difficult to sustain accounting manipulation. Our resultsshow that companies with higher Quality Rankings have higher quality of earnings.

Academics, practitioners, and regulators have used the term “quality of earnings” with varied meaningsover time as earnings of a corporation can be manipulated in several ways. We look at quality of earningsfrom three different perspectives. First, we analyze the difference between Standard & Poor’s Core Earningsand reported earnings. (Standard & Poor’s Core Earnings methodology, which standardizes the definition ofoperating earnings, has received wide recognition). Second, we analyze the magnitude of special andextraordinary items in relation to the reported earnings, a simple measure frequently analyzed in academicstudies (for example, Ball and Shivakumar (2001)). Finally, we show that the cross-sectional variation in ana-lyst estimates is lower for high-quality firms, suggesting that the reporting practices of high-quality firmsallow analysts to consistently analyze the underlying businesses.

5.1 Quality Rankings and Standard & Poor’s Core Earnings

Standard & Poor’s Core Earnings refers to the after-tax earnings generated from a corporation’s principalbusiness. Standard & Poor’s Core Earnings begins with as-reported earnings and then makes a series ofadjustments. Standard & Poor’s Core Earnings back out the following items from as-reported earnings asdefined by GAAP: extraordinary items, cumulative effects of accounting changes, discontinued operations,goodwill impairment charges, gains/losses from asset sales, pension gains, litigation or insurance settle-ments and proceeds, and reversal of prior- year provisions. Items included in the calculation of Standard &Poor’s Core Earnings are employee stock option grant expense, restructuring charges from ongoing opera-


V. Quality of Earnings

19


20


tions, asset writedowns, pension costs, purchased R&D expenses, merger- and acquisition-related expens-es, and unrealized gains/losses from hedging activities.12

Figure 9 shows, for the most recent four years, the difference between Standard & Poor’s Core Earnings andas-reported earnings in aggregate for each Quality Ranking portfolio. To examine the pattern of differencebetween Standard & Poor’s Core Earnings and as-reported earnings without influential observations, wegraph the median difference for the cross-section of companies in each Quality Ranking portfolio.

Our results show a striking positive relationship between “quality of earnings” as defined by the Standard &Poor’s Core Earnings methodology and the Quality Rankings.

In any single year low-quality ranking companies reported a larger difference between Standard & Poor’sCore Earnings and as-reported earnings than high-quality companies. This difference tends to be larger dur-ing periods of economic recession and deceleration of corporate earnings growth due to the increasingoccurrence of asset writedowns and restructuring charges.

5.3 Quality Rankings and Special and Extraordinary Items

The previous section focused on operating earnings. Several academic studies note that analysts focus onoperating earnings and exclude special and extraordinary items when estimating a company’s earningspower. However, special and extraordinary items have implications for previously reported and future earn-ings. If nonrecurring charges are actually prior-year expenses taken too late, or future expenses charged offearly, then the practice of ignoring nonrecurring charges and focusing on recurring operating income results inan overestimation of the firm’s earning power.13 Furthermore, while special items are frequently associated with

12 Blitzer, Friedman, and Silverblatt (2002).

FIGURE 9. MEDIAN PERCENTAGE DIFFERENCE BETWEEN CORE EARNINGS AND AS-REPORTED EARNINGS

40%

35%

30%

25%

20%

15%

10%

5%

0%2001 2002 2003 2004

A+

AA-B+

B

B-C

A+ AA-

B+

B

B-

C

A+ A A-B+

B

B-

C

A+ A A-B+B

B-

C



firms experiencing challenges in operating environment, companies’ management may use both the timing andthe magnitude of special items to engage in “earnings smoothing.” Even extraordinary items that are excludedfrom the calculation of reported (GAAP) earnings, such as charges related to discontinued operations, mayimpact sustainability of earnings and affect analysts’ forecasting ability of corporate earnings per share.

Figure 10 reports, for the 1985-2004 period, special and extraordinary items and discontinued operations asa percentage of operating income for the different Quality Rankings portfolios. We note that over the periodunder study, low-quality companies have reported a higher percentage of special and extraordinary itemsand discontinued operations.14

21

FIGURE 10. SPECIAL AND EXTRAORDINARY ITEMS AND DISCONTINUED OPERATIONS AS A PERCENTAGE OF OPERATINGINCOME FOR QUALITY RANKINGS PORTFOLIOS

A+

60%

40%

20%

0%

Special Items

85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

A

60%

40%

20%

0%85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

A-

60%

40%

20%

0%85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

B+

60%

40%

20%

0%85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

B

60%

40%

20%

0%85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

S&P 500

60%

40%

20%

0%85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04

Extraordinary Items & Discontinued Operations

13 White, Sondhi and Fried (1997), p. 64.14 Note that graphs have same scale to facilitate comparison among Quality Ranking groups.


22

5.3 Quality Rankings and Dispersion in Analyst Forecasts

The presence of special and extraordinary items complicates the task of forecasting earnings. The accura-cy of earnings forecasts is of primary importance to market participants because earnings projections are acentral input to investment decisions. In addition, investors demand higher risk premiums for investments incompanies with higher uncertainty of future earnings.

Figure 11 illustrates the relationship between analysts’ average long-term projected growth rates of earn-ings and the uncertainty surrounding those forecasts as measured by the average standard deviation of theestimates as of May 2005. High-quality companies are associated with a lower degree of future earnings’uncertainty. Conversely, analysts’ disagreement on future earnings growth increases as we move from high-to low-quality companies. The distance between the hollow diamonds and the solid diamonds is equivalentto the estimated growth rate minus two standard deviations, and represents the downside risk embedded inthose estimates.

To summarize, companies ranked highly by the Quality Rankings System exhibit higher quality of earnings asindicated by the low divergence between their GAAP earnings and Standard & Poor’s Core Earnings, and bythe low ratio of special and extraordinary items to reported earnings. Lower dispersion in analyst estimatesalso indicates higher quality of earnings for high-quality companies. Earnings quality is of primary impor-tance to investment analysts since earnings are a very important input to valuation models that try to calcu-late the intrinsic value of a stock.


FIGURE 11: ANALYSTS’ GROWTH FORECAST CONSENSUS AND DISPERSION AS OF DECEMBER 2004

25.0

19.5

14.0

8.5

3.01.0 2.0 3.0 4.0 5.0 6.0 7.0

Standard Deviation of Long-Term Consensus Growth Estimates

A+A

A-

B+ B

B-

C & Below

Long

-Ter

m C

onse

nsus

Gro

wth

Est

imat

es


6.1 Quality Rankings Portfolio Characteristics and Composition

Table 6 illustrates the distribution of the Quality Rankings at different points in time. Currently, Standard &Poor’s ranks over 4,000 U.S. companies.15 The quantitative model that generates the rankings is based on anabsolute score, and not on a relative score to the universe. There is no adjustment made to force a certainpercentage of companies in each quality bracket; as a result, the rankings are not uniformly distributed.Currently, approximately only 13% of all the ranked stocks have ranks of A- or better; the majority of rankedstocks fall in the lower-quality segment.

23

15 The present study refers to the Quality Rankings System on U.S. companies that qualify under the 10 years of information requiredby the Quality Rankings model. Standard & Poor’s also ranks stocks internationally.

TABLE 6: QUALITY RANKINGS: NUMBER AND PERCENT OF TOTAL RANKED STOCKS

1985 1990 1995 2004QUALITY NUMBER PERCENT NUMBER PERCENT NUMBER PERCENT NUMBER PERCENTRANKING OF COMPANIES OF TOTAL OF COMPANIES OF TOTAL OF COMPANIES OF TOTAL OF COMPANIES OF TOTAL

A+ 173 6.4% 115 4.6% 82 2.8% 73 2.0%A 280 10.3% 205 8.1% 157 5.3% 182 5.0%A- 382 14.1% 248 9.8% 205 6.9% 237 6.5%B+ 623 22.9% 413 16.4% 504 17.1% 518 14.1%B 482 17.7% 483 19.2% 635 21.5% 662 18.1%B- 443 16.3% 603 23.9% 771 26.1% 889 24.2%C 334 12.3% 455 18.0% 597 20.2% 1106 30.2%

VI. Portfolio Characteristics of Recent and Historical Quality Rankings Portfolios

FIGURE 12: HIGH-TO-LOW QUALITY RATIO OVER TIME

70%

60%

50%

40%

30%

20%

10%

0%1985 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 2004


24

A historical analysis of Quality Rankings is more informative about the rankings’ dynamics than a snapshotat a specific point in time. Since the Quality Rankings are based on earnings growth and stability over a 10-yearperiod, one would expect that the quality distribution and sector makeup change over time in relation tomacro- and microeconomic factors. Table 6 and Figure 12 show that over the period under study, the pro-portion of lower-quality stocks has been increasing and that the high-to-low quality ratio has been steadilydeclining.16 A plausible explanation for the decline in the number of high-quality companies is that the busi-ness environment has become increasingly competitive due to market deregulation and global competition.As a consequence, companies able to achieve long-term stable earnings growth are becoming increasing-ly scarce. In addition, the percentage of companies paying a dividend has been steadily declining since 1985.

Table 7 reports the price per share, market value and trading volume by Quality Rankings portfolios. On aver-age, higher-quality companies have higher market values and higher prices per share. In addition, tradingvolume is significantly higher for the higher-quality portfolios. Liquidity is a significant factor that institution-al money managers evaluate before buying a stock, as they prefer to invest in very liquid issues that can bebought and sold without impacting the market price.

High-quality stocks are ideally employed in portfolio strategies that try to maintain low portfolio turnover. Ineffect, besides their greater liquidity, average prices per share and market size, high-quality companies rankingsare quite stable over time. This is intuitive, as the model is mainly based on stability of earnings and dividendsover 10 years. Table 8 is a transitional probabilities matrix for the rankings. It shows the percent of occasionsin which a company with a certain rank in the current year maintains the same rank in the next year.


TABLE 7: PRICE, MARKET VALUE AND TURNOVER BY QUALITY RANKINGS

QUALITY RANKS MEDIAN PRICE PER SHARE MEDIAN MARKET VALUE ($ MILLIONS) AVERAGE MONTHLY VOLUME ($ MILLIONS)

A+ 42 6,219.3 1,909A 35 1,570.8 800A- 31 1,632.6 697B+ 28 977.0 596B 23 713.6 484B- 12 180.4 272C 3 50.1 100

16 The high-to-low quality ratio is the ratio between the total number of A+, A and A- stocks to the total number of B, B-, C and Dstocks. B+ stocks (average rank) are intentionally omitted to highlight the high-low-quality relationship.


25

Thus, for example, based on past data, the probability that a company ranked A+ in the current year willmaintain the same rank in the next year is 84%. We notice that high-quality companies are significantly morelikely to maintain their high-quality ranking over time, making their current rankings a significant predictor oftheir future rankings.

6.2 Quality Rankings Sector Makeup

Figure 13 shows the sector share of higher-quality stocks (A- or better).18 Currently, financials dominate, rep-resenting about 31% of higher-quality stocks. An analysis of earnings quality by sector composition over timereveals that high quality is not dominated by one or two sectors. Instead, it oscillates between sectors andindustries over time in relation to sectors’ earning power and stability. In turn, steady growth is affected by sev-eral factors, such as competition, market deregulation and government intervention. For example, the deregu-lation of the electric utility and natural gas industries had a dramatic impact on the earnings quality of the util-ities sector. Prior to 1992, highly regulated and vertically integrated utility companies were assured stable earn-ings growth. Then, beginning with the National Energy Policy Act of 1992, the Federal Energy RegulatoryCommission (FERC) started the process of opening up the wholesale operations to a more competitive marketenvironment, which made earnings growth much more volatile and difficult to predict. Contrary to general per-ception, the technology sector has always represented a small fraction of the high-quality universe. This is dueto intense competition and technology’s inherent cyclical nature caused by the incessant introduction of newtechnologies that result in increasingly shorter product life cycles, and volatile profit margins and earnings.

TABLE 8: TRANSITIONAL PROBABILITIES MATRIX FOR QUALITY RANKINGS

PERCENTAGE BREAKDOWN OF RANKING IN FOLLOWING YEARLAPSED NUMBER OF

A+ A A- B+ B B- C D RANKING17 OBSERVATIONS

A+ 83.73 12.74 0.53 0.12 0.12 0.00 0.00 0.06 2.71 1,696A 5.22 74.25 15.21 1.25 0.10 0.00 0.03 0.03 3.91 3,122A- 0.00 9.84 68.23 16.80 0.55 0.02 0.20 0.02 4.34 4,035B+ 0.00 0.12 6.29 73.43 13.53 0.31 0.30 0.11 5.92 8,080B 0.00 0.00 0.01 9.03 69.50 13.13 1.30 0.18 6.84 9,266B- 0.00 0.00 0.00 0.00 8.89 70.27 12.94 0.41 7.49 10,982C 0.00 0.00 0.00 0.00 0.00 13.94 73.78 1.33 10.92 8,943D 0.00 0.00 0.00 0.00 0.00 0.38 1.89 41.21 56.5 529

17 Percent of companies whose Quality Rankings lapsed due to merger, bankruptcy, or other event.

CURR

ENT

YEAR

RAN

K

NEXT YEAR’S RANK


18 High Quality Rankings stocks as a percentage of total for the S&P 500.


26

The low percentage of health care companies among the high-quality companies may also be surprisingsince many investors generally view the health care sector as a defensive one capable of generating rev-enue and earnings growth in both good and bad times. The reality is that the healthcare sector is made ofdiverse sub-industries such as medical devices, managed health care, pharmaceuticals, and biotechnology,all driven by different factors. For example, in the 1991-1992 period, the sharp fall in prescription prices dimin-ished drugs companies’ pricing power, margins and, therefore, earnings growth. By the same token, gov-ernment regulation that affects reimbursement programs has, in the past, impacted the various segments ofthe health care sector making their growth patterns more volatile. On the other hand, we notice that a major-ity of large pharmaceutical firms have consistently been given high Quality Rankings. For example, Johnson& Johnson was consistently ranked A+ or A from 1968 to 2004. Over the 1985-2004 period, as one wouldexpect, the company generated respectable compounded annual growth rates of 14.8% in both dividendsand earnings.

The financial sector has the greatest concentration of high-quality companies, and its growing dominanceof the high-quality universe is explained by industry trends and macroeconomic factors. The performance ofthis sector has been driven by ongoing consolidation, technology-driven efficiency improvements, diversifi-cation into new lines of business, better duration matching of asset and liabilities, and a favorable interestrate environment (versus the late 1970s and early 1980s). The financial sector achieved more stable marginsand earnings growth as fee-based revenues increasingly represented a higher percentage of total revenues,and as they reduced their dependence on interest rate-based income. The major lesson we learn from Figure13 is that quality is not static, but fluctuates across sectors and industries according to numerous businessenvironmental factors. Thus, we should not assume that today’s high-quality sectors, industries or compa-nies will be tomorrow’s.


FIGURE 13: CURRENT BREAKDOWN OF AND TREND IN S&P 1500 SECTOR COMPOSITION OF ALL-A PORTFOLIO

Utilities6.6%

Technology4.5%

Telecoms1.0%

Energy0.3% Materials

4.5% Industrials15.7%

Discretionary15.7%Staples

11.2%Healthcare

5.6%

Financials34.6%

40%

35%

30%

25%

20%

15%

10%

5%

0%1994 95 96 97 98 99 00 01 02 03 2004

FinancialsTechnologyUtilities


6.3 Quality Ranking, Capitalization, and Growth-Value Split Analysis

Next, we present the distribution of Quality Rankings and their sensitivity to growth and value factors for thethree different stock capitalization universes: large-caps (S&P 500), mid-caps (S&P MidCap 400), and small-caps (S&P SmallCap 600).

Figure 14 shows that, as of June 2005, a majority of the high-quality companies are in the S&P 500 universe.Of the 80 A+ companies, 44 are in the S&P 500, 12 are in the S&P MidCap 400, and just 2 are in the S&PSmallCap 600. This does not come as a surprise since the S&P 500 is populated with large companies thathave longer operating histories. Conversely, smaller capitalization firms are likely to be relatively newer busi-nesses with shorter operating histories. Thus, small-cap stocks, which are traditionally associated with higherrisk premia, also have overall lower-quality rankings.

Table 9 reports the growth-value splits, by price-to-book value, for the three stock universes as of June 2005.We notice that high-quality companies (A+, A and A-) do not fall exclusively in either the value or growth category. Rather, we see a quite balanced split between growth and value for all three stock universes.

27

TABLE 9: GROWTH-VALUE SPLIT OF HIGH QUALITY (A+, A AND A-) AS OF JUNE 2005

MARKET VALUE ($ MIL) MARKET VALUE OF UNIVERSE AS AUNIVERSE OF UNIVERSE % OF TOTAL INDEX MARKET CAP GROWTH % VALUE %

All-A in S&P 500 5,320,557.7 48.2% 57.5% 42.5%All-A in S&P MidCap 400 258,001.7 23.2% 50.6% 49.4%All-A in S&P SmallCap 600 746,63.4 13.8% 51.8% 48.2%


FIGURE 14. QUALITY RANKINGS DISTRIBUTION BY INDEX

60%

50%

40%

30%

20%

10%

0%A+ A A- B+ B B- C

Perc

ent o

f Ran

ked

Stoc

ks in

Inde

x S&P 500S&P MidCap 400S&P SmallCap 600


28

Figure 15 reports the percentage of high-quality companies (all-A) classified as growth or value by the S&P500/Barra Growth and Value Indices.

We observe that over the period under study, the all-A portfolio has tilted toward value. More recently, theportfolio has been increasing its exposure to the growth universe.


FIGURE 15: ALL-A COMPANIES CLASSIFIED AS GROWTH OR VALUE AS A PERCENTAGE OF TOTAL

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%1985 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 2004

Value-HQ

Growth-HQ


29


6.4 Valuation Multiples Analysis

High-quality stocks in a portfolio provide higher risk-adjusted returns. But the question remains: Does thisrisk protection come at a cost? In other words, is the high-quality portfolio’s greater profitability reflected inhigher market valuation multiples?

In order to answer this question, we examined various valuation multiples. The left-side part of Figure 16graphs the price-to-book and price-to-sales for the different Quality Rankings portfolios. It is evident that thehigher the quality, the higher the market valuation multiples. A valuation matrix that relates market multipleswith their fundamental drivers is more informative than simply comparing market multiples across stocks,sectors or industries. On the right side of Figure 13 we plot the price-to-book as a function of return on equi-ty and the price-to-sales as a function of net profit margin for the different Quality Rankings portfolios. Thereis almost a perfect correlation between profitability and market valuation multiples — the higher the quality,the greater the profitability and the higher the market multiples. Higher price-to-book ratios reflect higherreturns on equity, and higher price-to-sales ratios reflect higher net profit margins. Thus, the market cor-rectly assigns valuation premia to high-quality stocks in terms of price-to-book as well as price-to-salesratios. These valuation premia appear to persist over the entire period under study.

FIGURE 16: PRICE-TO-BOOK AND PRICE-TO-SALES RATIOS FOR QUALITY RANKINGS PORTFOLIOS

PRICE-TO-BOOK

7.0

6.0

5.0

4.0

3.0

2.0

1.0

0.0

RELATIONSHIP BETWEEN PRICE-TO-BOOK AND RETURN ON EQUITY 1985-2004

4.54.03.53.02.52.01.51.00.50.0

PRICE-TO-SALES

3

2.5

2

1.5

1

0.5

0

RELATIONSHIP BETWEEN PRICE-TO-SALES AND NET PROFIT MARGIN 1985-2004

1.81.61.41.21.00.80.60.40.20.0

All-A

All-B & C

All-A

All-B & C

85 87 89 91 93 95 97 99 01 03 04 0.0% 5.0% 10.0% 15.0% 20.0% 25.0%

0.0% 2.0% 4.0% 6.0% 8.0% 10.0%85 87 89 91 93 95 97 99 01 03 04

Pric

e-to

-Boo

k Ra

tioPr

ice-

to-S

ales

Rat

io

Return on Equity

Net Profit Margin

A+

A

A-B+

BB-

A+A

A-B+

BB-


30

However, we do not find the same clear-cut relationship for the price-to-earnings multiple. Figure 17 graphsthe earnings yield, the inverse of the price-to-earnings multiple, for the high quality (A+, A & A-) portfolio andthe low-quality (B+,B & B- & C) portfolio.19 As expected, low-quality portfolios have more volatile earningsmultiples due to their higher earnings volatility. More importantly, we notice that despite superior long-termearnings growth and earnings stability, the market does not always attribute a valuation premium to high-quality companies in terms of earnings multiple.

The price-to-earnings for a stable growth firm can be derived from the stable-growth dividend discountmodel. According to this model, the price-to-earnings ratio is an increasing function of the payout ratio andthe growth rate, and a decreasing function of the riskiness of the firm. Therefore, during periods of strongcorporate earnings growth and low credit risk, low-quality companies’ earnings multiples will be higher thanthose of high-quality companies, as investors are willing to move to riskier investments. However, when cor-porate earnings growth decelerates and credit risk increases, the high-quality companies will be a moreattractive investment since they pay out more dividends and have less business and financial risk. Thus, theearnings yield ratio trend seems to reflect a cyclical component related to overall corporate earnings growthand credit risk. When earnings growth decelerates, investors might be willing to pay a premium for high-quality companies for the safety they provide; Section 4 shows that when profits decline and the credit envi-ronment tightens, high-quality companies provide safety by providing more stable earnings, higher dividendgrowth rates, lower financial and business risk, and higher profitability.


19 Since the price-to-earnings ratio is very volatile, for clarity of representation, we chose to plot the earnings yield.

FIGURE 17: EARNINGS YIELD FOR A+ AND B QUALITY RANKINGS PORTFOLIOS

12%

10%

8%

6%

4%

2%

0%

-2%1985 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 2004

All-A

All-B & C


VII. Conclusion

31

Standard & Poor’s Quality Rankings provide a simple yet very useful summary measure of the quality of acompany’s stock. The Quality Rankings System captures the growth and stability of earnings and dividendrecord of a company over the most recent 10-year period in a single symbol. The assessment of fundamen-tals over this long period ensures that the Quality Rankings are not unduly influenced by short-term factorsand possible accounting manipulations.

Quality Rankings are not designed to be a comprehensive measure of the quality of a company’s accountingpractices, or a tool to provide investment advice. Analytical products such as Standard & Poor’s CoreEarnings and STARS provide more detailed analysis of a company’s accounting practices. Standard & Poor’sSTARS are also designed to offer investment advice.

Our analysis shows, however, that despite their brevity and simplicity, Quality Rankings are correlated withseveral measures of quality of earnings, including Standard & Poor’s Core Earnings. Our analysis also showsthat portfolios of high-quality companies provide higher returns and lower risk. The risk characteristics ofhigh-quality portfolios are attractive, as they provide full participation in up markets and mitigate downmovements of the market.

We further characterize the factors that contribute to the better performance of high-quality companieswhen the market is declining. High-quality companies perform better – in terms of profitability and portfolioreturns, when aggregate earnings are declining and the credit cycle is tightening because of their steadi-ness of sales growth, level and stability of profitability, size, and lower leverage.

High-quality companies are appealing investments because of their better risk-return characteristics, higherliquidity and large size.


32

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34

Disclaimer

This report is published by Standard & Poor’s, 55 Water Street, New York, NY 10041. Copyright © 2003.Second Edition. Standard & Poor’s (S&P) is a division of The McGraw-Hill Companies, Inc. All rightsreserved. Standard & Poor’s does not undertake to advise of changes in the information in this document.Standard & Poor’s has used information available on public websites to produce this report.

These materials have been prepared solely for informational purposes based upon information generallyavailable to the public from sources believed to be reliable. Standard & Poor’s makes no representation withrespect to the accuracy or completeness of these materials, whose content may change without notice.Standard & Poor’s disclaims any and all liability relating to these materials, and makes no express or impliedrepresentations or warranties concerning the statements made in, or omissions from, these materials. Noportion of this publication may be reproduced in any format or by any means including electronically ormechanically, by photocopying, recording or by any information storage or retrieval system, or by any otherform or manner whatsoever, without the prior written consent of Standard & Poor’s.

Standard & Poor’s does not guarantee the accuracy and/or completeness of the Standard & Poor’s QualityRankings System, any data included therein, or any data from which it is based, and Standard & Poor’s shallhave no liability for any errors, omissions, or interruptions therein. Standard & Poor’s makes no warranty,express or implied, as to results to be obtained from the use of the Standard & Poor’s Quality RankingsSystem. Standard & Poor’s makes no express or implied warranties, and expressly disclaims all warrantiesof merchantability or fitness for a particular purpose or use with respect to the Standard & Poor’s QualityRankings System or any data included therein. Without limiting any of the foregoing, in no event shallStandard & Poor’s have any liability for any special, punitive, indirect, or consequential damages (includinglost profits), even if notified of the possibility of such damages.

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