- Х & Fahim's Kindle for PC - A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition) File View Go Tools Help Library Back S Go to v Аа Show Notebook : Q 6 charts. To my great embarrassment, Ionce choked conspicu- ously at the dinner table when a chartist made such a comment. I have since made it a rule never to eat with a chartist. It's bad for digestion. Although technicians might not get rich following their own advice, their store of words is precious indeed. Consider this ad- vice offered by one technical service: o TECHNICAL ANALYSIS AND THE RANDOM-WALK THEORY sustained upward move. One cannot look at a stock chart like this without noticing the self-evidence of these statements. How can the economist be so myopic that he cannot see whatis so plainly visible to the naked eye? The persistence of this beliefin repetitive stock-market pat- terns is due to statistical illusion. To illustrate, let me describe an experimentin which I asked my students to participate. The students were asked to construct a stock chart showing the movements of a hypothetical stock initially selling at $50. For each successive trading day, the closing stock price would be determined by the flip of a coin. If the toss was a head, the students assumed that the stock closed 12 point higher than the preceding close. If the flip was a tail, the price was assumed to be down by 12. The chart below is the hypothetical stock chart derived from one of these experiments. Things are seldom what they seem. Skim milk masquerades as cream. - Gilbert and Sullivan, H.M.S. Pinafore The market's rise after a period of reaccumulation is a bullish sign. Nevertheless, fulcrum characteristics are not yet clearly present and a resistance area exists 40 points higher in the Dow, so it is clearly premature to say the next leg of the bull market is up. If, in the coming weeks, a test of the lows holds and the market breaks out of its flag, a further rise would be indicated. Should the lows be violated, a contin- uation of the intermediate term downtrend is called for. In view of the current situation, it is a distinct possibility that traders will sit in the wings awaiting a clearer delineation of the trend and the market will move in a narrow trading range. NOT EARNINGs, Nor dividends, nor risk, nor gloom of high interest rates stay the technicians from their assigned task: studying the price movements of stocks. Such single-minded devotion to numbers has yielded the most colorful theories and folklanguage of Wall Street: "Hold the winners, sell the losers," "Switch into the strong stocks," "Sell this issue, it's acting poorly," "Don't fight the tape." All are popular prescriptions of technical analysts. They build their strategies upon dreams of castles in the air and expect their tools to tell them which castle is being built and how to get in on the ground floor. The question is: Do they work? that the pattern of wallpaper behind the mirror is the same as the pattern above the mirror. The basic premise is that there are repeatable patterns in space and time. Chartists believe momentum exists in the market. Suppos- edly, stocks that have been rising will continue to do so, and those that begin falling will go on sinking. Investors should therefore buy stocks that start rising and continue to hold their strong stocks. Should the stock begin to fall, investors are ad- vised to sell. These technical rules have been tested exhaustively by using stock-price data on the major exchanges going back as far as the beginning of the twentieth century. The results reveal that past movements in stock prices cannot be used reliably to foretell future movements. The stock market has little, if any, memory. While the market does exhibit some momentum from time to time, it does not occur dependably, and there is not enough persistence in stock prices to make trend-following strategies consistently profitable. Although there is some short-term mo- mentum in the stock market, as will be described more fully in chapter 11, any investor who pays transactions costs and taxes cannot benefit from it. Economists have also examined the technician's thesis that there are often sequences of price changes in the same direc- tion over several days (or several weeks or months). Stocks are likened to fullbacks who, once having gained some momentum, can be expected to carry on for a long gain. It turns out that this is simply not the case. Sometimes one gets positive price changes (rising prices) for several days in a row; but sometimes when you are flipping a fair coin you also get a long string of "heads" in a row, and you get sequences of positive (or negative) price changes no more frequently than you can expect random sequences of heads or tails in a row. What are often called "per- sistent patterns" in the stock market occur no more frequently than the runs of luckin the fortunes of any gambler. This is what economists mean when they say that stock prices behave very much like a random walk. rawwodvorto 48 If you ask me what this means, I cannot tell you, but I think the technician probably had the following in mind: "If the market does not go up or go down, it will remain unchanged." Even the weather forecaster can do better than that. Obviously, I'm biased. This is not only a personal bias but a professional one as well. Technical analysis is anathema to much of the academic world. We love to pickon it. We have two main reasons: (1) after paying transactions costs and taxes, the method does not do better than a buy-and-hold strategy; and (2) it's easy to pickon. And while it may seem a bit unfair, just re- member that it's your money we're trying to save. Although the computer perhaps enhanced the standing of the technician for a time, and while charting services are widely available on the Internet, technology has ultimately proved to be the technician's undoing. Just as fast as he or she) creates charts to show where the market is going, the academic gets busy constructing charts showing where the technician has been. Because it's so easy to test all the technical trading rules on the computer, it has become a favorite pastime for academics to see whether they really work. friend of mine who practically jumped out of his skin. "What is this company?" he exclaimed. "We've got to buy immediately. This pattern's a classic. There's no question the stock will be up 15 points next week." He did not respond kindly when I told him the chart had been produced by flipping a coin. Chartists have no sense of humor. I got my comeuppance when Business Week hired a technician adept at hatchet work to review the first edi- tion of this book My students used a completely random process to produce their stock charts. With each toss, as long as the coins used were fair, there was a 50 percent chance of heads, implying an up- ward move in the price of the stock, and a 50 percent chance of tails and a downward move. Even if they flipped ten heads in a row, the chance of getting a head on the next toss was still 50 percent. Mathematicians call a sequence of numbers produced by a random process (such as those on our simulated stock chart) a random walk. The next move on the chartis completely unpredictable on the basis of what has happened before. The stock market does not conform perfectly to the mathema- tician's ideal of the complete independence of present price movements from those in the past. There is some momentum in stock prices. When good news arises, investors often only partially adjust their estimates of the appropriate price of the stock Slow adjustment can make stock prices rise steadily for a period, imparting a degree of momentum. The failure of stock prices to measure up perfectly to the definition of a random walkled the financial economists Andrew Loand A. Craig MacKinlay to publish a book entitled A Non-Random Walk Down Wall Street. In addition to some evidence of short-term momentum, there has been a long-run uptrend in most averages of stock prices in line with the long-run growth of earnings and dividends. But don't count on short-term momentum to give you some surefire strategy to allow you to beat the market. For one thing, stock prices don't always underreact to news—sometimes they overreact and price reversals can occur with terrifying suddenness. We shall see in chapter 11 that investment funds managed in accordance with a momentum strategy started off with subpar results. And even during periods when momentum is present and the market fails to behave like a random walk), the systematic relationships that exist are often so small that they are not useful to investors. The transactions charges and taxes involved in trying to take advantage of these dependencies are far greater than any profits that might be obtained. Thus, an accurate statement of the "weak" form of the random-walkhy- pothesis goes as follows: 44 44 HOLES IN THEIR SHOES AND AMBIGUITY IN THEIR FORECASTS The chart derived from random coin tossings looks remark- ably like a normal stock price chart and even appears to display cycles. Of course, the pronounced "cycles" that we seem to ob- serve in coin tossings do not occur at regular intervals as true cycles do, but neither do the ups and downs in the stock market. It is this lack of regularity that is crucial. The "cycles" in the stock charts are no more true cycles than the runs of luckor misfortune of the ordinary gambler. And the fact that stocks seem to be in an uptrend, which looks just like the upward move in some earlier period, provides no useful information on the dependability or duration of the current uptrend. Yes, history does tend to repeat itselfin the stock market, but in an infinitely surprising variety of ways that confound any attempts to profit from a knowledge of past price patterns. In other simulated stockcharts derived from studentcoin- tossings, there were head-and-shoulders formations, triple tops and bottoms, and other more esoteric chart patterns. One chart showed a beautiful upward breakout from an inverted head and shoulders (a very bullish formation). I showed it to a chartist University professors are sometimes asked by their students, “If you're so smart, why aren't you rich?" The question usually ran- kles professors, who think of themselves as passing up worldly riches to engage in such an obviously socially useful occupation as teaching. The same question is more appropriately addressed to technicians. Since the whole point of technical analysis is to make money, one would expect that those who preach it should practice it successfully. On close examination, technicians are often seen with holes in their shoes and frayed shirt collars. I personally have never known a successful technician, but I have seen the wrecks of several unsuccessful ones. Curiously, however, the broke tech- nician is never apologetic. If you commit the social error of asking him why he is broke, he will tell you quite ingenuously that he made the all-too-human error of not believing his own JUST WHAT EXACTLY IS A RANDOM WALK? IS THERE MOMENTUM IN THE STOCK MARKET? The technician believes that knowledge of a stock's past be- havior can help predict its probable future behavior. In other words, the sequence of price changes before any given day is important in predicting the price change for that day. This might be called "the wallpaper principle." The technical ana- lyst tries to predict future stock prices just as we might predict To many people this appears to be errant nonsense. Even the most casual reader of the financial pages can easily spot pat- terns in the market. For example, look at the stock chart on page 138. The chart seems to display obvious patterns. After an initial rise the stock turned down, and then headed persistently down- hill. Later, the decline was arrested and the stock had another 27% Page 134 of 421 • Location 1716 of 6862 H jj WE ⓇO ITEN O 0 a 4x ENG 10:31 PM 5/9/2019 - Х & Fahim's Kindle for PC - A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition) File View Go Tools Help Library Back S Go to v Аа Show Notebook : a The history of stock price movements contains no useful information that will enable an investor consistently to outperform a buy-and-hold strategy in managing a portfolio. holding the representative list of stocks in the market averages, the Dow follower actually comes out a little behind, because the strategy entails a number of extra brokerage costs as the investor buys and sells when the strategy decrees. O The Relative-Strength System If the weak form of the random-walk hypothesis is valid, then, as my colleague Richard Quandt says, “Technical analysis is akin to astrology and every bit as scientific." I am not saying that technical strategies never make money. They very often do make profits. The point is rather that a simple buy-and-hold strategy (that is, buying a stockor group of stocks and holding on for a long period of time) typically makes as much or more money. When scientists want to test the efficacy of some new drug, they usually run an experiment in which two groups of patients are administered pills—one containing the drug in question, the other a worthless placebo (a sugar pill). The results of the administration to the two groups are compared, and the drug is deemed effective only if the group receiving the drug did better than the group getting the placebo. Obviously, if both groups got better in the same period of time, the drug should not be given the credit, even if the patients did recover. In the stock-market experiments, the placebo with which the technical strategies are compared is the buy-and-hold strategy. Technical schemes often do make profits for their users, but so does a buy-and-hold strategy. Indeed, as we shall see later, a simple buy-and-hold strategy using a portfolio consisting of all the stocks in a broad stock-market index has provided investors with an average annual rate of return of about 10 percent over the past eighty years. Only if technical schemes produce better returns than the market can they be judged effective. To date, none has consistently passed the test. moved down 5 percent from a peak is said to be in a downtrend. You're supposed to buy any stock that has moved up 5 percent from its low and hold it until the price moves down 5 percent from a subsequent high, at which time you sell and, perhaps, even sell short. The short position is maintained until the price rises at least 5 percent from a subsequentlow. This scheme is very popular with brokers. Indeed, the filter method lies behind the popular "stop-loss" order favored by brokers, where the client is advised to sell his stockifit falls 5 percent below his purchase price to "limit his potential losses." The argument is that presumably a stock that falls by 5 percent will be going into a downtrend. Exhaustive testing of various filter rules has been under- taken. The percentage drop or rise that filters out buy and sell candidates has been allowed to vary from 1 percent to 50 per- cent. The tests covered different time periods and involved individual stocks as well as stockindexes. The results are remarkably consistent. When the higher transactions charges incurred under the filter rules are taken into consideration, these techniques cannot consistently beat a policy of simply buying the individual stock (or the stockindex) and holdingit over the period during which the testis performed. The individ- ual investor would do well to avoid using any filter rule and, I might add, any broker who recommends it. In the relative-strength system, an investor buys and holds those stocks that are acting well, that is, outperforming the general market indexes. Conversely, the stocks that are acting poorly relative to the market should be avoided or, perhaps, even sold short. While there do seem to be some time periods when a relative-strength strategy would have outperformed a buy-and-hold strategy, there is no evidence that it can do so consistently. As indicated earlier, there is some evidence of mo- mentum in the stock market. Nevertheless, a computer test of relative-strength rules over a twenty-five-year period suggests that such rules are not, after accounting for transactions charges and taxes, useful for investors. the opposite direction." Before the stock turns around, its price movements are supposed to form one of a number of extensive reversal patterns as the smart-money traders slowly "distrib- ute" their shares to the “public." Of course, we know some stocks do reverse directions in quite a hurry (this is called an "unfortu- nate V formation"), but perhaps some chart configurations can, like the Roman soothsayers, accurately foretell the future. Alas, the computer has even tested more arcane charting techniques, and the technician's tool has again betrayed him. In one elaborate study, the computer was programmed to draw charts for 548 stocks traded on the New York Stock Ex- change over a five-year period. It was instructed to scan all the charts and identify any one of thirty-two of the most popularly followed chart patterns. The computer was told to be on the lookout for heads and shoulders, triple tops and bottoms, chan- nels, wedges, diamonds, and so forth. Because the machine is a very thorough (though rather dull) worker, we can be sure that it did not miss any significant chart patterns. When the machine found that one of the bearish chart patterns such as a head and shoulders was followed by a downward move through the neckline toward décolletage (a most bearish omen), it recorded a sell signal. If on the other hand, a triple bot- tom was followed by an upside breakout (a most favorable au- gury), a buy signal was recorded. The computer then followed the performance of the stocks for which buy and sell signals were given and compared them with the performance record of the general market Again, there seemed to be no relationship between the tech- nical signal and subsequent performance. If you had bought only those stocks with buy signals, and sold on a sell signal, your performance after transactions costs would have been no better than that achieved with a buy-and-hold strategy. that the "hot hand" phenomenon is a myth. The psychologists did a detailed study of every shot taken by the Philadelphia 76ers over a full season and a half. They found no positive correlation between the outcomes of successive shots. Indeed, they found that a hit by a player followed by a miss was actually a bit likelier than the case of making two baskets in a row. Moreover, the researchers looked at sequences of more than two shots. Again, they found that the number of long streaks (that is, hitting of several baskets in a row) was no greater than could have been expected in a random set of data (such as flipping coins in which every event was independent of its predecessor). Although the event of making one's last two or three shots influenced the player's perception of whether he would make his next shot, the hard evidence was that there was no effect. The researchers then confirmed their study by examining the free-throw records of the Boston Celtics and by conducting controlled shooting experiments with the men and women of the Cornell University varsity basketball teams. These findings do not imply that basketball is a game of chance rather than skill. Obviously there are some players who are more adept at making baskets and free throws than others. The point is, however, that the probability of making a shot isin- dependent of the outcome of previous shots. The psychologists conjecture that the persistent belief in the hot hand could be due to memory bias. Iflong sequences of hits or misses are more memorable than alternating sequences, observers are likely to overestimate the correlation between successive shots. When events sometimes do come in clusters and streaks, people refuse to believe that they are random, even though such clusters and streaks do occur frequently in random data such as are derived from the tossing of a coin. Price-Volume Systems The Dow Theory Price volume systems suggest that when a stock (or the general market) rises on large or increasing volume, there is an unsatisfied excess of buying interest and the stock will continue its rise. Conversely, when a stock drops on large volume, selling pressure is indicated and a sell signal is given. Again, the investor following such a system is likely to be dis- appointed in the results. The buy and sell signals generated by the strategy contain no information useful for predicting future price movements. As with all technical strategies, however, the investor is obliged to do a great deal of in-and-out trading, and thus his transactions costs and taxes are far in excess of those ne- cessitated in a buy-and-hold strategy. After accounting for these costs, the investor does worse than he would by simply buying and holding a diversified group of stocks. SOME MORE ELABORATE TECHNICAL SYSTEMS Randomness Is Hard to Accept A GAGGLE OF OTHER TECHNICAL THEORIES TO HELP YOU LOSE MONEY Devotees of technical analysis may argue with some justifi- cation that I have been unfair. The simple tests I have just de- scribed do not do justice to the "richness" of technical analysis. Unfortunately for the technician, even more elaborate trading rules have been subjected to scientific testing. Let's examine a few popular ones in detail. The Dow theory is a great tug-of-war between resistance and support. When the market tops out and moves down, that previ- ous peak defines a resistance area, because people who missed selling at the top will be anxious to do so if given another op- portunity. If the market then rises again and nears the previous peak, it is said to be "testing" the resistance area. Now comes the moment of truth. If the market breaks through the resistance area, it is likely to keep going up for a while and the previous resistance area becomes a support area. If on the other hand, the market "fails to penetrate the resistance area" and instead falls through the preceding low where there was previous support, a bear-market signal is given and the investor is advised to sell. The basic Dow principle implies a strategy of buying when the market goes higher than the last peak and selling when it sinks through the preceding valley. There are various wrinkles to the theory, but the basic idea is part of the gospel of charting. Unhappily, the signals generated by the Dow mechanism have no significance for predicting future price movements. The market's performance after sell signalsis no different from its performance after buy signals. Relative to simply buying and Reading Chart Patterns Once the academic world polished off most of the standard tech- nical trading rules, it turned its august attention toward some of the more fanciful schemes. The world of financial analysis would be much quieter and duller without the chartists, as the following techniques amply demonstrate. Human nature likes order, people find it hard to accept the notion of randomness. No matter what the laws of chance might tell us, we search for patterns among random events wherever they might occur-not only in the stock market but eveninin- terpreting sporting phenomena. In describing an outstanding performance by a basketball player, reporters and spectators commonly use expressions such as “LeBron James has the hot hand" or “Kobe Bryant is a streak shooter." Those who play, coach, or follow basketball are almost universally convinced thatif a player has successfully made his last shot, or last few shots, he is more likely to make his next shot. A study by a group of psychologists, however, suggests The Filter System Perhaps some of the more complicated chart patterns, such as those described in the preceding chapter, are able to reveal the future course of stock prices. For example, is the downward penetration of a head-and-shoulders formation a reliable bearish omen? As one of the gospels of charting, Technical Anal- ysis, puts it, "One does not bringinstantly to a stop a heavy car moving at seventy miles per hour and, all within the same split second, turn it around and get it moving back down the road in The Hemline Indicator Under the popular "filter" system, a stock that has reached a low and has moved up, say 5 percent (or any other percent you wish to name), is said to be in an uptrend. A stock that has Not content with price movements, some technical analysts have broadened their investigations to include other move- ments as well. One of the most charming of these schemes has 28% Page 140 of 421 • Location 1806 of 6862 IH jj WE *O JOEN 0 a 4x ENG 10:31 PM 5/9/2019 Х & Fahim's Kindle for PC - A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition) File View Go Tools Help Library Back S Go to v Аа Show Notebook : a a indicator to give you a leg up on market timing. No longer are women imprisoned by the tyranny of hemlines. As Vogue put it, you can now dress like a man or woman, and all hemline lengths are now okay. I'm afraid this stock-market theory has undoubtedly outlived its usefulness. been called by the author Ira Cobleigh the "bull markets and bare knees" theory. Check the hemlines of women's dresses in any given year, and you'll have an idea of the direction of stock prices. The following chart suggests a loose tendency for bull markets to be associated with bare knees and depressed markets to be associated with bear markets for girl watchers. For example, in the late nineteenth century and early part of the twentieth, the stock market was rather dull, and so were hemlines. But then came rising hemlines and the great bull market of the 1920s, to be followed by long skirts and the crash of the 1930s. (Actually, the chart cheats a bit: hemlines fell in 1927, before the most dynamic phase of the bull market.) legend, invariably wrong. It turns out that the odd-lotter isn't such a stupendous dodo after all. A little stupid? Maybe. There is some indication that the performance of odd-lotters might be slightly worse than the stock averages. However, the available evidence indicates that knowledge of odd-lotters' actions is not useful for the formula- tion of investment strategies. the stocks of small companies are substantially higher than those for larger companies (because of higher bid-ask spreads and lower liquidity), and there appears to be no way any ordi- nary investor could exploit this anomaly. Moreover, the effectis not dependable in each year. In other words, the January “loose change" costs too much to pick up, and in some years it turns out to be a mirage. The Super Bowl Indicator Dogs of the Dow A Few More Systems Why did the market go up in 2009? That's easy to answer for a technical analyst who uses the Super Bowl indicator. The Super Bowl indicator forecasts how the stock market will perform on the basis of which team wins the Super Bowl. A victory by an original member of the National Football League such as the Steelers in 2009 predicts a bull market in stocks, whereas a victory by an original member of the American Football League is bad news for stock market investors. In 2002 the Patriots (AFL team) defeated the Rams (NFL), and the market responded correctly by falling sharply. Although the indicator sometimes fails, it has been correct far more often than it has been wrong. Naturally, it makes no sense. The results of the Super Bowl indicator simply illustrate nothing more than the fact that it's sometimes possible to correlate two completely unrelated events. Indeed, Mark Hulbert reports that the stock- market re- searcher David Leinweber found that the indicator most closely correlated with the S&P 500 Indexis the volume of butter pro- duction in Bangladesh rest This interesting strategy capitalized on a general contrarian conviction that out-of-favor stocks eventually tend to reverse direction. The strategy entailed buying each year the ten stocks in the Dow Jones 30-Stock Industrial Average that had the high- est dividend yields. The idea was that these ten stocks were the most out of favor, so they typically had low price-earnings mul- tiples and low price-to-book-value ratios as well. The theory is attributed to a money manager named Michael O'Higgins, who publicized the technique in his book Beating the Dow. James O'Shaughnessy tested the theory as far back as the 1920s; he found that the Dogs of the Dow had beaten the overall index by over 2 percentage points per year with no additional risk. Members of the canine contingent of Wall Street analysts raised their ears and marketed billions of dollars of mutual funds on the basis of the principle. And then, just as might be expected, success bit the dogs. The Dogs of the Dow consistently underperformed the overall market. As the Dogs star O'Higgins opined, "the strategy became too popular" and ultimately self- destructed. The Dogs of the Dow no longer hunt. To continue this review of technical schemes would soon generate rapidly diminishing returns. Probably few people seriously believe that the sunspot theory of stock-market move- ments can make money for them. But do you believe that by following the ratio of advancing to declining stocks on the New York Stock Exchange you can find a reliable leading indicator of general stock market peaks? A careful computer study says no. Do you think that a rise in short interest (the number of shares of a stock sold short) is a bullish signal (because eventually the stock will be repurchased by the short seller to cover his or her position)? Exhaustive testing indicates no relationship either for the stock market as a whole or for individual issues. Do you think that a moving-average system as espoused by some of the financial television networks (for example, buy a stockifits price or its fifty-day average price goes higher than its average price over the past 200 days and sell itifit goes below the aver- age) can lead you to extraordinary stock-market profits? Notif you have to pay transactions charges—to buy and sell! Do you think you should "Sell in May and Go Away" until October? In fact, the market rises between May and October more often than OTHER AND Prechter was so excited about this discovery that he quit Merrill Lynch in 1979 to write an investor newsletter from the unlikely location of Gainesville, Georgia. Prechter's initial predictions were uncannily accurate. Early in the 1980s, he predicted a major bull market with the Dow e ex- pected to rise to the 3,600 level. Prechter was the golden knight of the day by keeping his followers fully invested through his predicted "interim stop" at 2,700. Tarnish set in after October 1987. To Prechter's credit, he did say that there was "a 50/50 risk of a 10% decline in the market on October 5, 1987. But he advised institutional investors to hang on for the ultimate target of 3,686 in the Dow. After the crash, with the Dow near 2,000, Prechter turned bearish for the long term and recommended holding Treasury bills. He pre- dicted that "the great bull market is probably over" and that by the early 1990s the Dow Jones Industrial Average would plunge below 400. Prechter missed out on the entire bull market of the 1990s. This was a mortal wound for a golden guru. Prechter re- mained a consistent bear, however, and did gain some renewed following during the market's meltdown of the early 2000s. This only proves that if one keeps predicting a market decline (or rise) one is bound to be correct at some time. Prechter was succeeded by Elaine Garzarelli, then an execu- tive vice president of the investment firm of Lehman Brothers. Garzarelli was not a one-indicator woman. She plunged into the ocean of financial data and used thirteen different indicators to predict the course of the market. Garzarelli always liked to study vital details. As a child, she would get animal organs from the local butcher and dissect them. Garzarelli was the Roger Babson of the 1987 crash. Turning bearish in August, she was recommending by September 1 that her clients get out of the stock market. By October 11, she was confident that a crash was imminent. Two days later, in a fore- cast almost frighteningly prescient, she told USA Today that a drop of more than 500 points in the Dow was coming. Within a week, her predictions were realized. But the crash was Garzarelli's last hurrah. Just as the media were coronating her as the "Guru of Black Monday" and adula- tory articles appeared in magazines ranging from Cosmopolitan to Fortune, she drowned in her prescience-or her notoriety. After the crash, she said she wouldn't touch the market and pre- dicted that the Dow would fall another 200 to 400 points. Thus, Garzarelli missed the bounce-back in the market. Moreover, those who put money in her hands were sadly disappointed. In explaining her lack of consistency, she gave the time-honored explanation of technicians: “I failed to believe my own charts." 19 The Odd-Lot Theory not. January Effect Technical Market Gurus Things did not workout as well in the post-World War II pe- riod. The market declined sharply during the summer of 1946, well in advance of the introduction of the “New Look" featuring longer skirts in 1947. Similarly, the sharp stock- market decline that began at the end of 1968 preceded the introduction of the midiskirt, which was high fashion in 1969 and especially in 1970. How did the theory workout during the crash of 1987? You might think the hemline indicator failed. After all, in the spring of 1987, when designers began shipping their fall lines, very short skirts were decreed as the fashion for the time. But along about the beginning of October, when the first chill winds began blowing across the country, a strange thing happened: Most women decided that miniskirts were not for them. As women went back to long skirts, designers quickly followed suit. The rest is stock-market history. And how about the severe bear markets of the first decade of the 2000s? Unfortunately, you guessed it, pants became the fashion Women business leaders and politicians always appeared in pants suits. Now we know the real culprit for the punishing bear markets of the period. Even though there does seem to be some evidence in favor of the theory, don't be too optimistic about expecting the hemline The odd-lot theory holds that except for the investor who is always right, no one can contribute more to a successful invest- ment strategy than an investor who is invariably wrong. The "odd-lotter," according to popular superstition, is that kind of person. Thus, success is assured by buying when the odd-lotter sells and selling when the odd-lotter buys. Odd-lotters are the people who trade stocks in less than 100- share lots (called round lots). Many amateurs in the stock market cannot afford the $5,000 investment to buy a round lot(100 shares) of stock selling at $50 a share. They are more likely to buy, say, ten shares for a more modest investment of $500. By examining the ratio of odd-lot purchases (the number of shares these amateurs bought during a particular day) to odd- lot sales(the number of shares they sold) and by looking at what particular stocks odd-lotters buy and sell, one can supposedly make money. These uninformed amateurs, presumably acting solely out of emotion and not with professional insight, are lambs in the street being led to slaughter. They are, according to A number of researchers have found that January has been a very unusual month for stock-market returns. Stock-market returns have tended to be especially high during the first two weeks of January. The effect appears to be particularly strong for smaller firms. Even after one adjusts for risk, small firms appear to offer investors abnormally generous returns—with the excess returns produced largely during the first few days of the year. Such an effect has also been documented for several foreign stock markets. This led to the publication of one book with the provocative title The Incredible January Effect. Investors and especially stockbrokers, with visions of large commissions dancing around in their heads, designed strategies to capitalize on this "anomaly" believed to be so dependable. Unfortunately, however, the transactions costs of trading in Technicians may not make accurate predictions, but the early ones were certainly colorful. During the 1980s, for example, the most influential market guru was Robert Prechter. Prechter became interested in the parallels between social psychology and the stock market while a Yale undergraduate. After college, Prechter spent four years playing drums in a rockband, after which he joined Merrill Lynch as a junior technical analyst. There Prechter stumbled on the work of an obscure accountant, R. N. Elliott, who had devised an arcane theory that he modestly entitled the Elliott wave theory. Elliott's premise was that there were predictable waves of investor psychology and that they steered the market with natural ebbs and flows. By watching them, Elliott believed, one could call major shifts in the market. 30% Page 146 of 421 • Location 1901 of 6862 H jj WE ⓇO JOEN 0 a 4x ENG 10:31 PM 5/9/2019 - Х & Fahim's Kindle for PC - A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition) File View Go Tools Help Library Back S Go to v Аа Show Notebook : IMPLICATIONS FOR INVESTORS a a chartist's durability suggests that the capitalist system may gar- denlike most of the rest of us. We like to see our best plants grow, but, as summer wears on the weeds frequently get the best of wrote it all up in Beat the Dealer. Since then, casinos switched to the use of several decks of cards to make it more difficult for card counters and, as a last resort, they banished the counters from the gaming tables. If such a regularity was known to only one individual, he would simply practice the technique until he had collected a large share of the marbles. He surely would have no incentive to share a truly useful scheme by making it available to others. us. The point is, the technicians often play an important role in the greening of the brokers. Chartists recommend trades, almost every technical system involves some degree of in-and- out trading. Trading generates commissions, and commissions are the lifeblood of many brokerage houses. The technicians do not help produce yachts for the customers, but they do help gen- erate the trading that provides yachts for the brokers. APPRAISING THE COUNTERATTACK Perhaps the most colorful investment gurus of the mid-1990s were the homespun, grandmotherly (median age seventy) Beardstown Ladies. Called by publicists "the greatest invest- ment minds of our generation," these celebrity grannies cooked up profits and hype, selling more than a million books and ap- pearing frequently on national television shows and in weekly magazines. They mixed explanations of their investment success ("heartland" virtues of hard work and churchgoing) with yummy cooking recipes (such as stock-market muffins guaranteed to rise). In their best-selling 1995 book, The Beard- stown Ladies Common Sense Investment Guide, they claimed that their investment returns were 23.9 percent per year over the preceding decade, far eclipsing the 14.9 annual percent return of the S&P 500 Index. What a great story: Little old mid- western ladies using common sense could beat the pants off the overpaid investment pros of Wall Street and could even put index funds to shame. Unfortunately, the ladies were discovered to be cooking the books as well. Apparently, members of the Beardstown group were counting their investment club dues as part of their stock- market profits. The accounting firm Price Waterhouse was called in, and it calculated the ladies' true investment return over the decade to be 9.1 percent per year-almost 6 points below the overall market. So much for getting rich by worship- ing investment idols. The moral to the story is obvious. With large numbers of tech- nicians predicting the market, there will always be some who have called the last turn or even the last few turns, but none will be consistently accurate. To paraphrase the biblical warning, "He who looks back at the predictions of market gurus dies of remorse." As you might imagine, the random-walk theory's dismissal of charting is not altogether popular among technicians. Aca- demic proponents of the theory are greeted in some Wall Street quarters with as much enthusiasm as Bernie Madoff address- ing the Better Business Bureau from his jail cell. Technical analysts consider the theory "just plain academic drivel." Let us pause, then, and appraise the counterattack by beleaguered technicians. Perhaps the most common complaint about the weakness of the random-walk theory is based on a distrust of mathematics and a misconception of what the theory means. “The market isn't random," the complaint goes, and no mathematician is going to convince me it is." Even so astute a commentator on the Wall Street scene as "Adam Smith" displays this misconception when he writes, “I suspect that even if the random walkers an- nounced a perfect mathematical proof of randomness I would go on believing that in the long run future earnings influence present value, and that in the short run the dominant factor is the temper of the crowd." Of course, earnings and dividends influence market prices, and so does the temper of the crowd. We saw ample evidence of this in earlier chapters of the book. But, even if markets were dominated during certain periods by irrational crowd behav- ior, the stock market might well still be approximated by a ran- dom walk. The original illustrative analogy of a random walk concerned a drunken man staggering around an empty field. He is not rational, but he's not predictable either. Moreover, new fundamental information about a company (a big mineral strike, the death of the president, etc.) is also unpre- dictable. It will occur randomly over time. Indeed, successive appearances of news items must be random. If an item of news were not random, that is, ifit were dependent on an earlier item of news, then it wouldn't be news at all. The weak form of the random-walktheory says only that stock prices cannot be pre- dicted on the basis of past stock prices. The technical analyst will also cite chapter and verse that the academic world has certainly not tested every technical scheme that has been devised. No economist or mathematician, however skillful, can prove conclusively that technical meth- ods can never work. All that can be said is that the small amount of information contained in stock-market pricing patterns has not been shown to be sufficient to overcome the transactions costs and taxes involved in acting on that information. Each year a number of eager people visit the gambling parlors of Las Vegas and Atlantic City and examine the last several hun- dred numbers of the roulette wheel in search of some repeating pattern. Usually they find one. And so they stay until they lose everything because they do not retest the pattern. The same thing is true for technicians. If you examine past stock prices in any given period, you can almost always find some kind of system that would have worked in a given period. If enough different criteria for selecting stocks are tried, one will eventually be found that selects the best ones of that period. The real problem is, of course, whether the scheme works in a different time period. What most advocates of technical analysis usually fail to do is to test their schemes with market data derived from periods other than those during which the scheme was developed. Even if the technician follows my advice, tests his scheme in many different time periods, and finds ita reliable predictor of stock prices, I still believe that technical analysis must ul- timately be worthless. For the sake of argument, suppose the technician had found a reliable year-end rally, that is, every year stock prices rose between Christmas and New Year's Day. The problem is that once such a regularity is known to market participants, people will actin a way that prevents it from hap- pening in the future.t Any successful technical scheme must ultimately be self- defeating. The moment I realize that prices will be higher after New Year's Day than they are before Christmas, I will start buy- ing before Christmas ever comes around. If people know a stock will go up tomorrow, you can be sure it will go up today. Any regularity in the stock market that can be discovered and acted upon profitably is bound to destroy itself. This is the fundamen- tal reason why I am convinced that no one will be successful in using technical methods to get above-average returns in the stock market. The past history of stock prices cannot be used to predict the future in any meaningful way. Technical strategies are usually amusing, often comforting, but of no real value. This is the weak form of the efficient market hypothesis. Technical theories enrich only the people preparing and marketing the technical service or the brokerage firms who hire technicians in the hope that their analyses may help encourage investors to do more in- and-out trading and thus generate commission business for the brokerage firm. Using technical analysis for market timing is especially dan- gerous. Because there is a long-term uptrend in the stock mar- ket, it can be very risky to be in cash. Aninvestor who frequently carries a large cash position to avoid periods of market decline is very likely to be out of the market during some periods where it rallies smartly. Professor H. Negat Seybun of the University of Michigan found that 95 percent of the significant market gains over a thirty-year period came on 90 of th 7,500 trading days. If you happened to miss those 90 days, just over 1 percent of the total, the generous long-run stock-market returns of the period would have been wiped out. Studying a longer period, Laszlo Birinyi, in his book Master Trader, has calcu- lated that a buy-and-hold investor would have seen one dollar invested in the Dow Jones Industrial Average in 1900 grow to $290 by the start of 2013. Had that investor missed the best five days each year, however, that dollar investment would have been worth less than a penny in 2013. The point is that market timers risk missing the infrequent large sprints that are the big contributors to performance. The implications of this analysis are simple. If past prices con- tain little or no useful information for the prediction of future prices, there is no point in following any technical trading rule for the timing of purchases or sales. A simple policy of buying and holding will be at least as good as any technical procedure. Moreover, buying and selling to the extent that it is profitable at all, tends to generate capital gains, which are subject to tax. By following any technical strategy, you are likely to realize short- term capital gains and pay larger taxes (as well as paying them sooner) than you would under a buy-and-hold strategy. Thus, simply buying and holding a diversified portfolio suited to your objectives will enable you to save on investment expense, bro- kerage charges, and taxes. WHY ARE TECHNICIANS STILL HIRED? It seems very clear that under scientific scrutiny chart reading must share a pedestal with alchemy. There has been a remark- able uniformity in the conclusions of studies done on all forms of technical analysis. Not one has consistently outperformed the placebo of a buy-and-hold strategy. Technical methods cannot be used to make useful investment strategies. This is the funda- mental conclusion of the random-walktheory. A former colleague of mine believed that the capitalist system would weed out all useless growths such as the flourishing technicians. "The days of these modern-day soothsayers on Wall Street are numbered," he would say. “Brokers will soon learn they can easily do without the technicians' services." The "Edward O. Thorp actually did find a method to win at blackjack. Thorp 31% Page 153 of 421 • Location 1993 of 6862 H jj WL ITEN O D 4x ENG 10:31 PM 5/9/2019 - Х & Fahim's Kindle for PC - A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition) File View Go Tools Help Library Back S Go to Аа Show Notebook : Q 7 HOW GOOD IS FUNDAMENTAL ANALYSIS? THE EFFICIENT-MARKET HYPOTHESIS is whether fundamental analysis is any good. Two opposing views have been taken about the efficacy of fundamental analysis. Wall Streeters feel that fundamental analysis is becoming more powerful all the time. The individ- ual investor has scarcely a chance against the professional port- folio manager and a team of fundamental analysts. Many in the academic community sneer at such pomposity Some academicians have gone so far as to suggest that a blind- folded monkey throwing darts at the stocklistings can select stocks with as much success as professional portfolio managers. They have argued that fund managers and their analysts can do no better at picking stocks than a rank amateur. This chapter will recount the major battle in an ongoing war between aca- demics and market professionals, explain what is meant by the efficient market hypothesis," and tell you why it is important to your wallet How could I have been so mistaken as to have trusted the experts? -John F. Kennedy after the Bay of Pigs fiasco ARE SECURITY ANALYSTS FUNDAMENTALLY CLAIRVOYANT? the public schools of New York City, and found that 611 of these had had their tonsils removed. The remaining 389 were then examined by a group of physicians, who selected 174 of these for tonsillectomies and declared that the rest had no tonsil prob- lem. The remaining 215 were reexamined by another group of doctors, who recommended 99 of these for tonsillectomies. When the 116 "healthy" children were examined a third time, a similar percentage were told their tonsils had to be removed. After three examinations, only 65 children remained who had not been recommended for tonsillectomies. These remaining children were not examined further, because the supply of ex- amining physicians ran out. Numerous studies have shown similar results. Radiologists have failed to recognize the presence of lung disease in about 30 percent of the X-ray plates they read, despite the clear presence of the disease on the X-ray film. Another experiment proved that professional staffs in psychiatric hospitals could not tell the sane from the insane. The point is that we should not take for granted the reliability and accuracy of any judge, no matter how expert. When one considers the low reliability of so many kinds of judgments, it does not seem too surprising that security analysts, with their particularly difficult forecasting job, should be no exception There are, I believe, five factors that help explain why security analysts have such difficulty in predicting the future. These are (1) the influence of random events, (2) the production of dubious reported earnings through "creative" accounting pro- cedures, (3) errors made by the analysts themselves, (4) the loss of the best analysts to the sales desk or to portfolio management, and (5) the conflicts of interest facing securities analysts at firms with large investment banking operations. Each factor deserves some discussion. IN THE BEGINNING he was a statistician. He wore a white starched shirt and threadbare blue suit. He quietly put on his green eyeshade, sat down at his desk, and recorded meticu- lously the historical financial information about the companies he followed. The result: writer's cramp. But then a metamor- phosis began to set in. He rose from his desk, bought blue button- down shirts and gray flannel suits, threw away his eyeshade, and began to make field trips to visit the companies that previ- ously he had known only as a collection of financial statistics. His title now became security analyst. As time went on, his salary and perks attracted the attention of his female cohorts, and they too donned suits. And just about ev- erybody who was anybody was now flying first-class and talking money, money, money. The new generation was hip; suits were out, and Gucci shoes and Armani slacks were in. They were so incredibly brilliant and knowledgeable that portfolio managers relied on their recommendations and Wall Street firms used them increasingly to cultivate investment banking clients. They were now equity research stars. Some, however, whis- pered unkindly that they were investment banking whores. “IBM," the cry immediately went up, "remember IBM." I do remember IBM: a steady high grower for decades. For a while it was a glaring exception. But after the mid-1980s, even the mighty IBM failed to continue its dependable growth pattern. I also remember Polaroid, Kodak, Nortel Networks, Xerox, and dozens of other firms that chalked up consistent high growth rates until the roof fell in. I hope you remember not the current exceptions, but rather the rule: Many in Wall Street refuse to accept the fact that no reliable pattern can be discerned from past records to aid the analyst in predicting future growth. Even during the boom years of the 1990s, only one in eight large companies managed to achieve consistent yearly growth. And not even one continued to enjoy growth into the first years of the new millennium. Analysts can't predict consistent long-run growth, because it does not exist. A good analyst will argue, however, that there's much more to predicting than just examining the past record. Some will even admit that the past record is not a perfect measurement. Rather than examine every factor that goes into the actual forecasting process, John Cragg and I decided to concentrate on the end re- sult the prediction itself. Donning our cloak of academic detachment, we wrote to nineteen of the most respected Wall Street firms engaged in fun- damental analysis. We asked these firms for their estimates of the future one-year and five-year earnings for a large sample of S&P 500 companies. These estimates, made at several different times, were then compared with actual results to see how well the analysts forecast short-run and long-run earnings changes. The results were surprising. Bluntly stated, the careful estimates of security analysts (based on industry studies, plant visits, etc.) do little better than those that would be obtained by simple extrapolation of past trends, which we have already seen are no help at all. Indeed, when compared with actual earnings growth rates, the five- year estimates of security analysts were actually worse than the predictions from several naive forecasting models. Our method of determining the efficacy of the security ana- lyst's diagnoses of his companies is exactly the same as was used before in evaluating the technicians' medicine. We compared the results obtained by following the experts with the results from some naive mechanism involving no expertise at all. Sometimes these naive predictors work very well. For example, if you want to forecast the weather tomorrow, you will do a pretty good job by predicting that it will be exactly the same as today. Although this system misses every turning point in the weather, most days it is quite reliable. How many weather fore- casters do you suppose do any better? When confronted with the poor record of their five-year growth estimates, the security analysts honestly, if sheepishly, admitted that five years ahead is really too far in advance to make reliable projections. They felt that they really ought to be judged on their ability to project earnings changes one year ahead. Believe it or not, it turned out that their one-year fore- casts were even worse than their five-year projections. The analysts fought back gamely. They complained that it was unfair to judge their performance on a wide cross section of industries, because earnings for high-tech firms and various "cyclical" companies are notoriously hard to forecast. "Try us on utilities," one analyst confidently asserted. So we tried it and they didn't like it. Even the forecasts for the "stable" utilities were far off the mark. This led to the second major finding of our study: Not one industry is easy to predict. Moreover, no analysts proved consistently superior to the oth- ers. Of course, in each year some analysts did much better than average, but no consistency in their pattern of performance was found. Analysts who did better than average one year were no more likely than the others to make superior forecasts in the next year. These findings have been confirmed by several other researchers. For example, Michael Sandretto of Harvard and Sudhir Milkrishnamurthi of MIT completed a massive study of the one-year forecasts of the 1,000 most widely followed com- panies. Their staggering conclusion was that the error rates each year were remarkably consistent and that the average annual error of the analysts was 31.3 percent over a five-year period. Financial forecasting appears to be a science that makes astrol- ogy look respectable. Amid all these accusations is a deadly serious message: Secu- rity analysts have enormous difficulty in performing their basic function of forecasting company earnings prospects. Investors who put blind faith in such forecastsin making their investment selections are in for some rude disappointments. Forecasting future earnings is the security analysts' raison d'être. As Institutional Investor put it, "Earnings are the name of the game and always will be." To predict future directions, analysts generally start by looking at past wanderings. “A proven score of past performance in earnings growth is," one analyst told me, "a most reliable indicator of future earnings growth." If management is really skillful, there is no reason to think that it will lose its Midas touch in the future. If the same adroit management team re- mains at the helm, the course of future earnings growth should continue as it has in the past, or so the argument goes. While it sounds suspiciously like an argument used by technical an- alysts, fundamentalists pride themselves on the fact thatitis based on specific, proven company performance. Such thinking flunks in the academic world. Calculations of past earnings growth are no help in predicting future growth. If you had known the growth rates of all companies during, say, the 1980-90 period, this would not have helped you at all in predicting what growth they would achieve in the 1990-2000 period. And knowing the fast growers of the 1990s did not help analysts find the fast growers of the first decade of the twenty- first century. This startling result was first reported by British researchers for companies in the United Kingdom in an article charmingly titled "Higgledy Piggledy Growth." Learned aca- demicians at Princeton and Harvard applied the British study to U.S. companies-and, surprise, the same was true here! 1. The Influence of Random Events WHY THE CRYSTAL BALL IS CLOUDED THE VIEWS FROM WALL STREET AND ACADEMIA Many of the most important changes that affect the basic prospects for corporate earnings are essentially random, that is, unpredictable. Take the utility industry, to which I referred earlier. Presumably itis one of the most stable and dependable groups of companies. But, in fact, many important unpre- dictable events made earnings even for this industry enor- mously difficult to forecast. Unexpected unfavorable rulings of state public utility commissions often made it impossible for utilities to translate rapid growth in demand into higher profits. In the 1970s and early 2000s, forecasts were very wide of the markas analysts failed to predict the increased fuel costs result- ing from the sharp increase in the international price of oil. It is always somewhat disturbing to learn that highly trained and well-paid professionals may not be terribly skillful at their calling. Unfortunately, this is hardly unusual. Similar types of findings exist for most groups of professionals. There is a classic example in medicine. At a time when tonsillectomies were very fashionable, the American Child Health Association surveyed a group of 1,000 children, eleven years of age, from No matter what title, derogatory or otherwise, these individuals hold, the great majority are fundamentalists. Thus, studies casting doubt on the efficacy of technical analysis would not be considered surprising by most professionals. At heart, the Wall Street pros are fundamentalists. The really important question 32% Page 159 of 421 • Location 2074 of 6862 H jj WL ⓇO JENO 0 a 4x ENG 10:32 PM 5/9/2019
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