e, and h, while the computer-generated data are charts a, c, f, and g.6
TRENDING MARKETS AND PRICE REVERSALSDespite the fact that many “trends” are in fact the result of the totallyrandom movement of stock prices, many traders will not invest againsta trend that they believe they have identified. Two of the most wellknown sayings of market timers are “Make the trend your friend” and“Trust the thrust.”Martin Zweig, a well-known market timer who uses fundamentaland technical variables to forecast market trends, has forcefully stated: “Ican’t overemphasize the importance of staying with the trend of themarket, being in gear with the tape, and not fighting the major movements. Fighting the tape is an open invitation to disaster.”7When a trend appears established, technical analysts draw channelsthat enclose the path of stock prices. A channel encloses the upper andlower bounds within which the market has traded. The lower bound ofa channel is frequently called a support level, and the upper bound a resistance level. When the market breaks the bounds of the channel, a largemarket move often follows.The very fact that many traders believe in the importance of trendscan induce behavior that makes trend following so popular. While thetrend is intact, traders sell when prices reach the upper end of the channel and buy when they reach the lower end, attempting to take advantage of the apparent back-and-forth motion of stock prices. If the trendline is broken, many of these traders will reverse their positions: buyingif the market penetrates the top of the trend line or selling if it fallsthrough the bottom. This behavior often accelerates the movement ofstock prices and reinforces the importance of the trend.Options trading by trend followers reinforces the behavior ofmarket timers. When the market is trading within a channel, traderswill sell put and call options at strike prices that represent the lower andupper bounds of the channel. As long as the market remains within thechannel, these speculators collect premiums as the options expireworthless.6Figure 17-1b covers February 15 to July 1, 1991; Figure 17-1e covers January 15 to June 1, 1992; andFigure 17-1h from June 15 to November 1, 1990.7Martin Zweig, Winning on Wall Street, New York: Warner Books, 1990, p. 121.
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If the market penetrates the trading range, options sellers are exposed to great risks. Recall that sellers of options (as long as they do notown the underlying stock) face a huge potential liability, a liability thatcan be many times the premium that they collected upon sale of the option. When such unlimited losses loom, these option writers “run forcover,” or buy back their options, accelerating the movement of prices.
MOVING AVERAGESSuccessful technical trading requires not only identifying the trend but,more importantly, identifying when the trend is about to reverse. A popular tool for determining when the trend might change examines the relationship between the current price and a moving average of past pricemovements, a technique that goes back to at least the 1930s.8A moving average is simply the arithmetic average of a given number of past closing prices of a stock or index. For example, a 200-daymoving average is the average of the past 200 days’ closing prices. Foreach new trading day, the oldest price is dropped and the most recentprice is added to compute the average.Moving averages fluctuate far less than daily prices. When pricesare rising, the moving average trails the market and, technical analystsclaim, forms a support level for stock prices. When prices are falling, themoving average is above current prices and forms a resistance level. Analysts claim that a moving average allows investors to identify the basicmarket trend without being distracted by the day-to-day volatility of themarket. When prices penetrate the moving average, this indicates thatpowerful underlying forces are signaling a reversal of the basic trend.The most popular moving average uses prices for the past 200 trading days, and it is therefore called the 200-day moving average. It is frequently plotted in newspapers and investment letters as a keydeterminant of investment trends. One of the early supporters of thisstrategy was William Gordon, who indicated that, over the period from1897 to 1967, buying stocks when the Dow broke above the moving average produced nearly seven times the return as buying when the Dowbroke below the average.9 Colby and Meyers claim that for the United8
See William Brock, Josef Lakonishok, and Blake LeBaron, “Simple Technical Trading Rules and theStochastic Properties of Stock Returns,” Journal of Finance, vol. 47, no. 5 (December 1992), pp.1731–1764. The first definitive analysis of moving averages comes from a book by H. M. Gartley,Profits in the Stock Market, New York: H. M. Gartley, 1930.9William Gordon, The Stock Market Indicators, Palisades, N.J.: Investors Press, 1968.
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States the best time period for a moving average of weekly data is 45weeks, just slightly longer than the 200-day moving average.10
Testing the Dow Jones Moving-Average StrategyIn order to test the 200-day moving-average strategy, I examined thedaily record of the Dow Jones Industrial Average from 1885 to the present. In contrast to the previous studies on moving-average strategies, theholding-period returns include the reinvestment of dividends when thestrategy suggests investing in the market and interest-bearing securitieswhen one is not invested in the stock market. Annualized returns are examined over the entire period as well as the subperiods.I adopted the following criteria to determine the buy-sell strategy:Whenever the Dow Jones Industrial Average closed by at least 1 percentabove its 200-day moving average, stocks were purchased at these closing prices. Whenever the Dow Industrials closed by at least 1 percentbelow its 200-day moving average, stocks were sold. When sold, theportfolio was invested in Treasury bills and earned interest income.There are two noteworthy aspects of this strategy. The 1 percentband around the 200-day moving average is used in order to reduce thenumber of times an investor would have to move in and out of the market. Without this band, investors using the 200-day moving-averagestrategy are often “whipsawed,” a term used to describe the alternatebuying and then selling of stocks in an attempt to beat the market. Suchtrades dramatically lower investor returns because of the large transactions costs incurred.The second aspect of this strategy assumes that an investor buys orsells stocks at the closing price rather than at any time reached duringthe day. Only in recent years has the exact intraday level of the averagesbeen computed. Using historical data, it is impossible to determinetimes when the market average penetrated the 200-day moving averageduring the day but closed at levels that did not trigger a signal. By specifying that the average must close above or below the signal, I present atheory that could have been implemented in practice.11
10
Robert W. Colby and Thomas A. Meyers, The Encyclopedia of Technical Market Indicators, Homewood, Ill.: Dow Jones-Irwin, 1988.11Historically, the daily high and low levels of stock averages were calculated on the basis of thehighest or lowest price of each stock reached at any time during the day. This is called the theoreticalhigh or low. The actual high is the highest level reached at any given time by the stocks in the average.
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Back-Testing the 200-Day Moving AverageIn Figure 17-2 are the daily and 200-day moving averages of the DowJones Industrial Average during two select periods: from 1924 to 1936and 1999 to 2006. The time periods when investors are out of the stockmarket are shaded; otherwise, investors are fully invested in stocks.Over the entire 120-year history of the Dow Jones average, the 200day moving-average strategy had its greatest triumph during the boomand crash of the 1920s and early 1930s. Using the criteria outlined above,investors would have bought stocks on June 27, 1924, when the Dowwas 95.33 and, with only two minor interruptions, ridden the bull market to the top at 381.17 on September 3, 1929. Investors would have exited the market on October 19, 1929, at 323.87, 10 days before the GreatCrash. Except for a brief period in 1930, the strategy would have kept investors out of stocks through the worst bear market in history. Theywould have finally reentered the market on August 6, 1932, when theDow was 66.56, just 25 points higher than its low.Investors following the 200-day moving-average strategy wouldalso have avoided the October 19, 1987, crash, selling out on the previous Friday, October 16. However, in contrast to the 1929 crash, stocks didnot continue downward. Although the market fell 23 percent on October19, investors would not have reentered the market until the followingJune when the Dow was only about 5 percent below the exit level of October 16. Nonetheless, following the 200-day moving-average strategywould have avoided October 19 and 20, traumatic days for many investors who held stocks.The returns from the 200-day moving-average strategy and a buyand-hold strategy of not timing the market are summarized in Table 171. From January 1886 through December 2006, the 10.21 percent annualreturn from the timing strategy beat the annual return on the holdingstrategy of 9.68 percent. As noted earlier, however, the timing strategyhad its biggest success avoiding the 1929 to 1932 crash. If that period isexcluded, the returns of the timing strategy are 43 basis points per yearbehind the holding strategy, although the timing strategy has lower risk.Moreover, if the transactions costs of implementing the timingstrategy are included in the calculations, the excess returns over thewhole period, including the 1929 to 1932 Great Crash, more than vanish.Transactions costs include brokerage costs and bid-ask spreads, as wellas the capital gains tax incurred when stocks are sold and are assumedto be on average half a percent when buying or selling the market. Thisnumber probably underestimates such costs, especially in the earlier
FIGURE
17–2
Dow Jones Industrials and the 200-Day Moving-Average Strategy (Shaded AreasAre Out of the Market)
January 2, 1924 – December 31, 19364003503002502001501005001924
1926
1928
1930
1932
1934
1936
January 1, 1999 – December 31, 200614000130001200011000100009000800070001999
298
2000
2001
2002
2003
2004
2005
2006
CHAPTER 17 Technical Analysis and Investing with the Trend
TABLE
299
17–1
Annualized Returns of Timing and Holding Strategies, January 1886 through December 2006
Holding StrategyPeriod1886 - 2006
Return
Risk
9.68%
21.5%
Timing StrategyNo. Trans. CostReturn
Risk
10.21% 16.7%
Net Trans. CostsReturn
Risk
% inMarket
No. ofSwitches
8.63%
17.3%
62.9%
350
Subperiods1886 - 1925
9.08%
23.7%
9.77%
17.7%
8.11%
18.0%
57.1%
122
1926 - 1945
6.25%
31.0%
11.10%
21.8%
9.44%
22.7%
62.7%
60
1946 - 2006
11.23%
16.0%
10.21%
14.2%
8.70%
15.1%
67.4%
168
1990 - 2006
11.76%
14.7%
6.60%
16.9%
4.30%
18.3%
73.7%
74
1886 - 2006
11.30%
20.5%
10.80% 16.5%
9.23%
17.2%
64.2%
334
1926 - 1945
17.72%
25.9%
15.75%
14.24%
22.1%
71.2%
44
Excl. 1929 - 1932 Crash
21.3%
years. In later years if this strategy is pursued with index futures orETFs, the transactions costs would be lower. Each 0.1 percentage pointincrease of transactions costs lowers the compound annual returns by 29basis points.Although the excess returns from the timing strategy disappearwhen transactions costs are considered, the major gain from the timingstrategy is a reduction in risk. Since the market timer is in the market lessthan two-thirds of the time, the standard deviation of returns is reducedby about one-quarter. This means that on a risk-adjusted basis, the return on the 200-day moving-average strategy is quite impressive, evenwhen transactions costs are included.Unfortunately, the timing strategy has broken down in the last 17years. The year 2000 was particularly disastrous for the timing strategy.With the Dow Industrials meandering most of the year above and belowthe 200-day moving average, the investor pursuing the timing strategywas whipsawed in and out of the market, executing a record 16 switchesin and out of stocks.Each switch incurs transactions costs and must overcome the 1 percent pricing band. As a result, even ignoring transactions costs, the timing strategist lost over 28 percent in 2000 while the buy-and-holdstrategist lost less than 5 percent. Since 1990, the buy-and-hold strategy
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has returned 11.76 percent annually whereas the timing strategy has returned only 6.60 percent, even before transactions costs.12The timing strategy did avoid some nasty bear markets over thepast decade. A timing strategist would have exited the market on June25, 2001, and avoided the entire drop associated with the terrorist attacks. But what looked like a big gain for the market timer was mostlyeliminated by the sharp stock rally to close the year. The timing strategist would have reentered the market on January 3, 2002, at a price only2.3 percent below the exit price six months earlier. But timing investorsdid miss the second leg of the bear market, exiting stocks on June 4, 2002,at 9,889 and not reentering until nearly a year later, on April 22, 2003,when the Dow was at 8,325, nearly 16 percent lower.
The Nasdaq Moving-Average StrategyIt is remarkable that during the 1990 to 2006 period when the movingaverage strategy on the Dow Industrials failed to generate good returns,the exact same strategy proved very successful on the Nasdaq. In Table17-2 it can be seen that the timing strategy outperformed the holdingstrategy by nearly 5 percent per year since 1972 and by nearly 4 percentper year since 1990. Again, the market timer achieved these superior returns with much lower risk.What is most important about the moving-average strategy is thatit keeps investors in major bull markets and out of major bear markets.The strategy worked beautifully during the technology bubble of 1999 to2001. Using the timing strategy, an investor would have entered the Nas12Note that during the 1990 to 2006 period, the risk, measured in annual returns, is surprisinglyhigher for the timing strategy than for the holding strategy. This unusual reversal of risks is due tothe extremely poor returns for the timing strategy in 2000. If monthly returns are considered, the timing strategy had lower risk than the holding strategy over the same period.
TABLE
17–2
Annualized Returns of Nasdaq Timing and Holding Strategies, January 1972 through December 2006
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daq market at 1,801 on November 2, 1998, and rode the market to thepeak of 5,049 on March 10, 2000. After moving in and out of the marketseveral times, the market timer would have exited the Nasdaq market at3,896 on September 11, 2000, and stayed out until December 5, 2001,when the Nasdaq was at 2,046, almost 50 percent lower. For those 15months the timing strategist in Nasdaq would have avoided the mostcrushing bear market since the 1929 to 1932 stock market crash.
Distribution of Gains and LossesThere is no question that the 200-day moving-average strategy, evenwith transactions costs, avoids large losses, but it suffers many small defeats. In Figure 17-3 is shown the distribution of yearly gains and lossesin the timing strategy after transactions costs and the holding strategyfor the Dow Industrials from 1886 to 2006. As noted above, the timingstrategist participates in most of the winning markets and avoids mostof the losing markets but suffers many small losses. These losses occurwhen the market does not follow a definite trend. Despite the use of the1 percent band to reduce whipsawing, investors in a trendless marketFIGURE
17–3
Distribution of Yearly Gains and Losses: Dow Jones Industrials Timing Strategy versus Holding Strategy
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often find themselves moving in and out of the market frequently, sometimes incurring heavy transactions costs and trading losses as occurredin 2000.The distribution in Figure 17-3 is quite similar to that of a buy-andhold investor’s purchasing index puts on the market. As noted in Chapter 15, purchasing index puts are equivalent to buying an insurancepolicy on the market, but the buyer must continually pay the premium.Similarly, the timing strategy involves a large number of small lossesthat come from moving in and out of the market, while avoiding mostsevere declines.
MOMENTUM INVESTINGTechnical analysis can also be used to buy individual stocks. Academiceconomists call this momentum investing, and it has received increasingattention. Momentum strategies, unlike fundamental strategies, relypurely on past returns, regardless of earnings, dividends, or other valuation criteria. Momentum investors buy stocks that have recently risenin price and sell stocks that have recently fallen, expecting that the stockprice will, for a time, continue to move in the same direction.While this may seem at odds with the old maxim of “buy low, sellhigh,” there is substantial research to support this “buy-high, sellhigher” strategy. In 1993, Narasimhan Jegadeesh and Sheridan Titmanfound that stocks with the highest 10 percent returns over the past sixmonths outperformed stocks with the lowest 10 percent returns byabout 1 percent per month over the next six months.13,14 Other technicalstrategies, such as buying stocks priced near their 52-week high, havealso been shown to be successful.15It should be emphasized that these momentum strategies workonly in the short term and should not be part of a long-term strategy. Inthe Jegadeesh and Titman study, over half of the excess returns generated in the first 12 months were lost over the following two years. Overthe longer periods, the advantage of buying “winning” stocks is com13
Narasimhan Jegadeesh and Sheridan Titman, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency,” Journal of Finance, vol. 48, no. 1 (March 1993), pp. 65–91.14Moskowitz and Grinblatt have found that much of the success of these strategies is due to theprice momentum in industries rather than of individual stocks. See Tobias Moskowitz and MarkGrinblatt, “Do Industries Explain Momentum?” Journal of Finance, vol. 54, no. 4 (August 1999), pp.1249–1290.15Thomas J. George and Chuan-Yang Hwang, “The 52-Week High and Momentum Investing,” Journal of Finance, vol. 59, no. 5 (October 2004), pp. 2145–2176.
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pletely eliminated. In fact, an earlier study by Werner De Bondt andRichard Thaler found that stocks that performed poorly over the previous three- to five-year period significantly outperformed, over the nextthree to five years, those stocks that had done well, implying a mean reversion of longer-run stock returns.16The success of momentum investing cannot be explained within anefficient-market framework. It appears that investors underreact toshort-term information, which causes the stock to continue to move inthe same direction over time rather than adjusting instantaneously. Unfortunately momentum investing does not guarantee success: recent evidence suggests that while professional investors achieve excess returnswith a momentum strategy, individual investors tend to underperformthe market. This may be because individual investors often focus on thevery best performing stocks, which tend to become overpriced quicklyand suffer poor returns, while those well-performing stocks that do notmake it to the very top of the list and are bought by professionals tend tohave the best momentum returns.17
CONCLUSIONProponents of technical analysis claim it helps investors identify themajor trends of the market and when those trends might reverse. Yetthere is considerable debate about whether such trends exist, or whetherthey are just runs of good and bad returns that are the result of randomprice movements.Burton Malkiel has been quite clear in his denunciation of technicalanalysis. In his bestselling work A Random Walk Down Wall Street, he proclaims:Technical rules have been tested exhaustively by using stock price data onboth major exchanges, going back as far as the beginning of the 20th century. The results reveal conclusively that past movements in stock pricescannot be used to foretell future movements. The stock market has nomemory. The central proposition of charting is absolutely false, and investors who follow its precepts will accomplish nothing but increasingsubstantially the brokerage charges they pay.1816
Werner F. M. De Bondt and Richard Thaler, “Does the Stock Market Overreact?” Journal of Finance,vol. 40, no. 3 (July 1985), pp. 793–805.17Glenn N. Pettengill, Susan M. Edwards, and Dennis E. Schmitt, “Is Momentum Investing a ViableStrategy for Individual Investors?” Financial Services Review, vol. 15, no. 3 (2006), pp. 181–197.18Burton Malkiel, A Random Walk Down Wall Street, New York: Norton, 1990, p. 133.
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Yet this contention, once supported nearly unanimously by academic economists, is cracking. Recent econometric research has shownthat such simple trading rules as 200-day moving averages or short-termprice momentum can be used to improve returns.19Despite the ongoing academic debate, technical analysis and trendfollowing draw huge numbers of adherents on Wall Street and amongmany savvy investors. The analysis in this chapter gives a cautious nodto these strategies, as long as transactions costs are not high. But tradingon the basis of charts requires full-time attention. In October 1987, theDow fell below its 200-day moving average on the Friday before thecrash and gave a sell signal. But if you failed to sell your stocks that Friday afternoon, you would have been swept downward by the 22 percentnightmare decline of Black Monday.Furthermore, as I have repeatedly noted throughout this book, actions by investors to take advantage of the past will change returns inthe future. As Benjamin Graham stated so well nearly 70 years ago:A moment’s thought will show that there can be no such thing as a scientificprediction of economic events under human control. The very “dependability” of such a prediction will cause human actions which will invalidate it.Hence thoughtful chartists admit that continued success is dependent uponkeeping the successful method known to only a few people.20
19
See William Brock, Josef Lakonishok, and Blake LeBaron, “Simple Technical Trading Rules and theStochastic Properties of Stock Returns,” Journal of Finance, vol. 47, no. 5 (December 1992), pp.1731–1764, and Andrew Lo, Harry Mamaysky, and Jiang Wang, “Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation,”Journal of Finance, vol. 55 (2000), pp 1705–1765.20Benjamin Graham and David Dodd, Security Analysis, 2d ed., New York: McGraw-Hill, 1940, pp.715–716.
18
CHAPTER
CALENDAR ANOMALIESOctober. This is one of the peculiarly dangerous months to speculatein stocks. The others are July, January, September, April, November,May, March, June, December, August, and February.M A R K T WA I N
The dictionary defines anomaly as something inconsistent with what isnaturally expected. And what is more unnatural than to expect to beatthe market by predicting stock prices based solely on the day or week ormonth of the year? Yet it appears that you can. Research has revealedthat there are predictable times during which stocks as a whole, and certain stocks in particular, outperform the market.The analysis in the first edition of Stocks for the Long Run, publishedin 1994, was based on long data series analyzed through the early 1990s.The calendar anomalies reported in that edition invited investors to tryto outperform the market by adopting their strategies to these unusualcalendar events. However, as more investors know of these anomalies,the prices of stocks may adjust so that much, if not all, of the anomaly iseliminated. That certainly would be the prediction of the efficient market hypothesis.In this edition of Stocks for the Long Run, I shall look at the evidenceover the past 14 years to determine whether the anomaly survived or305Copyright © 2008, 2002, 1998, 1994 by Jeremy J. Siegel. Click here for terms of use.
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not. The results are surprising. Some anomalies have weakened andeven reversed, while others remain as strong as they have always been.Here is a rundown.
SEASONAL ANOMALIESThe most important historical calendar anomaly is that small-capitalization stocks have far outperformed larger stocks in January. This effect isso strong that without January’s return, small stocks would have a lowerreturn than large stocks over the past 80 years!1This outperformance of small stocks in January has been dubbedthe January Effect. It was discovered in the early 1980s by Donald Keim,2based on research he did as a graduate student at the University ofChicago. It was the first significant finding that flew in the face of the efficient market hypothesis that claimed there was no predictable patternto stock prices.The January Effect might be the granddaddy of all calendar anomalies, but it is not the only one. For inexplicable reasons, stocks generallydo much better in the first half of the month than the second half, do wellbefore holidays, and plunge in the month of September. Furthermore,they do exceptionally well between Christmas and New Year’s Day, anduntil very recently, they have soared on the last trading day of December, which is actually the day that has launched the January Effect.Why these anomalies occur is not well understood, and whetherthey will continue to be significant in the future is an open question. Buttheir discovery has put economists on the spot. No longer can researchers be so certain that the stock market is thoroughly unpredictableand impossible to beat.
THE JANUARY EFFECTOf all of the calendar-related anomalies, the January Effect has been themost publicized. From 1925 through 2006, the average arithmetic returnon the S&P 500 Index in the month of January was 1.57 percent, whilethe average returns on the small stocks came to 6.07 percent. The 4.5 percentage point excess return of small stocks in January exceeds the entire1
This includes the dramatic 1975 to 1983 period during which small stocks returned over 30 percentper year.2Donald Keim, “Size-Related Anomalies and Stock Return Seasonality: Further Empirical Evidence,” Journal of Financial Economics, vol. 12 (1983), pp. 13–32.
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1.9 percentage point difference in annual compound returns betweenlarge and small stocks. In other words, from February through December, the returns on small stocks are lower than the returns on largestocks. On the basis of history, the only advantageous time to hold smallstocks is the month of January!To see how important the January Effect is, look at Figure 18-1. Itshows the total returns index on large and small stocks and on smallstocks if the January return on small stocks is replaced with that of theS&P 500 Index in January. As shown in Chapter 9, a single dollar investedin small stocks in 1926 would grow to $11,250 by the end of 2006, whilethe same dollar would grow to only $2,736 in large stocks. Yet if the smallstocks’ return in January is eliminated, the total return to small stocks accumulates to only $394, merely 14 percent of the return on large stocks!FIGURE
18–1
Small and Large Stocks, with and without the January Effect, 1926 through December 2006
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Also shown in Figure 18-1 is that if the large January small stock returns persist in the future, it could lead to some astounding investmentresults. By buying small stocks at the end of December and transferringthem back to the S&P 500 Index at the end of January, a $1 investment inthis strategy would have grown to $77,891 by the end of 2006 if begun inDecember 1925, or a 14.9 percent annual rate of return.There have been only 1