journal of technical analysis (jota). issue 43 (1994, summer)

SUMMER-FALL 1994 ISSUE 43

A PUBLICATION OF THE MARKET TECHNICIANS ASSOClATION

ONE WORLD TRADE CENTER, SUITE 4447 l NEW YORK, NEW YORK, 10048 l (212) 912-0995

MARKET TECHNICIANS ASSOCIATION JOURNAL

Issue 43 Summer - Fall 1994

Editor

Henry 0. Pruden, Ph.D.

Golden Gate University San Francisco, California

Associate Editor

George A. Schade, Jr., CMT

Scottsdale, Arizona

Manuscript Reviewers

Connie Brown, CMT Don Dillistone, CFA, CMT Richard C. Orr, Ph.D.

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Robert I. Webb, Ph.D. Associate Professor and

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TABLE OF CONTENTS

The Universal Skewness: An Applicability of Options Based Technical Analysis. . . . . . . . . . . . .9 Indicator to Robert R. Prechter In this article, Measure Sentiment . . . . . . . . . . .29 which reveals the wider applications of Carsten Lund Using German and technical analysis, Prechter challenges United States options market data, Lund us with the thesis that.. . “To under- investigated the relationship between stand the value of our craft, it is first volatility and subsequent price action. necessary to understand that in fact, all effective forecasting requires tech-

Some of his results were diametrically opposed to what he expected.

nical analysis. While technical analysis can be utilized perfectly well on its own, there is no such thing as valid analysis apart from technical analysis.” Engulfing Patterns:

Winning the Battle with Western

Information, Point and Figure Time and Risk.. . . . . . . . . . . . . . . . . .19 and Eastern William X. Scheinman A veteran Candlesticks . . . . . . . . . . . . . . . . . . . . .39 technician presents some of his and Edson Dodge 0. Dorland A trend of increas-

Gould’s theories and demonstrates them ing acceptance and wider applications with practical applications. Bill Scheinman has popularized the use of Japanese adds a provocative new twist: his first Candlesticks. In this article Dodge

market analysis and expectations, written Dorland conducts an exploratory test of in early 1994, are followed by a “what the hypothesis which suggests that the actually happened” sequel, written in Engulfing Patterns of Japanese Candle-

November 1994. sticks do improve timing decisions when coupled with a Western point-and-figure method.


Anatomy of a Trading Range.. . . . . . . . . . . . . . . .47 Jim Forte What are the distinguish- able phases of a trading range? How do we know that accumulation or reaccumulation is underway vs. distribution or redistribution? When and where within the trading range should one take a speculative position? Jim Forte illustrates answers to these questions by applying models from Richard D. Wyckoff to a variety of recent stock charts.

Membership and Affiliate Information . . . . . . . . . . . . . . . . . . . . . . . .2

Style Sheet for the Submission of Articles . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

MTA Officers and Committee Chairpersons.. . . . . . . . . . . . . . . . . . . . . .4

Editorial Opinion . . . . . . . . . . . . . . . . . . .7


Editorial Opinion

CMT, IFTA and the MTA/OURNAL* by Henry 0. Pruden, Ph.D., Editor

Those who propose to take charge of the affairs question is yes. The recipient of the CMT should of government, should not fail to remember two meet a single set of standards; the MTA and the of Plato’s rules: first, to keep the good of the MTA JOURNAL should act as the ultimate guar- people so clearly in view that regardless of their antors of the integrity of the CMT designation. own interests they will make their every action What is the justification for the foregoing con- conform to that; second, to care for the welfare elusion? How can it be implemented? For justifi- of the whole body politic and not in serving the cation we can look back to Cicero. To my mind, in interests of some one party to betray the rest. the context of market analysis and decisions,

Cicero “...the good of the people...” means the welfare of

Roman philosopher, orator our clients. The CMT is granted to assure clients

and statesman on the “Duties and the investing public at large that conclusions

of the Individual to the State” reached and advice granted on the basis of technical analysis are given by individuals who have dem-

The subject of this issue’s Editorial Opinion onstrated a professional level of competence in the deals with power, standards, control and justice. field of technical analysis. These topics may seem remote from trends, As markets become global this level of assur- intermarket analysis, candlesticks, market theo- ante becomes ever more vital. An investor in Ja- ries, research findings and the like. But the former pan must know that a CMT in Mexico means the subject matter-the elements of government-set same as a CMT in Great Britain, which in turn the framework for the quality, the growth and the means the same as a CMT in Japan and so on. If distinctive competence of technical analysis. This at any time a CMT from any one country becomes commentary is a brief discourse on the relative suspect, then all CMT’s are vulnerable to suspi- functions and authority of the MTA, the MTA cion. As a young and growing profession any threat JOURNAL, IFTA and those technicians who be- must be avoided. Should one wayward society at long to IFTA member societies. At the heart of this some time in the future be allowed to grant mean- discourse is an opinion regarding the guardianship ingless CMT’s, it betrays the CMT’s in all of the of the CMT. As part of the authority which grants other member societies. By insisting on the high- final approval of the CMT III paper, the MTA est standards of competence and integrity for each JOURNAL editors are interested parties in the recipient of the CMT, we assure the authenticity CMT process. And since the JOURNAL is part of and quality of all CMT’s. the MTA, the MTA is inevitably an interested party Implementation of a single set of standards

The issue before us is ageless. The question for the CMT can follow three tracks. One is the before IFTA, the MTA and the CMT candidate has creation of an IFTA REGISTRY which lists all been faced before in other situations by other legitimate CMT’s from around the globe. To groups: how can we maintain a single set of high become listed in the IFTA REGISTRY each candi- standards within a diverse community? At the po- date for the CMT must have met the single set of lar extremes it is a choice between centralization standards, and at this stage of development of our and one set of standards for the CMT versus de- discipline that means the standards imposed by centralization of governance and varying standards the MTA. The REGISTRY can be updated annually. for the CMT. In other more specific words, ought The second method of implementation is through the MTA in the United States of America and the the CMT EXAMINATION process. My recommen- MTA JOURNAL be the ultimate authority for dation would be the following: guaranteeing the highest professional standards l CMT I examinations - using the form of ques- for the CMT? tions and the grading standards of the MTA, modi-

In my opinion, the answer to the foregoing fied for the peculiarities of each country, the CMT I


examination can be administered and graded by each individual society. The exams and the results along with the names of the successful candidates to be sent to New York City for listing in the IFTA REGISTRY.

l CMT II examinations-use the format and questions of the MTA plus questions designed by the member society. Over one-half of the questions to come from a universal exam based upon the MTA’s CMT II level examination. Modifications for a local society to meet with the approval of sn official IFTA Committee. In the home country of a society, exams are to be administered in a way similar to exams for accountants, engineers or other professionals.

For the third track of control, members of IFTA can look to the CMT III level requirement. To advance to candidacy for the CMT designation and listing in the IFTA REGISTRY of CMT’s, a level III paper must first be approved by a CMT III Accreditation Committee of the MTA and the Editorial Board of the MTA JOURNAL. By insisting that all CMT papers be subjected to the same review process and be evaluated by the standards used by the MTA JOURNAL, we can all be better assured that a high level of competence will be shared by all who carry the CMT designation. For example, in this issue of the MTA JOURNAL there are articles from three different IFTA member societies: MTA, GERMANY and the TSAA of San Francisco, CA.

These papers reflect the strength which technical analysis gathers by combining and concentrating our collective efforts.

Editorial opinion of Henry Pruden is nol official policy of the MTA nor does it necessarily reflect the policy, OF

the wishes of the MTA, IFTA or any other society.

*CMT= Chartered Market Technician. An individual professional designation of competence.

IFTA=International Federation of Technical Analysts.

MTA JOURiVAL=Passes judgment on the CMT level III papers.


The Universal Applicability of Technical Analysis by Robert R. Prechter, Jr., CMT

Text of a speech presented to the 19th Annual Market Technicians Association Conference, Wesley Chapel, Florida, May 13,1994 by Robert R. Prechter, Jr, CM?: Past President of the MTA 1990-1991.

Four days ago I heard on television a long discussion about the stock market that focused on interest rates, the economy, corporate earnings and the Fed. This is, of course, quite common on financial television. However, the discussion was provided by a technician. In fact, it was an MTA member.

I have designed this talk so as not to disappoint any- one who came to hear Bob Prechter say something radical. This presentation will provide a broad sweep toward making my essential point, but certainly far more could be said about the various subjects if time allowed. I haven’t made a speech outside our own conferences for five years, and probably won’t for another five years, so I hope you’ll indulge me while I push the envelope a bit with something I feel pas- sionate about.

Despite the evidence of this well attended conference, today the term “technical analysis” is in lower repute than many of us realize. I’m not speak- ing only of its status in the eyes of money managers, TV commentators and the public. Of course, it has always been ignored at the tops of bull markets, when paper profits appear to have validated all kinds of incorrect decision making processes. No, I’m speak- ing of the fact that the term “technical analysis” is in low repute with technicians.

Some of you may not know that a former president of the MTA who for years had the word “technical” on the masthead of his institutional publication, recently took it off. Why did he do that? Part of the reason is that we ourselves have not defended the term to the extent that it deserves. We compromise like Neville Chamberlain and say that “technical analysis is useful in conjunction with fundamentals, ” “it can help the money manager decide when to buy the stocks he has already chosen using fundamentals,” and all sorts of other mealy mouthed non-de- fenses of our craft.

In January, I read in the newspaper that (quote) “stocks have been interest rate driven, and now they will be earnings driven.” Of course, we have all heard that statement a hundred times over the past six months. However, this time, the statement was made not by a fundamentalist money manager, but by a technician. In fact, it was an MTA member.

When I encounter such presentations, I become disturbed beyond measure. This kind of talk under- mines our profession, our case, our cause and our principles.

In case there is any question about it in this room, let’s examine the question, “Are stocks driven by earnings?” “Are they driven by the latest economic statistics?” Well, since 1932, corporate profits have been down in 19 years. The Dow rose in 14 of those years. In 1973-74, the Dow fell 46% while earnings rose 47%. 12-month earnings peaked at the bear market low. Earnings do not drive stocks. As Figures 1 through 5 illustrate and as Arthur Merrill showed years ago, earnings lag stocks. As many practitioners have pointed out, the economy lags stocks. It is therefore impossible for earnings or the economy to drive stocks. Even most economists know this, since they use the stock market as a leading indicator. Yet technicians, who are supposed to be looking at charts, which means studying history to see if their statements are valid, have been making these statements to the media.

Why do such false ideas continue to hold sway, even, apparently, among many technicims? I believe it stems from a lack of knowledge of the profound depth and validity of our basic premise, particularly in contrast to that of our competition.

Necessity of Utilizing Technical Analysis To understand the value of our craft, it is first

necessary to understand that in fact, all effective forecasting requires technical analysis. While technical analysis can be utilized perfectly well on its own, there is no such thing as valid analysis apart from technical analysis. How can I make such an outrageous statement?

First, let’s define our terms. Technical analysis is the study of intramarket data, that is, data generated by the action of a market and by the behavior


Figure I

S&P EARNINGS MOMENTUM

(both 52 week)

Prepared for Bob Precbter’8 11)~ MTA Seminar Prenentation by

@06)440-0167 (voice) Copyright 0 1664 All righta reserved

Figure 2

Figure 4

7

1.20 18

,1.05 16

I 0.90 0.75 14 12

I S&P 500 EARNINGS (heavy line)

and psychology of that market’s participants and observers, in other words a study of events, conditions and processes in the marketplace.

Conventional analysis is the study of extiurnurlzet data, that is, events, conditions and processes outside the marketplace, which are deemed to be the factors, or “fundamentals,” that drive the market.

Events outside the marketplace cannot provide a sufficient basis for anticipating the trend of a market. Let me explain by example. If someone is bearish on stocks because interest rates are rising, you are justified in asking, “How do you know that interest rates didn’t stop rising today, in which case stocks are a buy?” He might respond, “well, the latest economic report shows strength,” in which case you are

1964 19% 1956 1967

I 1.. 1.. . I. 1 . ' S&P Tftti;NDEX

I

460

lbT4 4601

16.0 420

16.5 S&P 500 EARNINGS 40~ (heavy line)

1992 1993 1994

Figure 3

Figure 5

justified in asking, “How do you know that the economy didn’t peak last month?” At some point he must respond that he will wait for a change of some kind, a report of a slower economy or a lowering of rates by the Fed. Then you can ask, “How do you know that that economic report won’t reflect the only economic downtick or that the Fed won’t lower rates once and then start raising them again?” If he answers that he doesn’t know, then he remains stuck with no basis for a decision. On the other hand, he might say, quite thoughtfully, “Well, the Fed has usually moved in multiple steps in the past.” Now, by forecasting the behavior of his supposed cause, he is engaging in technical analysis of his “fundamental” data He is forecasting the behavior of an agency based


,

on the history of its own behavior, in this case using the technical idea of trending. This agency is then considered to affect a market (i.e., interest rates) that will affect the one he actually wants to predict, i.e., stocks. He cannot avoid employing technical analysis at some point. Since he must employ it, we should ask him, “isn’t it far easier merely to perform technical analysis directly on the market in question?” Instead of saying, “the trend of Fed action is toward higher rates until that trend changes,” he simply could have said, “the trend of stocks is down until that trend changes,” and saved all the trouble and avoided the pitfall of requiring his whole chain of causality to maintain itself, for which history shows numerous exceptions. Please note: I am not saying that the trends of stocks and bonds, or the CRB and gold for instance, are unrelated. I’m saying that this is useless information without employing technical analysis, and that each step removed weakens any market conclusion.

We have now uncovered another secret, which is that conventional analysts must predict their own indicators. If earnings drive stocks, they still have to predict earnings, and even then, the predictions lag the market, invalidating the whole exercise. What’s more, the chain of predictions concerning each sup- posedly causal indicator will be endless until the conventional analyst finally provides a prediction based on technical analysis. More often than not, he simply says that he sees no evidence of a change in trend for his supposed cause, which is a technical statement. Trend following, of course, is the crudest form of technical analysis, and it is employed by nearly all conventional analysts and economists. Unfortunately for them, they often make it far less useful than it already is by following the trends of lagging events. Some such indicators, for instance earnings, can time themselves exquisitely to produce maximum error in forecasting the stock market. These analysts would do far better to trash all of their supposed indicators and just trend-follow the market with a single moving average, like Dick Fabian does.

A technician is not reduced to predicting his own indicators. This is not to say that such indicators are always right, but at least the chain of argument is direct and finite. The indicator speaks to the future, and that’s that.

Furthermore, a conventional analyst cannot adjust for error. If interest rates fall and stocks fall with them, or if earnings fall and stocks are going up, he has no basis upon which to modify his stance. Tech- nical analysis provides a built in method of changing one’s mind.

I apologize for saying “supposed” so often in referring to the indicators used by conventional analysts. However, they are truly not indicators at all.

They are utilized because of a simple presumption that they are valid, not because of any rigorous back-testing. Conventional analysts do not bother to study history They merely assure us, for instance, that the passage of NAFTA will guarantee another decade of rise in stock prices because it seems as if it should. Wouldn’t it be a delicious shock if some re- porter suddenly saw a light bulb and asked, “Pardon me, but have you by any chance checked the historical record to see if trade agreements in fact are typically followed by stock market rallies?” But don’t hold your breath. The reason conventional analysts get away with their suppositions is that they sound ut- terly reasonable to the average man on the street, who, as we all know, is sophisticated in the ways of Wall Street. Technicians, on the other hand, do study history That’s what a chart is.

There is a hybrid form of analysis called “fundamental analysis” that involves both technical and conventional ideas. This is the Graham and Dodd approach of searching for stock value by comparing stock price to company performance. Clearly this approach is based upon a measure of investor psychology, and thus crosses into the domain of the technical, so I have no quarrel with this approach as an adjunct to technical analysis. I do, however, have a quarrel with those practitioners who say it is the only valid approach, as many of them do. Those who hold that opinion are philosophically conventional analysts as per the definition I gave earlier, despite their closet use of technical principles. Actually, the reliance on corporate performance statistics, which is the “fundamental” factor, weakens the reliability of the mes- sage, because profits, earnings and dividends can all change after an investment decision has been made. An apparently cheap stock by such formulas can fall 50%, after which the company reports poor performance and dividend cuts and so on, so that it is no longer cheap by the same measures. One often hears of fundamentalists who realize what they’re doing and become technicians. In fact, several of our past presidents began their careers as fundamental analysts. Rarely does a conversion take place the other way around.

Like conventional analysts, fundamental analysts rarely appreciate the fact that they must incorporate technical thinking at some point for their analysis to have any validity Sadly, many technicians don’t know it, either. You must always, always think technically. Let me give you some examples of what I mean.

Thinking Technically About Events and Conditions

Suppose you make a good call on the market, a sector, a group or a stock, and your clients tell you they are too afraid to follow it. The market goes your

L


way and seven or eight weeks later you get a call con- gratulating you on your work. You might just say thanks and hang up the phone and be very self satisfied. Or, you might understand that the phone call has a technical meaning. If you get three more calls that day, you may want to take a good look at your indicators. Similarly, if you are ever so fortunate and simultaneously unfortunate as to be granted a certain measure of fame.. .or infame.. .you will find that publicly distributed attacks against you for all sorts of real and imagined sins are excellent market indicators, and the more vicious and inaccurate they are, the better they are as indicators. The same is true of widespread praise. In other words, instead of taking such things at face value, see if they are a comment on the prevailing psychology. Let’s try a less obvious example: in the 195Os, people built bomb shelters. They were responding to events that had already happened, preparing for the past, in essence, fearing the last bear market. This year the Smithsonian Institu- tion placed a bomb shelter in its collection as a relic. Observers, conventional analysts all, hailed it as reflecting the beginning of a new era of peace for mankind. What is the technical importance of that occurrence?

R.N. Elliott said quite properly in 1946, “In the matter of investment, timing is the most essential element. What to buy is important...but when to buy is more important.” Regardless of today’s rhetoric, that is still true. Once you are satisfied that the trend is safe, you can then concentrate on stock selection. In fact, just to demonstrate that this is not new with The Elliott Wave Theorist, I will read this quote from over eleven years ago, in April 1983: “Large institutions will probably do best by avoiding a market timing strategy and concentrating on stock selection remaining heavily invested until a full five Primary degree waves can be counted.” That statement was possible only because of the luxury of having a per- spective on the market from a timing standpoint. However, the last six years have brought back into fashion the recurring belief that market timing is passe and useless, if not counterproductive: “All one needs is good stock selection. Just stay in good stocks, and you will make money and be safe.” Many of you might agree substantially with that assessment. Indeed, I have heard many technicians say it.

But think about the technica meaning of that belief. Few people made this case in December 1974. Few said this in June 1984. Few said this in 1932, 1942, 1859 or 1842. What technical conclusion can you draw from the pervasiveness of this opinion today? It is a symptom of complacency about the trend of the overall market. In fact, it is philosophically impossible for today’s most successful money man-


agers to sell stocks or bonds and take a cash position. After all, it was that kind of thinking that brought them to their current state of success. This is not only the kind of thinking necessary to create a major top; it is the kind that will force them to hold their increasingly less valuable paper all the way down until a new philosophy assumes dominance. Now contem- plate the kind of irony that one continually notices when thinking technically. It is precisely the position of the market in its overall trend that induces people to say that the position of the market in its overall trend is irrelevant. At the bottom of a bear market, timing becomes the new philosophy, which assumes its place on the pedestal just when it is actually time to concentrate on holding and selecting stocks. Tech- nicians can observe and profit from such irony in the marketplace every day; conventional analysts produce irony every day without knowing it.

All right, we have explored a few of the short- comings of the conventional approach. But that is not enough to make us understand the value of our own approach. Let’s tackle that task next.

The Validation of Technical Analysis The real fundamentals of the market are the pat-

terns of human emotions. They can be revealed in the marketplace through studies of price behavior, volume behavior and psychological behavior. We could explore them all, but let’s look at just one example of a price pattern.

Take a look at Figure 6 and observe that the pattern of prices since 1932 has reflected R.N. Elliott’s stock market model, shown on the inset, exquisitely well. What’s more, the three bull markets dating from 1932 have all made percentage gains that create a perfect Fibonacci interrelationship, representing .618, 1.618 and 1.00 respectively The basis of these relationships was suggested by Elliott in the 1940s before any of these particular ones had been found. The last one shown will remain in place as long as the Dow does not exceed 4100, which based upon these relationships is a pretty good bet.

The patterns that we study are the fundamentals of the market. The odds of the outcome depicted on this chart being random is infinitesimal. Now consider this critical observation. For people to claim that the latest idea from the White House or the latest law passed by Congress or the latest statistic on the trade deficit or earnings or war or unprecedented natural disaster such as flood, earthquake or hurri- cane has any effect on this pattern, that such things are determinants of stock prices in any way, is sug- gesting a far more radical view of the harmony of the universe than did R.N. Elliott, who said simply that collective human behavior is patterned.

Think about it. Almost everyone believes that

40

Price Relationships in Supercycle (V): IMPULSE WAVES

Numbers are hourly prices; closes in brackets where different

@ August 1994 ELLIOTT WAVE INTERNATIONAL

PO Box 1618 Gainesville, GA 30503 USA

1932 1942 1952 1962 1972 1982 1992

Figure 6

events cause psychology. If that is true, then events ings lag stock prices because smart investors antici- must be so perfectly determinist that they create pat- pate, or discount, the future,” in other words, guess terns such as this. However, ifpsychology guides the the future correctly While this position is a time tenor of events, then it is only mass psychology that honored and valiant attempt to explain why events is patterned. Its patterns underlie social behavior, and lag stock prices, I believe it is false. In fact, because behavior ultimately produces results in the form of markets are patterned, it must be false. The truth is social actions that are viewed as important events. that rising earnings are caused by the action of Simply stated, social actions are an outlet for the human beings spurred on by an increasingly ebul- patterns of mass psychology, expressing it in count- lient social mood, and the presence of such a mood is less diverse ways that give rise to the myriad events reflected by a bull market in stocks. This direction of of human history If I have anything to contribute to causality explains why aggregate earnings can almost technical analysis, it is this idea, that the behavioral always be predicted by the movement of aggregate

patterns inherent in human interaction shape social stock prices. Rising earnings are the fruits of a bull

events. In my opinion, all of history flows from the market. When the fruit is ripe, the tree is already in technical truth that men have a nature, that this its declining season. If you wait for the fruit to ripen nature produces patterns of interaction, and that in order to turn bullish on the trend of the tree, it is

these patterns of interaction produce results. too late. In my opening discussion about the claim that This is a radical idea of social causality, and the

stocks will be “earnings driven,” some of you were only one that makes sense. With this background, probably thinking, “I know better than that. Earn- we can begin to discuss the wider applications of tech-


nical analysis, on the way to elevating it in our minds to the status it deserves.

Applicability of Technical Analysis Why are feature length Disney cartoons popular

again at the theaters? From 1966 to 1982, most people thought such films were outmoded, silly and senti- mental. Indeed, the studio hardly made any In the past decade, they are back, and they have been block- busters. Let’s take the long route to answering this seemingly trivial question.

If one knows the species of a tree, he can predict what kind of fruit it will bear. Events are the fruits of a bull or bear market. Since stock prices are a direct reflection of mood, some collective human behavior can be predicted from a reliable outlook for stock prices, behavior affecting entertainment trends, the style of the media, social themes and cultural symbols, the styling of consumption items such as cloth- ing and automobiles, social harmony vs. conflict, politics, war and even involving such deeply emotional tendencies as the social preference for relying on reason vs. relying on emotion to solve both individual and social problems.

It is believed by almost everyone that behaviors such as those I have just listed are “fundamentals,” i.e., determinants of the value of stocks and invest- ments, and come before such valuation. This false premise leads to a fog of uncertainty in every con- ceivable area of anticipating the social future, from market forecasting to anticipating cultural trends to predicting elections to planning for the comfort and well being of one’s family or the safety of one’s nation. However, they are results, and when you know what they result from, i.e., social mood trends, you can often predict the general tenor of such behaviors. It is the only logically sensible direction of forecasting between the two sets of data. Most investors try to forecast by reasoning in the other direction. As a result, news and other extramarket events and conditions become nothing more than a basis for the rationalization of a market opinion formed simply by one’s emotional state, the pervasiveness of which practice is precisely why markets are patterned. It is the rationalization that allows people to avoid exer- cising reason, and therefore to act on the basis of their emotional state.

I find that the guidelines of the Wave Principle of human social behavior are often useful in making forecast specifics. For example, there is one called the guideline of Alternation. It has a specific technical meaning in wave formation, but is also applicable to social trends. For example, you might recall that Richard Nixon won re-election in a landslide in late 1972 at the peak of a bull market and was driven from office in August 1974 by the social mood reflected

by the bear market. Today, the probability of a repeat event is the highest in 20 years. Bill Clinton took office near a market high amidst strong popularity, a Time “Man of the Year” cover and high hopes for his performance. A bear market increases the public’s and the media’s sensitivity to and desire for scandal, and if a leader is vulnerable to scandal, which in this case he certainly is, a bear market could destroy his popularity, and if it happens soon enough, even drive him from office. The guideline of alternation points out the difference this time around. In the 1973-1974 bear market, it was the liberal press that exploited the weaknesses of Richard Nixon. In this bear market, it is the conservative media that are exploiting the weaknesses of Bill Clinton.

Another example of Elliott Wave guidelines that are useful in social forecasting is that a fifth wave attempts to re-live the technical glory of the third, but manages in the end only a hollow echo. This observation also applies to social trends. It explains why Disney movies became popular again in wave V, they were popular during wave III from 1942 to 1966. That’s why we have oldies radio, playing the music of the 1950s and 1960s. That’s why in the early 1980s we elected a president, Ronald Reagan, who called for a return to the values of Calvin Coolidge and Dwight Eisenhower, presidents during previous bull markets. Notice that in most of these cases, the extent of innovation in the fifth wave is very low; innovation occurs in the third wave, copying in the fifth. Don’t bother to use demographics to explain these trends unless you can explain the demographics, which in fact the Wave Principle does quite well.

Bull markets result in increased harmony in every aspect of society, including the moral, religious, racial, national, regional, social, financial, political and otherwise. Bear markets bring polarization. With that realization, you can predict relative harmony in all those areas in bull markets, and relative conflict in bear markets. For example, apartheid was made official South African policy in the 1940s at the end of the last Supercycle bear market and the peak of their negative mood. It has been eliminated at the peak of this bull market and the peak of their positive mood, and Wednesday’s paper showed black and white leaders, enemies for decades, clasping hands over their heads in the spirit of brotherhood. Reli- gious wars were big in the Dark Ages and for awhile afterward, but have been a minor concern in the past eight centuries of rising long term trend. Indeed, Catholic, Jewish and Arab leaders are all shaking hands today at the top of a long bull market for civi- lization. Nationalism was the political theme in the 1940s during a bear market; as this bull market has been peaking out, we have seen plans for a European Community, a New World Order, and for the former


r Communist countries of Eastern Europe to join life. Let me give you an example. The Atlanta Braves NATO. Several months ago, the leaders of the U.S. went to the World Series in 1991 and 1992, for which and Russia, enemies for decades, clasped hands over I had tickets. Ticket prices soared for the 1993 sea- their heads in the spirit of cooperation. These trends son. I did some technical analysis on the Braves and reflect classic bull market sentiments of human so- concluded that while they would have a good season, cial harmony The bear market will bring back na- they would not be playing in the 1993 World Series. tionalism, racial exclusion and perhaps even religious So I declined to buy season tickets, the primary bene- conflict. The bull markets of 1949 to 1966, and 1974 fit of which is first dibs on playoff tickets. They had to today, were nearly free of war. War will also return their best record ever, but didn’t play in the World by the end of the bear market, just as it did on the Series. heels of the Supercycle bear market of the 1850s and Technical analysis is also applicable in your pro- that of the 1930s. Each time one of these grand events fessional life. I published a piece in December 1992 occurs, whether viewed as good or evil, the world sees that charted my business and concluded that a fourth it as a turning point for mankind. Such observations wave was bottoming. Two months later, our five year are true, but because they think conventionally in contraction ended and our expansion resumed. In terms of the direction of causality, it is a turning point fact, technical analysis is useful in predicting trends in precisely the opposite direction that they assume within the Market Technicians Association. One of it to be. They are therefore entirely unprepared for my observations with respect to bull vs. bear mar- the next chain of events. Thinking technically about kets is that bull market psychology is inclusionary of events, that is, observing what they reveal about other people, and bear market psychology exclusion- social psychology, prepares you for those changes. ary. In a bull market, the social mytholoa increas- Figure 7 illustrates this point. ingly sees mankind as a brotherhood. At a bear mar-

The Elliott Wave Theorist has predicted many ket low, in contrast, everyone is a potential enemy, fundamental events: the feel-good pop music of the for whatever silly reason: his color, his religion, his 1980s the end of the exercise boom in the late 198Os, nation of birth, his social status, his planet. How and the defeat of George Bush when he had a record might this theme apply to the MTA? 91% approval rating, and others. We also forecast that Old timers will recall that the MTA was a small when the bull market peaked out, Star Trek-The club of professionals from its commencement in 1970 Next Generation would go off the air. Go out and buy to the end of the inflation-adjusted bear market in this week’s TV Guide and you’ll see the cover story 1982. During the bull market, it suddenly became is “Star Trek: The TV Voyage Ends.” Such forecasts highly inclusionist and expansionary In the process, may seem trivial until you realize that you can pre- the advocates of exclusion were overridden. The asso- diet wars, and even their severity, using the same ciation changed its by-laws in 1985 to accommodate methods. All of the forecasts I just mentioned were more people, and the requirement of being a full time strictly technically based, on the premise that mass professional practitioner of technical analysis was psychological trends produce events. dropped so that we could include people who extensively

If you’re still not convinced, I beg you to con- use technical analysis, substantially widening the uni- sider this question. Who is more sensible, a techni- verse of potential members. This is classic bull mar- cian who says, “War is the result of a negative social ket human behavior. psychology, which is why it occurs near the end of So what can we expect next? In the bear market, bear markets,” and therefore counsels you to beware the MTA will become more exclusionist and polar- of the impending risk of war in such environments, ized. Like the nation, which will finally take action or an economist who says, “I can see that stocks and against illegal aliens, like regions, which will in a few the economy tend to pick up during or after wars, so years begin demanding secession from larger politi- war must create economic expansion and is there- cal entities, and like races, who will begin to support fore a good thing”? Who would you rather have ad- separatist leaders, the MTA will become more de- vising the President? Or another country’s leader? sirous of identifying an “us” and a “them.” This “us Was Hitler’s coming to power bullish for stocks world- vs. them” dynamic could show up ultimately in a wide, as a conventional analyst is forced to conclude, tightening of the MTA’s membership requirement. or was he put in power at a market low as a result of Or perhaps in a secession by a regional affiliate. Or the most negative social psychology since 1859, as I perhaps in an east-west split of the entire organiza- would postulate? Which explanation makes more tion. The bear market low is years away, so specifics sense? cannot be surmised yet. But as time passes, the spe-

All right. Technical analysis can be used to fore- cific divisionary forces will become clear. Such oscil- cast social trends and events. What else? lation between division and cohesion will continue

Technical analysis is applicable in your personal in our organization as long as there is an MTA, just


4 Political Results of Social Sentiment

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Historic day for South Africa

‘End of an era’ Races equal under new

Walls keep crumbling NAFTA passes easihr

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MAY 3. 1994 . USA TODAY

‘HEAVEN IS

SMILING’ MAY Il.1994

Has the west triumphed at last?

Figure 7


as it does in politics. And the styles of the changes are predictable based upon the principles of technical analysis. By the way, I didn’t know until this morning that the reason this conference has only 160 attendees despite an impressive roster is that the membership overwhelmingly voted for the first time in years not to advertise it to thepublic because it wanted to have a more intimate professional gath- ering. This is an exclusionist policy, one that wasn’t on my list!

OK, technical analysis can be used to forecast personal and professional trends as well as social trends and events. What else?

I believe that technical analysis is also applicable to the study and understanding of history If man’s actions are patterned over five days, five weeks, five years and fifty years, they might be patterned over 500 years and 5000 years. Indeed, it is my contention that all of history can be understood from a technical standpoint, and in fact only from a technical standpoint. Figure 8 is one possible categorization of the

historical trends of Western culture since Roman times. The same patterns appear to be in force back to the start of the Bronze Age. This kind of analysis can give you a panoramic view not only of the past, but of the future.

Scientific Forecasting These charts and hundreds of others that I could

show you reveal in human social activities a continually repeating pattern that is typical of a progressive life form, and mankind has been following it relent- lessly With knowledge of how the patterns unfold, to the extent of your ability and effort, you will be able to anticipate the tenor ofthe future. That is an ability that has deftly eluded man throughout his existence, and indeed has been considered impossible. Never- theless, we finally have a way to anticipate much about our social future, not with magic or revelation or sorcery, but with science.

Not only is our profession roaring toward the realm of science, but science itself is roaring toward

MILLENNIUM WAVES WITH

GRAND SUPERCYCLE SUBDIVISIONS

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50 B.C. - 50 A.D. Judnian the Great

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copyright @ 1994

ELLIOlT WAVE INTERNATIONAL P.O. Box 1616

Gainesville, GA 30503 USA

Faith Dominant I

1 Reason Dominant 1

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Figure 8


technical analysis. In fact, it will change our profession over the next decade in a most shocking way The latest scientific frontier, that of chaos science, will eventually make conventional analysis, involving the idea of causality from events to markets, obsolete, just as those same studies have quite swiftly made obsolete the idea of Random Walk, which held academia captive for decades. Chaos science recog- nizes nature’s processes of self organization. Now that that principle is understood, it is only a short step to realize, as some have already done, that society oper- ates the same way. That’s why free societies are more successful and productive than controlled ones. They self organize far more efficiently than any human directors could make them do. Nature’s processes of self organization, furthermore, are patterned. This applies to human self organization as well, which is exactly what R.N. Elliott said and exactly the phe- nomenon that technical analysis studies. Just like the Communists who could never figure out who was directing the industrial success of the United States, conventional analysts keep trying to find the uniden- tified “directors” that make everything in the market happen, and guess what, there aren’t any. The only director is the behavioral dynamic that human interaction produces. Chaos science is beginning to understand this fact, albeit in a foggy way to date. Academics are years behind, presenting studies that admit to a slight psychological component to stock price activity by investigating whether the stock market occasionally “overreacts,” when in fact it does not “react” in the first place. I have always main- tained that analytical study should be focused upon the patterns of human self-organization, and at least increasingly, if haltingly, that is exactly where it is being focused. We as technicians will benefit immensely from this trend, if we have the sense to know that it is providing a ringing validation of our approaches.

Championing Our First Principles In general, advocates of technical analysis have

been content to defend it meekly as having an ancil- lary value, as providing a little extra that might help some investors make some decisions. However, the truth is far more profound than that. Technical analysis is not just one approach to determine value or a trend. It is based upon a fundamental overriding fact, the fact that collective human behavior is patterned. Conventional analysis is not a hallowed sensible ap- preach; it is nonsense. It is founded upon a false premise, which is that there are no patterns, only unpredictable, random causes of behavior to which men respond like puppets. Conventional analysts can’t see their own contradiction, that it is men who cause the causes. It is men who raise interest rates

and create earnings and all the rest. But to the conventional analyst, each is as detached a cause as a meteorite striking the earth. Because many of us have not made this distinction and contemplated and validated its meaning, we have been afraid to defend technical analysis as one would defend any dearly held fundamental truth of human existence. We are afraid to say that the real fundamentals of market analysis are human beings and their patterns of behavior. The result is that today, university professors, who have recently validated the spread between futures and cash prices, relative IPO volume and even trend following as being predictive of stock prices, are getting the credit for work we did decades ago. Why? Because today too many of us are talking about the economy, the Fed, interest rates and the health care bill instead of breadth, volume, point & figure, on-balance volume, rates of change, non-confirmation, divergence, trendlines, relative strength, institutional cash levels, allocation percentages, derivative premiums, short selling ratios, public participation ratios, fear, hope, greed, and the cycles and patterns of human behavior.

So how do we deal with the low repute of the term “technical analysis” among our own practitioners? My recommendation years ago was that we drop the term “technical,” which is used as if it is some subspecies in a universe of various acceptable types of market analysis. Our craft is market analysis. At a larger scale, it is social analysis. And the approaches we take are the only valid approaches to performing it. Conventional analysis is something else entirely, and we can leave it up to its practitioners to define and defend it. When someone asks whether you use corporate earnings in your stock market analysis, tell him no, you analyze markets, not their lagging results. In the end, however, the label doesn’t matter. You can call yourself a technical analyst. You can call yourself a market analyst. You can call yourself an analyst of the behavior patterns of human beings. Whichever label you choose, do not be ashamed of it; do not excuse it; do not compromise it. Announce it with firmness, finality and authority, but above all, with a deep and justified pride, let- ting the world see in you the respect that our field deserves, and the respect that you deserve by practicing it. Thank you.

Robert Prechter is founder andpresident ofElliott Wave International, a market forecasting firm that covers every majorglobal market 24 hours a day, serving both institutional andprivate investors. Mr. Prechter has published four books on Elliott Wave analysis and has a new one scheduled for 1995. Agraduate of Yale Universit.y, Bob serves on the Board of Directors of the Foundation for

the Study of Cycles, and is a member of Mensa and Intertel. Bob served as president of the Market Techni- cians Association in 1990-91.


Information, Time and Risk by William X. Scheinman

“The nature of risk is highly sensitive to whether we act before or after we have all the information in hand. This is just another way of saying that risk and time are only opposite sides of the same coin, because the availability of information increases with the passage of time. Thus, risk, time and information interact upon one another in complex and subtle ways.”

From keynote address by Peter L. Bernstein upon receiving the Inaugural Distinguished Scholar Award from the Southwestern Economic Association, Dal- las, March 4,1994.

The reader should keep in mind that any discussion of the financial markets is of necessity a discussion of constantly changing statistics and other data. This article was originally written in May 1994 and was submitted to the MTA Journal at that time. Therefore, while the data used herein were current as of May 20, 1994, such data applied to any specific situation described may no longer be applicable. The same caveat applies to the Sequel, which was written and submitted on November 11, 1994 market close, and briefly discusses how each of the theories or methods described herein worked or failed to work during the period subsequent to May 20,1994.

Synopsis This article outlines the core theories of Charles

H. Dow and Edson Gould. Three of Gould’s methods used to forecast stock prices, which are based on quan- tifying investor psychology, are described and then illustrated using current data. Several forecasts are then made based on how Gould’s three methods and those of the author combine, in the author’s opinion, to operate in current financial markets. Future levels of interest rates, stock prices, an industry group, the technology sector, as well as two individual stocks, are estimated. A sequel, written six months after the original article was submitted, discusses how the forecasts turned out.

Dow’s Theories The granddaddy of all stock market technical

studies is the Dow theory, which was originated by

Charles H. Dow around the turn of the century Ac- cording to Dow, major bull or bear trends are indicated when the Dow Jones Industrial and Transpor- tation averages, one after the other, set new highs or lows. A divergence between the indices often indi- c&es a potential turning point in the underlying trend of the stock market. Dow set the stage for the later theories, still used and elaborated on by market analysts today, of what may broadly be defined as divergence analysis. That is the study of divergences among and between a broader universe of indices and indicators than were available to Dow.

Dow’s theory was used in the context of his basic commandment: “To know values is to know the meaning of the market.“l But Dow also said that wise investors, knowing values above all else, buy them when there is no competition from the crowd. Indeed, they buy them from the crowd during periods of mass pessimism, and sell them to the crowd in return for cash during late stages of advancing markets. The stock market as a whole, said Dow, “represents a serious, well-considered effort on the part of far-sighted and well-informed men to adjust prices to such values as exist or which are expected to exist in the not too remote future.“’

Gould’s Theories Edson Gould, who first studied the Dow Theory,

was a practicing market analyst for more than fifty years between the early 1920s and late 1970s. His main focus was on forecasting the stock market. Though a student of physics and the harmonics of music, as well as business cycles and Greek civiliza- tion, each of which he believed helped explain certain aspects of how the stock market behaved, he came to believe, after reading Gustave LeBon’s classic, The Crowd,3 that “the action of the stock market is nothing more nor less than a manifestation of mass crowd psychology in action”.4

The methods and techniques Gould utilized in his service, Findings & Forecasts, attempted to “. integrate the many economic, monetary and psychological factors that set the level and cause the changes in stock prices.“5 He regarded the economic factors as important but typically late so far as the stock


-

market is concerned. He regarded the monetary factors as crucial for the stock market and typically early Whereas, he believed that, “Of all three sets of factors, the psychological factors are by far the most important-in fact, the dominant factors affecting the cyclical swings of stock prices.“6

Thesis It follows from the above that one of the most

important aspects of all in successfully analyzing the stock market is measuring investor sentiment. The consensus view, the most difficult factor of all to gauge accurately, can be glimpsed at times-and only in part-through not only such transaction-based data as put/call ratios, premiums and open interests, but also poll-based data such as the weekly Investors In- telligence reports of what percentage of investment advisors are bullish or bearish.

Whereas the author regularly screens such data for extremes, the theories and methods which are derived from Gould and are discussed below are, in an of themselves, measures of the behavior of the investment crowd and, in his opinion, more practically useful in making and implementing investment decisions. And inasmuch as they are also applied to the monetary factors, a bond market opinion is derived therefrom, as well.

The index and stock charts used to illustrate this article are of

1. Treasury Bonds Nearest Futures, Monthly 2. Treasury Bonds Nearest Futures, Weekly. 3. New York Stock Exchange Financials Index,

Weekly

Standard & Poors 40 Utility Stock Composite, Weekly

4. Standard & Poors 400 Industrial Stocks Com- posite, Monthly

5. Drug Shares Index, Weekly Close-(Sum of BMY, LLY, MKC, MRK, PFE, UPJ X 4.50541).

6. TXB-Hambrecht & Quist Technology Stock Index Less CBOE Biotechnology Stock Index, Weekly Average.

7. Merck (MRK), Weekly

8. U.S. Robotics (USRX), Daily

Gould’s Methods and Techniques Edson Gould is, perhaps, best known for his

monetary rule and valuation barometer: His Three- Step-and-Stumble Rule states that, “Whenever any one of the three rates set by monetary authorities- the rediscount rate, the rate for bank reserve requirements, and margin requirements on stocks-increases three times in succession.. . invariably.. the stock market has subsequently.. .suffered a sizable setback.“? Whereas his Senti-Meter is, “the ratio of

-

the Dow Jones Industrial Average to the average rate of annual cash dividends paid on that average. “8 When the Senti-Meter reads $30 per $1 of dividends or more it indicates a high and risky market. A reading of $15 or less indicates a relatively low and cheap market.

Lesser known and, perhaps, too arcane for many, the author has found that three of Gould’s methods and techniques are more practically useful in helping decide when and at what levels a given stock or price index is “too” high, or “too” low and what constitutes a sentiment extreme. With this background in mind, let’s examine Gould’s theories and applications of Resistance Line Measurement, Unit Measure- ment and the Rule of Three, as well as the author’s theory of the Cut-in-Half principle and its opposites.

Resistance Line Measurement According to Gould, “ . . . the market continually

reveals a quantum of mass psychology comprising time and price. It follows that a sharp decline in a short period of time generates as much bearishness as a slow and minor decline over a long period of time.“g This theory, then, is based on three principal determinants of crowd psychology in the market place: price change itself, elapsed time to achieve it and the perceived amount of risk.

The resistance line theory attempts to measure these three elements of mass psychology mathemati- cally, weighing both the vertical price change and the horizontal elapse of time. This measure of potential risk or reward must be keyed off whatever the investor regards as any pair of prices which consist of an important high and low of the particular security’s price history. Four of the charts which are discussed below illustrate how the resistance lines are applied.

The theory is that a trendline rising at one-third (or two-thirds) the rate of an advance movement is likely to produce resistance to subsequent decline, but, if violated, the decline will accelerate from the point of penetration. Similarly, a trendline declining at one-third (or two-thirds) the rate of a decline movement may provide resistance to a subsequent advance, but, if penetrated, the advance will accelerate from that point. Sometimes these resistance lines work, sometimes they don’t; they are not fool-proof. But the author uses resistance lines because they seem to be more accurate than ordinary trendlines and- most importantly-because they can be drawn before the subsequent price action takes place.

Long Treasury Bonds Let’s see how resistance line theory may be

helpful this year in gauging when Treasury Bonds Nearest Futures, which have been falling mostly since their September 1993 peak, etch a major low. Inas- much as these Treasuries, Monthly (Chart 1) made a


major low in 1981 at 55.156 and more than doubled it at the 1993 high of 122.313, the most important set of resistance lines derive from that low and that high. Referring to the chart, we observe that the May 11, 1994 low of 101.125 slightly broke the rising 2/3 speed line before reversing upward to close May 20 at 105.000. Important here are the facts that this same resistance line approximately defined each of the 1987,199O and 1991 Treasury lows. Translated into an opinion on May 20, this means that Treasuries won’t decisively break par this year. Should they do so, it might imply the onset of a renewed inflationary cycle.

Moreover, the second of Gould’s methods, the unit measurement principle, also helps to determine the importance of the early-May intraday low of 101.125.

Unit Measurement This technique is sometimes helpful in estimat-

ing terminal phases of advances and declines, of both individual stocks and market indices. In other words, what constitutes a price which is “too” high or “too” low. Its measurements are expressed in terms of bull and bear “units”. A bull unit consists of the number of points of an initial advance by a stock or price index following the bottom of a prior important decline, succeeded by a subsequent reaction which, however, remains above that bottom and then is followed by a second advance that goes beyond the first one. A bear unit is formed in the same manner but in the opposite direction. These measurements sometimes por-

CHART 1

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IRFMRY Pa&3 ItalRBT FUTURES, mnrtllY MY#y, 1334Pll5.~

tend the length of an overall advance (or decline) and indicate levels at which a trend may meet resistance, or, at times, an extreme reversal.

Price action with the primary trend frequently “works off” units three times (sometimes four times), in accordance with the Rule of Three, the basis of which is discussed below. In other words, for a move with the trend, expect three units, but be prepared for the fourth. One other important point about unit measurement is that recognition of the 2-unit level, by a sharp reaction from it, often indicates that following such a reaction the security will go all the way and work off three, or four units. Whereas recognition of that level which is defined by 2-l/3 units, without recognition of the 2-unit level (by resistance from it), is grounds for caution, especially for trend followers, since that is often the hallmark of a contratrend move.

Now we are equipped to develop a second opinion about Treasury Bonds Nearest Futures, Weekly, which is illustrated in Chart 2. Referring to the chart, we observe that these Treasuries etched a bear unit of 4-718 points by their initial September 7-22, 1993 decline from 122.313 to 117.438. According to unit measurement theory, then, the contratrend, upward reaction from the 2-bear unit level of 112.563, which was reached at the November 23 low of 112.031, implied that Treasuries would go down all the way- to work off either 3 or 4 bear units to 107.688, or 102.813, respectively. With the actual intraday May 11 low of 101.125, this close-less than 2 percent away-recognition of the theoretically maximum

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CHART 3

4-bear unit count, also leads to the conclusion that that was a low in Treasuries of major importance.

Interest-Sensitive Stock Market Indices Because of the importance of the monetary fac-

tors, ideally the resistance line and unit measurement theories should also be reflected in interest-sensitive stock market indices. Sure enough, the New York Stock Exchange Financials and Standard & Poors 40 Utilities indices (both on Chart 3) did, so far, in 1994 faithfully reflect both resistance line measurement and unit measurement theory, respectively Referring to the chart, we observe that the Financials’ week of April 8,1994 low of 200.01 and all subsequent lows, which were higher (itself a positive divergence), reversed upward ahove the rising 2/3 speed resistance line from the 1990 low. Gould always said that the ability of a price index to stay above its rising 213 speed resistance lines during reactions was the hallmark of a powerful advance.

Whereas the S&P 40 Utilities, which etched a bear unit of 10.29 points by the September 17-Octo- ber 15, 1993 decline from 189.49 to 179.20, worked off a fairly precise 4-bear unit count to 148.33, compared to the actual May 13 low of 146.85. Close enough. Moreover, these Utilities also respected their rising 2/3 speed resistance line from the 1981 low, which approximated this 4-bear unit count.

It logically follows from each of these two theories that should the aforesaid risk parameters of these

three interest-sensitive indices - Treasuries, NYSE Financials, S&P 40 Utilities - be decisively downside penetrated on a closing basis that the bear market in bonds not only had more to go on the downside but also that stocks might have begun a bear market as well. However, the author does not believe that is the case at May 20,1994, as we examine next.

A Stock Market Road-Map Gould also said that over longer periods of time

unit measurement was useful, too: “A ‘grand unit’ is, as the name implies, a big unit sometimes taking months to complete and years to confirm.“10 We think this theory has been remarkably accurate since the stock market’s 1982 low and that it is relevant now. Referring to Standard 8z Poors 400 Industrials (Chart 4) we observe that during the 14-month long 1982-1983 advance from 113.08 to 195.25, a grand bull unit of 82.19 points was etched - the lo-month- long 1983-1984 decline to 167.64 not exceeding the 1982 low.

Thereafter, the S&P 400 steadily rose until hitting the 1986 peak of 282.87, which was less than 2 percent above the 2-bull unit count at 277.46. The subsequent 12 percent reaction to that year’s Sep- tember low of 252.07 constituted recognition that the unit measurement principle was operative, and that the S&P 400 would go on to work off at least 3 or 4 bull units.

From the 1986 low, the S&P 400 gathered steam L

22 MTA JOURNAL/SUMMER - FALL 1994

and began to accelerate in 1987, reaching the 3-bull unit count of 359.65 in June. That level was potentially an important peak level in accordance with the theory - expect three units. During the next two months the S&P 400 overshot the 3-bull unit count but peaked 9.7 percent higher (intraday) in August, followed by the crash.

From the 1987 crash low, stocks steadily rose until hitting the July 1990 peak of 438.56 which was less than 1 percent below the 4-bull unit count to 441.84. That was a perfect fourth and final move, according to Gould’s unit measurement theory. Dur- ing the next three months stocks fell by 21 percent.

Of current relevance, in the author’s opinion and experience, is that sometimes unit counts will work off a double set of units, i.e., 6 or 8 units. This appears to be the current case for the S&P 400 Industrials, which, rising from the October 1990 low of 345.79, recognized the five-bull unit count to 524.03 repeatedly last year by resisting further advance. However, by late-1993 that level was decisively exceeded. This means to us that the theory is saying the stock market should continue to rise until reaching at least the 6- bull unit count to 606.22, before the bull market which began from the 1982 low is over.

four steps is apparent in both very short-term moves as well as those encompassing months and even years.

Drug Shares Index However, to simply illustrate the Rule of Three

we next examine the Drug Shares Index (Chart 5), a composite of Bristol Meyers, Lilly, Marion Merrill Dow, Merck, Pfizer and Upjohn. Between January 8, 1992 and August 13, 1993 the Drugs dropped 42.8 percent in a classic bear market, which consisted of four steps down. Also, helping define the fourth step as the final one was the fact that the August 13,1993 low of 1011.46 closely approximated the 3-bear unit count from the 1992 peak, at 1012.93.

After rallying 20 percent from the 1993 low, to 1217.04 on January 14,1994, the Drugs came down again to etch a successful test of last year’s low, at the April 15,1994 low of 1014.84. In other words, we are confident that a classic double bottom has been put in place for this group. Additionally, as illustrated later, another yardstick of extreme investor behavior

CHART 5

In 1994 the S&P 400 Industrials advanced further to reach the 560.88 level in February, before re- acting to the April 20th low of 507.36, a drop of 9.5 percent. Referring again to Chart 4, we further observe that during the February-April reaction the rising 2/3 speed resistance line from the 1990 low, which during April was at the 500 level, was effective in defining that month’s low. This means we believe current risk from the May 20th close of 530.58 approximates 4 percent, say 510, whereas potential reward - to 606.22 - would be a gain of 14 percent. Those seem like good odds.

The Rule of Three Now, we examine the third of Edson Gould’s theo-

ries, the Rule of Three. For reasons about which people have speculated for thousands of years, the numbers “three” and “four” have a meaning of finality about them. For example, Aristotle said, the “Triad is the number of the whole, inasmuch as it contains a beginning, a middle and an end.” This concept may be deeply rooted in the natural family unit of father, mother and child, which is given religious expression in the concept of the Holy Trinity. The financial markets, which, after all, reflect human emotions, also frequently act in the same way Sometimes there is a fourth movement, which usually is charac- terized as a “now or never” action, climactic in nature. (Three strikes you’re out; four balls take a walk). That financial markets and individual stocks typi-

tally -but not always - move in a series of three or

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targeted both Lilly and Merck as having etched final lows last year and this year.

Technology and Growth Stocks No discussion of the stock market would be com-

plete without addressing the role of the technology

and growth sectors. They are important not only be-


cause they often represent the fastest growing companies, but also, as I stated in my book which was first published in 1970, “. . .glamour/growth stocks which, because they are highly volatile - ordinarily two-and-a-half times more so than those in the DJIA - are favorite vehicles of sophisticated investors.“” This volatility provides greater time opportunity than is available in the behavior of most other stocks.

Edson Gould, “put together the first ‘glamour average’ back in 1960,“12 though, surprisingly, the pamphlet, A Vital Anatomy, from which we’ve also earlier quoted various Gould statements about his theories and methods, says nothing whatsoever about “glamour” stocks. Having originally gotten this idea from Gould in the late 1960s I created my own “Glamour Price Index”, which consisted of the stocks of eleven highly regarded, well known, technology oriented companies. l3 However, in the most recent edition of my book, I noted that in recent years I’ve scrapped my original “Glamour” and several other technology or growth based indices in favor of the more representative Hambrecht & Quist Technology Stock Index14 and its sub-index of even more rapidly growing, smaller companies, the H&Q Growth Stocks Index. But inasmuch as the H&Q indices include stocks in the biotechnology sector, which I believe march to a different tune than other growth and technology types, I also have created two other indices which consist of the numerical values of each of the respective H&Q indices less the CBOE Biotechnology Stock Index. Hence, in the technology and growth sectors, we examine these five different indices:

1. H&Q Technology Stock Index, which is comprised of the publicly traded stocks of 200 technology companies, broadly defined in five basic groups: Computer Hardware, Computer Software, Communications, Semiconductors, Health Care (within which is a Biotechnology sub-index). The index was originally conceived in the 1970s as a price- weighted index. In 1985 it was reconstructed and market capitalization weighted. Changes in the index occur as mergers, acquisitions and failures dictate - not infrequently.

2. H&Q Growth Stock Index is a subset of the Technology Index and is comprised of all companies in the Technology Index which have annual revenues of less than $300 million. Companies are removed every January if they have passed $300 million in revenues.

3. CBOE Biotechnology Stock Index.

4. TXB Index, which is the H&Q Technologies Excluding Biotechs.

5. GXB Index, which is H&Q Growth Stocks Excluding Biotechs.

The TXB Index Of these five indices, the author thinks the TXB

Index is both the most representative of the overall technology sector as well as being the most orthodox in reflecting investor psychology We examine it next. Referring to Chart 6, we observe that between their respective 1990 lows and 1994 highs (through May 20, 1994), whereas the DJIA gained almost 71 percent and the Dow Transportations rose more than 131 percent, the TXB Index more than tripled. So much for volatility!

We also observe that at its March 18,1994 peak, the TXB Index completed a third step up from its 1991 low. In accordance with the Rule of Three, this allows for either the possibility that that was a final step, or allows for the emergence of a fourth and final higher high, after the current reaction is over. We favor the latter possibility and believe Gould’s

CHART 6

140

188

3654

3202

2750

2290

two other theories provide well defined potential risk and reward parameters for the outcome we envisage.

As to risk in the TXB Index, which at May 20, 1994 was down 14-l/2 percent from its March 18 peak, it must not break below the rising 213 speed resistance line from the 1991 low, in order to maintain its bullish uptrend, in accordance with Resistance Line Theory Inasmuch as TXB closed at 303.15 on May


20, and the aforesaid 213 speed line was nearing the 287 level, that means we think that risk of this date approximates 5 percent.

Whereas potential reward of a possible fourth and final rise of the TKR Index we think may be estimated through the Unit Measurement method. Referring again to Chart 6, we further observe that the TKR Index etched a bull unit of 99.96 points by its initial advance from the September 20,199l low of 112.29 to the April 24, 1992 high of 212.25. The 2-bull unit level of 312.21 was briefly recognized by its l-week reaction from near that level in early 1994, before advancing to the higher March 18 all-time high. Assuming then, that the aforesaid resistance line risk parameter holds on the current reaction, we believe that potential reward from the May 20 level is about 35 percent to the 3-bull unit count at 412.17.

These sound like favorable odds of 7-to-1 between possible risk and reward, in the author’s opinion. I note, too, that an overhead trend, which is projected through the 1992, 1993 and March-1994 peaks and which also parallels the rising 2/3 speed resistance line, approximates the 400 level by year-end 1994, as well. In other words, the author believes that the TXB Index will rise by about one-third before this sector is vulnerable to a bear market.

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CHART 7

tant stock or price index loses 50 percent of its value, Bear Market

After the reward area is approximated, that’s from where I think a bear market in technology and growth, as well as one for the stock market, overall, may begin. That there will likely be a bear market between now and 1995 is suggested by the facts that every single “5” year in this century has been an up year, which means that there “should” be an inter- vening bear market before the 1995 bull market begins. However, an alternative scenario is simply that it will take between now and year-end 1994 for the reward area to be reached.

If that proves to be the case and the stock market rises to record levels and nears the potential reward areas we have outlined herein, by year- end 1994 (possibly narrowly extending into early 19951, that would be the fourth consecutive up year - a possible “final” up year, according to the Rule of Three. In that event, 1995, especially if perceived by “too” many as always an up year since it is a “5” year, would then set the stage for it to become the first down “5” year during the past century, in the author’s opinion, i.e., 1995 happens in second- half 1994.

The Cut-In-Half Rule and Its Opposite The fourth gauge for measuring investor extremes

is conceptually the simplest of all - the Cut-In-Half Rule and its opposite. Briefly stated, when an impor-

a rally or even major reversal often originates from near that level. Keep in mind that the Cut-In-Half Rule and a 50 Percent Retracement are quite different. For example, two stocks each base at the level of 50 and both rise to 100. If one declines to 75, before advancing once again, it has retraced 50 percent of its advance from 50 to 100. However, if the other one drops back to 50 from 100, it has been “cut-in-half.” A textbook example of the Cut-in-Half Rule is shown in Chart 7 of Merck, which we discuss below.

Why the Cut-In-Half Rule and its related spinoffs often work is probably because the investor crowd quantifies 50 percent off the top as “too” cheap. Whereas the opposite is that after an important stock or index doubles it often runs into trouble. At that point, investors tend to take at least some profits. But since some indices, individual stocks, commodities and interest-bearing securities are more volatile than others, this same yardstick is sometimes extended on the way up to a triple, quadruple, quin- tuple, or even a sextuple, (with low price stocks sometimes squaring their lows). Whereas, on the way down there is sometimes a double cut-in-half (off 75 percent), or - more rarely - a triple cut-in-half (87-l/2 percent off the top). Keep in mind, however, that in applying these Cut-In-Half yardsticks as potential long entry points, one should be satisfied that the company’s balance sheet is not in serious question.


Stock Selections Though it can be repeatedly demonstrated that

these four theories of investor behavior are constantly operating in all financial markets, in the author’s opinion, it does not necessarily follow that one can readily use them in every instance. Sometimes the units are not readily discernible and the resistance lines don’t work. Moreover, sometimes there is a fifth step in an overall advance or decline movement, which appears to contradict the Rule of Three-though a case might be made that such a fifth step represents an undercut (or overcut) test of the fourth step.

However, after using these theories over time to make day-to-day investment decisions, I have found that they are valuable when discernible and add confidence to a decision. That is particularly the case when more than one theory appears to be operative in a given situation.

For example, referring to Chart 7 of Merck (MRK @ 30-l/4), we can observe that when it closely approximated its theoretical cut-in-half level of 28-9132 during August 1993, at the actual low of 2%5/8, on a fourth (and presumably final) step down from the January 3, 1992 peak of 56-g/16, it appears to have constituted a classic buyingjuncture. Thereafter rallying to 38 by January 51994, Merck subsequently tested last year’s low at this year’s April 15, 18 lows both at 28-l/8. This makes me confident that the cut-in-half level was, or approximated, a fi-

nal low, especially since there is no great mystery about Merck’s fundamentals and fifty percent off the top seems a reasonable - if not “too” great - a discount for those investors critical of the Clintons’ health care plans.

More volatile technology and growth stocks some- time reflect these theoretical principles of how crowd behavior plays out in the financial markets in an ex- traordinary way For example, referring to Chart 8 of U.S. Robotics (USRX @ 30-3/4), a world-wide leader in data communications, we can observe that after doubling the late-1991 low of 12-l/4 by the early-1992 high of 24-l/4, Robotics dropped sharply (off 45 percent). Whereas the early-1993 high of 25-112 almost doubled the summer-1992 low of 13-318. Then the March 1993 low of 17 was slightly more than doubled at the October high of 35-l/4, whereas the subsequent decline to 23 worked off an almost-perfect 4-bear unit count to 23-114.

Moreover, this year’s high of 46 (on March 8) was a perfect double, from which a reaction has begun, with a bear unit of 5-l/4 points already etched and confirmed (by a lower low), and more recently ap- pearing to recognize the 3-bear unit level of 30-l/4, by the May lo-11 lows of 29-114, as the new low from which to key off. That the stock of a single company could have gone through so many extreme bull and bear moves, in such a short period of time, shows not only that Alvin Toffler’s “future shock”lj has arrived on Wall Street but also that traditional Wall Street research is incapable of dealing with it effectively The arrival of “future shock”, what some now call the information age, also presents a challenge to stock market technicians - to do their homework in order to stay ahead of the curve.

May 22, 1994

SEQUEL

At Market Close November 11,1994: What Happened During the Subsequent Six Months

Treasury Bonds Nearest Futures (Charts 1 and 2) perfectly tested their May 11 low at their virtually identical July 11 low of 100.0625 - compared to the May 11,100.2500 (the numerical value of the Futures are about one point lower than shown on the chart because the Nearest Futures had rolled over from June’s to September’s, and currently December’s). Thereafter Treasuries rallied back to the August 5 high of 105.21875, then slowly eroded until par was broken at the September 22 close of 99.40625. At that point we conceded the 13-year long uptrend in Trea- suries was clearly broken and that the major trend inference of bonds should be assumed as being down.


S&P 488 INDUSTRI~ e 5XLB7, TXB INDMIIEONOLOCY LESS BIOTCMSI e 379-73

CHART 9

By November 11, Treasuries slumped even more, closing at 96.0625. Moreover, since this break of the grand resistance line of Treasuries also took out the 4-bear unit count level, it implies to us that ultimately at least six bear units will be worked off. That level is 93.0625.

However, we never changed our positive stock market opinion because the two interest-sensitive stock market bellwethers we mostly rely on remained intact, notwithstanding the break in bonds. The NYSE Financials (Chart 3), which had hit an intraday low of 199.95 on April 4, closing May 20 at 214.27, slightly exceeded the 220 level during four days in June, then also slowly eroded until closing November 11 exactly at 199.56. While this does con- stitute a break of its resistance line, and hence is clearly negative as of November 11, it seems such an obvious “test” of the April 4 low, that it is conceiv- able to us the Financials may be able to mount at least a weak rally from here.

We draw this tentative conclusion because the third interest-sensitive index, Standard & Poors 40 Utility Stock Index (also on Chart 31, which

closed November 11 at 148.51- still above its May 13 low -we don’t think will take out that level. Not only has the 4-bear unit count level of 148.33 been repeatedly and successfully tested during 15 trading days in October and November but is also defined by these Utilities’ rising 2/3 speed resistance line from the March 1980 low. That is about as precise recognition of a Gouldian-defined risk parameter as it ever gets! Naturally, this also means that a decisive break of it would undoubtedly require some change in our current stock market opinion.

Our Stock Market Road-Map for Standard & Poors 400 Industrials (Chart 4 and Chart 9), successfully tested the April 20 low (507.30) at the June 27 low of 511.90, thereafter rising to an all time high of 564.50 on October 31. Closing November 11 at 550.87, potential reward has now moved down to only 10 percent whereas near-term risk remains about 4 percent (the rising 2/3 speed resistance line moving up to about 527). Not quite as good odds as on May 20.

The Drug Shares Index (Chart 5) was up almost 18 percent at November 11 from May 20 and we think


is headed substantially higher. Though gaining almost 30 percent from its April low at the November 11 close of 1316.70, we think the Drugs will work off at least three bull units, a further gain of 25 percent from here. Three bull units were worked off on the way down, so why not three bull units on the way up?

The TXB Index (Technologies Less Biotechs) (Chart 6 and Chart 91, at its June 23 daily close of 293.97, never broke below its 2/3 speed resistance line risk parameter and subsequently rose 28.9 percent from that low to 378.83 on November 9. Obviously the odds of further gain from here have sharply dete- riorated, potential remaining reward only a possible additional 8.8 percent, in our opinion. We have chosen to deal with this change of the odds by building cash as specific technology and growth components reach their individual, respective potential reward zones.

Merck (MRK @ 36-3/4) (Chart 7) hit a recovery high of 37-518 on November 10 and we believe is headed into the 44-45 zone. That is defined by both a bull unit count and an overhead declining l/3 speed resistance line.

Whereas U.S. Robotics (USRX @ 3%3/4) (Chart 8) worked off a fourth bear unit at its June 2nd low of 24, then etched a new bull unit of 5-l/2 points by its subsequent initial rise to 29-112. USRX went on to slightly exceed the 3-bull unit count of 40-l/2 at the November 9 high of 42-l/4. The maximum upside potential we see from here, is a 4-bull unit count to 46, which would also be a prospective double top with the early-1994 peak.

Conclusion I believe that this real-time experience in using

the Gouldian theories amply demonstrates both their usefulness as well as their drawbacks, though only scratching the surface of their potential applications. Their key advantages are that Gould’s quantifications of investor sentiment help one to both reach and act upon specific investment conclusions on a case by case basis, without being held hostage to an endless, self- imposed debate about what to do.

REFERENCES I

1. why Host Investors Are Mostly Wrong Most of the Time, W!x. Scheinman, 1991, Fraser Publishing Company (p.139).

2. Scheinman, ibid.

3. The Crowd, G. LeBon, 1896, Fraser PublishingCompany (1982).

4. A Vital Anatomy, E. Gould, (Undated), Anametrics, Inc.

5. Gould, ibid.

6. Gould, ibid.

7. Gould, ibid.

8. Gould, ibid.

9. Gould, ibid.

10. Gould, ibid.

11. Scheinman, ibid.

12. Gould, ibid.

13. Scheinman, ibid.

14. Hambrecht & Qnist Technology and Growth Indices, Michael De Witt and Shiela Ennis, Hambrecht & Quist Incorporated, January 1993.

15. Future Shock, A.Toftler, 1971, Bantam Doubleday

BIBLIOGRAPHY

Numbers

Jung, C.G., Collected Works of C.G. Jung, General Index, (Volume 20, pp. 485-489, “Numbers”), Princeton University Press, 1979.

Menninger, K., Number Words and Number Symbols; A Cultural History of Numbers, The M.1.T Press, 1970.

Von Franz, M-L, Number and Time, Northwestern University Press, 1974.

Technology

Veblen, T., Imperial Germany and the Industrial Revolution, Transaction Publishers (1990 reprint).

William X. Scheinman, a registered investment advisor since 1968, moved from Wall Street to Reno, Nevada in December 1974 from where he advises financial institutions world-wide. One of the founding members of the Market Technicians Association, Mr Scheinman was the founder of the African-American Students Foundation, Inc. which between 1956 and 1961 brought more than 1000 students from all over Africa to the United States to attend institutions ofhigher learning in America, and the more recent founder of the African-American Lead- ership Foundation, Inc.


Skewness: An Options Based Indicator to Measure Sentiment by Carsten Lund

Introduction and Background The dominant forces that drive the financial markets are changes in the perception of the market participants of what the fair values of the markets are. The perceived fair market value is a function of both fundamental quantities and what individuals believe these fundamentals should be worth. While the fundamentals consist of easily accessible, objective data, the evaluation process can be quantified only roughly Fortunately, one can get an idea about it through its strong relationship to mass mood. Mass mood, by definition, is representative of the sum of all individual opinions and can be analyzed by appropriate methods. Technical analysis offers proven methods to measure and quantify sentiment by exploiting information which is generated by market participants.

Over time a variety of indicators and methods have been developed to pursue this, all with the in- tention to help the analyst evaluate the prevailing sentiment. Some of the most powerful tools to quantify sentiment are indicators which are based on options related data. Since option buyers in general don’t buy an ‘asset’ itself (like stocks or futures traders do) but hope on a future price movement of the asset, options related data are very much influenced by the bullish or bearish mood of the traders (I do not consider hedging, arbitrage or other intricate options strategies here but only directional trades). The creation of the put-call ratio as a sentiment indicator by Dr. Martin Zweig’ marked a starting point of option related indicator analysis and opened the door to a new field in the technical analysis of the financial markets. In line with this developing field, I want to present a new sentiment indicator which takes advantage of information inherent in option prices through their implied volatility and through the analysis of the volatility change over time.

price of the underlying asset has changed in recent history It is derived from the asset’s price distribution over a specified time window and by calculating the width of this distribution.

Implied volatility: Implied volatility is calculated by comparing the actual price of an option with the fair value of that option, whereby the fair value was arrived at by comparison of the actual price with a theoretical options pricing model (such as Black- Scholes). These theoretical models need several parameters of which volatility is the only unknown. They give the fair value of the option under the specified conditions.

Future volatility: the quantity that measures how volatile the price path of the underlying asset will be from now till expiration. Future volatility is what everybody wants to know but is unknown by definition and can only be estimated.

For trading purposes future volatility is the most important one, since it allows one to exactly calculate the fair value of an option. For the con- struction of a sentiment indicator however, implied volatility is much more important as it reflects the expectations of the traders right at the moment of the trade and thus allows an estimate about the prevailing sentiment.

Skewness Looking at only one specific asset, the implied vola-

tilities should be the same for all call and put series, i.e. for all strike prices. This is not the case! The phe- nomenon that options with different strike prices yield different implied volatilities is well known (Robert E Krause2 and Sheldon Natenberg) and is called skewness (this differs from the statistical definition of the term skewness as the third integer moment of the probability distribution [Turnball and Wakeman4]). To illustrate skewness in graphical form one plots the im-

Implied volatility plied volatilities of an option series as a function of the Volatility is a quantity that specifies how an un- strike price (see Figure 1). Implied volatilities to the

derlying asset travels through a 2-dimensional price- left of the actual price are calculated from (out-of-the- time space. money) puts and to the right from (out-of-the-money)

For clarity let me define the types of volatility calls, respectively Implied volatility of in-the-money- that I am talking about: options tends to go to zero rapidly and is hence disre-

Historical volatility: measures how much the garded in skewness analysis.


4.2

4,o 94 95 98 97 98

strike price

Figure 1: Skewness for options of the Bund futures October 1992 contract on 0312611993. The closing price on 031261 1993 was 96.02. L

There are several theories that try to explain the different implied volatilities at different strike prices by means of trading restrictions, of probability distribution inaccuracies or of a lottery effect (Krause2), just to name a few. Besides these structural causes for skewness, at least one additional effect has to be taken into account which I observed frequently while working as the head of the options and futures department at a German bank in Hamburg.

As every market analyst observes over time, investors tend to get more and more bullish the longer a bull market lasts, At the beginning of the move they predominantly buy blue chips, but then turn to sec- ondaries, warrants and finally, as prices go higher and higher, to options. They typically begin with buying in-the-money calls but then go for the more speculative out-of-the-money options to increase their le- verage (it’s more fun being long 10 calls worth $1 each than being long 2 calls worth $5 each), thus bid- ding them up to unproportionally high prices. The growing optimism is thus translated into an increase of the implied volatility of the out-of-the-money options and in a steepening of the slope of the skewness. The same occurs during bear markets on the put side.

The market makers, on the contrary, try to lo- cate mispricing situations from which they can get a profit opportunity. If they recognize that the prevailing implied volatility is too high with regard to the current situation they tend to sell the overpriced options, thus pushing the prices back to an equilibrium again. In rare cases only will they enter directional positions which might result in a trend of the skewness in to off-equilibrium values.

The skewness-slope indicator that I want to present measures the change in skewness over time and its aberration from the normal shape. To do this, normal shape has to be defined, first of all. Different markets exhibit different skewness-

32b 1 I I I I 1 1

28 -

7 24 - @ E z 20 -

s “m 16 - z

2 ‘- 12 -

8- implied volatiliy points

98.0 98.5 99.0 99.5 100.0 100.5 101.0 101.5 102,o

strike price

Figure 2: Illustration of the bullish and bearish slope as defined in the text.

shapes due to different restrictions that are imposed on them. In the stock market for instance, put options tend to have a higher implied volatility than call options due to the fact that institutional investors instead of selling stocks prefer to buy puts as an insurance against a market decline. In the currencies the shape of the skewness is symmetrical in general, since no such restrictions exist. There- fore, each market has to be analyzed separately with respect to its normal skewness shape, whereas the interpretation of the slope changes is invariant with respect to the specific market.

Analysis Procedure In general, calculated implied volatilities depend

very sensitively on the underlying options pricing model. In my analysis this is not a crucial point since I am not interested in absolute values but in differences of implied volatilites.

To measure precisely how the skewness shape changes over time not only the slope but also the con- vexity of the graph would have to be examined. This will be done in a further study In this paper I will concentrate on the bullish and bearish slopes only (see Figure 2).

The bullish slope is defined as the slope of the line connecting the implied volatility of an at-the- money call with the implied volatility of a call which is 100 basis points above the present price (this re- fers to Bund futures, with which the analysis starts in this paper). For each day the at-the-money strike price has to be fixed. In general the closing price in a given market will not exactly match a given strike price. In these cases I extrapolated between the implied volatility of the nearest in- and out-of-the-money calls to get the lower implied volatility point. I then used the two calls nearest to the price 100 basis points above the current price to calculate the higher implied volatility point with the same extrapolation

30 MTA JOURNAL/SUMMER-FALL1994

procedure (example: closing price: 100.1, implied volatility 100 call: lo%, implied volatility 100.5 call: 15%, implied volatility 101.0 call: 20%, implied volatility 101.5 call: 25%; lower implied volatility point = O.B*lO% + 0.2*15% = ll%, higher implied volatility point = 0.8*20% + 0.2*25% = 21%, slope = lo%/ lOOpts). The same analysis procedure applies to any other choice of the price distance of the strike prices.

The bearish slope was calculated in exactly the same way by using puts instead of calls to deduce the implied volatilities.

99 0,025

97 0,020

96 0.015 g

8 5

.z 95 ::

0,010 ” %

94 0,005

93

O,ooO 19.03.93 20.04.93 19.05.93 17.06.93 15.07.93 12,09,93

Lime

Figure 3: Skewness (thin line) as a function of time for the calls on the October 1993 Bund future (thick line).

Analysis of Bund Futures Options Figure 3 gives us an idea of how skewness be-

haves over time and which general features one can expect to find in the slope-change over time. Figure 3 was derived from call-options data, but put-options yield the same result and can be explained in the same way as is done in the following for calls. The out-of- the-money options had been chosen to be 150 basis points away from the actual price.

The change of the skewness over time is charac- terized by two main features. First, one observes a steady increase in the skewness itself in an exponential growth-like fashion. This behavior can partly be accounted for by means of theoretical pricing models like Black-Scholes. Everything else being constant, these models predict the price of an option to drop to zero exponentially as time goes on. Since options traders know that in reality prices do not adhere to the theoretically assumed gaussian price-change distributions (real life distributions have higher peaks and fatter tails [PET]), they try to compensate for that inefficiency by allowing higher and higher implied volatilities as the expiration date approaches, thus allowing skewness to increase almost exponentially, too.

Secondly, one observes very jittery behavior during the last couple of trading days. This is caused by the discrete nature of the strike and option prices. As the expiration date approaches, out-of-the-money

options loose their value very rapidly until they are quoted near their smallest possible price levels. A small absolute price change in the price of an option of one cent then is very large percentage wise, imply- ing also a very large percentage wise change in the implied volatility of the options.

In my analysis I want to concentrate on skewness changes which are independent of these structural reasons. This requires to clean the data from those side effects. Since I found no reasonable way to get rid of the jitters at the end of the contract (or options) life, I simply skipped the last 15 trading days before expiration and replaced them by the data of the next contract month. In case of the jitter-side ef- feet one has to compromise between cleaning the data and losing too much information, as the liquidity and hence the volatility of the second nearest contract is only limited.

To remove the exponential bias from the data, I added and normalized the skewness-data of four contract series into one and fitted an exponential to the resulting spectrum which was then subtracted from the data.

In the last step the change in the skewness was calculated. First, a 20-day exponential moving average was calculated for the skewness which was in the second step subtracted from a 5 day exponential MA of the most recent skewness values. Thereby one generates an oscillator which indicates whether the skewness is higher or lower this week than it has been over the last 4 weeks.

Interpretation There are several ways how the skewness slope

can be interpreted. In general, one is interested in shifts of the skewness slope away from the norm. To visualize these shifts the difference of the actual slope to the normal slope is plotted as an oscillator, separately for calls and puts. Positive oscillator values are indicative of optimism (the put oscillator has to be reversed to make it comparable to the call oscillator) and negative values of pessimism.

Looking at Figure 4 one finds four areas in which the call-skewness deviates significantly from its previous values (labeled A - D). Points A, B and D mark periods where after a decline the skewness suddenly increases, indicating growing optimism, whereas at C optimism decreases during a price increase. At points A, B and D the price deterioration is stopped after the rise in optimism, whereas after point C nothing significant happens. This behavior is NOT what is expected from typical sentiment indicators, since optimism usually grows with price increases instead of decreases. Instead this is a hint that in these cases the “smart money”, which we assume has better estimates of the future price direction, dominates


BUND - future 96.50

94.50

pessimism skewness of calls

optimism skewness of puts

eb Mar Apr May Jun JUI

Figure 4: Skewness-change for options on the German Bund-future as traded on the LIFFE, September 1993 contracts.

the options market and positions itself correctly at turning points. From the put-skewness no deli- nite conclusion can be drawn, since here the changes in the indicator are only very small (the steady decrease in the skewness at the end of the period is due to the normalization procedure). This might be due to the dominance of hedging operations on the short side, which washes out possible signals, accompanied by only a very restricted retail participation in the Bund futures options market. On the other side, due to a lack of more historical data there is only a very limited number of signals, so that no statistically valid conclusion can be drawn. Also the normalization procedure may cause some ambigui- ties, since the fit function was derived by educated guess and not by analytical reasoning.

A third major problem related with the Bund futures options data is that for the analysis of their skewness I used the implied volatility data which was provided by the London International Finan- cial/Futures Exchange (LIFFE). As I was told, these volatilities have partially been corrected by the exchange to eliminate obvious arbitrage opportunities whichresult from incorrect settlement prices. Thus the derived numbers no longer reflect the mood of the traders. A better way to derive

-

the value of the implied volatility is to take an intraday price-snapshot of the options and the underlying (if tick data are available, cf. DAX analysis) or to use the closing bid and ask price of the options as a basis for the calculations (c.f. OEX analysis).

Analysis of DAX Options The same analysis was applied to DAX options

traded on the DTB in Frankfurt (DAX is the Ger- man blue chip stocks index, comparable to the DJIA). The out-of-the-money options were chosen to be 50 points away from the actual price and the implied volatility number was calculated by the same exponential weighted averaging procedure as for the Bund options. Here I calculated the implied volatilities of the options by myself. As price-quotation for the options for which the implied volatility was calculated I took the average of the bid and ask price for these options at 1:30 p.m. and compared it to the quotation of the DAX at 1:30 p.m. (1:30 p.m. corresponds to the end of the open outcry market time, after which computer trading sets in). This was done to remove artificially dis- torted volatility values,

For the DAX options I didn’t observe the runtime


effect visible in the Bund-futures data. This might be due to the fact that the DAX options are Euro- pean style options which can only be exercised at the expiration day or it might result from a different options pricing model used by the LIFFE than the one used by me. As no runtime effect had to be corrected for, I achieved a better signal statistic than for the BUND-futures data. The volatility was calculated from the nearest options series and roll over was done 10 days prior to expiration (the DAX options expire every month). The results can be seen in Figure 5.

One observes a behavior similar to that of the Bund options. Neither the call, nor the put-skewness behaves as would be expected from a typical sentiment indicator, i.e. reaching extremely optimistic values mostly at highs or extremely pessimistic values mostly at lows. Instead the skewness sometimes goes with the trend and sometimes against it. But again, a trend in the skewness opposite to the price trend indicates the future price direction as optimistic readings imply lows and/or price increases and pessimistic readings give a warning of a pending top and/or a retreat of prices. Of special interest in case of the DAX is a comparison of a classical sentiment indicator with the skewness change. To do this I took the open interest corrected call/put ratio (Hines

Ratio), plotted a 10 day EMA of it below the skewness indicators and looked for divergences between these two sentiment indicator groups. Five such occasions can be found in the available data set, labeled A - E. At points A and B the Hines Ratio had a rather optimistic reading and both skewnesses were rather pessimistic. At point A a short correction followed whereas after point B a major decline began (at point B put-skewness turned optimistic rather quickly but was not confirmed by the call-skewness). At points C and D the Hines ratio was rather pessimistic while the skewness was positive. C marked the bottom of the decline and D occurred shortly before a major upleg. At the end of the data series again a divergence built up resulting in 3 month sidewaysidown- ward correction afterwards (not shown in this picture). As in the case with the Bund futures, perhaps this can be explained by a dominance of the market makers in the DAX options market.

Analysis of OEX Options The longest history of options data that was avail-

able for me is for the OEX index options traded on the CBOE, for which I have daily data from 1986 till 1993, sufficient to generate a statistically significant number of signals. The data were analyzed in the

1WOW

E 175ow

CsVpul ratio (Hines ratio)

Figure 5: DAX index, skewness of DAX call-options, put-options and the Hines call/put indicator for the DAX options.

MTA JOURNAL / SUMMER> - FALL 1994 33

une way as described earlier. The price distance ztween the at- and the out-of-the-money options was xed to 10 OEX-points and rollover to the next con- .act month was done 10 days prior to expiration. he implied volatility was calculated based on a nomial model. Like for the DAX options, I didn’t )serve the runtime effect which was visible in the und futures options data.

Two difficulties related to the calculation of the nplied volatility for the OEX options should be men- oned. First, as I only have closing prices for the ptions and the OEX index to calculate the volatility ‘om, and since the OEX trades 15 minutes longer mn the options do, the calculated implied volatility light have an incorrect absolute value if the OEX idex moved strongly in the last 15 minutes of trad- lg. This effect can not be corrected.

The other problem was the fast market around ie 1987 crash. The market dropped so fast so far rat no 10 point out-of-the-money puts and calls were vailable for October 16, 19, and 20, 1987. New op- ons series with lower strike prices are introduced nly on the next trading day so that for these 3 days o implied volatilities could be calculated.

To get a rough idea about how skewness behaves, Ike a look at Figure 6 where, on a weekly chart, the

Figure 6: Weekly chart of the OEX index together with the call-skewness, the inverted put-skewness and the Hines call/ put ratio, calculation as described in the text.

skewness and the Hines call/put ratio are plotted. For the skewness I summed the call-skewness and the inverted put-skewness to amplify the signals. Then a 5-day exponential MA was subtracted from a 20 day exponential MA. At first glance one observes a rather similar behavior of the Hines call/put ratio and the skewness-changes, whereby the skewness signals

OEX index (daily)

-o.moo

Sep

Hines CalVpkd ratio -Qsoo.oo

-875O.W

-QQCS.OO

-10050.00

OU NW 87

Figure 7: Daily chart of the OEX index with together with the call-skewness, the inverted put-skewness and the Hines Ratio, calculated as described in the text.

34 hITA JOURNAL / SUMMER - FALL 1994

(overbought, oversold, divergencies) in general occur thing changed. This can be seen in Figure 8. somewhat earlier than for the Hines ratio. This is As mentioned earlier, no skewness data are avail- what I intuitively expected for all the skewness data. able around crash-day, therefore not too much atten- However, if one examines the skewness change in tion should be paid for that period. After some back- more detail and on a daily basis one finds some re- ing and filling the skewness got into sync with the markable aberrations. market again around 12/87, but this time procyclical,

To start with let’s take a look at the period of i.e. rising optimism with rising prices and vice versa sideways price action in the second half of 1986 for falling prices. This is a classical example of how (Figure 7). Call- and inverted put-skewness-changes an indicator may lose effectiveness over time (in this are plotted together with the Hines Ratio. Call- and case a 180 degree phase shift during a very short time put-skewness act rather similarly and both exhibit a period due to the violence of the crash). pronounced anticyclical behavior, i.e. the call-skew- After the crash both skewness indicators acted ness rises into falling prices, indicating that some- similarly to the Hines Ratio except for a few, but body wants to own out-of-the-money call options very notable, exceptions. In May of 1988 the call skew- eagerly The same conclusion can be drawn from the ness increased during a period of price erosion, inverted put-skewness. Here a falling indicator value indicating that somebody wanted to own out-of- indicates an increase in the volatility of out-of-the- the-money options against falling prices (indicated money puts. The use of the skewness-change as an by the ellipses) and against rising pessimism as overbought/oversold indicator would have yielded extra- indicated by the Hines Ratio (Figure 9). After only ordinary results, whereas the Hines Ratio reacted a few more days a short term rally started. much more slowly and with less volatility and thus The same pattern occurred at the end of the Gulf generated fewer signals together with mostly poorer crisis correction in the summer of 1990 (Figure 9). timing. During the trending market (118743187) which After going synchronous with the market and the followed the trading range time span, the signals were Hines Ratio for several months, the call skewness not as superb as for the shown time period, but still I suddenly increased against falling prices and a sec- very reliable. Then came October, 19,1987, and every- 1 ond pessimism low in the Hines Ratio, marking the

& 320.00

310.00

3w.00 OEX index (weekly) 20000

28O.W

270.00

$$11”$1 dF’~q$ ,P+@ i-r”““-

260.00

pv

b

i”iiisi

25o.w

9

240.w

230.w

call skermev. 22ow

o.wsw

-0 w500

-0.01500

pul skemass (inverled) -0.025w

O.OOOW

Hines CalUpul ratio

ocl NW Dee 88 Feb Mar Ap4 May JUtT JUl AUQ

Figure 8: Weekly chart of the OEX index together with the call-skewness, the inverted put-skewness and the Hines Ratio, calculation as described in the text. Encircled is the area with a divergence between skewness and Hines Ratio.


,320.OO

-9800 w

-9950 00

~10100.00

od NW 91 Feb Mar

Figure 9: Daily chart of the OEX index together with the call-skewness, the inverted put-skewness and the Hines Ratio, calculation as described in the text. Encircled are areas with divergencies between skewness and Hines Ratio.

OEX index (dally)

OEX index (daily)

385.W

3M).Oo

375.00

37000

385.W

call skewness O.OOSW

-0w3w

ooaw

-0.w4w

Hines calUpu1 ralio

Mar Apr sep

Figure 10: Daily chart of the OEX index together with the call-skewness, the inverted put-skewness and the Hines Ratio, calculation as described in the text. Encircled is the area with a divergence between skewness and Hines Ratio.


end of the bear market. During the following bottom building process another divergence to the Hines Ratio occurred, this time in the put skewness-change.

Then, towards year end of 1990 prices rallied with increasing pessimism as expressed by the put-skewness, indicating that someone bought out-of-the- money-puts rather aggressively Again the put buyers found themselves on the correct side of the market as the prices took another nose-dive as the threat of a war in the Middle East increased. And then, again, a divergence between prices of the Hines Ratio and the call-skewness developed, just prior to the explo- sive up-move as the war broke out.

Another more recent example is the October 1992 intermediate term price low (Figure 101, which occurred after some major trendlines had been broken (broadly published) and emotions were rather single- sidedly bearish. Quite a lot of pessimism had built up prior to the final sharp two day break. During this hefty decline the inverted put-skewness increased very quickly indicating that the former bears had sold their puts, thereby dampening the implied volatility of the out-of-the-money puts. Again this marked the end of the decline.

Unfortunately, these divergence patterns occur predominantly during emotionally driven price movements, of which we haven’t had too many during the last two years. Therefore, even though a relatively large amount of data was available for the OEX index, they do not give as many signals as I think would be necessary to define a conclusive trading strategy

compared to other sentiment indicators? I believe the skewness-change provides added value in at least two areas. First, most of the time it reacts faster to changing prices, than for instance the Hines Ratio does, thus generating more signals. Additionally, put/call ratio signals can be filtered on occasions where the skewness shows a significantly different behavior than the other sentiment indicators. At these divergencies, future price direction is better predicted by the skewness. Secondly, in comparison to commitment of traders data, signals in the skewness occur much more often and as they are derived from daily data instead of weekly, allow one to examine the market with better resolution. The best results -though they occur only infrequently and can at the time being only be derived for the American markets (there are no COT data for other countries) - are achieved by combining the put/call ratio and the COT data with the skewness-change by looking for divergencies between the skewness-change and the put/call ratio which are confirmed by a corresponding signal in the COT oscillator in favor of the skewness.

The advantage of the skewness-change indicator compared to other indicators is that it is made of easily accessible data (this is not true for the historical data and the testing) and that is has only very few free parameters (on which it doesn’t depend heavily). In comparison to sentiment indicators based on bullish/bearish advisory figures, the skewness is not biased by the poll taker but consists only of data. On the negative side is the fact that historical testing is rather computer-time intensive and requires an enor-

Conclusion and Outlook mous effort on part of the data handling procedure. Two major conclusions can be drawn from my The general idea is that a divergence between the

research. skewness-change and the call/put ratios should give 1. NEVER in the financial area believe anything an early warning signal to look at the market in more

until you have tested it thoroughly by yourself While detail. The fact that during divergencies between the I found some rather interesting results-as I believe classical put/call ratio (which is assumed to be influ- -they are in part diametrically opposed to what I enced the most by the uninformed public) and the expected to find based on my previous experiences. skewness, the latter is better suited to predict future My gut feeling was that with rising prices skewness price direction, indicates that at times a group of rises as well, indicating optimism on the side of the investors in the options market has a better estimate small investors. For the German DAX and Bund fu- of coming price direction (the so called “smart tures market this is not true, but these markets money”). This is unique advantage of the skewness- appear to be dominated most of the time by anticyc- change against the other sentiment indicators which lical investors who influence the options premiums do not allow to distinguish between different inves- such that they override the prevailing mood. The OEX tor groups. index is a different game and behaves as I expected, Interestingly, those periods of divergencies some- but sometimes anomalies occur there which can be times coincide with strong buy signals from the com- attributed to anticyclical traders. This dissimilar mitment of traders data and the COT index (BRI), behavior of the markets may be attributed to the respectively This is true for September 1986, May fact that the American options market is a rather 1988, Summer 1990 and October 1992. The COT buy old one compared to the German market and has signals are generated by large commercials who, even a much larger retail participation resulting in a if they don’t have superior knowledge, at least have higher efficiency. superior ammunition to turn markets and generate

2. “Where is the beef” with the skewness-change trends. This coincidence of signals is another hint


that on certain occasions “smart money” dominates the options market and subsequently the underlying trends too.

There are a lot of refinements which could/should be applied to the indicators shown. Just to name a few: It would be desirable to determine the length of the “normalization” window, which was set to 20 days in this analysis rather arbitrarily, as a function of the prevailing volatility, to avoid jittery signals during high volatility periods. The same holds true for the distance between the at-the-money options to the out-of-the money options, which for the sake of more sensitive should be chosen to be volatility dependent, too. In addition to measuring changes in the slope of the skewness-changes, variations in the shape of the skewness distributions should also yield information about the prevailing mood of the options players. These are only some ideas, anybody with additional suggestions is invited to follow the path of my investigation. I am always willing to share my ideas with everybody, since according to my understanding the only holy grail in the markets is to accept that there is no holy grail.

REFERENCES

1. Martin Zweig, Winning on Wall Street, Warner Books, New York, 1986.

2. Robert F? Krause, The Volatility Handbook, 2nd edition, R.P Krause, PO. Box 873, Chicago, IL 60690, 1992.

3. Sheldon Natenberg, Option Volatility and Pricing Strategies, Probus Publishing Company, Chicago, 1988.

4. SM. Turnbull, L.M. Wakeman, ‘A Quick Algorithm for Pricing European Average Options,” Journal ofFinancial and Quantitative Analysis, September 1991, pp. 377-389.

BIBLIOGRAPHY

Briese, Stephen E., “Commitment of Traders as a Sentiment Indicator”, Technical Anal.ysis of Stocks & Commodities, May 1990.

Hines, Ray, “Hines Ratio”, Technical Analysis of Stocks & Commodities, April 1989.

Martin, James F!, “On Composite Sentiment”, Technical Analysis of Stocks & Commodities, April 1992.

Martin, James l?, “Updating Option Ratios with Market Sentiment”, Technical Analysis of Stocks & Commodities, February 1991.

Martin, James F?, “Options Ratios for Sentiment”, Technical Analysis of Stocks & Commodities, June 1990.

Merrill, Arthur A., C.M.T., “Customer Option Activity”, Technical Analysis of Stocks & Commodities, December 1990.

Peters, Edgar E., Chaos and Order in the Capital Markets, John Wiley & Sons, Inc., New York, 1991.

Prechter, Robert R. and Allman, David A., “Put-call Sentiment Indicator”, Technical Analysis of Stocks & Commodities, January 1990.

Sterge, Andrew, “Volatility Skews”, Technical Analysis ofstocks & Commodities, February 1990.

Yates, Jim, “The World’s Greatest Technical Stock Market Indicator”, The Market Technicians Association’s Monthly Meeting, December 1991.

ACKNOWLEDGEMENTS

Thank you to:

Mr. Jan Dubois, Hamburg Mannheimer Versicherungs AG, for the programming involved in this paper.

Mr. Georgios Koliopoulos, Deutsche Bank-Frankfurt, for providing data for the pricing of DAX options.

Mr. Alfred Moeckel, Morgan Stanley-Frankfurt, for the assistance in pricing the OEX options.

Dr. Dieter Rentsch, Hamburg Mannheimer Versicherungs AG, for his help in the mathematics required for this project,

Mr. Jack Staufer, Commodity Systems Inc., for their generosity in providing the historical data for the OEX options.

C. Lund is Vice President at Hamburg-Mannheimer ’ Insurance Company, Hamburg, the second largest life insurance company in Germany. He is head of the asset allocation & research department. His responsibilities include the development, testing and evaluation of tn- / vestment strategies for the strategic and tactical asset allocation. One of his main research topics has been the

/

development of new sentiment indicators derived from the options market. The skew based sentiment indicator is only one of several indicators that has been developed

I

in the last couple ofyears.

38 MTA JOURNAL/SUMMER-FALL1994

Engulfing Patterns: Winning the Battle with Western Point and Figure and Eastern Candlesticks by Dodge 0. Dorland

Introduction Japanese candlestick charting techniques have only recently been added as a weapon for Western technical analysts to use on the investment battleground, where the bulls and bears are constantly fighting to achieve superior performance. However, as Steve Nison pointed out in the first definitive work in the United States on this discipline,’ candles have existed since the mid-1700s, when they were first used for rice trading in Japan, and are used extensively for many foreign exchange and commodities markets throughout the world.2

Steve Nison’s work and most of the existing Western literature to date covering candles focus on the use of candles for non-equity markets. How- ever, I have been using candles for equities since 1991 and find they have improved my investment performance, particularly with regard to the timing of my trades.

My research to date has evaluated whether or not candlestick analysis provides an invaluable tool which supplements traditional Western technical weaponry and improves performance on the investment battlefield. As part of my ongoing research, this paper focuses on one candlestick pattern, the Engulfing Pattern (Tsutsumi) and tests whether or not, and how, it improves investment performance when used with traditional disciplines such as point and figure analysis, moving average convergence/divergence (“MACD”), relative strength, and stochastics.

Japanese Candles While using the same opening-high-low-closing

price data as bar charts, Japanese candlesticks provide a more vibrant, graphical presentation which lights up the investment battlefield with signals not given by bar charts.

In order to create candles, the bar created for bar charts is broadened between the opening and closing price to give that range a rectangular shape or “real body”. Activity outside the open-close body is depicted the same as for a bar chart (a straight line) and is referred to as the “shadow” of the candle.

The color of the body is determined by the direction of the trading. Figure 1 is a comparison of the same price data reflected in a bar chart and candle pattern. If, as in Example A, the closing price is higher than the opening price, the activity is positive and the body remains white.3 If, as in Example B, the closing price is lower than the opening price, the activity is negative and the body is black.

Example A Example B

&h Wh

ClOS Open

Open u II

ClOS.¶

LOW LOW

Figure 1: Comparison of Bar Chart and

Method To determine the validity of my hypothesis, I ana-

Candle Pattern Using Identical Data

lyzed equities trading on the New York Stock Exchange Candlestick analysis was developed in Japan (NYSE), American Stock Exchange (AMEX), and the in the combative environment of 1500-1750,4 a time over-the-counter market (NASDAQ). I selected peri- which reflected many similar characteristics of the ods involving bull markets, bear markets, and trendless investment environment throughout the ages. Just markets. I analyzed different timeframes via intraday, ask any portfolio manager, trader, or individual in- daily, weekly and monthly charts. I used the analysis vestor how he or she feels about the conditions of the stock’s trend and relative strength to determine under which he or she makes investment decisions the timing of the candle signal and whether it was sup- today! ported (or at least not in contravention to) the other Understanding the psychology behind specific technical disciplines. I finally reviewed the actual price candle patterns and how the pattern reflects the cur- performance after the signal was given. rent environment is critical to the analyst’s ability


to identify the pattern and interpret its emotional and technical significance accurately. For example, the engulfing pattern reflects a significant reversal in battle psychology between the bulls and bears and, consequently, can prove to be a meaningful early pre- cursor to a reversal in trend.

The Engulfing Pattern

A. Formation

As shown in Figure 2, the engulfing pattern com- prises two candles and reflects trading activity over two periods. The first candle reflects the previous trend (a white candle in an uptrend or a black candle in a downtrend). The second candle engulfs the first candle completely and is the opposite color of the first candle.

Bullish Bearish I

10 Figure 2: Engulfing Pattern

B. Criteria for the Engulfing Pattern

Steve Nison has described the three criteria for a valid engulfing patterns:

1. “The market has to be in a clearly definable uptrend or downtrend, even if the trend is short term.”

In addition to up trends and down trends, the market can trend sideways. Markets trending sideways represent an above average opportunity for engulfing patterns to provide an early warning signal that a trend reversal is about to occur and the direction of the change.

2. “The second real body of the pattern must engulf the prior real body (it need not engulf the shadows).”

3. “The second real body of the engulfing pattern should be the opposite color of the first real body. The exception to this rule is if the first real body of the engulfing pattern is so small it is almost a doji (opening and closing prices are the same.). Thus, after an extended downtrend, a tiny white real body engulfed by a very large white real body could be a bottom reversal. And in an uptrend, a minute black real body enveloped by a very large black real body could be a bearish reversal pattern.

C. The Psychology Reflected in the Pattern

As with most Japanese candlestick patterns, the

psychology reflected in the engulfing pattern can be explained in terms of the ongoing battle between bulls and bears. On the first day of the pattern, the army that has been previously winning (the army of the bulls if the trend is up and the army of the bears if the trend is down) continues its march forward. Typically, the body of the candle of the first day is relatively small and may reflect the progress of an army that is somewhat tired from its previous advances. At the beginning of the second day, this army starts the day with its continued advance. During the second day, however, the psychology of the battle shifts significantly. The army that has been retreating gathers its strength, charges forward, and pushes the previously advancing army back to a worse position than at the beginning of the previous day.

Thus, at the end of the second day, the previously retreating army is advancing and has adopted an aggressive attitude, having taken back all the ground it had lost the previous day. The newly advancing army has turned its enemy back in a blaze of glory, sending a signal of strength, that analysts watching the battle may not yet see when using Western tools of technical analysis, to assess this battle between bulls and bears.

Using The Engulfing Pattern With Point And Figure And Other Technical Analysis

There is a rather unique fit between Japanese candles and point and figure analysis. While Japa- nese candles light the investment battleground and signal entry and exit points, they do not project price objectives for the army to obtain. And while point and figure analysis locates natural areas of support and resistance on the battlefield and determines price targets, it does not tell the army when best to enter the battle.

As with any single weapon, neither candlestick nor point and figure analysis represent an invincible weapon. However, when the two weapons are used together, they increase an army’s chance for investment victory

One example of how Japanese candles can work with point and figure analysis and complement other Western tools can be seen with Federal National Mortgage Association (FNM), a New York Stock Exchange listed equity. The following charts are provided to better assess the technical battlefield for the decisions analyzed: Figure 3 - Point and Figure Chart - one point reversal; Figure 4 - Point and Figure Chart-three point reversal; Figure 5 - Monthly High-Low-Closing Price Activity from 1980. For the daily price activity between 10/25/91 and 2/14/92 see: Figure 6 - Daily Candlestick Chart; Figure 7 - Daily Stochastics;

‘it) MTA JOURNAL / SUMMER - FALL 1994

‘Fcdctal Nalional Mlg (rwy

Figure 3: Federal National Mortgage Association Point and Figure Chart-one point reversal

Source: Market Charts Inc.

Figure 4: Federal National Mortgage Association Point and Figure Chart-three Source: Market Charts Inc.

point reversal

‘igure 8 - Moving Average Convergence/Diver- ‘ence; Figure 9 - Historical (14 Day) Relative Strength.

The long term “campaign” of the bulls vs. the ears, seen in Figure 5, reflects the ascent of the ulls dating back to 1981, which from time to time .as experienced pullbacks to up trendlines. Hav- ng exceeded $65 in 1991, FNM then proceeded to etreat in a downtrend, as defined in a one point eversal chart (Figure 31, until it again found sup- Nort above 55. FNM then traded between 55 and 8, with the bulls attempting a new attack but nable to overcome the bears. Which way will the attle turn?

Decision Point 1: November 29-30, 1991

FNM trades sideways for two weeks, between November 15 and November 29. At the end of this period, a bullish engulfing pattern indicates the previous sideways trend is about to reverse to the upside, a signal which is supported by a second, smaller bullish engulfing pattern completed on December 6. A buy was triggered at the open on December 3 at 57 7/~ (offered price).

At the same time, point and figure analysis would be looking for a breakout to the upside, which occurred the following Monday when FNM traded at 59. FNM having broken out, FNMA’s one point


Figure 5:

Federal

National

Mortgage

Association

Source:

Long Term

Values

reversal chart would establish a price objective of 65. In this case, the engulfing pattern would send

the investment decision forward at 577/a but would not have given a price objective. Point and figure would have given a buy signal at 59, where FNM broke out of its previous consolidation pattern as well traded above its previous down trendline, with a price target of 65 (see Figure 3). Together, the army of the bulls would have entered the battle at 577/~ and remained on the field until 65 for a return of 12.08% (before commissions) in four weeks. Most important, the risk of the trade was 2 ‘1s points, for a reward/risk ratio of 2.43 to 1. This risk/reward ratio may or may not be high enough for army generals to order the bullish charge when using one technical tool. How- ever, the generals would find a confluence of support- ing technical weapons occurring at the same time or shortly thereafter.

MACD confirmed a change in trend over the days immediately following the engulfing pattern as the solid line crossed the dotted line from below.

The relative strength indicator (as defined by Bloomberg Financial MarketQ), supports FNM’s increasing strength but does not give a clear signal as it is not low enough to indicate an oversold condition nor high enough to indicate an overbought condition.

Stochastics, at the point of the bullish engulfing pattern, are hovering just above the oversold zone

and give a buy signal (depending on the interpretation of stochastics) shortly after the bullish engulfing pattern.

Decision Point 2: January 8-9, 1992

Having reached 67 on December 26, 1991, FNM continued to fight its way to 70, reaching it on Janu- ary 7,1992. At this point, the advancing army of bulls fails to make further progress. Fatigue has set in after a 15 point (27%) advance in six weeks. On January 8, the bulls move FNM from 69 ‘14 to 71 Ya but settle for an advance to 70 l/4. On January 9, the bulls continue the advance with an opening charge to 70 l/z (the open and high for the day), lose ground to 68 31~ and fight back to 69. The bulls, however, lost all the ground on the 9th that they had won on the 8th and then some. The army of bears, having finally turned back the bulls, are ready to take over.

At the same time, point and figure analysis would have had an insufficient area of congestion to enable a decision. However, once FNM broke below 68, point and figure could have targeted 65 as an objective.

In this case, the bearish engulfing pattern would send the investment decision forward with a short at 68 7l~ but could not have established a price target. Point and figure would not have given an investment signal but would have set a price objective of 65 after the breakdown. This price target was achieved five

d!i? MTA JOURNAL / SUMMER - FALL 1994

PRICE GRAPH for FNM US ZB RANGE m TO

MOVING AVE PERIODS PERIOD 0 (D-W-M-Q-Y) BAR/CANDLE CHART 1 (B-C)

VOL (V-N) VOL MAVE B PERIODS

!Ei$!c;;i;;;;;; [ -...; -..- .iI ; < . . . . , . . . . ., . . . . . ,. . . . . ,. . . . . ( . . . . . ; ?O!~rr+9.~K!+;~.. . . .;.. . . j... ..$ : : P

II I t :. . . . i.. . . :. . . . -1.. I 1 +oi,p in g+ r-b . . . .

. . .m: : r : : :1

. . . . . . 11

lwu 6 15 22 29 WEC 13 20 27 3JAH92 10 17 24 31 7FEB 14

Figure 6: Federal National Mortgage Association Candlestick Chart of Daily Activity 10125191-2114192 Source: Bloomberg

T%?OTDi

STOCHASTICS for FNM US s PERIOD 0 (D-W-M-Q-Y) %K/%D CHART’B Slowed %D CHART

%D q %D-Slow G!DS) E] Smoothed %D-Slow (%DS-Slow)

. . . . . 1 . . ‘- ’ ‘I . . . . . . . . . . . . . . . . . . . . . . . . 1; 1 : I : t:I

: . . . . . . . . . . . . . . . . . . . +..+#&~Jd’ . ’ -l-r1 -‘(A ’ . :r-. . ,

2SOCTSl 1WJ 15 22 I291 6oEc 13 20 17 24 3 7FEB 14

Figure 7: Federal National Mortgage Association Stochastics Analysis: 10125191-2114192 Source: Bloomberg

MTA JOURNAL / SUMMER FALL 1994 43

days later for a 5.63% return. The reward/risk ratio was 3.44 to 1.

MACD confirmed the sell signal four days later. Relative strength showed a reduction in strength

but gave no signal. Stochastics confirmed the sell signal either

simultaneously or shortly after the bearish engulfing pattern, depending on how this indicator is used.

Decision Point 3: February 3-4, 1992

On February 3, after four days of the bears beating back the bulls on the battlefield, the bears lose ground. Starting at 647/~, the bears tight the bulls down to 635/a but are moved back to 643/8. On February 4, happy with having fought the bears back the previous day, the bulls retreat at the open to 64, but fight the bears with renewed vigor back to 65 3l4, and rest at the end of the day at 653l~, having re- gained all the price territory lost the previous day

In this case, the bullish engulfing pattern would send the investment decision to buy which, if acted on in isolation, would have been executed on Janu- ary 5 at 653/~. There was no follow-through, and in this case the “reversal” in trend was from down to sideways and not to up. The bullish army would not have gained ground and ultimately would have lost ground if its general had made a tactical move based

on the strength of one weapon alone. But:

Point and figure had insufficient data to develop a strategy

MACD issued no signal.

Relative strength issued no signal.

Stochastics issued no signal.

Alone, Japanese candles would not have won a victory; the army of the bulls gained no ground and ultimately was forced to retreat. However, Western technical analysis saved the infantry from entering the battle, a testament to how the East and West can work together for their mutual benefit.

When Japanese Candles Do Not Work Well With Equities

1. Japanese candles do not work as successfully alone as when their signals are confirmed by other technical disciplines. A confluence of technical indi- caters becomes particularly important when the signals by candles illuminate a move contrary to the existing trend.

2. Candles do not give price objectives or targets, but candles and point and figure analysis together can provide entry and exit strategies.

3. The validity of engulfing patterns needs to be more carefully assessed with NASDAQ stocks. A wide spread between the bid and the offered price

“-9-%g$~2ti~rY~d~&~~~~~ si 19~19~~’ 226-m ’

Figure 8: Federal National Mortgage Association MACD Analysis: 10125191-2114192 Source: Bloomberg


HISTORICAL PRICE RSI FNM US S

El DfiY k~L~fl’f/~ Sm EXCHANGE COMPOSITE

RSI P P=PRICE OR Y=YIELD MARKET n (T=TRADE, B=BID. A=ASK)

Figure 9: Federal National Mortgage Association Historical Relative Strength: 10129191-2114192

.Source: Bloomberg

In one day can create an engulfing pattern relative o the previous day if the previous day has a narrower pread or traded within a relatively narrow range. in engulfing pattern under these circumstances ends to be subject to greater “whipsaw” trading lerformance.

In general, I have found trading NASDAQ equi- ies with candles has a significantly higher risk- eward ratio than trading NYSE stocks, due in part o illiquidity and volatility factors. One must be uepared for the attendant circumstances of the espective markets.

4. In order to create Japanese candlesticks, one ias to wait for the close of a session before being able o draw a candle. A simple solution to this specific broblem is to use intraday candles. However, intraday andles raise new concerns.

5. For intraday candles the period to be used for he drawing of the candle will vary with each equity md market each equity trades in. I have found lo- ninute candles to afford a good starting place for flSE-traded equities with good liquidity and rea- ionable volatility If too many dojis or no candles at 111 are created (as can be the case for NASDAQ stocks vith high illiquidity), 30-minute candles when ana- yzed over two or more days give successful signals vhen combined with Western technical analysis.

6. As seen in one of the three examples, the engulfing pattern may signal either a loss of drive or momentum of the prior trend or a reversal in trend to neutral.

Conclusion Japanese candles light the investment battle-

field and, when supported by additional weaponry from Western technical analysis, assist investment warriors in achieving performance success. The bullish and bearish Engulfing Pattern can provide an early signal and improve investment performance when used with point and figure and other technical tools such as MACD, relative strength, and stochastics.

When not confirmed or supported by Western technical analysis, however, Japanese candles may give signals which are misinterpreted or should not be acted upon.

Federal National Mortgage Association, a stock trading on the New York Stock Exchange, provided three examples of how Japanese candles can work with Western technical analysis in late 1991-early 1992. At Decision Point 1, a bullish engulfing pattern signaled a reversal in trend from sideways to up. At Decision Point 2, the bearish engulfing pattern signaled a reversal in trend from sideways to down. At Decision


Point 3, a bullish engulfing pattern signaled a reversal in trend from down to sideways.

Given the relatively recent entry of Japanese candlestick analysis to U.S. markets, much research needs to be done to integrate this centuries-old analysis with tools the West is more familiar. The success of candles in many other markets, over several centuries, increases the probability that this research will find numerous ways to integrate the technical analysis of the East with that of the West

Candles do light a path on the investment battlefield, but investment warriors need additional weaponry to cross it successfully.

FOOTNOTES

1. Nison, Steve, Japanese Candlestick Charting Techniques: A Contemporary Guide To The Ancient Investment Techniques Of The Far East, New York, New York Institute of Finance, 1991.

2. Steve Nison pointed out in Barron’s (8/23/93): “To illustrate the importance of the candles to the Japanese, the following is a segment from a European magazine EuroLoeek. That article quotes an English trader who works at a Japanese bank. He states that ‘all of the Japanese traders here-and that’s in the foreign exchange, futures and equity markets use the candles. It might be difficult to work out the billions of dollars traded in London on interpretations of these charts each day, but the number would be significant.’ ”

3. The Japanese have used the color red for positive bodies. Red cannot be differentiated from the color black in monocolor photo copies and, therefore, positive bodies are white.

4. During this time, two major transitions occurred. First, hundreds of local fiefdoms fought for control of their neighbors, with the final result being one unified country. Second, Japan’s agrarian society took advantage of the first transition to move from a system of local markets which operated independently to a centralized market. For a more detailed description, read Chapter 2 of Nison’s book.

5. Nison, ibid., pp.3839.

6. “RSI determines...overbought or oversold conditions by identifying the percentage of days it closed higher than the day before. An RSI value above 75 indicates an overbought condition. Avalue below 25 indicates an oversold condition.” “Stars to Steer by in Your Technical Analysis”, Bloomberg, March, 1994.

BIBLIOGRAPHY

Bloomberg, LP, 499 Park Avenue, New York, N.Y. 10022 (provider of charts as indicated).

Long Term Values Charting Service, Los Angeles, Ca., Daily Graphs, Inc.

Market Charts, Inc., Quarterly Long Term (20 x 3 Hourly) and Semi-Monthly (20 x 1 Hourly), New York City, 1994.

Murphy, John J., Technical Analysis of the Futures Markets: a Comprehensive Guide To Trading Methods and Applications, New York, New York Institute of Finance, 1986.

Nison, Steve, Japanese Candlestick Charting Techniques: a Contemporary Guide to the Ancient Investment Techniques of the Fur East, New York, New York Institute of Finance, 1991.

Shaw, Alan R., “Market Timingand Technical Analysis”, Financial Analysts Handbook. seconded., chap. 11, Homewood, Ill., Dow Jones-Irwin, Inc., 1988.

“Stars to Steer by in Your Technical Analysis,” Bloomberg, March, 1994.

Wagner, Gary S. and Matheny, Bradley L., “Candlestick and Intraday Market Analysis”, Technical Analysys of Stocks and Commodities: April, 1993.

Wagner, Gary S. and Matheny, Bradley L., Trading Applications of Japanese Candlestick Charting, New York, John Wiley & Sons, Inc., 1994.

Dodge 0. Dorland is a Registered Investment Advisor and Chief Investment Officer for LANDOR Investment Management, Inc. He is a Board member of the Market Technicians Association and has been instrumental in expanding its CMT program. His prior experience includes extensive investment and commercial banking, focusing on the Media, Communications, and Entertain- ment industries. He received his MBA in Corporate

/ F’ inance from New York University.


Anatomy of a Trading Range by Jim Forte

In the following article I will discuss the analysis of a Trading Range, employing terms and principles developed by Richard Wyckoff in the 1920s and 30s and more recently by the “Stock Market Institute”. In technical analysis, there are a variety of methods used to analyze trading range formations and forecast the expected direction and extent of the move out of a trading range. Most practitioners of technical analysis, whether familiar with the Wyckoff method or not, will be able to relate many of the points and principles being discussed to those they are already familiar with.

Much of Wyckoff’s analysis and working principles were based on what he identified as three fundamental laws:

1. The Law of Supply and Demand-which simply states that when demand is greater than supply, prices will rise and when supply is greater than demand, prices will fall.

2. The Law of Cause and Effect-postulates that in order to have an effect you must first have a cause, and that effect will be in proportion to the cause. This law’s operation can be seen working, as the force of accumulation or distribution within a trading range works itself out in the subsequent move out of that trading range. Point and figure chart counts can be used to measure this cause and project the extent of its effect.

3. The Law ofEffort vs. Result-helps us evaluate the relative dominance of supply vs demand, through the divergence or disharmony between volume and price, when considering relative strength, comparative price progress and trading volume.

An objective of Wyckoff analysis is to aid in establishing a speculative position in correct an- ticipation of a coming move where a favorable reward/risk ratio exits (at least 3 to 1) to justify taking that position. Trading Ranges (TR’s) are places where the previous move has been halted and there is relative equilibrium between supply and demand. It is here within the TR that dominant and better informed interests conduct campaigns of accumulation or distribution in preparation for the coming move. It is this force of accumulation or

distribution that can be said to build a cause which unfolds in the subsequent move.

Because of this building of force or cause, and because the price action is well defined, trading ranges represent special situations that offer trading opportunities with potentially very favorable reward/risk parameters. To be successful however, we must be able to correctly anticipate the direction and magnitude of the coming move out of the trading range. Fortunately, Wyckoff offers us some guidelines and models by which we can examine a trading range.

A preview of the guidelines and model schemat- its presented here, along with the accompanying explanation of the terms and principles represented in the schematics, will go a long way to further the reader’s understanding of the text.

It is through the identification and analysis of the price and volume action and certain principles in action within the various phases of the trading range (TR) that the trader can become aware and conclude that supply or demand is becoming dominant and correctly anticipate the coming move. It is through the analysis of the phases of the TR that we can distinguish accumulation/reaccumulation from distribution/redistribution.

The Wyckoff method employs bar charts along with certain terms and principles in action to determine the expected direction and timing of a coming move. It also employs point and figure chart counts to aid in projecting the extent of the move.

For those interested in exploring the use of point and figure charts, references are available from the Wyckoff “Stock Market Institute” (SMI) and from other sources on technical analysis. Our emphasis here will be primarily on the analysis of bar chart formations.

The following illustrations represent an idealized Wyckoff model of market cycles involving supply and demand, accumulation and distribution, and a conception of the primary market phases.

Accumulation Schematic 1 is a basic Wyckoff model for accu-

mulation. While this basic model does not offer us a

MTA JOURNAL I SUMMER - FALL 1994 47

Idealized Cycle Conception of Primary Market Phases

DISTRIOUnON AIICA DISTRIBUTION

DISTRIBUTION

ACCUMUUTIDN A”tA

CAUSED BY GRCCD ACClJMU!mATION

PRICE UYL

CAUSED I” FEAR

Accumulation: The cstabushment of an lnvcstment or speculative posltlon by professIonal tntcrests ln antklpatlon of an advance In price.

Markup: A sustained upward pdcc movement.

Dlstributlon: the cllrnlnatlon of a long lnvcstment or spcculaUvc posltlon.

Markdown: A sustaIned downward prlcc movement.

schematic for all the possible variations in the anatomy of the TR, it does provide us a representa- tion of the important Wyckoff principles, often evident in an area of accumulation, and the identifiable phases used to guide our analysis through the TR toward our taking of a speculative position.

Phase A In Phase A, supply has been dominant and it

appears that finally the exhaustion of supply is becoming evident. This is illustrated in Prelimi- nary Support (PS) and the Selling Climax (SC) where widening spread often climaxes and where heavy volume or panicky selling by the public is being absorbed by larger professional interests. Once exhausted an Automatic Rally (AR) ensues and then a Secondary Test (ST) of the selling climax. This Secondary Test usually involves less selling than on the SC and with a narrowing of spread and decreased volume. The lows of the Sell- ing Climax (SC) and the Secondary Test, and the high of the Automatic Rally (AR) initially set the

boundaries of the trading range. Horizontal lines may be drawn here to help us focus our attention on market behavior in and around these areas.

It is also possible that Phase A can end without dramatic spread and volume, however it is usually better if it does, in that more dramatic selling will generally clear out all the sellers and clear the way for a more pronounced and sustained markup.

Where a TR represents Reaccumulation (a trading range within a continuing upmove), we will not have evidence of PS, a SC, and ST as illustrated in phase A of Schematic 1. Phase A will instead look more like Phase A of the basic Wyckoff distribution schematic (Schematic 2 or 3); but none the less, Phase A still represents the area of the stopping of the pre- uious moue. The analysis of Phase B through E would proceed the same as is generally advised within an initial base area of accumulation.

Phase B In Phase B, Supply and Demand on a major basis

are in equilibrium and there is no decisive trend. The L

48 hTTA JOURNAL / S-R - FALL 1994

Accumulation Schematic Phases A through E: Phases through which the Trading

Range passes as conceptualized by the Wyckoff method and ex-

plained in the text. Lines A and B...defme support of the Trading Range. Lines C and D.. .defme resistance of the Trading Range.

(PS) Preliminary Support is where substantial buying begins to provide pronounced support after a prolonged downmove.

Volume and spread widen and provide a signal that the downmove may be approaching its end.

(SC) Selling Climax...the point at which widening spread

and selling pressure usually climaxes and heavy or panicky selling by the public is being absorbed by larger professional interests at prices near a bottom.

(AR)Automatic Rally.. .sellingpressure has been pretty much exhausted. A wave of buying can now easily push up prices which is further fueled by short covering. The high of this rally will help

define the top of the trading range. (STsj Secondary Test(s). .revisit the area of the Selling Cli-

max to test the supply demand balance at these price levels. If a

bottom is to be confirmed, significant supply should not resur- face, and volume and price spread should be significantly dimin-

ished as the market approaches support in the area of the SC. The “CREEK” is an analogy to a wavy line of resistance

drawn loosely across rally peaks within the trading range. There

are of course minor lines of resistance and more significant ones

that will have to be crossed before the market’s journey can continue onward and upward.

Springs or Shakeouts usually occur late within the trading

range and allow the market and its dominant players to make a definitive test of available supply before a markup campaign will

unfold. If the amount of supply that surfaces on a break of support is very light (low volume), it will be an indication that the way is clear for a sustained advance. Heavy supply here will usu-

ally mean a renewed decline. Moderate volume here may mean more testing of support and to proceed with caution. The spring or shakeout also serves the purpose of providing dominant inter-

ests with additional supply from weak holders at low prices. Jump Across the Creek @AC) is a continuation of the creek

analogy of jumping resistance and is a good sign if done on good

spread and volume-a sign of strength (SOS). Sign of Strength (SOS). an advance on good (increasing)

spread and volume. Back Up (BUj to a Lust Point of Support (LPSj-a pull back to

support (that was resistance) on diminished spread and volume after a SOS. This is good place to initiate long positions or to add

to profitable ones.

Note: A series of SOS’s and LPS’s is good evidence that a bottom is in place and Price Markup has begun.

SCHEMATIC #I D Trading Range C Resistance Lines

B Trading Range A Support Lines


clues to the future course of the market are usually more mixed and elusive, however here are some useful generalizations.

In the early stages of Phase B the price swings tend to be rather wide, and volume is usually greater and more erratic. As the TR unfolds, supply becomes weaker and demand stronger as professionals are absorbing supply The closer you get to the end or to leaving the TR, volume tends to diminish. Support and resistance lines, (shown as horizontal lines A, B, C, and D on the Accumu- lation Schematic 1) usually contain the price action in Phase B and will help define the testing process that is to come in Phase C. The penetrations or lack of penetrations of the TR enable us to judge the quantity and quality of supply and demand.

Phase C In Phase C, the stock goes through a testing

process. The stock may begin to come out of the TR on the upside with higher tops and bottoms or it may go through a downside spring or shakeout, breaking previous supports. This latter test is pre- ferred, given that it does a better job of cleaning out remaining supply from weak holders and creates a false impression as to the direction of the ultimate move. Our Schematic 1 shows us an example of this latter alternative.

Until this testing process, we cannot be sure the TR is accumulation and must wait to take a position until there is sufficient evidence that mark-up is about to begin. If we have waited and followed the unfold- ing TR closely, we have arrived at the point where we can be quite confident of the probable upward move. With supply apparently exhausted and our danger point pinpointed, our likelihood of success is good and our reward/risk ratio favorable.

The shakeout at point 8 on our Schematic 1 represents our first prescribed place to initiate a long position. The secondary test at point 10 is better, since a low volume pullback and a specific low risk stop or danger point at point 8 gives us greater evidence and more confidence to act. A sign of strength (SOS) here will bring us into Phase D.

Phase D If we are correct in our analysis and our tim-

ing, what should follow here is a consistent dominance of demand over supply as evidenced by a pattern of advances (SOS’s) on widening spreads and increasing volume, and reactions (LPS’s) on smaller spreads and diminished volumes. If this pattern does not occur, then we are advised not to add to our position and look to close our original position until we have more conclusive evidence that markup is beginning. If our stock progresses as

stated above, then we have additional opportunities to add to our position.

Our aim here is to initiate a position or add to our position as the stock or commodity is about to leave the trading range. At this point, the force of accumulation has built a good potential and could be projected by using the Wyckoff point and figure method (or perhaps another method of the reader’s own choosing).

We have waited to this point to initiate or add to our positions in an effort to increase our likelihood of success and maximize the use of our trading capital. On our Schematic 1, this opportunity comes at point 12 on the “pullback to support” after “jumping resistance” (in Wyckoff terms this is known as “Back- ing Up to the Edge of the Creek” after “Jumping Across the Creek”). Another similar opportunity comes at point 14, a more important point of support and resistance.

In Phase D, the mark-up phase blossoms as professionals begin to move up the stock. It is here that our best opportunities to add to our position exist, before the stock leaves the TR.

Phase E In Phase E, the stock leaves the TR and demand

is in control. Setbacks are unpronounced and short lived. Having taken our positions, our job here is to monitor the stock’s progress as it works out its force of accumulation. At each of points 8, 10, 12, and 14 we may take positions and use point and figure counts from these points to calculate price projections and help us to determine our reward/risk prior to establishing our speculative position. These projections will also be useful later in helping us target areas for closing or adjusting our position.

Remember our Schematic 1 shows us just one idealized model or anatomy of a trading range encompassing the accumulation process. There are many variations of this accumulation anatomy and we addressed some of these considerations earlier. The presence of a Wyckoff principle like a selling climax (SC) doesn’t confirm that accumulation is occurring in the TR, but it does strengthen the case for it. However, it may be accumulation, redistribution or nothing. The use of Wyckoff principles and phases identifies and defines some of the key considerations for evaluating most any trading range and helps us determine whether supply or demand is becoming dominant and when the stock appears ready to leave the trading range.

Distribution Accompanying our discussion of distribution are

Schematics 2 and 3, two variations of the Wyckoff model for distribution. While these models only represent two variations of the many possible variations

i% MTA JOURNAL / SUMMER - FALL 1994

in the patterns of a distribution TR, they do provide us with the important Wyckoff principles often evident in the area of distribution and thephases SMI uses to guide our analysis through the TR toward taking a speculative position.

Much of this discussion and analysis of the principles and phases of a TR preceding distribution are the inverse of a TR of accumulation, in that the roles of supply and demand are reversed.

Here, the force of “jumping the creek” (resistance) is replaced by the force of “falling through the ice” (support). Given this, I will not repeat all the points made earlier, but rather emphasize those areas where the differences merit discussion and where additional points need to be made or reemphasized. It is useful to remember that distribution is generally accomplished in a shorter time period as compared to accumulation.

Phase A In Phase A, demand has been dominant and the

first significant evidence of demand becoming exhausted comes at point 1 at Preliminary Supply (PSY) and at point 2 at the Buying Climax (BC). (See Schematic 2 and 3.) It often occurs on wide spread and climatic volume. This is usually followed by an Automatic Reaction (AR) and then a Secondary Test (ST) of the BC, usually on diminished volume. This is essentially the inverse of Phase A in accumulation.

As with accumulation, Phase A in distribution may also end without climactic action and simply evidence exhaustion of demand with diminishing spread and volume.

Where Redistribution is concerned (a TR within a larger continuing downmove), we will see the stopping of a downmove with or without climactic action in Phase A. However, in the remainder of the TR the guiding principles and analysis within Phases B through E will be the same as within a TR of a Dis- tribution market top.

Phase B The points to be made here about Phase B are

the same as those made for Phase B within Accumu- lation, except clues may begin to surface here of the supply/demand balance moving toward supply instead of demand.

Phase C One of the ways Phase C reveals itself after the

standoff in Phase B is by the “sign of weakness” (SOW) shown at point 10 on Schematic 2. This SOW is usually accompanied by significantly increased spread and volume to the downside that seems to break the standoff in Phase B. The SOW may or may not fall through the Ice,” but the subsequent rally back to point 11, a

“last point of supply” (LPSY) is usually unconvincing and is likely on less spread and/or volume.

Point 11 on both Distribution Schematics 2 and 3 give us our last opportunity to cover any remaining longs and our first inviting opportunity to take a short position. Even a better place would be on the rally testing point 11, because it may give us more evidence (diminished spread and volume) and/or a more tightly defined danger point.

Looking now at Schematic 3, Phase C may also reveal itself by a pronounced move upward, breaking through the highs of the TR. This is shown at point 11 as an “Upthrust After Distribution” (UTAD). Like the terminal shuke out discussed in accumulation, this gives a false impression of the direction of the market and allows further distribution at high prices to new buyers. It also results in weak holders of short positions surrendering their positions to stronger players just before the downmove begins. Should the move to new high ground be on increasing volume and “relative narrowing spread” and then return to the average level of closes of the TR, this would indicate lack of solid demand and confirm that the breakout to the upside did not indicate a TR of accumulation, but rather a formation of distribution.

A third variation not shown here in schematic form would be an upthrust above the highs of the trading range with a quick fall back into the middle of the TR, but where the TR did not fully represent distribution. In this case, the TR would likely be too wide to fully represent distribution and there would be a lack of concentrated selling except in the latter portions of the TR.

Phase D Phase D, arrives and reveals itself after the tests

in Phase C show us the last gasps or the last hurrah of demand. In Phase D, the evidence of supply becoming dominant increases either with a break through the “ICE” or with a further SOW into the TR after an upthrust.

In Phase D, we are also given more evidence of the probable direction of the market and the opportunity to take our first or additional short positions. Our best opportunities are at points 13,X, and 17 as represented on our Schematics 2 and 3. These rallies represent “Last points of Supply” (LPSY) before a markdown cycle begins. Our “averaging in” of the set of positions taken within Phases C and D as described above represent a calculated approach to protect capital and maximize profit. It is important that additional short positions be added or pyramided only if our initial positions are in profit.

Phase E In Phase E, the stock or commodity leaves the


r PHASES:

-Ad B.->/-C+/--D+i E--+

SCHEMATIC ~72

Distribution Schematics the ICE will likely be followed by attempts to get back above it. A

Schemarics 2 and 3 show us two model variations of a distri- failure to get back above firm support may mean a “drowning” bution Trading Range. for the market.

Phases A through E...phases through which the Trading (LPSY)Last Point ofSupply.. .(Schematic 2iPoint 11): after Range (TR) passes as conceptualized by the Wyckoff method and we test the ICE (support) on a SOW a feeble rally attempt on explained in the text. narrow spread shows us the difficulty the market is having in

(PSY) Preliminary Supply.. .is where substantial selling be- making a further rise. Volume may be light or heavy, showing

gins to provide pronounced resistance after an upmove. Volume weak demand or substantial supply. It is at these LPSY’s that the and spread widen and provide a signal that the upmove may be last waves of distribution are being unloaded before markdown is approaching its end. to begin.

(BC) Buying Climax.. .is the point at which widening spread Schematic a/Point 13: after a break through the ICE, a rally and the force of buying climaxes, and heavy or urgent buying by attempt is thwarted at the ICE’s surface (now resistance). The the public is being filled by larger professional interests at prices rally meets a last wave of supply before markdown ensues.

near a top. LPSY’s are good places to initiate a short position or to add (AR) Automatic Reaction.. .with buying pretty much ex- to already profitable ones.

hausted and heavy supply continuing, an AR follows the BC. The (UTAH) Upthrust After Distribution.. (See Schematic 3 I low of this selloff will help define the bottom of the Trading Range Point 11). Similar to the Spring and Terminal Shaheout in the

(TR). trading range of Accumulation, a UTAD may occur in a TR of (ST) Secondary Test(s). .revisit the area of the Buying Cli- distribution. It is a more definitive test of new demand after a

max to test the demand/supply balance at these price levels. If a breakout above the resistance line of the TR, and usually occurs

top is to be confirmed, supply will outweigh demand and volume in the latter stages of the TR. and spread should be diminished as the market approaches the If this breakout occurs on light volume with no follow through resistance area of the BC. or on heavy volume with a breakdown back into the center of the

(SOW) Sign of Weakness. .at point 10 will usually occur on trading range, then this is more evidence that the TR was Distri- increased spread and volume as compared to the rally to point 9. bution not Accumulation.

Supply is showing dominance. Our first “fall on the ICE” holds This UTAD usually results in weak holders of short posi-

and we get up try to forge ahead. tions giving them up to more dominant interests, and also in more

The ZCE...is an analogy to a wavy line of support drawn distribution to new, less informed buyers before a significant de- loosely under reaction lows of the Trading Range A break through cline ensues.


SCHEMATIC #3

TR and supply is in control. Rallies are usually feeble. Having taken our positions, our job here is to monitor the stock’s progress as it works out it’s force of distribution.

Successful understanding and analysis of a trading range enables traders to identify special trading opportunities with potentially very favorable reward/risk parameters. When analyzing a TR, we are first seeking to uncover what the law of supply and demand is revealing to us. However, when individual movements, rallies or reactions are not revealing with respect to supply and demand, it is important to remember the law of “effort uersus result”. By comparing rallies and reactions within the trading range to each other in terms of spread, volume, velocity and price, additional clues may be given as to the stock’s strength, position and probable course.

It will also be useful to employ the law of “cause and effect”. Within the dynamics of a TR, the force of accumulation or distribution gives us the cause and the potential opportunity for substantial trading profits. It will also give us the ability, with the use of point and figure charts, to project the extent of the even- tual move out of the TR and help us to determine if those trading opportunities favorably meet or exceed our reward/risk parameters.

Real World Examples In addition to the model schematics provided

here, some empirical examples of real world trading ranges are also presented (see pages 54-581, where Accumulation/Reaccumulation preceded a Markup, and Distribution preceeded a Markdown. While these empirical examples may not fit the idealized schematics exactly, I have identified and annotated on each of the chart examples, the Wyckoff principles in action and the five Wyckoff phases of a trading range.

BIBLIOGRAPHY

Hutson, J., Weis, D., and Schroeder, C., “Charting the Market, The Wyckoff Method”, Technical Analysis ofstocks and Com- modities, Seattle, 1990.

Pruden, H.O. and Fraser, B., “The Wyckoff Seminars”, Golden Gate University, San Francisco, Fall 1992 and Spring 1993.

Wyckoff/StockMarket Institute, literature, illustrations, and audio tapes. 13601 N. 19thAvenue, Suite 1, Phoenix, Arizona 85029. Tel: 602-942-5581 Fax: 602-942-5165.

Charts supplied by “Telescan 3.0”, Houston, Texas.

Jim Forte has been using Technical Analysis profession- ally andpersonally in both stocks and commodities since 1986. He is currently employed in the research services department of a major brokerage firm where he main- tains a market update service. He studres and teaches Technical Analysis at Golden Gate University in San Francisco and also offers seminars. He is aprofesslonal member of IFTA and the TSAA of San Francisco.


Long Term Accumulation

Phase A: Shows us the PS & SC with the exhaustion of supply as the steep downtrend ia ending.

The The AR & ST set the appmximate boundried of the TR to follow. Phase B: In the early stage, we (~bc a wide swing & higher vol, and tic first signs of demand asserting ita dominance, as

pmfcssionals are absorbing supply. Late in Phase B. low vol shows supply has dwindled at the TR lows.

Thii is followed by a Phase C: Gives us a fmal and unconvincing test & break of the TR lows on extremely light volume.

SOS on dramatically increased volume. Phase D: We see a consistant & pronounced dominance of demand over supply on widening spreads and increased volume

to the upside. Reactions are comparatively weak and on light volume. Demand remains in control. Phase E: The stock is marking up on rising volume.


Intermediate Reaccumulation

J?b.w~& Stops Previous Move.

PhaseBBc: Shows Comparatively weak volume on consolidation as stock moves down. Volume very light on series of lower lows on Shake- outs. No new supply on #3 Spring. Demand showing dominance as stock comes off spring.

FW&LL Shows continuing pattern of demand in control. Gives us sufficient evidence to add to our longs on pullbacks. Ifha&& Stock Marking Up. Demand in Control.


Intermediate Reaccumulation

w Shows Buying Climax stopping previous up mow and more pronounced preliminary support and selling climax facilitating accumulation into stmongcr hands. EbnreB; Inmnclusivc evidence but does show us evidence of rally on good spread and volume. Ehprd; Shows fmal low on diminished volume compared to ST and holds suppoct area above climax low. Move off of low shows pattern on expanding spread and volume. EhprrsEU Continues pattern of Demand in Control.

L

56 MTA JOURNAL / SUMMJZR - FALL 1994

Distribution

;i

&gg-& Shows us PSY and Push to new highs (EC) on failing volume. ST fails and closes below BC high. The subsequent reaction downward immediately precedes. T%e next attempt, a few days later, is on poor volume and cannot reach previous highs.

&&$&Q Gives us some early clues that supply is in control. Bearish actjvity is evident showing a SOW on increased volume and the rallies

on comparatively low vohtme indicating a lack of demand. Phase B also shows a break through the TR Support Lines Subsequent rallies are

also on poor volume. Additional Breaks of Support line on we” higher volume.

-5;; We break through the ice and manage to rise above it, however, volume is unconvincing. We can only rise to meet resistance at the supply line and the bottom of our initial trading range. This gives us a LPSY and an opporhmity to take a short position with a well delineated

risk just about the previous high at 19 %.

WB We fall through the ice again, but on signiticantly higher volume. We have no rallying power and a feeble attempt to reach the ice

fails. Supply has continued its dominance. We arc given a last oppommity to add to our short position on the rally back to the ice m&. Markdown accelerates and supply is in control.


Distribution

-B; WesCCthCuPmOVestOppedbyPSYandmeBC. WebavcanARandanST. w In pha B relative equilibrium on low vohmx No clear indications seem revealed but a #3 spring before the upthrust.

M As in our #3 Schematic, MID however shows us a UTAD and then quickly returns to the tradiig range. The UTAD fallows the right

side of the TR in phase C. w Shows a progression of declines and rallies with higher volume on tbe down swings. A Supply Line is evident MDT Breaks through

the ice.

M Our rally back to the ice fails and markdown accelerates.

58 h4TA JOURh’AL/ SUMMER - FALL1994

journal of technical analysis (jota). issue 43 (1994, summer)

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