Options buyers never needed to worry aboutprice gaps or being able to get out of their position since the price of theinsurance was specified at the time of purchase.Certainly there were factors other than portfolio insurance contributing to Black Monday. But portfolio insurance and its ancestor, thestop-loss order, abetted the fall. All of these schemes are rooted in thebasic trading philosophy of letting profits ride and cutting losses short.Whether implemented with stop-loss orders, index futures, or just amental note to get out of a stock once it declines by a certain amount, thisphilosophy can set the stage for dramatic market moves.
CIRCUIT BREAKERSAs a result of the crash, the Chicago Mercantile Exchange, where theS&P 500 Index futures traded, and the New York Stock Exchange implemented rules that restricted or halted trading when certain price limitswere triggered. To prevent destabilizing speculation when the DowJones Industrial Average changes by at least 2 percent, the New YorkStock Exchange’s Rule 80a placed “trading curbs” on index arbitrage between the futures market and the New York Stock Exchange.4But of greater importance are measures that sharply restrict or stoptrading on both the futures market and on the New York Stock Exchangewhen market moves are very large. When the S&P 500 Index futures fallby 5 percent, trading in futures is halted for 10 minutes. If the Dow In4
The New York Stock Exchange Index replaced the Dow Jones Industrials to compute the 2 percentcollar in 2005.
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dustrials decline by 10 percent before 2 p.m., the New York Stock Exchange will declare a one-hour trading halt.5 If the decline is 20 percent,a two-hour halt will be declared, and if the Dow declines by 30 percent,the NYSE will close for the day.6 Futures trading will halt when the NewYork Stock Exchange is closed.7The rationale behind these measures is that halting trading givesinvestors time to reassess the situation and formulate their strategybased on rapidly changing prices. This time-out could bring buyers intothe market and help market makers maintain a liquid market.The argument against halts is that they increase volatility by discouraging short-term traders from buying when prices fall sharply sincethey might be prevented from unwinding their position if trading is subsequently halted. This sometimes leads to an acceleration of price declines toward the price limits, thereby increasing short-term volatility, asoccurred when prices fell to the limits on October 27, 1997.8
THE NATURE OF MARKET VOLATILITYAlthough most investors express a strong distaste for market fluctuations, volatility must be accepted to reap the superior returns offered bystocks. For risk is the essence of above-average returns: investors cannotmake any more than the risk-free rate of return unless there is some possibility that they can make less.While the volatility of the stock market deters many investors, itfascinates others. The ability to monitor a position on a minute-byminute basis fulfills the need of many to quickly validate their judgment. For many the stock market is truly the world’s largest casino.Yet this ability to know exactly how much one is worth at any givenmoment can also provoke anxiety. Many investors do not like the instantaneous verdict of the financial market. Some retreat into investments
5If the decline occurs between 2:00 and 2:30 p.m., the halt is one-half hour. After 2:30 p.m., there isno trading halt.6These percentage changes are converted into points in the Dow Industrials and adjusted once eachquarter. See www.nyse.com/press/circuit_breakers.html.7These limits were established in 1998. Previously the New York Stock Exchange suspended trading for one-half hour when the Dow fell by 350 points and closed the exchange when the Dow fellby 550 points. Both of these halts were triggered on October 27, 1997, when the Dow Industrials fellby 554 points. Because of intense criticism of these closings, the NYSE sharply widened the limits tokeep trading open. The new trading limits for closing the exchange have never yet been breached.8When the markets reopened after the 350-point limit was reached, traders were so anxious to exitthat the 550-point limit was reached in a matter of minutes.
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such as real estate, for which daily quotations are not available. Othersbelieve that not knowing the current price somehow makes an investment less risky. As Keynes stated nearly 60 years ago about the investingattitudes of the endowment committee at Cambridge University:Some Bursars will buy without a tremor unquoted and unmarketable investments in real estate which, if they had a selling quotation for immediate cash available at each audit, would turn their hair grey. The fact thatyou do not know how much its ready money quotation fluctuates doesnot, as is commonly supposed, make an investment a safe one.9
HISTORICAL TRENDS OF STOCK VOLATILITYThe annual variability, measured by the standard deviation of themonthly returns, from 1834 to 2006 is plotted in Figure 16-2. It is strikingthat there is so little overall trend of any sort in the volatility of the market. The period of greatest volatility was during the Great Depression,and the year of highest volatility was 1932. The annualized volatility of1932 was over 65 percent, 17 times higher than 1964, which is the leastvolatile year on record. The volatility of 1987 was the highest since theGreat Depression, but the volatility in the mid-1990s and 2006 fell to nearrecord lows. Excluding the 1929 to 1939 period, when the volatility was34 percent, the volatility of the market has remained remarkably stableat about 13 to 14 percent over the past 170 years.These trends are confirmed by examining Figure 16-3a, which displays the average daily percentage change on the Dow Jones IndustrialAverage during each year since 1896. The downward trend in the Dowvolatility in the early twentieth century is partially due to the increase inthe number of stocks in the Dow Industrials from 12 to 20, and then to 30in 1928. The average daily change in the Dow Industrials over the past100 years is 0.73 percent, slightly less than three-quarters of 1 percent.Since the 1930s, there have been only three years—1974, 1987, and2000—when the average daily change has exceeded 1 percent.10The percentage of trading days when the Dow Industrials changedby more than 1 percent is shown in Figure 16-3b. It has averaged 23 percent over the period, or about once per week. But it has ranged fromas low as 1.2 percent in 1964 to a high of 67.6 percent in 1932, when9Charles D. Ellis, ed., “Memo for the Estates Committee, King’s College, Cambridge, May 8, 1938,”Classics, Homewood, Ill.: Dow Jones-Irwin, 1989, p. 79.10The average percentage change in the Dow Industrials in 2001 was 0.9934 percent.
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FIGURE
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16–2
Annual Volatility of Stock Returns (Annualized Standard Deviation of Monthly Returns), 1834 throughDecember 2006
the Dow changed by more than 1 percent in two out of every three trading days.Most of the periods of high volatility occur when the market hasdeclined. The standard deviation of daily returns is about 25 percenthigher in recessions than in expansions. There are two reasons whyvolatility increases in a recession. First, recessions are more unusual andentail greater economic uncertainty than expansions. The second is that,if earnings fall sharply, then the burden of fixed costs becomes higherand the volatility of profits greater. This leads to increased volatility inthe equity value of firms.If earnings turn into losses, then the equity value of the firms actslike an out-of-the-money option that pays off only if the firm eventuallydoes well to cover its costs. Otherwise, it is worthless. It is not a puzzlewhy stock volatility was the greatest during the Great Depression when,
FIGURE
16–3
Daily Risk on the Dow Jones Industrial Average
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with aggregate profits negative, the equity market as a whole was trading like an out-of-money option.
THE VOLATILITY INDEX (VIX)Measuring historical volatility is a simple matter, but it is far more important to measure the volatility that investors expect in the market. Thisis because expected volatility is a signal of the level of anxiety in the market, and periods of high anxiety have often marked turning points forstocks.By examining the prices of put and call options on the major stockmarket indexes, one can determine the volatility that is built into the market, which is called the implied volatility.11 In 1993, the Chicago Board Options Exchange (CBOE) introduced the CBOE Volatility Index, also calledthe VIX Index or the VIX, based on actual index options prices on the S&P500 Index, and it calculated this index back to the mid-1980s.12 A weeklyplot of the VIX Index from 1986 appears in Figure 16-4.In the short run, there is a strong negative correlation between theVIX and the level of the market. When the market is falling, investors arewilling to pay more for downside protection and they purchase puts,causing the VIX to rise. When the market is rising, the VIX typically goesdown as investors gain confidence and are less anxious to insure theirportfolio against a loss.This correlation may seem puzzling since one might expect investors to seek more protection when the market is high rather than low.One explanation of the behavior of the VIX Index is that historicalvolatility is higher in bear markets than bull markets, so falling marketsshould cause the VIX to rise. But a more persuasive argument is thatchanges in investor confidence change investors’ willingness to hedgeby buying puts. As put prices are driven up, arbitrageurs who sell putssell stocks to hedge their position, thus sending stock prices down. Thereverse occurs when investors feel more confident of stock returns.It is easy to see in Figure 16-4 that the peaks in the VIX corresponded to periods of extreme uncertainty and sharply lower stockprices. The Volatility Index peaked at 172 on the Tuesday following theOctober 19, 1987, stock market crash, far eclipsing any other high.11This is done by solving for the volatility using the Black-Scholes options pricing formula. SeeChapter 15.12Until 2003, the VIX Index was based on the S&P 100 (the largest 100 stocks in the S&P 500 Index).See the CBOE Web site (www.cboe.com) for more details on its calculation.
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FIGURE
16–4
The CBOE Volatility Index (VIX), 1986 to 200617090
October 19, 1987Stock CrashLTCM Hedge Fund Bailoutand Russia DefaultTerroristAttacks
8070
Collapse ofUAL Buyout
Asian Currency CrisisOct. ’02Market Trough
60504030
Iraq InvadesKuwait
Iraq Invasion
Beginning ofGulf War
201001986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
In the early and mid-1990s, the Volatility Index sank to between 10and 20. But with the onset of the Asian crises in 1997, the VIX moved upto a 20 to 30 range. Spikes between 50 and 60 in the VIX occurred onthree occasions: when the Dow fell 550 points during the attack on theHong Kong dollar in October 1987; in August 1998 when Long-TermCapital Management (LTCM) was liquidated; and in the week followingthe terrorist attacks of September 11, 2001.In recent years, buying when the VIX is high and selling when it islow has proved to be a profitable strategy for the short term. But so hasbuying during market spills and selling during market peaks. The realquestion is how high is high and how low is low. For instance, an investor might have been tempted to buy into the market on Friday, October 16, 1987, when the VIX reached 40. Yet such a purchase would haveproved disastrous given the record one-day collapse that followed onMonday.
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RECENT LOW VOLATILITYAs can be seen from Figures 16-3 and 16-4, volatility in 2005 and 2006was among the lowest in history. There are goods reasons for this: (1)lower economic volatility as the business cycle is muted, (2) the globalization of financial markets that allows investors to diversify risks, and(3) the increased liquidity of markets that allows capital to be instantlyallocated to take advantage of profitable opportunities.But too much stability invites firms and investors to take increasingrisk and leverage their positions with lower-cost debt. This means thatinvestors should not become sanguine about recent low volatility. Theinterconnectedness of markets, for all its benefits, invites global volatility because bullish and bearish sentiment cannot be contained to onemarket.
THE DISTRIBUTION OF LARGE DAILY CHANGESChapter 13 noted that there were 126 days from 1885 through 2006 whenthe Dow Jones Industrials changed by 5 percent or more: 59 up and 67down. Seventy-nine of these days, or nearly two-thirds of the total, occurred from 1929 through 1933. The most volatile year by far in terms ofdaily changes was 1932, which contained 35 days when the Dow movedby at least 5 percent. The longest period of time between two successivechanges of at least 5 percent was the 17-year period that preceded theOctober 19, 1987, stock crash.Some of the properties of large daily changes are displayed in Figure 16-5. Monday has seen only slightly more large changes than the restof the week, and Tuesday has seen significantly fewer. Monday has thelargest number of down days, but Wednesday has by far the highestnumber of up days.Thirty of the large changes occurred in October, which has witnessed more than twice the large moves as any other month. October’sreputation as a volatile month is fully justified. Not only has Octoberwitnessed nearly one-quarter of all big moves but it has also seen thetwo greatest stock crashes in history, in October 1929 and October 1987.It is interesting to note that nearly two-thirds of the large declines haveoccurred in the last four months of the year. Chapter 18 presents the seasonal aspects of stock price changes.One of the most surprising bits of information about large marketmoves relates to the period of the greatest stock market collapse. FromSeptember 3, 1929, through July 8, 1932, the Dow Jones Industrials
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FIGURE
16–5
Distribution of Dow Jones Industrial Average Changes over 5 Percent, 1885 through December 2006
collapsed nearly 89 percent. During that period, there were 37episodes when the Dow changed by 5 percent or more. Surprisingly,21 of those episodes were increases! Many of these sharp rallies werethe result of short-covering, which occurred as speculators whothought the market was on a one-way street rushed to sell stock theydid not own and were then forced to buy it back, or cover their positions, once the market rallied.It is not uncommon for markets that appear to be trending in onedirection to experience occasional sharp moves in the other direction. Ina bull market, the expression “up the staircase, down the elevator” is anapt description of market behavior. Ordinary investors must beware: itis not as easy to make money in trending markets as it looks, and investors who try to play these markets must be ready to bail out quicklywhen they see the market change direction.
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THE ECONOMICS OF MARKET VOLATILITYMany of the complaints about market volatility are grounded in the belief that the market reacts excessively to changes in news. But how newsshould impact the market is so difficult to determine that few can quantify the proper impact of an event on the price of a stock. As a result,traders often “follow the crowd” and try to predict how other traderswill react when news happens.Over half a century ago, Keynes illustrated the problem of investors who try to value stock by economic fundamentals as opposed tofollowing the crowd:Investment based on genuine long-term expectation is so difficult today asto be scarcely practicable. He who attempts it must surely lead much morelaborious days and run greater risk than he who tries to guess better thanthe crowd how the crowd will behave; and, given equal intelligence, hemay make more disastrous mistakes.13
In 1981, Robert Shiller of Yale University devised a method of determining whether stock investors tended to overreact to changes in dividends and interest rates, the fundamental building blocks of stockvalues.14 From the examination of historical data, he calculated what thevalue of the S&P 500 Index should have been given the subsequent realization of dividends and interest rates. We know what this value is because, as shown in Chapter 7, stock prices are the present discountedvalue of future cash flows.What he found was that stock prices were far too variable to be explained merely by the subsequent behavior of dividends and interestrates. Stock prices appeared to overreact to changes in dividends, failingto take into account that most of the changes in dividend payouts wereonly temporary. For example, investors priced stocks in a recession as ifthey expected dividends to go much lower, completely contrary to historical experience.The word cycle in business cycle implies that ups in economic activity will be followed by downs, and vice versa. Since earnings and profits tend to follow the business cycle, they too should behave in a cyclicalmanner, returning to some average value over time. Under these cir13
John Maynard Keynes, The General Theory of Employment, Interest, and Money, New York: Harcourt,Brace & World, 1965, First Harbinger Edition, p. 157. (This book was originally published in 1936 byMacmillan & Co.)14Robert Shiller, Market Volatility, Cambridge, Mass.: MIT Press, 1989. The seminal article thatspawned the excess volatility literature was “Do Stock Prices Move Too Much to Be Justified bySubsequent Changes in Dividends?” American Economic Review, vol. 71 (1981), pp. 421–435.
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cumstances, a temporary drop in dividends (or earnings) during a recession should have a very minor effect on the price of a stock, whichdiscounts dividends into the infinite future.When stocks are collapsing, worst-case scenarios loom large in investors’ minds. On May 6, 1932, after stocks had plummeted 85 percentfrom their 1929 high, Dean Witter issued the following memo to itsclients:There are only two premises which are tenable as to the future. Either weare going to have chaos or else recovery. The former theory is foolish. Ifchaos ensues nothing will maintain value; neither bonds nor stocks norbank deposits nor gold will remain valuable. Real estate will be a worthless asset because titles will be insecure. No policy can be based upon thisimpossible contingency. Policy must therefore be predicated upon the theory of recovery. The present is not the first depression; it may be the worst,but just as surely as conditions have righted themselves in the past andhave gradually readjusted to normal, so this will again occur. The only uncertainty is when it will occur. . . . I wish to say emphatically that in a fewyears present prices will appear as ridiculously low as 1929 values appearfantastically high.15
Two months later the stock market hit its all-time low and ralliedstrongly. In retrospect, these words reflected great wisdom and soundjudgment about the temporary dislocations of stock prices. Yet at thetime they were uttered, investors were so disenchanted with stocks andso filled with doom and gloom that the message fell on deaf ears. Chapter 19 discusses why investors often overreact to short-term events andfail to take the long view of the market.
THE SIGNIFICANCE OF MARKET VOLATILITYDespite the drama of the October 1987 market collapse, there was amazingly little lasting effect on the world economy or even the financial markets. Because the 1987 episode did not augur either a further collapse instock prices or a decline in economic activity, it will never attain the notoriety of the crash of 1929. Yet its lesson is perhaps more important. Economic safeguards, such as prompt Federal Reserve action to provideliquidity to the economy and assure the proper functioning of the financial markets, can prevent an economic debacle of the kind that beset oureconomy during the Great Depression.15
Memorandum from Dean Witter, May 6, 1932.
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This does not mean that the markets are exempt from violent fluctuations. Since the future will always be uncertain, psychology and sentiment often dominate economic fundamentals. As Keynes perceptivelystated more than 70 years ago in The General Theory, “The outstandingfact is the extreme precariousness of the basis of knowledge on whichour estimates of prospective yield have to be made.”16 Precarious estimates are subject to sudden change, so prices in free markets will bevolatile. But history has shown that investors who are willing to stepinto the market when others are running to the exits reap the benefits ofmarket volatility.
16
Keynes, The General Theory, p. 149.
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CHAPTER
TECHNICAL ANALYSIS ANDINVESTING WITH THE TRENDMany skeptics, it is true, are inclined to dismiss the whole procedure[chart reading] as akin to astrology or necromancy; but the sheerweight of its importance in Wall Street requires that its pretensions beexamined with some degree of care.B E N J A M I N G R A H A M A N D D AV I D D O D D , 1 9 3 4 1
THE NATURE OF TECHNICAL ANALYSISFlags, pennants, saucers, and head-and-shoulders formations. Stochastics,moving-average convergence-divergence indicators, and candlesticks.Such is the arcane language of the technical analyst, an investor who forecasts future returns by the use of past price trends. Few areas of investment analysis have attracted more critics, yet no other area has a core ofsuch dedicated, ardent supporters. Technical analysis, often dismissed byacademic economists as being as useful as astrology, is being given a newlook, and some of the recent evidence is surprisingly positive.1Benjamin Graham and David Dodd, Security Analysis, 1st ed., New York: McGraw-Hill, 1934, p.618.
289Copyright © 2008, 2002, 1998, 1994 by Jeremy J. Siegel. Click here for terms of use.
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Technical analysts, or chartists as they are sometimes called, stand insharp contrast to fundamental analysts who use such variables as dividends, earnings, and book values to forecast stock returns. Chartists ignore these fundamental variables, maintaining that useful informationmay be gleaned by analyzing past price patterns. These patterns tend torepeat themselves and are the result of market psychology or unusualprice movements caused by informed traders. If these patterns are readproperly, chartists maintain, investors can use them to outperform themarket or share in the gains of those who are more knowledgeable abouta stock’s prospects.
CHARLES DOW, TECHNICAL ANALYSTThe first well-publicized technical analyst was Charles Dow, the creatorof the Dow Jones Industrial Average. But Charles Dow did not analyzeonly charts. In conjunction with his interest in market movements, Dowfounded the Wall Street Journal and published his strategy in editorials inthe early part of this century. Dow’s successor, William Hamilton, extended Dow’s technical approach and published the Stock Market Barometer in 1922. Ten years later, Charles Rhea formalized Dow’s concepts ina book entitled Dow Theory.Charles Dow likened the ebb and flow of stock prices to waves inan ocean. He claimed that there was a primary wave, which, like the tide,determined the overall trend. Upon this trend were superimposed secondary waves and minor ripples. He also claimed you could identifywhich trend the market was in by analyzing a chart of the Dow Jones Industrial Average, the volume in the market, and the Dow Jones Rail(now called the Transportation) Average.Those that follow the Dow theory acknowledged that the strategywould have gotten an investor out of the stock market before the October 1929 stock crash. Martin J. Pring, a noted technical analyst, arguesthat, starting in 1897, investors who purchased stock in the Dow JonesIndustrial Average and followed each Dow theory buy-and-sell signalwould have seen an original investment of $100 reach $116,508 by January 1990, as opposed to $5,682 with a buy-and hold strategy (these calculations exclude reinvested dividends).2 But confirming profits thatcome from trading based on the Dow theory is difficult because the buy2Martin Pring, Technical Analysis Explained, 3rd ed., New York: McGraw-Hill, 1991, p. 31. Also seeDavid Glickstein and Rolf Wubbels, “Dow Theory Is Alive and Well!” Journal of Portfolio Management, April 1983, pp. 28–32.
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and-sell signals are purely subjective and cannot be determined by precise numerical rules.
THE RANDOMNESS OF STOCK PRICESAlthough the Dow theory might not be as popular as it once was, technical analysis is still alive and well. The idea that you can identify themajor trends in the market, riding bull markets while avoiding bearmarkets, is still a fundamental pursuit of technical analysts.Yet most economists still attack the fundamental tenet of thechartists—that stock prices follow predictable patterns. To these academic researchers, the movements of prices in the market more closelyconform to a pattern called a random walk than to trends that forecast future returns.The first to make this connection was Frederick MacCauley, aneconomist in the early part of this century. His comments at a 1925 dinner meeting of the American Statistical Association on the topic of “forecasting security prices” were reported in the association’s officialjournal:MacCauley observed that there was a striking similarity between the fluctuations of the stock market and those of a chance curve which may be obtained by throwing dice. Everyone will admit that the course of such apurely chance curve cannot be predicted. If the stock market can be forecast from a graph of its movements, it must be because of its differencefrom the chance curve.3
More than 30 years later, Harry Roberts, a professor at the University of Chicago, simulated movements in the market by plotting pricechanges that resulted from completely random events, such as flips of acoin. These simulations looked like the charts of actual stock prices,forming shapes and following trends that are considered by chartists tobe significant predictors of future returns. But since the next period’sprice change was, by construction, a completely random event, such patterns could not logically have any predictive content. This early researchsupported the belief that the apparent patterns in past stock prices werethe result of completely random movements.But does the randomness of stock prices make economic sense?Factors influencing supply and demand do not occur randomly and are3
Journal of the American Statistical Association, vol. 20 (June 1925), p. 248. Comments made at the Aldine Club in New York on April 17, 1925.
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often quite predictable from one period to the next. Shouldn’t these predictable factors make stock prices move in nonrandom patterns?In 1965, Professor Paul Samuelson of MIT showed that the randomness in security prices did not contradict the laws of supply and demand.4 In fact, such randomness was a result of a free and efficientmarket in which investors had already incorporated all the known factors influencing the price of the stock. This is the crux of the efficient market hypothesis.If the market is efficient, prices will change only when new, unanticipated information is released to the market. Since unanticipated information is as likely to be good as it is to be bad, the resultingmovement in stock prices is random. Price charts will look like a randomwalk since the probability that stocks go up or down is completely random and cannot be predicted.5
SIMULATIONS OF RANDOM STOCK PRICESIf stock prices are indeed random, their movements should not be distinguishable from counterfeits generated randomly by a computer. Figure 17-1 extends the experiment conceived by Professor Roberts 50 yearsago. Instead of generating only closing prices, I programmed the computer to generate intraday prices, creating the popular high-low-closebar graphs that are found in most newspapers and chart publications.There are eight charts in Figure 17-1. A computer, using a randomnumber generator, has simulated four of these charts. In these charts,there is absolutely no way to predict the future from the past because future movements are designed to be totally independent from the past.The other four charts were chosen from actual data of the Dow Jones Industrial Average over recent years. Before reading further, try to determine which are real historical prices and which are computer created.Such a task is quite difficult. In fact, most of the top brokers at aleading Wall Street firm found it impossible to tell the difference between real and counterfeit data. Only two-thirds of brokers correctlyidentified Figure 17-1d, which depicts the period around the October 19,1987, stock crash. With the remaining seven charts, the brokers showed4
Paul Samuelson, “Proof That Properly Anticipated Prices Fluctuate Randomly,” Industrial Management Review, vol. 6 (1965), p. 49.5More generally, the sum of the product of each possible price change times the probability of its occurrence is zero. This is called a martingale, of which a random walk (50 percent probability up, 50percent probability down) is a special case.
CHAPTER 17 Technical Analysis and Investing with the Trend
FIGURE
293
17–1
Real and Simulated Stock IndexesFigure A
Figure B
Figure C
Figure D
Figure E
Figure F
Figure G
Figure H
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no ability to distinguish actual from counterfeit data. The true historicalprices are represented by charts b, d,