The goal of active equity management is to earn a portfolio return that exceeds the return of a passive benchmark portfolio, net of transaction costs, on a risk-adjusted basis. The job of an active equity manager is not easy. If transaction costs and fees total 1.5 percent of the portfolio’s assets annually, the portfolio has to earn a return 1.5 percentage points above the passive bench- mark just to keep pace with it. Further, if the manager’s strategy involves overweighting specific market sectors in anticipation of price increases, the risk of the active portfolio may well exceed that of the passive benchmark, so the active portfolio’s return will have to exceed the benchmark by an even wider margin to compensate for its higher risk.
Exhibit 17.5 provides a broad overview of the different strategies that investment managers might adopt in forming their portfolios, as well as the investment “philosophy” that underlies each strategy. Notice, first of all, that the passive strategies we just considered are based (at least implicitly) on the notion that capital markets are efficient and so equity portfolios should be invested to mimic broad indexes and not traded actively. The realm of active management, how- ever, is one in which managers are effectively “betting” against markets being perfectly efficient.
For convenience, Exhibit 17.5 characterizes these bets as falling into three general categories:
(1) fundamental, (2) technical, and (3) market anomalies and security attributes.
As we saw in Chapter 11, the three-step investment process begins at the top with an analysis of broad country and asset class allocations and progresses down through sector allocation deci- sions to the bottom level where individual securites are selected. The alternative to this “top- down” approach to investing was a “bottom-up” process that simply emphasized the selection of securities without any initial market or sector analysis. In similar fashion, active equity manage- ment based on fundamental analysis can start from either direction, depending on what exactly the manager thinks is mispriced relative to his or her valuation models. Generally, active man- agers use three generic themes in an attempt to add value to their portfolios relative to the bench- mark. First, they can try to time the equity market by shifting funds into and out of stocks, bonds, and T-bills depending on broad market forecasts and estimated risk premiums. Second, they can shift funds among different equity sectors and industries (e.g., financial stocks, technology Fundamental
Strategies
EXHIBIT 17.4 DETAILS OF THE SPDR EXCHANGE-TRADED FUND
© 2002 Bloomberg L.P. All rights reserved. Reprinted with permission.
A. Description
SPDR TRUST SERIES 1 OBJECTIVE—INDEX FUND—LARGE CAP
SPDR Trust Series 1 issues exchange-traded funds called Standard & Poor’s Depositary Receipts or “SPDRs.” The SPDR Trust holds all of the common stocks of the Standard & Poor’s 500 Composite Stock Price Index and is intended to provide investment results that, before expenses, generally correspond to the price and yield performance of the S&P 500 Index.
BLOOMBERG CLASSIFICATION DATA
Asset Class Equity Style Index Fund
Market Cap Focus Large Cap Geographic Focus U.S.
CURRENT DATA
Underlying Index 12) SPX
1) GP Price $114.52
52Wk Hi 5/22 $132.090
52Wk Lo 9/21 $ 93.800
NAV 3/28 $114.72
INAV $115.00
%Premium n.a.
Shares Out (×000) 3/28/02 250783.0
Market cap(mil) $28719.67
SPDRs are designed to provide a security whose market value approximates 1/10 the value of the underlying S&P 500 Index.
B. Historical Returns
CURRENT RETURN PERCENTILE
AS OF3/28/02 FUND SPX DIFFERENCE ALL OBJECTIVE
3) TRA 1 Week –.67 –.52 –.15 31 50
1 Month 3.32 3.76 –.44 68 30
3 Month –1.00 –.84 –.16 22 52
4) COMP YTD .48 .27 .21 39 54
1 Year .84 .87 –.03 25 56
3 Year –2.66 –2.43 –.23 11 16
9) HRH 5 Year 9.59 9.68 –.09 82 n.a.
HISTORICAL FUND SPX DIFFERENCE ALL OBJECTIVE
2001 –11.75 –11.89 .14 22 62
2000 –9.73 –9.10 –.63 17 42
1999 20.39 21.04 –.65 80 54
1998 28.69 28.58 .11 94 n.a.
1997 33.48 33.38 .10 90 n.a.
1996 22.55 22.96 –.41 87 n.a.
1995 38.05 37.62 .43 94 n.a.
1994 .40 1.33 –.93 95 n.a.
1993 n.a. 10.06 n.a. n.a. n.a.
1992 n.a. 7.62 n.a. n.a. n.a.
20
10
0
–10
–20
20
10
0
–10
–20 29MAR 31JAN02
30NOV 28SEP
31JUL 31MAY 30MAR01
1 Yr Performance vs. Benchmark Indexes
SPY SPX
stocks, consumer cyclicals, durable goods) or among investment styles (e.g., large capitalization, small capitalization, value, growth) to catch the next “hot” concept before the rest of the market does. Third, equity managers can do stockpicking, looking at individual issues in an attempt to find undervalued stocks—that is, to buy low and sell high.
An asset class rotation strategy is one that shifts funds in and out of the stock market depend- ing on the manager’s perception of how the stock market is valued compared to the various alter- native asset classes. Formally, such a strategy is called tactical asset allocationand will be described in more detail later in the chapter. Alternatively, a sector rotation strategyinvolves positioning the portfolio to take advantage of the market’s next move. Often, this means empha- sizing or overweighting (relative to the benchmark portfolio) certain economic sectors or indus- tries in response to the next expected phase of the business cycle. Exhibit 17.6 contains sugges- tions on how sector rotators may position their portfolios to take advantage of stock market trends during the economic cycle.
In general, asset and sector rotation strategies can be extremely profitable but also very risky for a manager to follow. This is shown in Exhibit 17.7, which lists the annual returns in each of several asset and sector classes from 1981 to 2000. The chart documents the tremendous volatil- ity that existed during this period. For instance, bonds, which was the best-performing asset class in 1990, was the next-to-worst class in the following year. Conversely, large-cap growth stocks were the single best place to invest funds for six years (i.e., 1994–1999) but this period was bracketed by years when this sector performed quite poorly. The message from this display is clear: While there are impressive gains to be made by correctly timing the “hottest” (or the
“coldest”) market sectors, a manager must be right substantially more than he or she is wrong.
Because this is an extremely difficult thing to do consistently, many investors choose to interpret Exhibit 17.7 as ultimately extolling the virtue of asset and sector class diversification.
Finally, a fundamental stock-picker operating on a pure “bottom-up” basis will form a port- folio of equities that can be purchased at a substantial discount to what his or her valuation model indicates they are worth. As we discussed in Chapter 15, these valuation models might be based on absolute judgments about the future of the company (i.e., discounted cash flow) or relative 662 CHAPTER 17 EQUITYPORTFOLIOMANAGEMENTSTRATEGIES
EQUITY PORTFOLIO INVESTMENT PHILOSOPHIES AND STRATEGIES Passive Management Strategies
1. EFFICIENTMARKETSHYPOTHESIS Buy and hold
Indexing
Active Management Strategies 2. FUNDAMENTALANALYSIS
“Top down” (e.g., asset class rotation, sector rotation)
“Bottom up” (e.g., stock undervaluation/overvaluation) 3. TECHNICALANALYSIS
Contrarian (e.g., overreaction) Continuation (e.g., price momentum) 4. ANOMALIES ANDATTRIBUTES
Calendar effects (e.g. weekend, January)
Security characteristics (e.g., P/E, P/B, earnings momentum, firm size) Investment style (e.g., value, growth)
EXHIBIT 17.5
assessments of how attractive the stock is compared with shares in otherwise similar firms that might be acquired (i.e., relative price multiples). In either case, it is usually true that the active manager will find stockpicking to be a more reliable, although less profitable, way to add value to a client than through market timing.
In Chapter 16, we discussed the role that technical analysis plays in the stock evaluation process.
As we saw, assessing past stock price trends in an effort to surmise what information they imply about future price movements was one of the primary tools of this analytical approach. Active managers can form equity portfolios on the basis of past stock price trends by assuming that one of two things will happen: (1) past stock price trends will continue in the same direction, or (2) they will reverse themselves.
A contrarianinvestment strategy is based on the belief that the best time to buy (sell) a stock is when the majority of other investors are the most bearish (bullish) about it. In this way, the contrarian investor will attempt to always purchase the stock when it is near its lowest price and sell it (or even short sell it) when it nears its peak. Implicit in this approach is the belief that stock returns are mean reverting, indicating that, over time, stocks will be priced so as to produce returns consistent with their risk-adjusted expected (i.e., mean) returns. DeBondt and Thaler demonstrated the potential benefits of forming active portfolios based on this notion.6Specifi- cally, they showed that investing on an overreaction hypothesis could provide consistently supe- rior returns. Exhibit 17.8 illustrates a summary of their experiment in which they measured returns to a portfolio of stocks that had had the worst market performance over the prior three years (i.e., “losers”) and a portfolio of stocks with the best past performance (i.e., “winners”). If investors overreacted to either bad news or good news about companies, as DeBondt and Thaler contended, we should see subsequent abnormal returns move in the opposite direction. The cumulative abnormal returns (CARs) shown in the display appear to support this notion, although the evidence is stronger for losers than for winners.
Technical Strategies
Economic Cy cle
T r o ugh
Peak
Financial Stocks Excel
Capital Goods Excel
Basic Industries
Excel
Consumer Staples Excel Economy's
Current Phase Consumer
Durables Excel
EXHIBIT 17.6 THE STOCK MARKET AND THE BUSINESS CYCLE
Source: Susan E. Kuhn, “Stocks Are Still Your Best Buy,” Fortune, 21 March 1994, 140. © 1994 Time Inc. All Rights Reserved.
6Werner F. M. DeBondt and Richard Thaler, “Does the Stock Market Overreact?” Journal of Finance 40, no. 3 (July 1985): 793–805.
ASSET AND SECTOR CLASS RETURN PERFORMANCE: 1981–2000 19811982198319841985198619871988198919901991199219931994199519961997199819992000 SVBSVBFFFSVLGBSGSVFFLGLGLGLGSGSV 14.85%32.65%38.63%15.15%56.14%69.46%24.64%29.47%36.40%8.96%51.18%29.15%32.57%7.78%38.13%23.97%36.52%42.16%43.09%22.83% BSVSLVLGLVLGFLLGSSSVLGLLLLLGB 6.26%28.52%29.13%10.52%33.31%21.67%6.50%28.26%31.69%0.20%46.05%18.42%23.86%3.14%37.58%22.96%33.36%28.58%28.25%11.63% SSLVFLLLSLVLSVLVSLLVLVSVFFLV 2.03%24.95%28.89%7.41%31.73%18.67%5.25%24.89%26.13%–3.11%41.70%10.52%18.89%1.32%36.99%22.00%31.78%20.00%26.96%6.08% LVLGFLSBLVLVSGLVLGSGLVLVSGSVLVLVSS 0.02%22.03%23.69%6.27%31.04%15.30%3.68%21.67%20.16%–6.85%38.37%7.77%18.61%–0.64%31.04%21.37%29.98%14.69%21.26%–3.02% FLLLGSVLGBSGSSGLLSGSVSSSBLL –2.27%21.55%22.56%2.33%31.01%14.50%2.75%20.38%16.25%–17.42%30.47%7.62%13.37%–1.55%28.44%16.53%22.36%8.70%21.04%–9.11% LLVSGSVSGSVSVLBSLVBLSSVSGSGSGLVF –4.92%21.04%20.14%2.27%30.97%7.41%–7.12%16.61%14.53%–19.50%22.56%7.40%10.08%–1.81%25.75%11.32%12.93%1.23%12.72%–13.96% SGSGLGSLVSSLGSVSVBLGBSGBFBSBLG –9.23%20.99%16.24%–7.13%29.68%5.69%–8.76%11.95%12.43%–21.77%16.00%5.06%9.75%–2.44%18.46%6.05%9.64%–2.25%–0.82%–22.08% LGFBSGBSGSGBFFFFLGBFBFSVSVSG –9.81%–1.86%8.19%–15.84%22.13%3.59%–10.48%7.89%10.53%–23.45%12.14%–12.18%1.68%–2.92%11.21%3.64%1.78%–6.46%–1.48%–22.43%
EXHIBIT 17.7 Legend:L=large stocks(Standard & Poor’s 500 Index) LG=large-growth stocks(S&P 500/BARRA Growth Index) LV=large-value stocks(S&P 500/BARRA Value Index) S=small stocks(Russell 2000 Index) SG=small-growth stocks(Russell 2000 Growth Index) SV=small-value stocks(Russell 2000 Value Index) F=foreign stocks(MSC EAFE Index) B=bonds(Lehman Brothers Aggregate Bond Index) Source:Standard & Poor’s,Franklin Templeton Investments.
At the other extreme, active portfolios can also be formed on the assumptions that recent trends in past prices will continue. A price momentumstrategy, as it is more commonly called, assumes that stocks that have been hot will stay hot, while cold stocks will also remain so.
Although there may well be sound economic reasons for these trends to continue (e.g., company revenues and earnings that continue to grow faster than expected), it may also simply be the case that investors periodically underreact to the arrival of new information. Thus, a pure price momentum strategy focuses just on the trend of past prices alone and makes purchase and sale decisions accordingly. Chan, Jegadeesh, and Lakonishok investigated the profitability of this approach. They divided all of the stocks traded in U.S. markets over the period 1994–1998 into 10 different portfolios based on their past six-month price movements and calculated returns over the following year.7Panel A of Exhibit 17.9 shows these annualized returns for each of the portfolios, from the one with the most positive past price trend (#10) to the worst price trend (#1). The data appear to justify the price momentum strategy in that the portfolios with the high- est (lowest) level of price momentum generated the highest (lowest) subsequent returns. Also, the last column of the display shows that a momentum-based hedge fund that is long in the best- trend portfolio and short in the worst-trend one would also have been quite profitable.
The price momentum strategies just discussed could either be based on pure price trend analy- sis or supported by the underlying economic fundamentals of the company. An earnings momentumstrategy is a somewhat more formal active portfolio approach that purchases and Anomalies and
Attributes
0.20
0.15
0.10
0.05
0.00
–0.05
–0.10
0.20
0.15
0.10
0.05
0.00
–0.05
–0.10
CAR
Months after Portfolio Formation
0 5 10 15 20 25 30 35
Loser Portfolio
Winner Portfolio
EXHIBIT 17.8 ABNORMAL RETURNS TO A MARKET OVERREACTION INVESTMENT STRATEGY
Source: Werner F. M. DeBondt and Richard Thaler, “Does the Stock Market Overreact?” Journal of Finance 40, no. 3 (July 1985): 793–805. Reprinted with permission of Blackwell Publishing.
7Louis K. C. Chan, Narasimhan Jegadeesh, and Josef Lakonishok, “The Profitability of Momentum Strategies,” Finan- cial Analysts Journal 55, no. 6 (November/December 1999): 80–90.
666 CHAPTER 17 EQUITYPORTFOLIOMANAGEMENTSTRATEGIES
PROFITABILITY OF MOMENTUM STRATEGIES: 1994–1998
1 2 3 4 5 6 7 8 9 10 10–1
(LOW) (HIGH) (PPS)
A. Classification Based on Prior Six-Month Return
1994 –12.00 –6.10 0.40 2.10 0.50 –0.90 –1.80 3.10 –4.50 –6.40 5.60
1995 35.70 27.40 32.30 35.00 32.30 32.20 30.30 36.70 35.30 42.10 6.40
1996 11.90 15.60 17.90 20.20 27.90 22.50 22.00 21.90 20.40 15.30 3.40
1997 7.20 05.70 14.80 20.80 26.60 32.80 35.60 37.30 37.50 23.80 16.60
1998 –2.30 –4.40 –7.00 –3.30 –0.40 0.00 04.50 0.10 –0.80 04.40 6.70
1994–98 average 8.10 7.64 11.68 14.96 17.38 17.32 18.12 19.82 17.58 15.84 7.74
B. Classification Based on Standardized Unexpected Earnings
1994 –2.30 –2.40 –6.80 –1.00 –4.60 –1.20 –0.10 –3.30 0.90 –2.00 0.30
1995 36.70 25.40 27.80 31.00 33.40 27.50 36.10 36.90 38.60 40.60 3.90
1996 16.30 17.90 19.20 16.30 21.90 19.60 23.10 22.70 24.70 18.40 2.10
1997 25.50 21.70 23.50 22.80 24.10 24.50 25.20 28.40 29.60 28.10 2.60
1998 –3.20 –5.20 –1.30 04.40 –0.60 5.00 –0.10 –0.60 0.00 –6.20 –3.00
1994–98 average 14.60 11.48 12.48 14.70 14.84 15.08 16.84 16.82 18.76 15.78 1.18
EXHIBIT 17.9
Copyright 1999, Association for Investment Management and Research. Reproduced and republished from “The Profitability of Momentum Strategies,”
from the November/December 1999 issue of the Financial Analysts Journal, with permission from the Association for Investment Management and Research. All Rights Reserved.
holds stocks that have accelerating earnings and sells (or short sells) stocks with disappointing earnings. The notion behind this strategy is that, ultimately, a company’s share price will follow the direction of its earnings, which is one “bottom line” measure of the firm’s economic success.
In judging the degree of momentum in a firm’s earnings, it is often the case in practice that investors will compare the company’s actual EPS to some level of what was expected. Two types of expected earnings are used most frequently: (1) those generated by a statistical model and (2) the consensus forecast of professional stock analysts. Panel B of Exhibit 17.9 shows that, over the 1994–1998 period, earnings momentum strategies were generally successful as well, although surprisingly not to the same degree as price momentum strategies.
In our examination of market efficiency in Chapter 6, we saw several anomalies that sug- gested a role for active equity management. Two of these—the weekend effect and the January effect—involved investing during particular times of the year. While conceptually viable, the limitations inherent in these anomalies do not produce particularly effective portfolio strategies.
That is, managers investing in stocks only in January are not likely to be able to justify their annual fees, while the number of transactions implied by the weekend effect (i.e., buy every Monday, sell every Friday) generally makes for a cost-ineffective portfolio. Remember, however, that whether or not these calendar-related anomalies produce successful active portfolios, they still are useful rules for trades that an investor plans to make anyway.
A more promising approach to active anomaly investing involves forming portfolios based on various characteristics of the companies themselves. Two such characteristics we have seen to matter in the stock market are the total capitalization of the firm’s outstanding equity (i.e., firm size) and the financial position of the firm, as indicated by its various financial ratios (e.g., P/E, P/BV). The studies we saw in Chapter 6 came to two general conclusions about these firm char- acteristics. First, over time, firms with smaller market capitalizations produce bigger risk- adjusted returns than those with large market capitalizations. Second, over time, firms with lower P/E and P/BV ratios produce bigger risk-adjusted returns than those with higher levels of those
ratios. In fact, we saw in Chapter 9 that low and high levels of these ratios are used in practice to define value and growth stocks, respectively.
To see another reason why these firm-specific attributes may be important to active investors, recognize that the term sector considered earlier in the context of rotation strategies also can be defined by different stock attributes. Thus, because the market seems to favor some attributes more than others over time, sector rotation may involve overweighting stocks with certain char- acteristics, such as small- or large-capitalization stocks, high or low P/E stocks, or stocks clas- sified more generally as value or growth stocks. For example, Panel A of Exhibit 17.10 shows the difference in returns to portfolios invested in small- and large-cap stocks on a monthly basis from 1979–1999. The graph shows the large-cap portfolio return minus the small-cap return, so any net return above the horizontal axis indicates a period when the former outperformed the lat- ter. Notice in particular the sizable firm size rotation and spread in returns that occurred in this period; in given months, both large- and small-cap stocks outperformed the other by over 30 per- cent. An important point to keep in mind, however, is that small-cap stocks are almost always riskier than large-cap stocks. This is shown in Panel B of Exhibit 17.10, which reports the dif- ference in the standard deviations of the large- and small-cap portfolios.
Similar analysis reveals the potential benefits of forming active global portfolios around financial ratios. For the period spanning 1975–1995, Fama and French divided the stocks in 13 world markets using several different ratios, including P/E and P/BV.8They formed portfolios of stocks based on the highest and lowest 30 percent of each ratio and measured returns and stan- dard deviations over the entire 20-year period. Exhibit 17.11 summarizes their findings. For each country and each ratio, the display reports the average annual return differential between the lowest-ratio portfolio and the high-ratio portfolio, as well as difference in standard deviation for those two portfolios. Two facts are clear from these results. First, over time, portfolios with the lowest P/E and P/BV ratios produced the highest returns everywhere in the world except Italy.
Second, those low-ratio portfolios also tended to be more volatile, although this finding was far less uniform across countries. As we will see shortly, these results are important for understand- ing the differences between the value and growth investment styles.
Regardless of which broad philosophical approach they adopt, an important issue for active man- agers and their clients to resolve is the selection of an appropriate benchmark (sometimes called a “normal” portfolio). The benchmark should incorporate the average qualities of the portfolio strategy of the client. Thus, an active portfolio manager who invests mainly in small-capitalization stocks with low P/E ratios because the client specified this strategy should not have his or her performance compared to a broad market index, such as the S&P 500. Similarly, a global equity manager will not want to have his or her performance compared to a portfolio of stocks drawn from a single country, or even a single region in the world.
Active managers must overcome two difficulties relative to the benchmark. First, an actively managed portfolio will almost always have higher transaction costs. Second, active portfolios can often also have higher risk than the passive benchmark. One key to success is for active man- agers to be consistent in their area of expertise. Market gyrations occur, and investment styles go in and out of favor. Successful long-term investing requires that you maintain your investment philosophy and composure while others are deviating from theirs. Another key to success is to minimize the trading activity of the portfolio. Attempts to time price movements over short hori- zons will result in lower profits because of growing commissions.
Finally, notice that most active equity strategies are inherently quantitative in nature. This suggests that computer-assisted portfolio formation procedures can be quite useful. In fact, the Miscellaneous
Issues
8Eugene F. Fama and Kenneth R. French, “Value versus Growth: The International Evidence,” Journal of Finance 53, no. 6 (December 1998): 1975–1999.
668 CHAPTER 17 EQUITYPORTFOLIOMANAGEMENTSTRATEGIES
40.0 30.0 20.0 10.0 0.0 –10.0 –20.0 –30.0 –40.0
40.0 30.0 20.0 10.0 0.0 –10.0 –20.0 –30.0 –40.0
Return Differential % (Large–Small)
Year 1979 1981 1983 1985 1987 1989
Higher Large-Cap Returns
Higher Small-Cap Returns
1991 1993 1995 1997
EXHIBIT 17.10 PERFORMANCE LARGE- AND SMALL-CAP PORTFOLIOS: 1979–1999 A. Rotation of Large-Cap and Small-Cap Returns
B. Rotation of Large-Cap and Small-Cap Standard Deviations
15.0
10.0
5.0
0.0
–5.0
–10.0
–15.0
15.0
10.0
5.0
0.0
–5.0
–10.0
–15.0
Volatility Differential % (Large–Small)
Year 1979 1981 1983 1985 1987 1989
Higher Large-Cap Volatility
Higher Small-Cap Volatility 1991 1993 1995 1997
Source: Fidelity Management and Research. Data based on relative rolling 12-month returns to Russell 1000 and Russell 2000 indexes.