a winning streak tothrill players and onlookers. The excitement is conveyed by the common expressions “hot hand” and “in the zone.” In Fools Die, the late Mario Puzo described the magic of a gambler’s $400,000 lucky night:
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Practical SpeculationHe bet two hundred on the line, backed up his numbers and then bought all thenumbers for five hundred dollars each. He held the dice for almost an hour. Afterthe first fifteen minutes the electricity of his hot hand ran through the casino andthe table jammed full. . . . [When] the dice passed from his hands to the nextplayer, the gamblers at the table gave him a cheer. The pit boss gave him metalracks to carry his chips to the casino cage.8
Plenty of examples of winning streaks in sports come to mind, particularly in basketball. There was the 8,829-game run of the Harlem Globetrotters from the 1960s to the 1990s. Before Michigan State’s basketball teambeat them in November 2000, they had not lost a college game since 1962.The Los Angeles Lakers won 33 games in a row from November 5, 1971, toJanuary 7, 1972.North Carolina’s NCAA Women’s soccer team had a 103-game unbeatenstreak from September 30, 1986, to September 17, 1990. From 1987 to 1997,the Cuban National baseball team won 150 consecutive games.Sometimes the hot hand shows up in an individual player during a singlegame. In Game 3 of the NBA playoffs between the New Jersey Nets andBoston Celtics on May 22, 2002, the Nets were ahead by 21 points at the endof the third quarter, 74–53. That’s when Paul Pierce of the Celtics, perhapsinspired by rousing comments from teammate Antoine Walker, entered “thezone.” Until then, he had scored just 9 points, but he piled up 19 in the finalquarter. The Celtics won the game 94–90. (In this case, Walker’s individualstreak won out over a statistical streak in NBA history that had favored theNets. Until that day, 171 teams had headed into the fourth quarter with leadsof 18 points or more, and none had ever lost.)The critical question is whether streaks are consistent with chance. Ifathletes or teams are good, they are likely to win more than half the time. Istheir chance of winning better after they win a few times than when theylose? Are hot hands real, or do they just seem that way because of the vagaries of memory?Most researchers who have studied hot hands conclude the concept is amyth. The expert in the field is Cornell University psychology professor ThomasGilovich. In a series of studies, he looked at records of shots from the floor byplayers in the Philadelphia 76ers, foul shots by the Boston Celtics, three-pointshots in the All-Star contest, and a shooting experiment with the Cornell collegeteam. In each case, he concluded, “detailed analyzes provided no evidence for apositive correlation between the outcomes of successive shots.”After sinking a few in a row, a player may think he is in the zone. But thenumbers show that the chance of hitting the next shot tends to decreaseslightly from the average level of some 50 percent.
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One of the criticisms of these basketball studies is that they attempt tomeasure individual hot hands in team sports where there is significant interaction. However, Jim Albert and Jay Bennett examined streaks of baseball batters and teams during the 1998 season in their 2001 book Curve Ball: Baseball,Statistics, and the Role of Chance in the Game, and found that only six of 30teams showed streakiness, a result consistent with chance.9Some studies have found evidence of streaks in other sports. A study ofhot hands in the Professional Bowling Association tour found some shortterm persistence in individual scores. In a noteworthy study of horseshoepitchers’ hot hands, Pomona College economics professor Gary Smith foundthat the number of double ringers pitched showed strong persistence. Aftertwo doubles in a row, the players in world championships pitch doubles 60percent of the time. After two nondoubles in a row, they pitch double ringersonly 47 percent of the time. Smith disagreed with the basketball data of Cornell’s Gilovich, and concluded that horseshoe players do have modest hot andcold spells. Barry Nalebuff and Avinash Dixit, game theory experts and coauthors of The Competitive Edge in Business, Politics, and Everyday Life, have thisto say about the apparent difference between individual and team streaks:While the statistical evidence denies the presence of streak shooting, it doesn’t refute the possibility that a hot player might warm up the game in some other way.The difference between streak shooting and a hot hand arises because of the interaction between the offensive and the defensive strategies. Suppose AndrewToney does have a truly hot hand. Surely the other side would start to crowd him.This could easily lower his shooting percentage. That is not all. When the defensefocuses on Toney, one of his teammates is left unguarded and is more likely toshoot successfully. In other words, Toney’s hot hand leads to an improvement inthe 76ers team performance, although there may be a deterioration in Toney’s individual performance.10
“Which,” observed Hany Saad, the equities and derivativestrader at the Royal Bank of Canada who called our attention tothe Dixit-Nalebuff study, “takes us back to Robert Bacon’shandicapping principles and ever-changing cycles.”
The Market’s Momentum PendulumThe belief in streaks is as common in the market—where it goes by the names“trend” and “momentum”—as it is in gambling and sports. Just as a cardplayer feels “in the zone” after filling in a few flushes, everyone’s bullish whenstocks go up three weeks in a row and bearish after three down weeks. While
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players have memories, most people would agree that cards don’t have memory. But do stocks have memory?The evidence on individual stocks favors the antitrend school. JonathanLewellen, an instructor at the Massachusetts Institute of Technology, concluded in a series of seminal studies that the evidence for mean reversion isstrong. He used 66 years of data, from 1932 to 1998, going through millionsof careful calculations and correcting for all the usual biases in studies of thisnature. Calculating the mean average price of a stock in a single year, he foundthat stocks returned 41 percent toward the mean, on average, over the next sixquarters. From 1968 through 2000, Lewellen found the correlation was a negative 24 percent. Thus, if the return on a stock was 50 percentage points belowthe mean in one year, the best prediction for the next six quarters would be arise of 24 percent times 50 percent, or 12 percent above the mean.Normally, after showing that all the evidence is against atheory, we would be content to end with a snappy conclusionto the effect of “The trend is not your friend.” Yet no fixed rulecan be expected to last forever. Too many smart people arearound to anticipate and dissipate the effect. The cycles, as we often remindourselves, are always changing.
Have Things Changed?Given that the evidence over the past 60 or 70 years is antithetical to the trendfollowers on individual stocks, and that recent evidence on trends in the averages is equally unfavorable, we nevertheless had to ask ourselves, how istrend-following doing right now, at the start of the new century, comparedwith mean-reversion investing?After all, academic findings too often come down the pike at exactly thewrong time for investors. Take the groundbreaking 1981 study published inthe Journal of Financial Economics which concluded that small stocks consistently registered higher returns than larger ones. The study’s release was followed by 18 years in which small stocks lagged larger stocks. Regrettably, thebad stretch began in 1983, after a honeymoon period gave the numerous newsmall-cap investment vehicles inspired by the study enough time to attract alot of money. Dimson, Marsh, and Staunton called attention to this reversal offortune in a 1999 article entitled “Murphy’s Law and Market Anomalies.”11Ironically, in 1999, the year the article was published, small caps recordedone of their best years ever. In 2000 and 2001, they continued to do wellenough to outperform the S&P 500.
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The truth is that the market panorama is rich enough tofind anecdotes that seem to support any kind of market relation. To find out whether the cycle might be changing onceagain, whom are you going to call? The Speculators.We took the 20 best and worst performers in the S&P 500 during the year2000. (The current S&P 500 contains a few companies that were not aroundat the beginning of 2000, so it was necessary to eliminate all such new additions from our tally.) We found that the 20 best stocks of 2000 returned an average of −11 percent over the subsequent 16 months (through April 29, 2002).Calpine, down 76 percent, PerkinElmer Inc., down 76 percent, and Allergan,down 32 percent, were among the bests that stumbled badly. (The situationwould have been even worse if such stocks as Enron, a stalwart member andtop performer of the S&P in 2000, had been included. Enron was delisted inNovember 2001, and we had to drop its bad results, which would have takenanother 5 percentage points from the 20 best.)The 20 worst stocks of 2000 were unchanged in the next 16 months, onaverage. That list included some standout winners such as American Greetings, up 91 percent from December 29, 2000, through April 29, 2002; AppleComputer, up 55 percent; Cendant, up 91 percent; Circuit City, up 86 percent;and Dell, up 48 percent. The S&P 500 Index itself declined 19 percent in the16-month period (see Table 3.3).Of course, buying the worst is by no means the road to guaranteed riches.Yahoo!, down 86 percent in year 2000, went on to lose 53 percent more in thenext 16 months. Novell, Lucent, and Gateway suffered similar fates. WorldCom collapsed from $13.15 to $2.35, and proceeded to fall to 6 cents a share onJuly 1, 2002.We next tested large stocks to see if they are subject to trending. We hadnoticed that large pharmaceutical companies often show three consecutiveweeks of rises or declines. For example, Johnson & Johnson fell three weeksin a row starting the last week of April 2002. Would you have predicted thatthe stock would rise the next week? Or would you have bet that it would fallfurther into the cellar? A “yes” answer to the first question would indicate a
Table 3.3 Rankings and ReturnsS&P 500 Stocks2000 Rank
Return Next16 Months (%)
20 best20 worstS&P 500 index
−110−19
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“gambler’s bias” and a vulnerability to the law of small numbers. The secondquestion would show a “representation,” or hot hands bias. (In fact, Johnson& Johnson fell for 10 straight weeks.) But this seeming piece of evidence forthe trend followers is anecdotal, nothing more. As Daniel Kahneman, PaulSlovic, and Amos Tversky point out in their classic Judgment under Uncertainty: Heuristics and Biases, the common habit of assessing the probability ofan event by the ease in which instances can be brought to mind leads to an assortment of predictable biases.12 An example would be assessing the risk ofheart attack among middle-aged people by recalling such occurrences amongone’s acquaintances. No one would take such an estimate seriously, but people do its equivalent in the market all the time.There are not enough Big Pharma companies to run a proper test of theseperceptions. Therefore, we chose as proxies the current 10 largest Nasdaqstocks and the 10 largest S&P 500 stocks by market capitalization. Since Inteland Microsoft were common to both lists, we were left with 18 companies. Westudied weekly prices from May 1997 to May 2002. To simplify our tests andmaintain a reasonable homogeneity in the results, we calculated the signs ofthe moves in each of the first three weeks for each stock. There were eightpossibilities in all. Then we looked at the results that occurred in the remaining week of the month for each stock. The averages and numbers of observations appear in Table 3.4.We conclude that stocks in the lead triumph and prosper in the last week,whereas those that are near the bottom meet disaster in the final week. Whena stock is up three weeks in a row, it adds an average 1.6 percent in the finalweek. When a stock is down three weeks in a row, it falls an average 0.8 percent. If stocks fall the first two weeks and then rise, they drop 1.4 percent by
Table 3.4 Streaking Stocks—Moves in the Last Week of the MonthCompared with Previous Weeks, 1997–2002Week 1
Week 2
Week 3
Number ofObservations
Average MoveWeek 4 (%)
UpUpUpUpDownDownDownDown
UpUpDownDownUpUpDownDown
UpDownUpDownUpDownUpDown
15616518812510891114100
+1.6+0.6+0.6+1.3−1.3+2.8−1.4−0.8
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the end of the month. Most striking of all was the group that reversed like apendulum during the first three weeks. Stocks that were down the first week,up the second week, and down the third week tend to go up 2.8 percent in thefinal week.We can classify eight different groups of stocks based on their persistence and reversibility in the first three weeks. Within each group and withinthe sample of 1,047 company-weeks, there is much variation in performance. The average variation in the performance of an individual companyduring the final week is 10 percent. Chance doubtless contributes in largemeasure to the results.Yet putting it all together, after some simulation and calculations, we conclude that the superior performance of 2.8 percent in the final week for thegroup of companies that zigzagged down up down during the first three weeksis unlikely to have occurred by chance. Let’s call it a 1-in-20 shot.By contrast, the tendency for momentum to continue in the final week forthe companies that registered three consecutive rises or three consecutive declines is suggestive but not conclusive. It is about a 1-in-10 shot.Putting one consideration with another, we found no evidence of aregime shift in market dynamics that would favor trend following. The weightof academic findings and practical results showed the tendency to mean reversion to be intact, for all periods, all individual stocks, all averages, and allnew indexes that we might reasonably think of.We conclude that the pendulum, rather than the streak, is the superiormodel for U.S. stocks.
A Venerable Indicator of Great AmbiguitySome countries have developed forms of technical analysis that are ideallysuited to their own cultural traits. In Japan, where ambiguity in negotiation isa way of life, traders have developed and refined over many centuries the technique of candlestick analysis. As Steve Nison notes in his popular referencebook, Japanese Candlestick Charting Techniques, “As with all charting methods,candle chart patterns are subject to the interpretation of the user.”13 Thisshould come as no surprise. All who have done business with the Japaneseknow of their polite reluctance to give a simple “yes” or “no.” It would havebeen amazing indeed if a country that prizes indirection had come up with aprecisely defined method susceptible of confirmation by experimentation.Candlesticks show open, high, low, and close points. A rectangular bar—“the body”—encompasses the close and the open, while “whiskers” extend
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from the top and bottom to mark the high and low, if necessary. The body isempty when the close is higher than the open, and colored in when the close islower than the open. A candlestick’s features and its relationships to the candlesticks on adjacent days constitute the raw material of candlestick analysis. Atypical chart for the S&P for the last six months of 1999 appears in Figure 3.3.With no intended disrespect to Japanese politesse, we undertook a test ofthe validity of Japanese candlestick patterns. We began by selecting five of themost prominently mentioned patterns found in two sources: the Nison bookand a standard Internet source for candlestick analysis, LitWick.com.The test consisted of defining each of the occurrences of these patterns,using daily high-low-open-close for the six-year period 1995–2001. One of thepatterns did not show up in the data at all. (An Abandoned Baby has not beenfound in the S&P 500 since 1995.) We made predictions for three separate intervals for each of the remaining four patterns. The intervals were to the nextclose, to the next open, and to the close two days after the occurrence of thepattern. Each trade was initiated at the open of the day after the appearance ofthe candlestick pattern (see Table 3.5).
Figure 3.3 S&P 500 Candlestick Chart, July–December 1999. Source:Bloomberg L.P.
Chapter 3 • The Hydra Heads of Technical AnalysisTable 3.5
PatternThree blackcrows
Engulfing
Doji in anuptrend
Abandonedbaby
Tweezers top
Bearish/BullishBearish
Bearish
Bearish
Bearish
Bearish
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Japanese Candlestick Pattern Trades
Period
Number ofObservations
S&PPointChange
Up%
Z
Open to close
21
3.7
57
119
Open to open
21
4.9
67
156
Open to nextday ’s close
21
5.7
57
156
Open to close
22
2.3
36
−79
Open to open
22
3.2
41
−92
Open to nextday ’s close
22
2.2
50
−47
Open to close
10
−0.6
50
−21
Open to open
10
−3.0
50
−69
Open to nextday ’s close
10
−2.5
40
−69
Open to close
0
Open to open
0
Open to nextday ’s close
0
Open to close
57
0.9
51
Open to open
57
0.8
56
Open to nextday ’s close
57
−0.5
60
Of 15 tests, 4 came up with results in the direction of traditional candlestick interpretations. None of the patterns was statistically significant at theusual 1-in-20 levels typically used by researchers as the minimum cutoff fordetermining whether the phenomenon was consistent with mere chancevariations. Our tests thus failed to verify the validity of Japanese candlestickanalysis.But perhaps we have been too scientific. Perhaps an unusual ability tointerpret these patterns might yield better results. “Technical analysis isan art as well as a science” is an oft-repeated refrain we hear from technical
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analysts. Doubtless many practitioners are more gifted with visual modes ofdecision making than with numerical methods. Chess players, for example,often see visual relations that they find difficult to quantify when explaininghow they came up with that one perfect move that won the game. Similarly,architects, engineers, and artists frequently can look at a depiction of ascene and fathom many relations that would be difficult even to define, letalone quantify.The great problem with that line of reasoning is that people are prone tothe “validity bias”—they believe that they are much more accurate in comingto valid conclusions than they actually are. Humans are much too adroit at believing that relations exist when they don’t, and this illusion is responsible formany errors in judgment and decision making in the markets and in life. Inparticular, people tend to place unwarranted confidence in predictions thatmatch stereotypes, “with little or no regard for the factors that limit predictiveaccuracy,” as Kahneman, Slovic, and Tversky wrote in Judgment under Uncertainty. And they persist in this misplaced confidence even if they know theinput information is scanty, unreliable, or outdated.Even if a psychological bias were not involved in interpreting candlestickcharts and the like, it would not seem overly useful to tell the average investorthat certain people are gifted in visualization but find it impossible to puttheir finger on how they arrive at their interpretations. The investor wouldhave no clear path to learn such techniques. And by merely following theguidance of the superior visualizer, the investor could never know with assurance that the person’s gifts would continue to yield superior forecastsunder different conditions.Technical analysis is silent on such crucial questions as what time frameto use when searching for patterns. As our friend Shui Mitsuda, a great market philosopher who works for a Japanese brokerage, observed: “By changingthe range of variables in a chart (duration, price range), the graph often showscompletely different faces. In the one-year range, Sony is a strong buy. In the10-year range, I get too scared. In the one-month range, I have no idea.”The greatest problems with using candlestick patterns totrade, however, lie in the principle of ever-changing cycles andthe role of deception in the market.Our friend Glenn Escovedo, a chess expert who trades for a white-shoeWall Street firm, sent us one of the most popular books in China, The Book ofStratagems by Harro von Senger, to give us some insight into Japanese technical analysis.14 The book contains deceptive techniques of great antiquity, twoof which we summarize here:
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1. Fool the emperor and cross the sea: The Emperor Taizong, arriving at theshore of the Yellow Sea with an army of 300,000 on the way to a battle inKogouryo, loses heart. Turning to his military advisors, he asks for advice.Fearing the emperor will abort the campaign, the advisors build a boatcamouflaged as the home of a wealthy merchant. They lure him aboard,then take to sea. When the candelabra starts swaying, the emperor ordersthe curtains to be pulled back. “Where are we?” he roars. Faced with a faitaccompli, he regains his decisiveness and bravely sails on.2. Openly repair the walkway, secretly march to Chencang: In 206 B.C.,the military leader Liu Bang retreats to Hanzhong to escape a murderous rival. To protect himself from attack, he burns the wooden walkways and bridges in the mountain gorges along the way. Later that year,he prepares for a new campaign in Chencang. To distract his enemies,he orders a few troops to begin repair work on the walkways. The military commander in Chencang laughs, thinking it will take such a modest number of workers many years to restore the walkways. But LiuBang’s forces secretly march on a different route to Chencang, takingthe city by surprise.“The Chinese have lived and died by deception for thousands of years,”observed Escovedo. “Hard to believe they or the Japanese would take charts atface value.”What is even harder to fathom is the Western craze for Japanese candlestick analysis. In Japanese Candlestick Charting Techniques, Nison talks aboutthe technique’s gratifying popularity:Online traders, day traders, institutional proprietary traders, and market makersare just some of the candle charting enthusiasts. Web sites, real-time trading systems, and technical analysis software packages include candle charts. This atteststo the popularity and universal appeal candles have to trading today’s volatile markets. Candles are hotter than ever.
Even so, Nison’s book includes many Western-style elaborations on purecandlestick patterns for “the seasoned technician,” including candlestickswith trend lines, candlesticks with retracement levels, candlesticks with moving averages, candlesticks with oscillators, candlesticks with volume and openinterest, candlesticks with Elliot Wave, and candlesticks with market profile.Acquaintances familiar with our thinking take care to discuss candlestickpatterns only behind our backs. Sometimes, however, a stray reference willslip through, as when an e-mail extolling Nison’s book, meant for a more receptive target, mistakenly was sent to us. “Candlestick charting dates from
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Tokugawa times—late 16th, early 17th century,” the writer gushed. “The bookhas pages and pages on the psychology underlying patterns like head andshoulders, which the Japanese rice traders called ‘Three Buddha Top.’ The oneI like is ‘High Waves’—makes me seasick just to think about it.” After confiding his yen to explore such formations as “Doji Star,” “Three White SoldiersAdvance on the Dark Shadow,” and “Candles Exhaust Themselves to GiveLight to Men,” the writer concluded:Much as I admire Vic and Laurel, for me it is going to take [a lot] to overturn 400years of profitable tradition.
Others among our correspondents tell us they have found creative uses fortheir books on candlestick analysis. John Lamberg of Minnetonka, Minnesota,one of our most sagacious correspondents—engineer, Monty Python aficionado, Father Knows Best family man, and reformed technical analysis practitioner—uses his book on candlestick patterns to steady the shaky leg of hiscoffee table.
The Hydra’s ArmsWe next studied another prominent Hydra head–the well-known TRIN, shortfor the New York Stock Exchange Short-Term Trade Index. Its inventor,Richard Arms, who charges $8,000 a year for his advisories, prefers theeponymous “Arms Index.” CNBC, the most widely watched financial TV network, uses the latter name when it flashes the current index reading every 20minutes past the eyes of viewers.The Arms Index represents the ratio of New York Stock Exchange up volume scaled down by number of rises, divided by the ratio of down volume,scaled down by the number of declines. Some traders use a five-day averagefor short-term forecasts.Some favorable press came in early 2001, when punditDon Hays told Barron’s that he used the Arms Index to call theexact bottom of the Dow Jones Industrial Average on March22.15 (The Dow peaked 60 days later on May 21 after rallying 21percent, then resumed its decline.)So TRIN works, right?It sounded intriguing. We decided to check. Working with Dr. BrettSteenbarger, who has used TRIN in his own trading, we ran hundreds of regressions with many lags and leads for many different back periods. We studied correlations of one-day, two-day, five-day, and 10-day TRIN with S&P 500
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Index moves over the next 1, 5, and 10 days. Briefly, we found the results to beconsistent with randomness, with correlations close to or right at zero overthe last three and a half years. In other words, the Arms Index does not predict the future.We were not the only ones to find difficulties with TRIN. In a study citedby The Encyclopedia of Technical Market Indicators, Robert Colby and ThomasMeyers tested TRIN from January 1928 to March 1987.16 Using daily data, theyperformed many different tests to come up with predictions for one to twelvemonths. Their finding: “We can only conclude that it has relatively limitedforecasting value for stock prices.”Some may feel that the above conclusion is premature since it is based ononly 59 years of data. But in The New Technical Trader, Tushar Chande andStanley Kroll note three difficulties with using TRIN:1. The ratios used in TRIN often obscure, rather than clarify, market action. This is particularly true when market action is “mixed.”2. The very process of smoothing TRIN with moving averages distorts thepicture of relative volume flows.3. TRIN has a bounded scale for upside activity, but an unbounded scalefor downside activity.17We spoke with Richard Arms in May 2001 to find out what he thought ofour conclusions, and to learn how he uses the index. In his words:Laurel: Do you trade much?Arms: I trade some money for myself, but my primary work is talkingwith my clients. I put out an advisory for dozens of institutions. Idon’t trade much any more, because I’m occupied with other things.Laurel: Millionaire? Centimillionaire?Arms: Somewhere in the middle.Laurel: From trading?Arms: From trading, and from the fees I charge my clients.Laurel: How would you advise people to use the index?Arms: If you’re a trader, watch the five-day moving average. When it’s inthe 0.75 sort of area, you become a seller, and when it’s over 1.25 youbecome a buyer. It’s a judgment thing. . . . The 10-day moving average allowed us to call the bottom perfectly on March 22, 2001.Laurel: Can you elaborate on how to use judgment?Arms: After working with it for so many years, it becomes a little . . . instinctive. I’m not sure I can explain it, really. I explain it to my . . .institutional clients. I look at a lot of things. I’m not just looking
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Practical Speculationblindly at this index and saying buy or sell. It’s not just a simplisticsort of thing.Laurel: How many times have you used the Arms Index as a primary signal in the past five years?Arms: It has given only two of those big major signals in the last fiveyears, this one and in October 1997. Then we have to go back to 1987to get a similar signal.
If There Is Proof, We Cannot Find ItThe problem is that “buy” levels for the 10-day average do not happen enoughto scientifically evaluate the Arms Index. You cannot estimate uncertaintybased on something that happens twice every five years.Also, the signals happen to occur at times when the market is most down,so basically what you are taking advantage of is the old adage to buy in panics.Statistically, it is exceedingly difficult to evaluate a ratio of two ratios. Instatistical terms, the distribution of the ratio of two normal variables has aninfinite mean and an infinite variance. Larger samples do not help you reduceuncertainty about the mean or variability of the indicator.Numerically, the ratio is also highly problematic. Its variations are dominated by changes in volume, which are themselves highly correlated withprice changes. The ratio itself varies from zero to infinity. A more stable measure might be based on the differences between volume and advances versusdeclines, perhaps with a logarithmic operator thrown in for stability.All things considered, working with the Arms Index is about as easy anduseful as holding a moonbeam in your hand.We told Arms that we had found no correlation between TRIN’s movingaverages and subsequent S&P 500 moves, and he said it bothered him to hearus say that. “All of Wall Street uses