JOURNAL OF
TECHNICAL ANALYSIS
Issue 56, Fall/Winter 2001

Editorial Board
David L. Upshaw, CFA, CMT
Jeffrey Morton, MD, CMT
Connie Brown, CFTe, MFTA
Founder
John A. Carder, CMT
Ann F. Cody, CFA
Cynthia A Kase, CMT, MFTA
Expert Consultant
Charles D. Kirkpatrick
Cornelius Luca
Theodore E. Loud, CMT
John R. McGinley, CMT
Michael J. Moody, CMT
Dorsey, Wright & Associates
Richard C. Orr, Ph.D.
Robert Peirce
Ken Tower, CMT
Chief Executive Officer, Quantitative Analysis Service
J. Adrian Trezise, M. App. Sc. (II)
Barbara I. Gomperts

CMT Association, Inc.
25 Broadway, Suite 10-036, New York, New York 10004
www.cmtassociation.org
Published by Chartered Market Technician Association, LLC
ISSN (Print)
ISSN (Online)
The Journal of Technical Analysis is published by the Chartered Market Technicians Association, LLC, 25 Broadway, Suite 10-036, New York, NY 10004.New York, NY 10006. Its purpose is to promote the investigation and analysis of the price and volume activities of the world’s financial markets. The Journal of Technical Analysis is distributed to individuals (both academic and practicitioner) and libraries in the United States, Canada, and several other countries in Europe and Asia. Journal of Technical Analysis is copyrighted by the CMT Association and registered with the Library of Congress. All rights are reserved.
Table of Contents
JOTA ISSUE 56, Fall/Winter 2001
Letter from the Editor
by Henry O. “Hank” Pruden, PhD
Letter from the Editor
by Henry O. “Hank” Pruden, PhD

EDITOR’S COMMENTARY
A DYNAMIC BODY OF KNOWLEDGE
The six articles, reprinted in this issue, span the life of the existence of the MTA Journal. These articles give testimony to the growing, dynamic quality of the body of knowledge we know as Technical Analysis. The first two articles reflect the dynamic balance between the artful practitioner (Laubscher) and the scientific academic (Shomali); Ralph Acampora’s classic on Dow Theory appeared in the very first issue of the Journal. This broad treatise on the market (joined by Dines) is followed by more specialized studies such as Fraser and Leonard on sentiment, Forte on pattern recognition and Timmer on combining technical indicators and fundamental information. And these articles are just a sample of the publications from the MTA Journal. Some articles were selected from a list assembled by the MTA Educational Foundation; others were chosen by the Editor. The two research notes by Safian and Morton are fresh contributions.
Henry O. Pruden
EDITORS’ FAREWELL
Henry (Hank) O. Pruden, Ph.D., Editor & David L. Upshaw, CFA, CMT, Associate Editor
Our deep and sincere thanks to the referees and staff of the MTA Journal, most notably Barbara Gomperts. We are pleased to entrust the Editorship of the MTA Journal to the capable hands of Charles D. Kirkpatrick II, CMT. And with the following, slightly modified verse from Rudyard Kipling, we bid our adieu.
The Long Trail
There’s a whisper down the field where the year has shot her yield,
And the ricks stand grey to the sun,
Singing: “Over then, come over, for the bee has quit the clover,
“And your eleven years are done.”
You have heard the beat of the offshore wind,
And the thresh of the deep-sea rain;
You have heard the song – how long? how long?
Pull out on the trail again!
Ha’ done with the Tents of Shem, dear lass,
We’ve seen the seasons through,
And it’s time to turn on the old trail, our own trail that is always new!
It’s North you may run to the rime-ringed sun
Or South to the blind Horn’s hate;
Or East all the way into Mississippi Bay,
Or West to the Golden Gate –
Were the blindest bluffs hold good, dear lass,
And the wildest tales are true,
And the men bulk big on the old trail, our own trail, the out trail,
And life runs large on the Long Trail – the trail that is always new.
This Article Appeared in the MTA Journal, February 1986
by Harry W. Laubscher
About the Author | Harry W. Laubscher
Harry W. Laubscher is a member of the MTA and a Technical Analyst at Tucker Anthony, New York, NY.
Having spent almost twenty-nine of the last thirty years working in the stock market’s highways and byways, I hope that I have learned something. We all manage to learn a great deal, regardless of what field we work in, but all too often many of us tend to forget many of the things that were learned and which should not have been forgotten. It has been often said that the stock market, along with drink and women, is one of the great levelers of our time. Many of the important pieces of market lore that we learned along the way, and then in later years tended to forget, no doubt could have saved many of us from experiencing many of the mistakes that all of us make. I am reminded of this lately as I see a great rush on the part of inexperienced brokers and traders to be “in the crowd” regardless of where that crowd is headed. For some strange reason, the more the stock market rises, the more bullish many of us tend to become, finally resulting in a great rush to own shares right at the top of the market. On the other hand, it usually works out that the lower the market goes in bear markets, the more bearish more people tend to become. It has always been so, and as long as people are the driving force behind all market movements, up or down, it will always be so.
We have all heard some of the sayings for which Wall Street is so well known, such as “sell on the good news and buy on the bad news.” I’ve found that this does, indeed, work out to one’s benefit more often than not. During the Union Carbide fiasco in India when the shares of the company dropped sharply to near 33, the wise people were there buying all they could get, knowing full well that the lemming instinct had once again taken things too far. The recovery in price of those shares since then is in the record for all to read and great profits have been made in what “everyone knew” was going to be a disaster for the company. More recently, we have the situation of Texaco and Pennzoil. Many savvy traders recognized the rather silly awarding to Pennzoil of several billions of dollars as an opportunity to acquire an historically “good” company at what appeared to be bargain priced levels. As of this writing, the shares of Texaco are still floundering near the 30-31 level, and although my point and figure work suggests a potential downside count to approximately the 29 level, I am advising investors with some patience to start acquiring Texaco shares in the 30-31 area. In time, this should work out to be a good buy. I use it as another example of the unsophisticated atmosphere that appears to be so prevalent today.
And yet, I stop to wonder if I ever really did meet anyone at all who could accurately be described as sophisticated in the stock market. Being sophisticated in the stock market probably is as out of place as being logical. And we all know that in order to be successful in the world of investing, logic has to be left outside the door. This brings me around to the inevitable question: “Is understanding the stock market now becoming more of a science and less of an art?” No doubt, it is a question that has troubled the minds of many marketeers for many years. I know, as a result of my recent trip to Japan, that the Japanese believe that scientific applications can be applied to the stock market, and they have gone to great lengths in employing those applications. More than any group I know, the Japanese are attempting to make it more of a science than it has been. And yet, I know that whenever you have to deal with something that involves people to any great extent, science can only be carried so far before art has to take over. Thanks to many of the new inventions that have come along over the years, such as the price quoting machines, information is much more readily available, making the formerly onerous job of keeping up to date much less so. Today, a great deal of information is quickly available – perhaps too much so – and thus the odds in decision-making have increased on the side of error. Now I know that that last sentence doesn’t seem right somehow, but then you are still thinking logically, aren’t you? And that doesn’t work in regard to the market. Too much information, too easily obtained leads one into too many possible byways, and therefore, increases the chances for error. Too many people believe that the more you know about something, the better off you are apt to be. I thoroughly agree, except in the stock market. In this arena, one often can lose sight of the forest for all the trees that are available and it often helps to use less data and a bit more gut feel. And, very often, who you know is just as important, if not more so, than what you know. How else do you explain the success levels of those who tend to make it in the market?
And this brings me to one of my favorite sayings about the market. It is one in which I thoroughly believe and have seen the workings of it spread far and wide, among all types of marketeers. “The stock market is one of the easiest places in the world to get rich.” All you have to do to make it so is to avoid what most of the others are doing. For example, I long ago gave up buying The Wall Street Journal. It has too much information of too little worth and not enough of the really valuable stuff. Barron’s is somewhat better in that respect, but the new newspaper Investors Daily has it all over both of the Dow Jones papers. Once you start getting really good news on what is going on in the market, the path to wealth is soon beneath your feet. It helps also to look around you, ask the man in the street what he thinks about the economy, or whatever, and when you have determined what the general drift of conventional wisdom is, go the opposite way. One of the biggest obstacles to obtaining wealth in the stock and bond markets is to fall prey to the enticements of quick profits. Of course, they are grand to have but more often than not it pays to “let your profits run, while making all endeavors to cut losses short.” Too often, technically oriented traders and investors see more in the chart than really is there to be seen. False breakouts, up or down, make us nervous and we jump, only to find out later on that there was no alarm except in our own minds.
I also believe that it is a bit wise to be skeptical of almost everything. At times you will have to depend on what appears to be the wisdom of those around you, those in whom you have faith to do the jobs with which they are involved. But one also should take the time to hear what others have to say, and then go and do a bit of “checking it out.” It can’t hurt. I also believe that too many investors fall prey to the belief that information on revenues, management, contracts, industry items, sales and earnings are what makes stocks move up and down. They seldom stop to think that all that kind of information only has to do with the company itself, NOT the shares of the company in question. The only thing that makes shares move up or down in price is buying or selling pressure outweighing one another. If nobody sells, then all the good information on dividends and earnings isn’t going to move shares upward. If all the bad news makes buyers disappear, then shares can’t move downward. So trying to gauge what the buying pressure is probably is the most important thing that anyone can do in the search for profitability. At PaineWebber, every week we publish a relative strength analysis of over 4000 issues that when taken in conjunction with some other information, affords a very good indication of whether or not buying, or selling, pressure is rising or declining. Once you have that tool in your hands, the game becomes a lot easier. Over the last ten-eleven years, every single issue recommended in my Trends & Opportunities Market has been based on my reading of the buying or selling pressures. That has helped us achieve a 95% success ratio in those recommendations, 250 profits, nine losses and three unchanged since 1974, regardless of whether a bull market or a bear market was in the driver’s seat. Get to know what direction the pressure is moving in and you are halfway to your objectives. And that goes just as importantly for short-selling.
While we are on the subject of short selling, technical analysis can be of great help in helping clients make money on the short side. Once you find a chart pattern that is descriptive of distribution, move on to find out if the selling pressure has been increasing, or if the buying pressures are ebbing. If both suggest you should be shorting the stock, go a step further and check out the short interest. If it is high, so much the better, since most of the shorting is still done by professionals. And don’t fall for that old saw about stocks with high short interest holding up well, because there is a buyers’ floor under the price. It is quite true that those who sell short must sooner or later buy back in again in order to take their profit, or their loss. But a check of past bear markets will show that stocks that had the highest levels of short-interest usually sold off quite nicely, enabling those who sold short to repurchase shares at lower levels. A floor under stocks with high short interest is about as fleeting as support levels in a bear market. I always try and remind brokers who ask me about support levels in a bear market that support is only a seven-letter word and usually doesn’t afford the support sought. Support, on the other hand, is much more important, technically, in a rising market. The same goes for resistance levels. In bull markets, those resistance levels usually provide only fleeting roadblocks to advances. In bear markets, upside resistance takes on much more power, on average. There always are exceptions, of course.
I guess if I had only one tool to select from all those that are available among the various charts and chart services, I would come down on the side of a good weekly bar line service. Something like Mansfield that provides the relative strength indicator graphically presented, various moving averages, and then throws in upside volume and downside volume to make it a bit easier. If you like having the fundamentals, those are provided as well. They once used to give earnings’ estimates, but not anymore. Too bad! It helped to gauge things better if you knew what the “street” was expecting. Then, when the winds of winter were blowing and I was all snug by my fireside, I’d take out my barline book of charts and go through it every week, looking for those seven cardinal patterns that indicate either accumulation or distribution. You all know what they are. You don’t need me taking up valuable space to repeat them again. Once I was able to correctly identify some of those patterns, I would put some of my funds to work. I guess that when push comes to shove, those important patterns of accumulation or distribution are the most important things in our world of Technical Analysis. Without the knowledge of them, we’re always back at square one.
Now I certainly don’t mean to knock point and figure analysis. I have found it to be too helpful over the years to give it a position below the salt. It is an invaluable tool in trying to gauge just how far a move is going to carry once that move has started. But, if pressed, I still would have to say that a bar line chart will tell you when the move is going to start. Then you would move on to a P&F chart. If anyone out there wants to make a lot of money in this business, I would suggest that they start a point and figure weekly chart service of the 500 most actively traded listed bonds. As far as I know, there is no such service available. Since we are in the still early stages of a super cycle bull market in bonds, their price performance will become increasingly important as the next five to seven years roll by. And their volatility also will increase, making a point and figure analysis far more valuable. I’ve thought of doing it myself, but am just too tired to take on another chore.
The twenty-nine years will soon be rolling into a nice round thirty. I came to Wall Street intending to stay only twenty years, but the work was so interesting and the people with whom I worked were so pleasant and helpful, that I stayed on and on and on. This has been the most fascinating of my three careers and I am wondering if the fourth and next career will be as rewarding.
This Article Appeared in the MTA Journal, Winter 1994 / Spring 1995
by Hamid B. Shomali, Ph.D.
About the Author | Hamid B. Shomali, Ph.D.
Hamid Shomali, Ph.D., is professor of Finance and Economics, and Dean of the School of Business at Golden Gate University. Dean Shomali joined Golden Gate University in 1986 after a distinguished career in banking and finance. At the Bank of America, he completed several policy studies that impacted the international lending of the bank. Also as a member of the energy-lending group, he made a substantial contribution to the bank’s energy loan portfolio. As Deputy Managing Director of Bank Farhangian, Iran, he managed the bank’s construction and mortgage lending as welt as its international operations. Prior to that he was an economist for the Central Bank of Iran where he completed analytical projects on a broad range of macroeconomic and monetary issues. Dean Shomali has served on the faculty of several universities including the University of California at Berkeley, University of Houston and the National University of Iran. His teaching and research has been in international trade and finance as welt as oil economics. Dean Shomali consults with international companies on banking, finance and international management. Dean Shomali received a Ph.D. in Economics from the University of California in Los Angeles (UCLA) in 1973. His undergraduate education was completed at the University of Salford, England where he received a B.S. degree in Mathematics and Economics (Joint Honors) in 1968.
In the last several decades, there have been two competing schools of thought regarding the analysis and valuation of financial securities. The traditional finance experts have espoused fundamental financial analysis, dealing with identification of variables that will determine the underlying value of securities. These traditional security analysts have downplayed the significance and the relevance of the other school, namely “technical analysis.” The strict fundamentalists have viewed technical analysts as mere “chartists” who pass over past data in order to find certain patterns in the behavior of security prices over time. These traditional finance theorists at times have likened the technical analysts to “astrologers” in the field of finance. The technical analysts, on the other hand, would like to gain recognition for their successes in forecasting security prices and be considered more like astronomers than astrologers. But the debate continues.
In recent years technical analysis has been gaining wider acceptance in academia. Technical analysis received prominent and favorable review in a seminal article surveying the frontiers of finance which appeared in the October 21,1993 issue of The Economist. The offering of courses in technical analysis at some universities such as Dartmouth College, Golden Gate University and the McIntire School at the University of Virginia, as well as the New York Institute of Finance, demonstrates the increasing recognition of the field of technical analysis by academia. As technical analysts align their field with “behavioral finance,” they will gain even wider acceptance.
It is interesting to observe that both schools can be viable by explaining different behavior patterns at different time frames, and as such do not have to be necessarily competing schools. The fundamental analysis rests on the assumption of a rational person who incorporates all of the relevant data concerning a certain asset before making a decision about its acquisition. In that regard, the past history of the asset is totally irrelevant. In other words, with all the past glory of IBM, if the fundamentals are pointing towards a dismal outlook, the investor will disregard the past history. In a sense, the rational school of thought, or the fundamental analysts, regard the valuation of financial assets determined by a “random walk.” In random walk, the prices of securities are likened to steps of a drunken sailor, where each step is independent of the previous one. Fundamental analysts basically assume an “efficient market” when the stock prices reflect all information available to the public. The efficient market theory, that the fundamentalists adhere to, assumes rationality at all times on the part of investors and does not allow behavior based on emotion and all other impulses. Yet as a practical matter, human irrationality is important. Even in the legal code, the plea of insanity allows for impetuous behavior that is not based on rationality and simply stems from a sudden urge or instant decision. Perhaps some of the most persuasive evidence against the “efficient market” theory comes from the “anomaly” literature, which has discovered unusual patterns in the price behavior of securities. Some of the most puzzling price anomalies are related to seasonal patterns in the movement of stock prices. Other anomalies relate to returns that are dependent upon the size of a firm and the impact of new stock issues. It is the contention of this author that in the short run (anything from a day to a few months), emotions and other biases may lead us to make a decision that may not be based on rationality. Impulsive behavior, herd mentality or any other decision-making process which relies on mechanisms other than rational analysis of all relevant factors are not allowed in the fundamental analysis or the theory of efficient markets. But how else can one explain the events such as markets behaving differently on Monday mornings than Friday afternoons, or that every year there is a sense of nervousness in the markets around October?
One of the major problems that behavioral analysts have to face is that in their analysis of the market they often ignore the concept of probability. In other words, they often sound as if they are stating their forecasts with certainty. As a consumer I may react to a 50% discount offer based on sudden impulse, but such impulse may not dictate my actions every time I encounter such a discount. The behavioral analysts have to specify that their technique is only for shortrun decisions and as such may be more useful to traders than institutional investors, such as pension plans, who are concerned with the long term returns on assets. The technical analysts also have to find a way to incorporate probability analysis into their analysis. Otherwise, there is no basic problem with their use of past data to arrive at certain conclusions about the future. In traditional forecasting models, such as “time series analysis” such as “Box-Jenkins” the past data is also used to make inferences about the future. In fact in econometric forecasting, the “least square estimation” or “maximum likelihood” method, the forecast of a dependent variable is based on a weighted average of the past observations of the same variable. The above statistical methods simply determine the weights through statistical manipulation, and the forecasts are based on probabilistic assumptions about the behavior of variables, and as such are not deterministic numbers. In fact, “auto regressive” estimation methods are an important part of econometrics where the past values of a variable are used to determine its future forecast.
The fundamental analysts can point to the strength of an underlying security based on the fundamental variables that will impact its value in the future. But this analysis, by its nature, is a long-term phenomenon that is incapable of pinpointing the time that such movement will begin. In other words, the fundamental analysts can never provide us with the turning point.
Should we dismiss one theory in favor of another? The study of these two methods of security analysis reveals that they are concerned with different time horizons and different decision-making processes. Fundamental variables can certainly affect the value of a security over the long run. However, in the last few years, the economists have accepted that there are a lot of human emotions entering the process of decision making, not just calculating rational behavior, at least in the short-run. Granting of the Nobel Prize in economics in 1993 to Professor Douglas North is testimony of admission by mainstay economists that other modes of behavior such as culture, habit, bias and prejudice as well as impulsive or random behavior could be used to explain consumer behavior. Increased attention paid to “behavioral finance” by some well-known finance scholars should open the door for a less-biased approach toward “technical analysis” by the traditional finance professors. The fact that industry, such as Japan’s, has decided to invest $30 million in researching such topics indicates the security industry’s serious interest in the topic of technical analysis.
This Article Appeared in the First Issue of the MTA Journal, January 1978
by Ralph Acampora, CMT

About the Author | Ralph Acampora, CMT
Ralph Acampora, CMT is a pioneer in the development of market analytics. He has a global reputation as a market historian and a technical analyst, providing unique insights on market timing and related investment strategy issues to a wide audience within the financial industry. Ralph has been an instructor at the New York Institute of Finance for close to four decades, and previously served as the NYIF’s Director of Technical Analysis Studies. Before joining NYIF, he was Director of Technical Research at Knight Equity Markets.
Prior to joining Knight, he worked for 15 years at Prudential Equity Groups as its Director of Technical Analysis. Ralph is one of Wall Street’s most respected technical analysts and has been consistently ranked by Institutional Investor for more than ten years. He is regularly consulted for his opinion on market events by several major business news networks as well as national financial publications. He helped create the Chartered Market Technician designation and continues to advocate for its application in distinguishing practitioners of technical analysis.
Ralph co-founded the Market Technicians Association (now called the CMT Association) in 1970. He established the first technical library (now the CMT Library) in 1975 at the New York Institute of Finance at 70 Pine Street, New York City. He also co-authored “The First Fifty Years” – a history of the CMT Association – a must read.
by Rosemarie I. Pavlick
About the Author | Rosemarie I. Pavlick
Bio Coming
After many years of observations, Charles Dow concluded that the stock market, like the ocean, had three movements: primary, secondary and daily fluctuations. The major advances and declines of the market were equated with the tides – a dominant force that lasted for a period of time. These long-term movements were subject to secondary reactions (waves) that lasted for a shorter period of time and might temporarily appear to contradict the primary trend. And finally, the waves themselves were broken down into ripple (daily) reactions. But Dow strongly felt that no means of manipulator could divert the eventual course of a major primary move. It is for this reason that he dedicated his theory to the long-term outlook for the stock market.
The discovery of the rhythmic movements of price led to the advent of the Dow Jones averages. Beginning in 1897 The Wall Street Journal published two sets of averages: the industrials and the railroads. The logic behind the specific makeup of these separate indices is rooted in Dow’s premise that both of these sectors of the market were interdependent. For example, if the large industrial firms of the day were faring well, they depended upon the use of railroads to transport their products. Whenever the price trends showed disparate movement between these two indices, it meant that one sector was stronger or weaker than the other, and if allowed to continue, it would eventually result in a major reversal for the general stock market.
At this time in history, as our nation was still growing – pushing its way across the entire expanse of the North American continent – the iron horse was the only means of transporting people and produce. Thus industry and railroads prospered and suffered together. As our country matured and the transportation revolution took hold, the use of railroads diminished considerably. It was for this reason that the Dow Theory came under recent attack. “What about the airlines or the truckers – why are they not incorporated in this theory?” This argument was valid. So on December 22, 1969 Dow Jones & Company revised the rail average to include other means of transportation. Today, the new Dow Jones Transportation Average satisfies the original requirements of a balance between industrial firms and the transportation network.
The following is an excerpt from The Dow Theory Explained by Charles B. Stansbury:
“We now come to a fundamental tenet of the Dow Theory and that is that any signal to be authentic must be affirmed by both the industrial and railroad averages. While this concept may seem a little confusing at first, we have only to return to our simile of the movement of the tide to clear it up. Instead of watching a single beach (or chart) we now must imagine ourselves standing at the mainland end of a narrow peninsula from which we can watch two beaches: Both are parts of the same ocean (market) which is divided into two parts (industrial average and railroad average) by the peninsula. While both beaches are subject to the same tidal action they may show varying wave action. The wave action on one beach may often prove highly deceptive as to the course of the tide unless we find the movement confirmed by similar action on the other beach.”
The February 11, 1922, The Wall Street Journal stated:
“… the stock market is acting not upon the known news of today but upon what conditions will be as far ahead as the combined intelligence and knowledge of Wall Street can foresee. There are plenty of bear arguments in the complicated conditions in Europe, the uncertainties of taxation and the interested aberrations of Congress. All these factors are known and, if possible, over discussed.”
Charles Stansbury also wrote that
“Over the years during which the averages have been observed and recorded this confirmation by both averages has established itself as an essential part of the theory.
“The confirmation which carries authority need not develop in our chart on the same day or even in the same week. It is deemed sufficient if one average follows the other into new low ground, or new high ground, before the first average retracts its half of the signal. The first average retracts if it makes a new extreme in the opposite direction before confirmation by the second average.”
Confirmation of Primary Bull and Primary Bear Markets
In Chart I we depict the price trends of both the Industrial and Transportation Averages. Note that drop B to C does not register a new low (below A). This is the first sign of a potential positive shift in the making. At C, one or both averages holds above the low (A). A bear market bottom is confirmed at point D – the first time that the averages penetrate a previous rally of substance.
A bull market reversal occurs when there is tremendous euphoria; the “things couldn’t be better” syndrome. Some time during this period, the average(s) is unable to register a new high (G) above the previous and, in hindsight, ultimate peak (E). It is at point H that the primary downtrend is established – a decisive break below a previous important (real) secondary low (F).
Secondary Reactions
In every primary move, whether ascending or descending, there is a time when prudent investors commence profit taking (Chart II, point A). This normal process invariably causes the average(s) to weaken – perhaps both industrials and transportations show signs of divergent trends at this point. Significant redeployment of funds becomes evident at point D – a time when the buyers’ activity supports sagging prices and prevents a new low from occurring below point B. Point E suggests more optimism as the minor high (C) is breached. It is not until a new high (F) is attained that the primary trend can still be considered in force. This entire pullback phase (A thru F) is known as a secondary reaction (waves within the tides).
How does one distinguish between a secondary and a major reversal? It is at this extremely critical juncture that one pay close attention to all the characteristics present during secondary reactions. To begin with, secondary declines have a multiple effect (several downward swings in price). In Chart III, the most recent primary upswing began at point A. At point E the Dow theoretician must come to gripes with the problem of identifying B through E as a secondary reaction or a major reversal. If the verdict is “Bear Market,” he will sell all of his or her stock and perhaps go short. However, if the interpretation reveals the existence of a secondary reaction phase he or she will deem this decline a normal happening and slowly commit funds in order to take advantage of an eventual major “up” move. Listed below are those characteristics common during secondary phases:
- The movement is more rapid in a reversal than in a primary trend; they may last from three weeks to three months and typically retrace perhaps 40 percent of the movement since the end of the last major reversal. But there have been occasions when a secondary reversal retraced as little as 30 percent of the primary move – and as much as 70 percent.
- The length of time needed to complete this reversal is usually a much shorter time than the previous advance. From top to bottom (B thru E) more than three months time usually indicates a bear market.
- If volume during the reaction (B thru E) equals or exceeds the level that prevailed at the time of the top (B) it would be bearish. However, if volume continues to drop lower as prices decline there is a good chance that this decline is nothing more than a reaction.
- The atmosphere surrounding this entire period is also very important. If excessive speculation is present then this type of reaction could be interpreted as the beginnings of a bear market.
“…The market barometer does not pretend to do the impossible. It forecasts, defines and confirms the major swings… It does not pretend to forecast the secondary reactions any more than it clearly foretells the corresponding rallies in a major bear market.
“This is because the secondary reaction, as distinguished from the major movement, is governed by the unexpected.”
The Wall Street Journal, September 19, 1922
It is now imperative to define the distinctive phases present in Dow’s bull and bear markets:
The Bull Market
- Phase One is known as the accumulation phase – very depressed prices – basic industry, utilities and high yielding stocks dominate.
- Phase Two is characterized by increased activity, rising prices and an improving business scene. Secondary stocks are in vogue.
- Phase Three, the final explosive move, a by-product of excessive public speculation. The ‘cat and dog’ syndrome.
The Bear Market
- Phase One is called the distribution phase. As the “public” scrambles for stocks, the farsighted begin their deliberate selling. Stocks go from strong to weaker hands.
- Phase Two is referred to as the panic phase. Selling begets selling as the urgency to liquidate mounts. Margin calls escalate.
- Phase Three is marked by continued erosion in prices, the crunching of lesser quality issues – object pessimism prevails. “It’s always darker before the dawn.”
THE THEORY TODAY
Charles Dow specifically emphasizes the use of the closing prices for both averages, because he felt that these figures would give a true picture of the floor traders’ and specialists’ positions. Despite their long and short dealings, during the day, these professionals would invariably even up before the close.
On Chart IV are depicted graphs of both averages: we have inserted the closing figures of the key reversal points and non-confirmation levels since September 21, 1976.
This entire period is in question. Are we in a secondary reaction phase or has a Dow Theory bear market signal been given?
In determining a trend, previous high and low points are used. A succession of new highs is positive while a series of new lows is negative. The Dow Jones Industrial Average on Chart IV has been tracing out a progression of lower highs since September 1976 (note points A, D, E, G, H, J and K). Points B, C, F, I and L vividly portray a succession of lower lows – this combination is negative.
When viewing the Dow Transportation Average from October 1976 to May 1977, a distinct divergence is seen. Points. P, S and T represent a classic series of new highs while N, Q and R are important higher reaction points – this combination is positive. The DJIA reached its high on September 21, 1976 at 1014.79 (A) while the DJTA registered its high on May 18, 1977 at 246.64 (T).
Remember Dow’s fundamental tenet: “for any signal to be authentic, both averages must confirm. It is deemed sufficient it one average follows the other into new low ground, or new high ground, before the first average retracts: its half of the signal.”
Now the question is raised – since the Transportation Average has recently come under sharp selling pressure (points W and X), does this move constitute a confirmation of the Industrial Average’s negative behavior?
To begin with, the Dow Jones Transportation Average was confined to a tight trading range during the months of June and July 1977 (U and V). This is called a line formation. It usually lasts several weeks with price fluctuations in the magnitude of 5%. Such movements indicate accumulation or distribution. Any break below this formation is distribution and implies lower prices. Needless to say the Transportation Average has decisively penetrated the lower end of this pattern (W); in so doing, it also weakened below its February 25 close of 221.81 (Q). It is here that the Dow theoreticians differ. Is 221.81 the critical secondary low? If so, then the DJTA has confirmed the breakdowns in the Industrial Average and has initiated a primary bear signal. A secondary low must be considered the beginning of the recent primary upswing. We interpret the Oct. 3 low (N) of 203.85 the focal point for the primary upswing. Thus, until the Transportation Average closes below 203.85, the move down from T is still considered a secondary reaction.
The following excerpt from Richard Russell’s The Dow Theory Today is noteworthy:
“Bear market signals, however, must not be oversimplified. The great Dow Theorist Robert Rhea wrote in 1938: ‘Beginners frequently make the mistake of basing conclusions wholly on the matter of penetration. Familiarity with the correlated factors such as duration, extent, activity, divergence, and secondary implications of primary bull markets is needed to make a correct diagnosis.’ Anyone who has studied the works of Hamilton and Rhea knows that it is only in the third and last phase of an extended bull market that a bear signal is valid. Ignorance of this fact has led to one of the most disastrous misreading of the Averages in modern stock market history.
“Over and over again the great Dow theorists have warned us not to take a shallow, mechanical reading of the Averages while disregarding phases, duration and extent of the market movements. By calling a bear market on a ‘false’ second phase signal, the majority of
the financial fraternity has committed one of the most costly errors in market annals.
“Once the fact is accepted that bear market signals are valid only when they occur within the third phase of a bull market, the utmost importance must be attached to identifying the third phase. ‘This is the time,’ wrote Rhea, ‘when brokers and soothsayers prosper, and when an excited public, lured by the bait of advancing prices, buys stocks without regard to values; basing their action on nothing more than hopes and expectations.’ He observes that ‘this is the phase where worthless stocks are bought for no other reason than because they look cheap and because gamblers hope they will double in price. This condition always has prevailed in the third phase of bull markets. . . .’”
Let us now investigate Rhea’s co-related factors:
- Duration: The Dow Industrials has easily exceeded the three-week to three-month time limitation used in measuring a secondary reaction. The Transportation’s reaction began on May 18 (T), also overstaying this requirement.
- Extent of the Decline: A secondary reaction typically retraces perhaps 40% of the movement since the end of the last major reversal. On occasion, retracement of 30% or as much as 70% of the primary move have been noted. The DJIA has retraced 34% of its primary advance that began in December 1974. The DJTA has only retraced 26% from its primary low, registered in October 1974.
- Phases: To date we have witnessed impressive moves in the basic industries, utilities, and high yielding stocks – the fulfillment of Phase One in a bull market. Secondary stocks have moved to the fore and dominated the scene in the past twelve months, thus satisfying Phase Two. However, the overheated, speculative fever stage has not been witnessed; thus the paramount requirement has not been met. The reactions to date (A to L and T to X) have not taken place during the third and final phase of a bull market. In conclusion, “it is only in the third and last phase of an extended bull market that a bear signal is valid.”
203.85 This number represents the important secondary low registered in the Dow Jones Transportation Average on October 12, 1976. Since September 1976, divergence has existed between the DJIA and the DJTA causing many Dow theoreticians to question the viability of the bull market that began in January of 1975. Last Monday, the Dow Jones Transportation Average closed below 203.85, giving a bear market signal. However, everyone was fully apprised of this development – leading Wall Street publications contained articles describing this phenomenon and its ominous consequences. The nonbelievers quickly responded with either a shrug of the shoulders or the statement that this signal was “too much and too late.” Some selling came to the fore because of the breakdown but quickly reversed into the first 5% rally in 1977. That rally nevertheless does not negate the importance of the signal. In fact, the rally comes as no surprise – the market had already suffered slow deterioration for several months, and at the time was in an extremely oversold condition. The reaction was anticlimactic, but don’t be fooled by the resultant rally. Much more is needed to reverse this negative signal. Charles Dow compared the market’s primary trend with the ocean’s major tides. He suggested that within the tides, waves would occur (secondary reactions) that move counter to the major flow. These counter moves could extend from three weeks to three months and have no lasting effect on the major trend. Thus, if this bear market signal is accepted, temporary rallies could be viewed as a selling opportunity within a major downward phase.
Written 8/19/1977 3:30 pm DJIA 862.27
This Article Appeared in the MTA Journal, November 1986
by James L. Fraser
About the Author | James L. Fraser
James L. Fraser, president and founder of Fraser Management (309 S. Williard St., Burlington, Vermont 05401), is responsible for overall investment guidance as well as fundamental economic research and portfolio management. He is a Chartered Financial Analyst and has been an investment counselor and financial publisher since 1962. He is also a member of the Market Technicians Association.
There has been a steadily growing interest in Contrary Opinion theory over the past few years. Beginning in the 1940s, Humphrey B. Neill, who died in the mid 1970s at his homestead in Saxton’s River, Vermont, wrote about Contrary Opinion in his now retired Neill Letter of Contrary Opinion. I joined him in furthering the essence of the theory in 1962 with The Contrary Investor, a newsletter on investment implications of Contrary Opinion that I continue to write today. Moreover, I began to reprint old books that deal with human behavior and the stock market while slowly moving into money management utilizing a Contrarian strategy.
Today, Contrary Opinion is accepted as an investment tool and, in fact, has become part of conventional wisdom. Whereas for years the uses of Contrary Opinion were always in the back room, now the mainstream has recognized that to make money you buy the downtrodden, the misunderstood and the overlooked. Also, there are numerous investment letters, books, and practicing managers who seek lesser recognized or secondary growth stocks which do have growth characteristics but not growth multiples. New investment books have contrary or contrarian in their titles and institutions, now responsible for perhaps 85% of stock market trading, nod sagely at committee meetings when a manager says he uses Contrary Opinion.
However, reality is not that pure. Many people use the words but not the strategy. Long-term Contrarian investors, which means value players, include Warren Buffet, John Templeton, John Neff, Dean LeBaron, Phil Carret, Irving Kahn, and David Dreman. They all manage significant sums of money and have done so for a number of years. Of course there are others, but at least this gives you an idea of what I mean.
Phil Carret said years ago in his book, The Art of Speculation, published in 1930 (he is still alive today managing money in New York at the age of 89) that the road to success in speculation is the study of values. “The successful speculator must purchase or hold securities which are selling for less than their real value, avoid or sell securities which are selling for more than their real value. The successful investor must pursue exactly the same policy.” Of course, the time requisite for prices to move up is more important to a speculator than an investor. “A security may be undervalued, but if it is also out of style it is of little interest to the speculator.” So, one has to study the psychology of the stock market as well as the elements of real value. When real value is out of favor, a Contrarian moves in. A Contrarian investor waits patiently. A Contrarian speculator, on the other hand, tries to judge the psychological climate with other tools, as charts and technical indicators that will allow him not to wait too long. Let me give you an example. The chart below from M. C. Horsey & Company shows Sears, Roebuck, a major American corporation. Just before the August 1982 rise began, Sears was our company’s largest holding. How did we get that way? Sears was a nifty-fifty stock back in 1972 and early 1973 and then declined with the bear market of 1973-74. It recovered in 1975 and early 1976 and then sank into its own tedious bear market.
During this time, the news was largely negative in that merchandising was not doing well, other firms were taking market share away from Sears and as each year went by the financial press reported more and more negative news. The price kept coming down until finally negative news no longer pushed it down. The stock began the bottoming process in 1980 and, as long-term investors, we began buying in late 1980 right up to late May in 1982. We felt we had value which was then not being recognized.
As long-term investors, we bought too soon but that was not very material once the stock moved up strongly in 1982 and 1983. However, a speculator would have timed the movement better and perhaps bought after a breakout above 21 in 1982. The main Contrarian point is that once negative news no longer pushed the price down to new lows, the price fairly represented all possible disappointments. Of course the chart looked terrible at that time as past history for ten years was downhill, but the unexpected income of positive change, which takes a long time in a corporation as large as Sears, was about to be the next major factor which coincided with a market move that began in August 1982.
Take another example of a recent out of favor company with the chart of Halliburton below. Everybody is aware of the great move that took place in energy related securities during the 1970s that, in most cases, peaked out in late 1980. We then had a sharp fall back, a rise that participated with a 1982-83 bull market, then a continuing down turn based on negative fundamentals for major industries within the energy area. Oil field services represent a volatile sector.
Finally a Contrarian is attracted to the stock price after seeing it decline significantly from a high level, keeping in mind that the high price represents an extremely optimistic scenario and one that would not last. The question becomes where is value and in relation to what level of oil prices. An investor might begin buying in the low 20s and certainly participates below 20. A speculator or trader would wait for more price confirmation, that is of the price stabilizing where bad news is no longer a factor and where perhaps the next level of news is likely to be favorable.
PREDICTIONS AND FORECASTING
Fred C. Kelly, a writer for the Saturday Evening Post back in the 1930s first published Why You Win or Lose in 1930 with a for ward, interestingly enough, by John B. Watson, the founder of behavioral psychology at Harvard. This book is a favorite reprint of ours and in my preface I say we have difficulty struggling against crowd behavior patterns. We don’t compel thinking and observation. We don’t work at contesting the popular view. We are mislead by financial propaganda that makes us untimely in our opinions and often wrong in our actions.
Kelly understands that human gullibility’s are a constant contributory force to speculation. The only change between Kelly’s days and our own time is that crowd reactions occur faster, thus opinions shift quicker, and jumping to conclusions becomes an unprofitable pastime.
Every natural human impulse seems to be a foe to success in the market. We all want to conform, to congregate as a herd. And yet we win by understanding human psychology and by thinking ahead in creating possible courses of action to today’s conformity. You don’t have to be a highly competitive mental person to succeed, you only have to watch and study the crowd in order to pick up useful clues as to what the intelligent minority is not doing.
To succeed in the market one must not do what most others are doing. He who does the opposite has a good chance to be right. We may not know what insiders are doing until after they have done it, but by watching and studying the investing crowd we pick up clues as to what they are not doing. I do not mean that you want to avoid a major current when it is strongly flowing because the uses of Contrary Opinion are most valuable at turning points. To get aboard a major move at the right time, it is only necessary to disagree with the opinion of most investors you know who follow logical reasoning processes fostered upon us by print and TV financial media.
It is not the stock market which beats us. It is our own unreasoning instincts and inborn tendencies which we do not master and which, when we give in to them, lead to disaster. Natural instincts govern action which means that fear and greed are at the opposite end of the investment spectrum. I know, we all think, times have changed, which they have, but human nature has not changed and that is the point of wisdom regarding Contrarian investing strategies.
Another way to look at this is to say that money may be managed profitably or conventionally but not both. Of course, stock prices represent consensus expectations. But to profit, the expectations have to be both correct and different from what is current conventional wisdom. A significant human problem is to withstand group forces that seek to modify and distort individual judgments.
The business of investing is an actual study of social influence. Personal investing is so widespread that a social group has been formed, and we, as individual investors, are no longer indifferent to this group. When we visit brokers’ offices we are alert to the group. If we hang around long enough, we tend to reach an agreement with the prevailing opinion since this is the dynamic requirement of a group situation. Otherwise, our personalities would suffer. Even watching business news on television puts us in the position to accept prevailing opinion. The antisocial solution is to turn off the set.
TREND IS NOT DESTINY – CHARACTER IS DESTINY
We tend to modify our judgment in response to the pressure of majority and expert opinion. Most financial media reinforces majority beliefs and convictions. Investment practices are adopted on the basis of reasons that appear valid. But each investor comes under the sway of an already existing system of practices and values so he cannot judge independently, and he is affected the most when he is least able to exercise his own judgment. In other words, character and temperament are more important than charts and systems. We want to endow investing with specific guides that can be counted on. This is good. But we should realize that our emotions and unconscious behavior patterns, as the tides of the Bay of Fundy, often overrun these guides and just as often leave them stranded.
Independence and basic confidence in your ability to control doubts is a primary requisite for successful investing. Take the case of Xerox as represented in the chart below. Obviously, when Xerox was above 150 in 1972 and 1973, there was little independent thinking regarding the idea that the stock deserved such a high price. This was group behavior in all its splendor. Then came the market drop of 1973-74 with a bit of a recovery thereafter, but not much when you consider the market bottom in recent times was year 1974 at 570 on the Dow, and the market has moved higher since then. What happened is that the majority belief and conviction that Xerox was a special company, deserving of high multiples and all good things, was dashed through the rest of the 1970s and into the 1980s. To be sure, the higher you were in 1973, the easier it was to fall down and hurt yourself.
Anyway, right through 1982 and into 1984 the majority belief become one of Japanese competition winning the day with copiers, first at the cheap end of the line and then finally across the board. Xerox management was perceived to be incompetent and not paying attention to what was going on. We bought the stock in 1982 and again in 1984 an the basis that management, though a bit thick, was slowly responding to the global changes influencing its business. These changes take time. Finally, by 1984, negative articles no longer influenced the price of the stock. That was the safe time to buy in what technicians might call a saucer bottom. The stock then became our largest holding.
Interestingly, as you might suspect, as the stock rose up, we finally began to see a few nice words about Xerox. News follows the price. As the price moves higher the financial media speaks sweetly.
PRIDE OF OPINION PRECEDES A FALL
I have been saying that a practicing Contrarian observes the psychological status of the crowd in question and then takes an opposite approach. Of course, there are more than one opposite approaches. Normally, if the crowd has decided upon a conventional future, then the successful opposite approach is either more positive or more negative, at the extremes, until one of the extremes becomes the conventional view and then the Contrarian again must take a different road from the conventional view. The theory is based upon estimating the prevailing crowd emotion and not on forecasting the future. We make no attempt to predict the future, and we keep an open mind. Any definite forecast of the future leaves one at the mercy of that forecast because pride of opinion will tend to tie us down to that forecast.
Take a look at a medium-sized stock chart, which is Ransburg below. This company is not followed by Wall Street very closely, is located in Indianapolis, Indiana which people may come from but rarely go to, and reflects future forecasting in price moves. Not of the company itself but of fields of activity that the company represents. Basically, Ransburg is a leader in industrial equipment and is associated with robots. Not surprisingly, the all time high price of above 37 was made in April 1981 when Time magazine had on its cover robots and the tremendous future they represented. This cover journalism forecast of the future left investors at the mercy of brokers who were pushing robotic stocks. Anybody who read Time wanted such items and Ransburg, normally a quiet stock, topped out at the peak of enthusiasm for robots. Obviously, this enthusiasm was not limited to the month of April but had been building up since the second half of 1980.
Again, the high technology boom in 1983, which maximized in June of that year, also saw Ransburg peak out on the basis of high technology and robots. The price came down again only to rise a bit in 1986 on the basis of industrial expansion and the improving of American productivity. Now the stock is back down once more to below the 15 area and is a Contrary Opinion buy since we can choose it with an open mind that is not influenced by delightful future forecasts. These forecasts will come to life but not when anticipated and so far we have had three false moves which undoubtedly will keep investors away until they miss the real move that takes place one of these days.
Oh, I realize that it is easy to make points from charts that back me up. And yet, investing is not a science, and one must enjoy it to do it well. However, we should stick to what we understand, have some guts, and never become too overconfident. Again, Phil Carret once said something to the effect that an investor who so lacks confidence in his own judgment that he won’t buy any security until it is favored by the consensus of the investment community, will buy few bargains and is unlikely to achieve superior results. Of course, a security favored among professional investors is good but that is not the same as being undervalued in price. If unpopular, or generally unrecognized, some investigation is required to estimate basic value. That is where security analysis comes in. Once assured the basic value is there, then unpopularity will not deter the investor who is looking for long-term results.
A good trader, speculator or market technician is trying to do the same thing though using somewhat different tools that offer insights into value. We are all trying to buy things where the future is not already discounted. We want stocks with merit and we should buy them when they are weak. But usually we buy stocks with merit when they are strong and thereby do not build good performance over time.
PATIENCE IS SUSTAINED COURAGE
Another way to look at this is at perspective and patience of the essential requirements. We all want to own shares of successful companies in areas of activity that have particularly promising future prospects. However, the Contrary lesson is that we all tend to be influenced by whatever feelings are sweeping over the investment community at the moment and that true investing, to be successful, requires fighting these feelings. Nevertheless, it is not that simple for the inexperienced investor to be contrary since inexperience breeds a certain contempt for long-term solutions.
Subscribers to advisory services aim at quick results, feeling that the game is not worth the candle unless a system or technique works immediately. An individual, fortunate enough to have an intuitive sense of values, should be able to achieve reasonable profits with some degree of consistency. The key words here are reasonable and consistency – words not in the vocabulary of those who do not yet have market experience.
R.W. McNeel, Financial Editor of the Boston Herald from 1912-1922 wrote Beating the Stock Market, published in 1921 on the human side of speculation – which means attitudes, beliefs, hopes, and fears – the emotions and characteristics that any of us associate with human beings. Now studying people may not seem rewarding. But if you subscribe to the thesis that confidence makes business you study people. Writers tend to emphasize their statistical figures, but people give these figures meaning.
My point is that character is as essential as knowledge, even more so today when basic statistical knowledge is readily available. In McNeel’s day balance sheet figures were less reliable and yet they were relied upon. In our day statistical analysis is clearly stated and asset values are known yet the same stock swings take place. The constant element is the human side of finance – that has not changed. Natural instincts will unquestionably govern action.
To illustrate, fear is probably the oldest human instinct. It is universal and deep rooted. It is the outgrowth of self-preservation whereby we have been able to survive over time. To quote McNeel: “Because of its ancient origin and its great strength, man is at times exposed to the absolute breaking down of his courage under certain conditions and frequently without cause.”
The other side of fear is greed or from the instinct point of view that of companionship or gregariousness. Investors tend to flock together. We have an inborn tendency to do what we see someone else doing. Investors become excited and tend to act like lemmings as they enter into the active or emotional states of others.
Consider how basic instincts cause us to act in the stock market. We are told to buy low and sell high. Yet stocks are never low unless the headlines are such as to cause the great majority of active investors to sell. Selling is usually a creation of financial necessity, needing money, or more largely through fear of pending developments in the world that make you feel that prospect of financial 1055 is certain. Stock market bottoms are created when we sell stocks at ridiculously low prices without conscious reason. Whatever that price level is at, it will look low in retrospect. Recent examples are Dow 570 in 1974, 770 in 1982, and 1079 in 1984. This may be a pattern of rising bottoms, but each one offered exceptional opportunities for the purchase of stocks. The opportunity is only there because most of us are unable to turn our instincts or emotions upside down and buy while others sell.
McNeel said: “In order to avoid selling, and on the other hand to buy, he must put his natural inclinations to the test of reason and determine whether they are sound or unsound.” Every investor tries to do this, and I find from my own personal experience that it is easier to do this if you are physically divorced from the financial black holes of enthusiasm or despair which means the major metropolitan centers. I am in Burlington, Vermont because it is just enough off the beaten path to make it a Contrarian’s delight. Hopefully, this keeps us a bit away from the inborn tendency to act in common with others.
A few axioms to the uncertain art of economic prophesy follow; I will create a baker’s dozen guidelines:
- The system is there is none. I know this sounds strange but successful techniques are counterproductive when widely followed. Systems that work usually come to your dinner table as food for the future when actually they are the result of previous activity that is now so popular the system is not worth buying. What one needs are systems at the breakfast table, for sustenance over the coming day. Usually, one receives a system too late.
- Consensus hopes or fears are embodied in current valuation levels. The corollaries to this are that realization of expectations results in no price change while realization of unexpected outcomes moves prices. The chart of Aetna illustrates this point of view which is represented by “The Trader” column by Floyd Norris in the 18 June 1984 issue of Barron’s [see Exhibit No. 1]. Norris had attended the seminar on Value Investing sponsored by the New York Society of Security Analysts where I was a speaker. His attention was drawn to my mention that property/casualty insurance companies appear cheap in the marketplace. The letter to the Editor is from the 25 June issue of Barron’s and concerns our mentioning of bottom fishing for property/casualty insurance companies [Exhibit No. 1]. The point of Mr. Swift’s comments is that the entire industry is so bad off that our timing is nowhere near correct and investors should continue to avoid the entire area.
Of course, Mr. Swift’s letter represents good thinking and its inclusion in Barron’s reflects a certain style of consensus wisdom. The question comes down to that once your worst investment fears are realized, there is only upside potential left. But what are the worst fears? Is there a real crisis in the property/casualty insurance group or is it a case of the negative atmosphere being so strong that this is not the time for selling but rather the time for buying? Needless to say, the stock prices of both Aetna and Continental were both within 30 days of lows that have not been seen since. - The ability to sense what is going on in the economy is more important than organizing facts. The result is that indicators are no substitute for judgment. Besides, a simple yardstick of value can beat exhaustive consideration of all relevant facts. When you have too many facts there is the question of selection. To illustrate, low price-earnings ratio investing is an extremely simple strategy which works over time, probably because of its simplicity.
- There is a failure to perceive new reality. In other words, it is difficult to see the significance of outside events which produce new watersheds. A recent example is the climb of energy prices into 1980 and their subsequent decline into 1986. Most of us act like generals who are fighting the last battle in a new arena where we carry our experiences forward without taking into consideration the changing environment. The future is not always a continuation of the past. Be skeptical of past trends being stretched far beyond the present. The elastic may break or snap back when least expected.
- There is a cultural-psychological lag in experience over expectations. We all have a tremendous capacity to believe anything until it is no longer worth believing. The human factor tells us that we see things according to our preconceptions, which then paralyze perceptions. Indeed, when the market operates correctly, each investor reports a slightly different version of what is going on in the market and what signals he feels the market is sending us.
- Trend is not destiny. The future is never clear, and one pays a high price for a cheery consensus. The result is that uncertainty is a friend of the long-term buyer, and we need to take a position when most lonely. Easy to say, but not easy to do. Be suspicious of widely held views. Educate yourself for ambiguity instead of certainty, and you have a chance for success.
- Character is destiny. Do not put your trust in those who are trying to hustle you but rather believe in your own common sense. Remember that our behavior patterns are restless and dynamic, with emotions often making for strange statistical measurements. For a Contrarian it is better to be right by oneself than be wrong in good company.
- The bedrock of reality is a world of disequilibrium. Instability is a fundamental characteristic of transition. As Le Bon, the French writer of The Crowd says, a crowd yields to instincts that individuals suppress. Rational outside perspective tends to remove you from current investment climates.
- The art of forecasting is in the choosing. One has to decide what is important and what is not. We need time to reach conclusions. We react to each new piece of information as concrete evidence of a new trend that supports some exciting premise. The rise of gold and silver in 1980 was a wonderful popular delusion. The Hunt family of Texas was then worth over $5 billion and now, after some years of adversity, the family fortune seems to be well under $1 billion. Still, a nice piece of change but not exactly what they were used to in 1980.
- The future is both promising and threatening. This is always the case whether or not perceived to be. So, how you look at the future is largely dependent upon your own psychological makeup. Every human is anxious. We want to hear answers we agree with.
- It is better to know some of the questions than all of the answers. That is because the answers don’t work out. To be sure, things are more like they are today than they ever were, but most of us worry over answers to an extent that worry consumes the spirit of action.
- Complacency breeds surprises while fear breeds opportunity. We have a few dozen buttons with sayings on them, some of which are part of this article in various sentences. In this regard, patience is sustained courage, and without curiosity, conviction is stubbornness.
- Take not thyself too seriously. Take your work seriously but don’t confuse brains with a bull market.
This is a good place to say that it is of major importance in using the Theory of Contrary Opinion to be contrary to words and opinions, not to facts. It is words that mislead, distort, and delude. To paraphrase Gustave LeBon, one of the great writers on the crowd mind, we see how words are used as a mechanism of persuasion. The four requisites are:
- Affirmation – affirm the word as truth
- Repetition – repeat over and over
- Contagion – finally it catches
- Prestige – and imitation results
Contrary thinking cannot advise you – it can only suggest Contrary trends. We are creatures of habit and prone to recession or prosperity mentality. The irony is that widely followed forecasts bring about their own demise.
Furthermore, one does not get by in being contrary alone, one must also be curious. Nobody can afford to jump to conclusions since we have to look at the whole picture. The Contrarian can clarify thought so that recommendations fall into place. But don’t force them. Think first. Don’t expect the market to conform to your own preconceived opinions. It won’t. Flexibility plus thought plus work equals a chance for success. Rigidity of mind does rot.
OBJECT, PURPOSE, METHOD, PREMISE
Let us review a bit and put more pieces together. The object of contrary thinking is to challenge generally accepted viewpoints on the prevailing trends in politics, socio-economics, business, and the stock market. Opinions react sharply as people’s emotions – their hopes, fears, and passions – sway back and forth.
The contrarian’s purpose is to contest the Popular View because the view is usually untimely, misled by propaganda, or plain wrong.
The method is to compel thinking and observation in place of conclusion hopping and snap-guessing. “Think prodding” or the necessary concentrated reflection takes practice.
The premise is that alternative ideas make for a clearer, betterdefined judgment. Taking a contrary position frequently will suggest what is NOT coming next. When thinking through opposites, one is led to sound thoughts as to what might come next.
Is the public always wrong? Is the Crowd never correct? After all, we live in the most enlightened democracy of contemporary times, and individuals – acting in mass – pull the voting levers.
For a correct answer we must rephrase the question. Is the public wrong all the time? No. The public is probably right more of the time than not. But the public is right only during the trends and wrong at both ends – usually wrong when it pays to be contrary. (I feel we may include institutions as acting public-like in their investment activities. The market sheep are not all individuals. The fatter flocks just trample more ground.)
Professor H. F. Harding of Ohio State once wrote me that “the odds are always good that the exceptional man is well ahead of the crowd. When they catch up he is off in another direction.” The modern problem is that the speed of change influences the process and tends to compress all movements. Remember Voltaire who said: “It is only charlatans who are certain. Doubt is not a very agreeable state, but certainty is a ridiculous one.”
Contrary Opinion theory is being discussed more and more in the financial media as both professional managers and amateur individuals tend to use the expression when it fits them. Accordingly, everybody is becoming aware that to do the opposite of what most people are doing is the way to win. Simply, you win by being contrary.
Most of us should act as true investors. Forgetting about market liquidity and the speedier ticker tape, while relying on our judgments of what an investment will bring us over longer periods of time than a trading cycle.
There are different approaches to the problem. The specific investment need of many Contrary Opinion readers is to tailor a program around undervaluation. This means you establish that securities purchased are worth more than they are selling. Characteristics and criteria are set up. The following fundamental guidelines serve as a beginning:
- Past records give a point of departure for analysis. Average earnings, dividends, asset values and their trends should be examined. Tangible value is the secret, either in a turnaround situation or a special asset stock.
- New and relevant facts that expect to have an influence may be present. These facts should not yet be fully realized and appreciated by a majority of the financial community. (Clearly, technical analysis offers portraits of sentiment which aid the decision making process.)
- A lower speculative component is essential. The measurement and delimitation of securities into investment and speculative areas is desirable. The method is largely to ignore popular trends and to buy ex-public participation.
- After basic principles, the distinction is still one of personal imagination and ingenuity. Confidence in market level factors influence price-earnings multiples. But a strict ladder analysis, where you try to escalate your stock over comparative choices, is not good practice.
- Try to purchase under favorable conditions. A clear-cut demonstration of superior attractiveness is still subjective judgment. Facts and ideas favorable to purchase are remembered, while negative factors are forgotten.
Do not adhere to any formula or system. Keep no idols, but rather stoke your noggin with antidotes for the temptation of conformity. Rely not on a consensus indicator approach as a substitute for common sense. Then you will not be short-circuited. In fact, you may even win.
This Article Appeared in the MTA Journal, Winter 1989/1990
by James Dines
About the Author | James Dines
James Dines, Editor of The Dines Letter (PO Box 22, Belvedere, CA 94920) and a well-known gold bug, has written several books on technical analysis including The Invisible Crash and How the Average Investor Can Use Technical Analysis for Stock Profits.
Any investor who thinks, “a bull market is a bull market, is a bull market, is a bull market” does not understand bull markets. There exists a very special type of bull market, a “Runaway Bull Market,” or RBM. Because I know of no literature on RBMs, I would like to pull together some of the conclusions about their characteristics.
The most difficult challenge of all, of course, is the very act of identifying this special type of bull market. (That brings to mind the vignette about how to grow a great English lawn: the gardener describes using the greatest seed stock, the finest loam and fertilizer in the soil, the need to tend it carefully every day, to have good location, and so on. And finally the punch line: one needs to do all these things for 300 years.) Comparably, I spotted the RBM based on many years of experience. In fact it is more in the fulfillment of a set of characteristics that we know a RBM is in force, rather than in some specific signal. The young man knows the rules, but the old man knows the exceptions.
Here are the identifying features that I feel delineate a Runaway Bull Market:
1. A wholesale disregard of classic Technical Indicators; not just a few, or many, but where nearly all negative Indicators are wrong. Indeed, the RBM of the late eighties has shrugged off such hoary negative Technical Indicators as Stovall’s Four-Month General Motors Rule, Gould’s Three-Step-and-Stumble Rule, the Inverted Yield Curve, “overbought” markets, and more.
2. Setbacks are either aborted or are too small and brief to trade. In other words, after a sharp rise, instead of the typical “1/3 to 2/3 Technical Correction” such as that first identified by Charles H. Dow at the beginning of this century, a RBM will have virtually no setback. Instead, they have rolling adjustments within flat trading ranges that simply amount to preparation for the next surge of buying.
3. One would logically expect bad economic news to send the market lower, but RBMs seem to be stimulated by bad news to better performance! For example, automobile sales dropped during 1989, yet General Motors continued to make new highs. In fact, negative economic numbers can actually trigger buying frenzies. A RBM either has no perceivable reaction to bad news (1) say, an oncoming recession (2) or, perhaps, it dips slightly but is then followed by explosive buying surges.
4. There is no stock market more profitable – or dangerous to overstay – than a RBM. Since RBMs tend to run their course like the “young blood” of youth, this is a great time for call options: stocks just seem to go up, up, up. Research suggests that RBMs frequently occur after great economic prosperity, especially during the speculative finale in low-priced stocks that usually occurs near the end of long bull markets. During a long prosperity, profits have time to filter down to the lowest common-denominator companies, where a small profit has a huge impact on the bottom line. Thus, during a RBM, especially in its later phases, one would expect more bullish action on the ASE and OTC markets than on the New York Stock Exchange. If, it is mostly blue-chips on the New York Stock Exchange that are in the limelight, we know that there is more time ahead of us before we need to sell.
5. When a RBM ends, it tends to provide a spectacular opportunity to make money on declining markets. In other words, a RBM is apt to end in a “spike” rather than a leveling off to form a gradual Top, so selling must be executed with great precision. RBM’s are incredibly profitable and well worth playing, but very close attention must be given to stop points. You should instruct your broker to act accordingly as soon as a trigger point is reached. How to detect the Top, or sell point, therefore assumes paramount importance, especially considering that we cannot rely on the usual Technical Indicators.
Are we merely reduced to selling whenever an Uptrend line is broken, or when a stop-loss point gets triggered? No, but the main technique will be in the psychological realm. Therefore you might want to review the first third of my first book Technical Analysis, which covers mass psychology, especially the “Greed/Fear Oscillation.”
6. By far the most prominent characteristic of a RBM is that the investing public and professionals regard it with profound skepticism and disbelief. This is a crucial element, and there can be no RBM without it. Thus, we are led to consideration of how we can judge when public fear is replaced by greed, for that will be the first sign of the RBM’s end. Focusing on that crucial aspect of RBMs, we first must distinguish between stock market and economic factors.
The Conference Board reported that consumer confidence reached a 20-year high in July 1989. Psychologically, that was because consumers are looking at low unemployment levels around 5%. Also, with around 200,000 new jobs being created each month in the US, dropping interest rates, and low inflation levels, such confidence was understandable. But note very carefully that consumer confidence has little to do with stock-market investor confidence; the latter’s motivation is fear and a clear, sharp memory of the Oct 1987 bear market (or “crash,” as tyros might describe it).
For what then should we look when measuring the type of public pessimism that would keep us in this stock market-hopefully making big profits? Most important is what is NOT happening! For example, when the Dow Jones Industrial Average (DJI) made a new all-time high in August 1989, there were no magazine covers featuring this event; in fact the new high was greeted by yawning indifference! Also, there was no news of “hot new issues going to immediate premiums.” There were no large secondary offerings, and in fact the news emanating from Wall Street was remarkably subdued considering the DJI’s huge rise since 1987. Because the public buys its stocks through Wall Street, Wall Street is a wonderful mirror of what is truly happening in the minds and wallets of investors. Note carefully it doesn’t matter whether investors talk optimistically, only whether they actually buy stocks. During 1989 the cash position in mutual funds was increasing steadily. In other words, fund managers sold into the strength because they disbelieved it!
Yet more evidence of professional pessimism at that time could figure in the price of a seat on the New York Stock Exchange. In late 1989, the price was below where it had been in Oct 1987! Since such seats are bought by professionals, this was another gauge of negative professional sentiment,
7. Another characteristic of REMs is gloom and-doom in the financial publishing industry, which the following quotation exemplifies.
No Boom on Wall Street for Printers
While the stock market reaches new highs, the Crash of1987 is still taking its toll on the financial printing business. Sorg Inc., one of the nation’s oldest and largest financial printers, filed for protection under Chapter 11 of the Federal Bankruptcy Code, joining Charles P. Young, founded in 1902, which filed for bankruptcy earlier this month, and Packard Press and its parent company, the Basix Corporation, which filed in January 1988. It will not be long, analysts and industry experts say, before these companies are joined by others as the industry continues to reel.
The New York Times, 12 Aug 89
Normally, one would think the bull market of that time would have meant prosperity for the financial publishing industry. At this same time, Charles Githler’s Investment Seminars International held a seminar in San Francisco. I noted how much smaller the crowds were than in August 1987, just before the market broke dawn. Since tickets run $700 apiece, attendance is obviously not casual, and as such it is an important gauge of investor sentiment. Charles Githler told me that he had had a record 750 attendees in Aug 87, and a record low of around 350 the following year.
In 1989 according to a number of newsletter editors, the industry was in its worst depression ever. It has been my experience over the last 35 years that new subscriptions remain very low all the way up in a bull market, until a Top is approached. By the time the public turns bullish enough to subscribe to a newsletter, a Top is no longer far away.
8. Self-observation is a crucial aspect of self control. As a RBM rises in its final phases, excitement and greed will become palpable. Remember the theory that all gamblers secretly want to lose; it’s the source of mass masochism that leads the public to sell out at Bottoms and to buy at Tops.
The same thinking can be applied to the decline in the price of a seat on the New York Stock Exchange, mentioned above. Normally, one would expect such seat prices to rise with the market, because more public participation means higher commissions, but in a RBM this Indicator is reversed.
9. As an example of how self-observation becomes crucial during a REM, if you are afraid to buy, if you tremble at the thought that as soon as you buy something the stock market is going to collapse, that is bullish. It is when you take a second mortgage on your home to buy stocks, or when you are extremely confident when buying, that you should recognize the personal sign to get out.
10. The above nine points are a highly intangible evaluation. RBMs tend to move with great rapidity so we have to institute “trigger” points, just in case. Remember, deep Corrections are not a feature of RBMs, so at the first sign of a deep Correction it becomes necessary to take precautions. How deep is deep? Well, there is no easy answer to that one, and we will all have to use our own judgments and limits.
Excerpted from The Dines Letter, September 1, 1989
This Article Appeared in the MTA Journal, Summer-Fall 1994
by Jim Forte
About the Author | Jim Forte
Jim Forte has been using technical analysis professionally and personally in both stocks and commodities since 1986. He is currently employed in the research services department of a major brokerage firm where he maintains a market update service. He studies and teaches Technical Analysis at Golden Gate University in San Francisco and also offers seminars. He is a professional member of IFTA and the TSAA of San Francisco.
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:
- 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.
- 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.
- The Law of Effort 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 anticipation 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 schematics 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/re-accumulation 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 accumulation. While this basic model does not offer us schematic for all the possible variations in the anatomy of the TR, it does provide us a representation 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 Preliminary 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 Selling 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 re-accumulation (a trading range within a continuing up move), 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 previous move. 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 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 Don the Accumulation Schematic 1) usually contain the price action in Phase Band 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 preferred, 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 unfolding 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 timing, what should follow here is a consistent dominance of demand over supply as evidenced by a pattern of advances (SOSs) on widening spreads and increasing volume, and reactions (LPSs) 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 “Backing 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.
Accumulation Schematic
Phases A through E: Phases through which the Trading Range passes as conceptualized by the Wyckoff method and explained in the text.
Lines A and B… define support of the Trading Range.
Lines C and D… define 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 signa1 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… selling pressure 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.
(STs) Secondary Test(s)… revisit the area of the Selling Climax to test the supply demand balance at these price levels. If a bottom is to be confirmed, significant supply should not resurface, and volume and price spread should be significantly diminished 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 marketís 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 usually 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 interests with additional supply from weak holders at low prices.
Jump Across the Creek (JAC) 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 (BU) to a Last Point of Support (LPS) – 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 SOSs and LPSs is good evidence that a bottom is in place and Price Markup has begun.
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 in the patterns of a distribution TR, they do provide us with the important Wyckoff principles often evident in the area of distribution and the phases 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 widespread 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 Distribution market top.
Phase B
The points to be made here about Phase Bare the same as those made for Phase B within Accumulation, except clues may begin to surface here of the supply I 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 mayor 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 shake 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 up thrust 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 dominate increases either with a break through the “ICE” or with a further SOW into the TR after an up thrust.
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, 15, 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 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 its 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 versus 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 “”” 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 eventual move out of the TR and help us to determine if those trading opportunities favorably meet or exceed our reward/risk parameters.
Distribution Schematics
Schematics 2 and 3 show us two model variations of a distribution Trading Range.
Phases A through E… phases through which the Trading Range (TR) passes as conceptualized by the Wyckoff method and explained in the text.
(PSY) Preliminary Supply… is where substantial selling begins to provide pronounced resistance after an up move. Volume and spread widen and provide a signal that the up move may be approaching its end.
(BC) Buying Climax… is the point at which widening spread and the force of buying climaxes, and heavy or urgent buying by the public is being filled by larger professional interests at prices near a top.
(AR) Automatic Reaction… with buying pretty much exhausted and heavy supply continuing. an AR follows the BC. The low of this sell-off will help define the bottom of the Trading Range (TR).
(ST) Secondary Test(s)… revisit the area of the Buying Climax to test the demand/ supply balance at these price levels. If a top is to be confirmed, supply will outweigh demand and volume and spread should be diminished as the market approaches the resistance area of the BC.
(SOW) Sign of Weakness… at point 10 will usually occur on increased spread and volume as compared to the rally to point 9. Supply is showing dominance. Our first “fall on the ICE” holds and we get up try to forge ahead.
The ICE… is an analogy to a wavy line of support drawn loosely under reaction lows of the Trading Range. A break through the ICE will likely be followed by attempts to get back above it. A failure to get back above firm support may mean a “drowning” for the market.
(LPSY) Last Point of Supply… (Schematic 2/Point 11): after we test the ICE (support) on a SOW, a feeble rally attempt on narrow spread shows us the difficulty the market is having in making a further rise. Volume may be light or heavy, showing weak demand or substantial supply. It is at these LPSY’s that the last waves of distribution are being unloaded before markdown is to begin.
Schematic 2/Point 13: after a break through the ICE, a rally attempt is thwarted at the ICE’s surface (now resistance). The rally meets a last wave of supply before markdown ensues.
LPSY’s are good places to initiate a short position or to add to already profitable ones.
(UTAD) UPthrust After Distribution… (See Schematic 3/ Point 11). Similar to the Spring and Terminal Shakeout in the trading range of Accumulation, a UTAD may occur in a TR of distribution. It is a more definitive test of new demand after a breakout above the resistance line of the TR, and usually occurs in the latter stages of the TR.
If this breakout occurs on light volume with no follow through or on heavy volume with a breakdown back into the center of the trading range, then this is more evidence that the TR was Distribution not Accumulation.
This UTAD usually results in weak holders of short positions giving them up to more dominant interests, and also in more distribution to new, less informed buyers before a significant decline ensues.
REAL WORLD EXAMPLES
In addition to the model schematics provided here, some empirical examples of real world trading ranges are also presented (see pages 30-31), where Accumulation/Re-accumulation preceded a Markup, and Distribution preceded 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 of Stocks and Commodities, Seattle, 1990.
- Pruden, H.O. and Fraser. B., The Wyckoff Seminars, Golden Gate University, San Francisco, Fall 1992 and Spring 1993.
- Wyckoff/Stock Market Institute, literature, illustrations, and audio tapes. 13601 N. 19th Avenue, Suite 1, Phoenix, Arizona 85029, Tel: 602/942.5581, Fax: 602/942.5165.
- Charts supplied by Telescan 3.0, Houston. Texas.
Long Term Accumulation
Phase A: Shows us the PS & SC with the exhaustion of supply as the steep downtrend in ending. The AR & ST set the approximated boundaries of the TR to follow.
Phase B: In the early stage, we see a wide swing & higher vol, and the first signs of demand asserting its dominance, as professionals are absorbing supply. Late in Phase B, low vol shows supply has dwindled at the TR lows.
Phase C: Gives us a final unconvincing test and break of the TR lows on extremely light volume. This is followed by a SOS on dramatically increased volume.
Phase D: We see a consistent & pronounced dominance of demand over supply on widening spreads and increased volume to the upside. Reactions are comparatively weak and on light volume.
Phase E: The stock is marking up on rising volume. Demands remains in control.
Intermediate Reaccumulation
Phase A: Stops previous move.
Phase B & C: Shows comparatively weak volume on consolidation as stock moves down. Volume very light on series of lower lows on Shakeouts. No new supply on #3 spring. Demand showing dominance as stock comes off spring.
Phase D: Shows continuing pattern of demand in control. Gives us sufficient evidence to add to our longs on pullback
Phase E: Stock Marking Up. Demands in control.
Distribution
Phase A: Shows us PSY and Push to new highs (BC) on falling volume. ST fails and closes below BC high. The subsequent downward immediately precedes. The next attempt, a few days later, is on poor volume and cannot reach previous light.
Phase B: Gives us some early clues that supply is in control. Bearish activity is evident showing a SOW on increased volume and the rallies on comparatively low volume indicating a lack of demand. Phase B also shows a breakthrough the TR Support Lines. Subsequent rallies are also on poor volume. Additional Breaks of Support line on even higher volume.
Phase C: We break through the ice and manage to rise above it, however, volume in unconvincing. We can only rise to meet resistance at the supply line and the bottom of our initial trading range. This gives us as LPSY and an opportunity to take a short position with a well-delineated risk just about the previous high at 19 1/2.
Phase D: We fall through the ice again, but on significantly higher volume. We have no rallying power and a feeble attempt to reach the ice fails. Supply has continued its dominance. We are given a last opportunity to add to our short position on the rally back to the ice.
Phase E: Markdown accelerates and supply is in control.
Intermediate Reaccumulation
Phase A: Shows Buying Climax stopping previous up move and more pronounced preliminary support and selling climax facilitating accumulation into stronger hands.
Phase B: Inconclusive evidence but does show us evidence of rally on good spread and volume.
Phase C: Shows final low on diminished volume compared to ST and holds support area above climax low. Move off of low shows pattern on expanding spread and volume.
Phase D & E: Continues pattern of Demand in Control.
Distribution
Phase A: We see the up-move stopped by PSY and the BC. We have and AR and an ST.
Phase B: In phase B relative equilibrium on low volume. No clear indications seem revealed by a #3 spring before the upthrust.
Phase C: As in our #3 Schematic, MTA however shows us a UTAD and then quickly returns to the trading range. The UTAD follows the right side of the TR in phase C.
Phase D: Shows a progression of declines and rallies with higher volume on the down swings. A Supply Line is evident. Breaks through the ice.
Phase E: Our rally back to the ice fails and markdown accelerates.
This Article Appeared in the MTA Journal, Spring-Summer 1996
by Brent L. Leonard
About the Author | Brent L. Leonard
Brent L. Leonard is an Options Specialist at Schwab 500 in San Francisco, is Vice President of the Technical Securities Analysts Association of San Francisco, and is completing his Master’s in Finance and Level 3 of the CMT designation.
Brent has taught classes in technical analysis at Golden Gate University and Schwab University and has lectured before various groups such as A.A.I.I. He has written several articles on technical analysis both locally and nationally.
Brent attended Stanford University and University of the Pacific, receiving a degree in education, later completing a business curriculum with honors at Mesa College in San Diego.
The purpose of this review paper is to list, explain, and evaluate several well-known stock market sentiment indicators over many periods of time. These indicators include Option put/call ratios, advisory letters, short interest, mutual fund cash, and other contrary, against-the-crowd statistics.
The reason that this is a Review article rather than Research is that there has been much written on these indicators by the experts of the industry (although very little recently, which I hope to update). Each indicator’s peaks and troughs will be juxtaposed with the appropriate index or average. I intend to first define and describe each Indicator and assess its efficacy; then, in a Discussion section. I place each on a Bell/Growth Curve model in its appropriate place in time.
These findings should be of use to anyone who needs to ascertain market direction and reversals for trading.
Much has been written over the years about contrary opinion; it has become widely accepted and clever to go against the crowd – “When everyone looks one way, look the other!” Although primarily a true concept, there are a few considerations I would like to bring to light. Most serious investors are familiar with the South Seas Bubble and Tulip Bulb Mania from Mackay’s Extraordinary Popular Delusions and the Madness of Crowds. Although history repeats itself, it almost never does it exactly in the same way. Try developing a tulip craze in Holland today, or, observe the Deutschbank’s tight stance against inflation after the wheelbarrows of DMarks decades ago.
In his talk at the 1994 annual TSAA conference in San Francisco, John Bollingcr stressed how important it is to know against whom to be contrary. Should one take a position against the world being round, or the sun rising tomorrow? Rather, the successful investor has to establish, through introspection, an internal monitor which will warn him when he has stopped doing his own analysis and has begun relying on peers, media items, or a guru for opinions, “tips,” and timing.
In his book, Humphrey Neill explains that contrary opinion is not necessarily cynical or negative, but sees both sides of an issue using one’s experience and logic to see reality. Just as some oscillators can be useful in the middle of a trend but wrong at the extremes, so are the majority often correct during a Bull or Bear market but manically wrong when it reverses, especially when they are required to act, like buy or sell, rather than just observe. Examples of herd logic at these junctures are “This time it is different,” or “What can possibly go wrong.” or at the nadir, “This company is doing everything wrong – it’s hopeless.” In the following pages I would like to illustrate which indicators are the most effective in forecasting markets, individually and in combination.
One category of sentiment measurement is the surveys found in Barron’s and elsewhere on advisors, letter writers and investors. Although the majority or these surveys only go back a few years, their roots can be found (according to Neill) in an SEC poll before the Crash of ’46 where advice from Brokers and Advisors showed a bearish percent of only 4.1%. Earl Hadady of the Bullish Consensus feels so strongly about this indicator that he feels (in his excellent article in the 1986 MTA Journal) that Polling is a third and most important method of analysis, above Technical and Fundamental. The basic question of why investors bought or sold (the public needs answers, the media attempts to fill that need, either in honest attempts or in some cases intentionally misleading) is not important; rather what the public is really doing, as manifest in the Technical signals of Price and Volume over Time. Unfortunately, just as the media and economists range widely in their beliefs and advice, so do technically-oriented gurus and letter writers. As Hadady points out, extreme examples (70% or more) occur less than once a year. If 80% are of one mind, only 1 of 5 traders (especially in zero-sum Futures markets) hold a contra position – therefore they are the strong hands of Richard Wyckoff’s Composite Operator, or the Big Money that controls markets), impervious to margin calls or scared money and in no hurry to get out without a large profit when the majority is sated – as indicated when favorable news now has no effect. It is at this point that shorts are covered, margins are full, and complacency is rampant.
In summation then, by way of paraphrasing into an anagram, Edwin Lefevre in Reminiscences of a Stock Operator, the motto F.I.G.H.T. could represent Fear, Ignorance, Greed, and Hope over Time exemplifying the emotions which we need to control to be the ultimate, dispassionate Composite Operator, or ideal trader.
One way to analyze markets by the notion that there is a “controlling factor” or Wyckoffian Composite Operator behind market movements was portrayed in a white paper written by Dr. Henry “Hank” Pruden for a class at Golden Gate University. He likens the market to a clothing Fashion Cycle wherein one or more top designers in the haute couture world decides a new dress length, style, color is needed, it is then created and diffused throughout the fashion elite, adopted and imitated by the general public, until the last housewife in a farm community in the Midwest has given in to the new look. Magazines, stores, media shows have “told” the public what to wear, driving existing dresses, ties, and other clothing into premature obsolescence. Indeed, if print and television media can “hype” or market athletic events, songs and movies, why not glamour stocks, mutual funds and other securities?
THE INDICATORS
The odd-lot short ratio is derived by taking odd-lot purchases added to odd-lot sales, dividing by two (much like open interest in Futures is obtained), and dividing that into odd-lot short sales. I did not find this indicator an effective contrary tool, especially in relation to its success before the current bull market, for the following reasons: only 2 major spikes above 15 occurred in this 12-year time frame (see chart 1). Although both proceeded large up moves, they were the result of a sideways trading range (1986) and a sharp sell off (1990). However, seven other smaller spikes above 10 did not render bull markets. Conversely, low readings did not indicate down moves in the market with three exceptions – 1987, 1990, and mid-1991 – versus several that preceded up moves. Other reasons might include these: smart money was shorting in small odd-lots to avoid the uptick rule, now extant in over-the-counter stocks; some shorting was used in a derivative fashion to hedge and box positions, more than in the past; many odd-lotters with scarce money moved to index and equity options over the past fifteen to twenty years.
NYSE Short Ratio; S&P 500
Merrill Lynch data 1965-94
Looking at monthly data on NYSE short interest ratio and its effect on the S&P 500 Index, historically this was an accurate measure of contrary opinion, where the early adopters of trend were correct and profitable, and those at the manic end (see arrows on the left side of the bottom part of Chart 2) were 180% wrong. Sharp rallies, abetted by short covering, ensued in cyclic fashion. Once we ended the 17-18-year trading range cycle and started the current bull market of 1982, things noticeably changed: shorting became and remained excessive, again mostly due to derivative hedging wherein shorts do not have to be covered and strong hands do not have to meet margin calls. Another factor to consider is that currently over 10% of the NYSE is Closed End funds, mostly bond and country types. Still, as the arrows continue to show, rising spikes seem to jibe with up moves on the S&P 500, with the one exception.
Specialist Short Sales Vs. Public
Merrill Lynch data 1978-94
What appears to be a better indicator of shorting sentiment, although far from perfect, is the Specialist versus Public ratio, shown below (Chart 3). Specialists are the closest persons to buyers’ and sellers’ decisions, although there is a one- to two-week delay in finding their actions. We can observe that not only are the Buy and Sell signals mostly accurate (B & S not mine), with an occasional misfire (0), but over the long haul, timing market trades would afford you better than 50% gain over buy-and-hold. The “middle clip” in Charts 4 & 5 refers to the areas between the dotted lines, lower half.
Mutual Fund Cash Ratio
ICI – Ned Davis Research 1978-93
Chart 4 illustrates how excessive cash can power markets upward while, at least in a major Bull market, too little doesn’t always correlate to a major decline. One reason for this is that the pressure of shortterm performance, especially with “Money Management Consultants” demanding low cash ratios for clients, poses the threat of moving them to another money manager who will “rotate” the cash into another sector. In addition to the fact that excess mutual fund cash does precede rallies, the reciprocal occurrence of mutual fund buying climax (as depicted in the Ned Davis chart 5) precedes either substantial declines, or at least long, sideways trading ranges. Inversely, from the 1987 Crash until well into 1989, Mutual Fund redemptions exceeded sales throughout that up market, just in time to buy (A) into the next decline (B).
Margin Debt 1967-93
Merrill Lynch data
As the long-term chart indicates (Chart 6 with the opposing arrows) Margin Debt has historically been a correct indicator of major tops, especially in 1973, just before 1982 and dramatically in 1987. After the 1990 correction caused the last Margin debt reconciliation or covering, the chart shows a straight up trend, reflecting the investing consumer’s, government’s and even global appetite for spending on credit. Although accurate, like many oscillators the trend can stay in its extreme mode seemingly indefinitely only warning of its imminent bursting.
As I mentioned earlier in the odd-lot short paragraph, when the option market got popular, especially in March 1983 with the advent of the OEX (S&P 100 Index), the least accurate of traders, the under-financed public, switched from odd lots of stock to options on stocks and indices. At the present time, more than 1500 stocks, or 75% of the stock market capitalization, have equity options. The number of sector indices has also burgeoned dramatically. It has been commonly thought that when put volume heavily outnumbers call volume, this is a contrary indicator that the market or underlying entity will rise. This is true for the short-term day trader; however, looking at the history of the OEX on a weekly basis (Chart 7), the opposite seems to be true. Over the 12 years, using Reuter’s parameters of below 0.75 OEX put/call ratio as bearish and over 1.50 being bullish, we can see the high numbers are almost always at the top, providing the put buyers correct. Similarly, the lower numbers consistently occur at or near the bottoms, when the call buyers would benefit, especially in the mid-1985-86 span.
Curiously, from August 17, 1987 to October 16, 1987 the OEX put/call ratio was locked in a 60-100 range, actually rising into the last few days before the crash (theoretically bullish). The highest reading ever was in late 1983 – 9.28 – interestingly, just before the big decline of January 1984 of some 30 OEX points.
Being a veteran Option Specialist for the OEX’s largest trading firm and author of an article in the 1993 MTA Journal (#41) on V.O.I.C.E., a treatment of OEX Volume, and Open Interest input into a TRIN formula with excellent results (as did Jim Martin, Ray Hines, John Bollinger, and others in slightly different ways), I was quite surprised by these findings. Obviously further study using moving averages, and daily data abstracts are necessary to verify this conundrum. Looking at current daily data in the next chart, we do see a more positive correlation between high put volume, both in the OEX and all-equity CBOE charts, and upward price movement. This is fine for day and short term trading, but I cannot use a high coefficient in my Intermediate, positive-trading Master Indicator, for which I am currently collecting data and fine-tuning, possibly for a future paper.
VIX Index
CBOE 1983-91
Just a brief word about the VIX index, which measures the Volatility of the OEX index (S&P 100) from mid 1985 on, as shown in Chart 8 above. It actually depicts the implied volatility of 8 OEX options, in and out the money, near months. Since it has only been around in a Bull market, its only consistent behavior seems to be: down or nonvolatile during moves of the major uptrend, with sharp up spike when the market declines, and flat or coiling during trading ranges. Chart II shows the historical high of 150 in the Crash of 1987, and single digit lows during 1993 and 1994, possibly an harbinger of things to come. Although the VIX is very good for trading strategies (buying or selling options depending on the volatility), I find it less useful than the Option Premium Ratio, which combines put/call sentiment with volatility (see next page).
Option Premium Ratio by Christopher Cadbury, 1986-94
Stocks & Commodities Magazine
A rather recent indicator that has established many valid instances, primarily due to extensive research and several articles by Christopher Cadbury (to whom I owe much gratitude for endless data), is the Option Premium Ratio (OPR). This can only be found in the Sentiment Window, Chart Page of Investor’s Business Daily, item #5, and essentially combines Put/Call Option sentiment with Implied Volatility of the VIX, only it includes all equity options, not just the OEX index. Based on data from 10 years, (although listed Options have been around over twenty) dividing put premiums by call premiums has ranged from .03 to a high of 1.74. Cadbury established that values below .29 and above 1.18 indicate a continuation of the trends down and up respectively – like extreme levels of other oscillators. Conversely, OPR’s from 30 to mid-60s generate buy signals and levels to 1.18, sell signals in about 200 different combinations of occurrences.
Most of these abstracts are proven almost unanimously by 10 to 20 test examples, such as, “Four consecutive day’s of gains or unchanged values for the OPR starting from .32 to .51 have always produced significant rallies in the stock market. A few, however, such as Identical values for the OPR in the range between .80 to .88 separated by 5 to 7 days have always produced significant declines in the stock market have insufficient testing and border on the “whenever I wear a red tie on Friday the market goes up for 3 days” category. Table 1 is a data table of one of the most heavily tested “pattern recognition” examples: it includes the date the 5-7 day series began and the OPR values; the next four columns list the number or Dow Jones points and days just before the event, and the number of points in the subsequent rally with the number of days or weeks to complete it. More will be heard from on this excellent indicator – I intend to include it in my Master Indicator.
Sentiment Indicators – Opinions
Barron’s Polling Surveys
The following section discusses the derivation of the 4 major Sentiment surveys from newsletters along with charts which show Buy and Sell signals and their respective effectiveness, as shown by %Gains – again this paper is to review, not to research the gathering details. Most effective, I found, were the Market Vane and AAII Newsletters.
- Investor’s Intelligence 1966-95. Investor’s Intelligence is published by Michael Burke’s Chartcraft, and expresses the opinions of over 100 advisory letters every week on CNBC and later in Barron’s. Since 1966, this has been an excellent contrary indicator with its “trading range” giving its best signals from high 30s (% of Bulls) as a Buy signal and mid-70s as a Sell. Although the Buy signals have proven very consistent, the Sell indications, which before 1989 were quite consistent although very early (sometimes several months), have been effective in signaling trading ranges as our strong market ensues.
- Consensus, Inc., 1984-94, Kansas City, MO. The Bullish Consensus, from Consensus, Inc. in Kansas City, MO, also uses opinions from advisory services, mostly investment advisors from major brokerages using house organs versus newsletters. These figures also appear on a 900 line and Barron’s on Saturday. As Chart 12 shows, there were a few very minor price reversals on major Sell signals, especially in the coiling action of both the S&P 500 and the indicator the last 3 years. Still, profits would have bested the market as measured by the Buy-Hold strategy (see upper left corner of chart). As I write this paper, this indicator has reached a four-year high of 67 (twice), versus a 71 in the first quarter of 1991.
- Market Vane Corp., 1980-94, Pasadena, CA. An even better sentiment indicator is found in the Market Vane of Market Vane Corp., Pasadena, CA. Comprised of 100 of the top Investment Advisors from Brokers, and obtained on Monday each week, information appears on a 900 phone number and in Barron’s on Saturday of that week. Chart 12 indicates a more precise correlation between reversals, although again the sell signals in a strong Bull market tend to be more of a re-accumulation trading range than SAR (stop and reverse). Once more, the last several years resemble coiling action (extension waves of lesser degrees) with lower highs and higher lows in the Indicator. The chart ends with the spring of 1994 correction as the O/P line portends a large up move in the near future. During the writing of this paper, it rallied up to 62 for the first time since 1987. At this time, March 25, 1995, it is curiously near midrange, or 47 to 53 area, not forecasting the selloffs of the previous 3 indicators.
- American Association of Individual Investors Survey -1987-95. The final Indicator of the Barron’s group is the AAII, or American Association of Individual Investors of Chicago, IL, the true retail trade. With 25 postcards mailed out each day of each week, nearly 100 come back with each investor’s opinion of the market for the next six months. As might be expected, this indicator has an almost perfect correlation exemplifying the aforementioned “crowd” syndrome. Gains Per Annum show more than 3 to 1 improvement over buy and hold.
DISCUSSION SECTION
In assembling and analyzing all of the above data, what becomes increasingly evident is the difference in the time factor of each. After working nearly a year on constructing a Master Indicator from the most successful of these Sentiment Indicators, it is very apparent that each of them has a different time frame. For example, the timing of the Put/Call OEX ratio is much more short-term than Margin Debt or Mutual Fund Cash. Not only that, the optimum position on the Bell/ Growth Curve (taken from the work of Everett in 1970) on the next page is quite different. It is only through a corroborating “nesting” of several indicators that we can hope to validate the Master Indicator, which would be a great topic for a future paper. Using Table 2 as a guide, with help from data by Yale Hirsch in his book Don’t SeIl Stocks Monday, I will try to place each Indicator on the Curve on Chart 14 somewhere between A and E. The graph is a model illustrating a homogeneous population of investors and sentiment indicators, and not an actual frequency distribution. The Growth line represents a Price line and an accumulation of the aggregate Indicators, while the Bell Curve depicts Volume as well as the timing phases. Beneath the Bell and Growth Curves I have listed the indicators under study.
Odd-lot shorting would be the highest early in A, with Public entering in the C segment – they would have to cover by C, with the Specialists starting to short at E. Mutual Fund Cash would be large at A, fueling the run through D, when it would drop into the single digit percentage. Conversely, Margin would be at its low at A, becoming manic at C and D, where the rising slope is sharpest. After an intensive study of the history of the OEX Index, I can only find it useful in a contrary way on a very short-term basis. Another look at Chart 7 shows that in almost all cases, except in tops of 1986 and 1987, high numbers were found at tops, low at the bottoms, meaning traders were correct in the long view. I must say that our current Bull market has had high numbers from hedging and from those speculators trying to call the top of this market. Similarly, the VIX Index and the Option Premium Ratio, derived from option premiums rather than volume, are short-term, and would therefore be difficult to place on the Chart.
Finally, Bearish Sentiment and gloom from investment letters and media (magazine covers, financial newspapers and TV) respectively, would be persuasive coming into A; they would gradually mutate into complacency through C, and outright euphoria and certainly by E.
CONCLUSION
In conclusion, what I have learned in researching and writing this paper is that although the basic concepts of Sentiment and all of Technical Analysis are eternal, some things do change as markets change. For example, sentiment indicators such as Odd-Lot Shorting were rendered less effective by other inexpensive derivatives, such as options.
Also, just as some Oscillators change parameters in Bull versus Bear markets, Sentiment indicators are less reliable in cases like the present, where the stock market does virtually nothing but rise, with an occasional sideways trading range. Nonetheless, the most effective of the previously reviewed categories, newsletter polling results, mutual fund cash, specialist short selling, and even option put/call ratios, should be monitored for giving reversal signals at extreme excesses, in conjunction with other technical tools such as cycles, oscillators, and support/resistance.
Sentiment is as important as any other technical tools used by Technical Analysts, and will continue to be so as we enter the area of “Behavior Finance” employing Neural Networks to quantify the Psychology of Investing.
BIBLIOGRAPHY
- The Crowd by Gustave LeBon, 1982. Cherokee Publishing Co.
- The Art of Contrary Thinking by Humphrey B. Neill, 1992, Caxton Printers
- Reminiscences of a Stock Operator by Edwin Lefevre, 1923, Doran, Fraser Publishers
- Don’t Sell Stocks on Monday by Yale Hirsch, 1986. Facts On File Publications
- MetaStock Technician Odd-lot, 1982-94
- Trendlines Odd-lot Short Sales, 1991-95
- NYSE and Specialist Short Sales, Merrill Lynch Data
- Investment Company Institute – Mutual Funds
- Ned Davis Mutual Fund Buying
- VIX Chart, CBOE (Chicago Board of Options Exchange)
- Option Premium Ratio by Christopher Cadbury
- Merrill Lynch charts on Investor’s Intelligence, Consensus, Inc., Market Vane Corp., and American Association of Individual Investors
- OEX put/call ratio data, Bloomberg News
- OEX charts -Reuters/Quotron Advantage AE
This Article Appeared in the MTA Journal, Winter-Spring 1998
by Jurrien Timmer, CMT

About the Author | Jurrien Timmer, CMT
Jurrien Timmer, who holds a Chartered Market Technician (CMT) designation, is the director of Global Macro at Fidelity Investments. Fidelity Investments is a leading provider of investment management, retirement planning, portfolio guidance, brokerage, benefits outsourcing and other financial products and services to more than 20 million individuals, institutions and financial intermediaries. In this role, Mr. Timmer is part of Fidelity’s Global Asset Allocation (GAA) group, where he specializes in asset allocation and global macro strategy. Additionally, he is responsible for analyzing market trends and synthesizing investment perspectives across Asset Management to generate market strategy insights for the media, as well as for Fidelity’s clients. Mr. Timmer has been at Fidelity for 22 years and has more than 30 years of experience in the industry.
Prior to assuming his current position in 2005, Mr. Timmer held various other roles within Fidelity, including director of market research and technical research analyst. He also co-managed Fidelity Global Strategies Fund from 2007 to 2014. Before joining Fidelity in 1995, Mr. Timmer was a vice president in the Fixed Income group at ABN AMRO. He has been in the financial industry since 1985.
Mr. Timmer earned his bachelor of science degree in finance from Babson College. He was born and raised a Dutch citizen in Aruba, but has been living in the United States all of his adult life. He became a United States citizen in 2002.
ABSTRACT
It is a widely held assumption among stock market professionals that the two principal fundamental drivers of stock market performance over the intermediate term are earnings and interest rates, the combination of which form the dividend discount model. The goal of this paper is to create such an indicator for the S&P 500, and, through traditional technical analysis, develop a trend/momentum-based timing indicator that signals periods of intermediate term risk. This timing indicator is intended for investment managers for hedging purposes.
The idea of developing the indicator described in this report was inspired by Paul Macrae Montgomery’s presentation at the 1996 MTA Seminar.
PART I: THE FUNDAMENTAL INPUTS
The oldest and most traditional method of “fundamental” valuation in the stock market is the dividend discount model. This model takes actual or expected earnings or dividends (D) and divides that number by a discount rate (I) in the following formula to arrive at a “fair value” for stocks (P):
P = D/[1+I/100]
The numerator and denominator, earnings and interest rates, comprise the principal inputs for this fundamentally-driven valuation model. For the technical analyst, it may be useful to combine this kind of fundamental valuation with traditional technical analysis in the form of trend and momentum studies in order to identify specific time periods during which the stock market is at risk on the basis of earnings and interest rates.
In doing so, we first have to chose the fundamental inputs to be used for our study. The two primary options in terms of the numerator are earnings and dividends. Both are a manifestation of the same underlying fundamental condition of a stock or stock index, but earnings tend to fluctuate a bit more than dividends (because the latter are set quarterly by companies). As a result, earnings are probably a better gauge for valuation purposes, as long as they are taken over more than one quarter. The next decision is whether to use actual earnings or expected earnings. Actual earnings are conventionally looked at on a quarterly or four-quarter trailing basis (in order to smooth out quarter-to-quarter fluctuations), making it a backward-looking or lagging indicator. Since expected earnings are by definition forward-looking (making them a leading indicator), they offer a better guide for valuation purposes as long as the forecasts are reliable. Reliable in this case means reaching a critical mass in terms of earnings estimates by taking the consensus of major research analysts. Since the early 1980’s, two firms have been providing consensus earnings expectations for the S&P 500 by polling the estimates of major Wall Street firms for the earnings of the S&P 500 on a 12-month-forward basis. The companies are I/B/E/S and First Call. For this paper, the data from I/B/E/S are used. Chart 1 shows both the lagging and leading earnings figures for the S&P 500. The top clip depicts a weekly bar chart of the stock index, going back to 1982. The middle clip shows the expected earnings on a 12-month-forward basis, and the bottom clip shows actual quarterly earnings. While Chart 1 shows both estimated earnings and actual earnings, only expected earnings will used from here on in order to make it a true leading indicator. Because the earnings estimates begin in 1982, that will be the beginning of the study.
The next step is to look at the denominator: interest rates. Because equities are long-term assets, a long-term interest rate should be used, such as the 30-year Treasury or Moody’s long-term BAA corporate bond yield. For the purpose of this exercise, the Treasury long bond is used because data are widely available and because the bond is always about 30 years to maturity (whereas the Moody’s yield reflects an index which changes over time, making it unclear whether the duration has remained stable over the past 15 years). Now that the interest rate vehicle has been established, we have to determine how we are going to discount the earnings numbers. The conventional (orthodox) method divides the earnings number by [1+I/100]. Another way, however, was recently demonstrated by Paul Macrae Montgomery at the 1996 MTA Seminar, and consists of simply dividing the earnings number by [I/100]. We’ll call this the unorthodox method. Chart 2 shows both measures. The middle clip shows the orthodox method (right scale) while the bottom clip shows the unorthodox (left scale). The discount factors have been inverted to show their correlation to stock prices.
Note that, while both series look exactly the same, the bottom number is much larger (e.g. 14.14 vs. 0.934 as of September 13, 1996). As a result, when both series are multiplied by the numerator (or when the inverse is divided), the latter approach will cause a much bigger impact on the product of the discounting equation. The effect of both methods is shown on Chart 3.
The top clip shows again the weekly S&P 500. The middle clip shows expected earnings using the orthodox approach, and the bottom clip shows the effects of the unorthodox approach. It becomes immediately apparent that the second discounting method reflects the course of interest rates in a much more pronounced way. Thus rather than just reflecting the earnings outlook, this series now truly combines the effect of both earnings expectations and the course of interest rates. Because we want to create an indicator that uses both of these drivers, the unorthodox discounting formula of D/[I/100] is the one we will use to build our technical indicator.
Now that we have created the time series (which will be called “E/ I” from now on) on which to build our trend/momentum indicator, it is useful to show what the correlation actually is between our computed study and the S&P 500. Chart 4 shows both time series on a log scale.
The chart nicely illustrates how the stock market usually correlates with E/I, but that there are times when significant bearish divergences occur between the two, creating periods of risk. The 1983/84 correction, the 1987 crash, the 1990 correction, the 1994 correction and the sell-off in July 1996 all stand out as such periods. As was described earlier in this paper, the goal here is to identify these periods through the application of technical trend and momentum studies. The product of these studies will be an indicator that gives the appropriate warnings signs when these divergences reach dangerous levels.
First, however, we should quantify the reliability of E/I by performing a linear regression (using the least squares approach) in order to determine what the correlation is between E/I and the S&P 500. Table 1 shows the output of this regression (using the computer program “Econometric Views”), and below that is a graph depicting the independent variable (E/I), the dependent (fitted) variable (S&P 500), and the residual.
The key statistic to look at in Table 1 is “R-squared,” which measures the success of the regression in predicting the values of the dependent variable within the sample. An R² of 1.0 means that the regression fits perfectly while a reading of 0 means that it fits no better than the simple mean of the dependent variable. In our regression the R² is 0.95239, which is an excellent fit. This means that 95 pct of the behavior in the S&P 500 can be explained by the behavior of E/I. This is encouraging, because when we build our trend/momentum indicators, we will have confidence that we are “barking up the right tree,” as it were.
PART II: THE TECHNICAL INDICATOR
Now that the input has been created and tested for reliability using quantitative analysis, we can get to the juicy part as technicians and build a risk indicator for the S&P 500. Three traditional technical studies are calculated. Two are momentum studies: a 26-wk rate-of-change (ROC) and a 52-wk slowed stochastic (STOCH). One is a trend study: a 13-wk/26-wk Moving Average Convergence/Divergence (MACD). The time frame for these studies is the intermediate term (3-mo-12-mo), given that the intended audience for this indicator is portfolio managers.
Table 2 shows the one year’s worth of data and formulas. Column C shows the weekly closing levels for the S&P 500. Column D shows the I/B/E/S earnings estimates. Because the series is monthly and our study is weekly, the same number is repeated for all the weeks in any month. Column E shows the 30- year Treasury yield and Column F shows our indicator E/I. Columns G through P show the output for the above stated studies.
The technical studies are calculated as follows:
➱ 6 mo ROC: This is a simple rate of change indicator using the formula:
For example, the ROC (column G) of E/I (column F) as of 9/13/96 (row 52) is [566.20 ÷ 575.26] -1 * 100 = -1.575, meaning that E/I is 1.575 pct lower than it was 6 months ago (row 26). This is a useful measure for indicating positive or negative momentum in E/I.
➱ 52-wk STOCH: This is a more complicated momentum measure, and comprises the following calculations: First, we calculate Fast %K (column M) through the following formula:
Then we calculate the slow %D (column N) by taking a 3-week smoothed moving average (SMA) of the fast %D (the MA is smoothed by taking the sum of the previous three fields, subtracting the most recent MA, adding the latest value, and dividing the result by 3). A slow %D (column O) is calculated by taking a 9-week SMA of the Fast %D. Finally, Column P shows the difference between column N and column O in order to indicate whether STOCH is on a buy or sell signal. A buy signal is given when the fast %D is above the slow %D, and vice versa.
For example, the latest week’s fast %K value is (566.2 – 554.6) ÷ (632.9 – 554.6) = 14.76. The 3 week SMA is [(52.15+20.67+10.99) – 32.51 + 14.76] ÷ 3 = 22.02. The slow %D is 42.93, thus creating a sell signal. Besides giving buy or sell signals, this study is also useful in gauging whether the absolute momentum level is high or low. For instance, a level of less than 50 combined with a sell signal would be quite bearish.
➱ MACD: This is a useful trend study which consists of the spread between two exponentially smoothed moving averages (ESMA) of E/I. The conventional approach is to take 13 weeks and 26 weeks as the two M/A’s. The 13-week exponentially smoothed M/A (column H) is calculated as follows:
where ESMAt13 is the first MA in the series and consists of a simple 13 week MA. The number 0.153846 is the product of a smoothing constant 2 divided by the M/A period of 13. The 26 week ESMA is calculated in similar fashion (column I). The MACD is a simple spread between the 13-wk ESMA and 26-wk ESMA (column J). To create buy and sell signals, a 9-wk ESMA is taken of the spread (column K). Finally, column L shows the difference between columns J and K, indicating whether MACD is on a buy or sell signal. Also, the absolute level of MACD is important to identify the magnitude of rising and falling trends.
For example, the latest value for the 13-wk ESMA is 571.58 – (0.153846 * (571.58 – 566.2) = 570.75. The 26-wk ESMA is 571.58 – (0.076923 * (573.05 – 566.2) = 572.52. The MACD is the spread: 570.75 – 572.52 = -1.77. The ESMA is -2.37, creating a sell signal.
Chart 6 depicts these studies. Chart 6 nicely shows what happens to these indicators when E/I gets into the danger zone as a valuation model for the S&P 500. The major periods of correction/consolidation in the stock market all were signaled by negative readings in the ROC, MACD and STOCH. However, eyeballing these studies to determine risk in the S&P 500 is not very scientific, and a more systematic approach is needed. We accomplish this by establishing certain conditions on the three technical studies. The most straightforward MTA JOURNAL • Fall-Winter 2001 43 approach is to define an “if-then” condition for each study, and then combine the results into a composite trend/momentum signal.
The conditions will be very simple so we can determine if there is method that works (i.e. gives reliable signals) without having to get into back testing and optimization.
- ROC SIGNAL: For ROC, we simply tell the computer to return “TRUE” if the latest reading is below zero, that is E/I is below its level of 6 months ago. Otherwise, return “FALSE.” The results are depicted in Table 3 in column E.
- STOCH SIGNAL: Here we need to add a twist to account for the fact that this indicator can not only be on a buy or sell signal, but can also be overbought or oversold. Therefore, we tell the computer to return “TRUE” if STOCH is on a sell (i.e. the slow %D is below the fast %D) AND STOCH is below 50, indicating that momentum is below neutral (STOCH oscillates between zero and 100). If neither of these conditions is met, the computer returns “FALSE.” Column F shows the results.
- MACD SIGNAL: For MACD, we also set two conditions: return “TRUE” if MACD is below zero, AND it is on a sell signal, meaning that MACD is below its 9 week ESMA. Otherwise, return “FALSE.” Column G shows the output.
Finally, we set a last if-then condition to return “TRUE” when all three individual conditions are true. If only some are true, or if none are true, return “FALSE.”
A “TRUE” therefore will signal those time periods when all three technical studies tell us that the underlying trend and momentum conditions of our indicator E/I are reaching dangerous levels for the S&P 500.
Given that the stock market can ignore rising rates and deteriorating earnings momentum for some time without correcting (as was the case in 1987), it is important to note again that the objective of this signal is to flash a warning to get out of stocks (by hedging) when E/I’s trend and momentum conditions get really dangerous, rather than every time the slightest negative divergence occurs.
Bringing all of this together, Chart 7 shows the S&P 500, our indicator E/I and those periods of risk as defined by our trend/momentum signal. As has been the case with all charts, the S&P 500 and E/ I are charted as a log in order to show price changes in equal proportion.
PART III: IMPLEMENTING THE HEDGING STRATEGY
Before evaluating the success of our hedging strategy, certain assumptions need to be set regarding its implementation.
- The study beginning with a portfolio of $10,000,000 in January 1983. That date reflects the beginning of the various technical studies that are in use. Since they are trend and momentum based, there is by definition a lag between the beginning of the indicator E/I and its studies STOCH, ROC, and MACD.
- The cash portfolio is indexed to the S&P 500 index, and the timing signal is executed through the short sale of S&P index futures.
- The timing model is updated every Friday afternoon at 3:30 pm to allow for enough time for any transactions to be executed in the market as of that week. This is not entirely scientific because the indicator historically reflects end-of-week values, but it will have to do for the purpose of this study. Waiting for the next Monday leaves too large a gap in terms of potential price swings.
- When a signal is generated (i.e. when all three study conditions are TRUE), a transaction is immediately executed consisting of the short sale of S&P 500 futures equal to the total market value of the portfolio at that time. This is done as follows: The market value of the portfolio is divided by the product of $500 and the price of the S&P 500 index. An example illustrating the first signal in 1984 is shown in the table below. On Friday, April 13th, 1984, a signal is given. At that time, the value of one S&P contract is $500 x 156.27 = $78,135. The number of contracts needed to hedge the portfolio is therefore 145 (11,309,853 ÷ 78,135).
- Transaction costs associated with the short sale are as follows: The commission is $16 for a round-trip, and a financing spread of 2 percentage points is applied to the cost of the initial margin. The question of margin is tricky, because if cash on hand is available, then by definition the entire portfolio is not invested in the S&P 500. Therefore, for simplification’s sake, it will be assumed that the margin is borrowed at a cost of 2 pct over and above what the margin amount will earn in the futures account. Additional margin will be applied directly to the cash account, however. Table 4 shows the cumulative drawdown/profit for the hedge.
- When the signal ends (when the condition is FALSE again), the 145 contract short sale is covered. However, this will not be known until the end of that week when the closing figures are inputted into the model. Therefore, when looking at the history of signals, the P&L calculations start with a one week lag and continue for an extra week. The final column shows the portfolio value on a hedged basis.
Table 5 gives the details of all the signals: each observation with start and end date, the number of weeks that the signal is in effect, the start and end values for the S&P 500, the percentage change in the S&P 500, and finally the total effect of hedging the S&P 500 portfolio with futures contracts.
PERFORMANCE
There have been 9 observations, each of which has lasted anywhere from 3 weeks to 11 weeks. The average period lasted about 7 weeks. Six out of nine signals were profitable, or 67 pct. The biggest gain from hedging occurred during the 1987 crash (26.13 pct), while the largest drawdown occurred in 1990, totaling 5.75 pct. The average gain from hedging is 4.57 percentage points. The difference between the change in the portfolio value and the return of the hedge can be attributed to transaction costs and the rounding up or down of the number of contracts that need to be sold short.
Since the beginning of this study in 1983, the average annual total return of a buy-and-hold portfolio has been 15.90 pct, while the average annual return of an actively hedged portfolio using this timing indicator has been 19.64 pct. Hence, the average yearly excess return is 3.74 percentage points.
Chart 8 shows the cumulative total return of our hypothetical portfolio on an actively hedged basis. The dotted line shows the total return on a buy-and-hold basis.
ANALYSIS
A few issues arise when we look at the results.
- The biggest problem is immediately apparent when looking at the bottom two rows of the table as well as the chart with the cumulative total returns: while it is desirable that our indicator captured the 1987 stock market crash, the problem is that it accounts for a big part of the overall profitability. Including the crash, the average excess return is 4.57 pct, but excluding the crash, the excess return is only 1.83 pct. However, from the standpoint of eliminating market risk from a portfolio from time to time, this is still an acceptable performance (because all we’re giving up is upside performance, as opposed to being outright short).
- The study only includes the bull market of the 1980s and 90s, and therefore we are unsure whether it will stand the test of bull and bear markets. The problem is that we want a forward-looking indicator and are limited by the availability of earnings estimates, leaving only 1982 and after. However, we can go back farther in time to assess the validity of the unorthodox discounting method using actual earnings instead of expected earnings. If the correlation of the indicator stands up over a longer period of time (through the same regression analysis as before), we can at least ascertain that the fundamental idea behind E/I is valid. Chart 9 shows E/I using expected earnings after 1982 and actual earnings before 1982. The regression study (not shown) reveals an R² of 92 pct, which is still pretty good for a period of 35 years. As a result, we can maintain confidence that the idea behind the E/I indicator is valid.
- Chart 7 on shows that while the signal captured some corrections perfectly (namely the 1987 crash and the sell-off in July ’96), it has been on the late side in other instances, such as 1990 and 1994. It appears that the sharp price corrections are handled well by our indicator, while the more triangle shaped time-based corrections are handled with less success. By the time the signals occur in the latter type corrections, it seems a better time to buy than to sell. The problem is that if the three studies used for this exercise are made more sensitive (by giving an earlier signal), the sharp advances prior to the 1987 crash and July ’96 sell-off are hedged out, leaving profits on the table. The latter point is a valid one, and the performance table does shows a rather large maximum draw-down of 5.75 pct in 1990. One way to improve the effectiveness of the signal is to try different indicators and to run them through a computer spreadsheet (Microsoft Excel was used for this study).
- The indicator has not only been adept in signaling risk periods, but was very effective in signaling market bottoms as well. The chart shows that while E/I peaks well in advance of the S&P 500 index, it bottoms at the same time as the index. In other words, it is a leading indicator at tops and a coincident indicator at bottoms.
- Relating to the previous point, we see that E/I was also valuable as a confirming indicator of a rising stock market. Knowing that E/ I tended to peak well in advance of the stock market, we can assume that as long as E/I is in its uptrend (making new highs, uptrend lines intact, etc.), it is safe to be aggressively invested in stocks (note the 1995 period). In other words, the indicator worked both ways. When both stocks and E/I are rising and making new highs, stay invested. When the bearish divergence first occurs, it is OK to remain invested, but caution is warranted. As the divergence gets progressively worse and the retracement of E/Is preceding advance deepens, it is time to get ready to hedge. When the timing model kicks in, or when other technical studies indicate risk, the S&P is sold, at which point the end of the signal can begin to be anticipated (in terms of the percentage retracement and the time of the correction). Finally, the signal ends, and the S&P is bought back.
CONCLUSION
We know that the correlation of E/I is 95 pct, meaning that 95 pct of the action in the stock market has been explained by E/I. That is pretty valuable. Therefore, if we compliment the timing indicator with traditional technical analysis (on both E/I as well as the stock market itself), perhaps we can increase its value in identifying risky periods in the stock market, as well as periods during which a fully invested portfolio stance should be adopted. Complementing our indicator with traditional measures such as the Advance-Decline Line, Lowry’s Buying Power, Cash Flows into mutual funds and other sentiment measures should nicely round its effectiveness.
One example of performing additional ad hoc analysis on E/I is shown in Chart 10. There have been four major corrections in E/I (excluding the 1996 decline), each of which retraced between 46 pct and 52 pct of the preceding advance. The average correction is 48 pct. This falls right in the middle of the traditional Fibonacci retracement objectives of 38.2 pct, 50.0 pct, and 61.8 pct. Note also that out of those four corrections, three were doubles (two sell signals). Hence, there is a repeated pattern evident in the behavior of E/I, and that can be very valuable. For instance, we can deduce that the July ’96 correction was perhaps only the first of two correction phases, and that the stock market will remain at risk until E/I corrects by the 48 pct average. It will be up to the technical strategist to combine his or her skills with the knowledge that E/I is a valid leading indicator of stock market peaks. Anything from trendline analysis to time cycles may be of value here.
The indicator developed in this paper, E/I, can be of use when investing in the stock market in several ways. For portfolio managers and position traders alike, utilizing a fundamentally oriented indicator with a 95 pct correlation to stock prices is useful, either through the use of a timing indicator as done in this paper, or merely as an indicator of risk in combination with other indicators. The indicator works both as a risk indicator and as a fully invested indicator. While this paper has focused on portfolio managers who can use E/I to hedge during high risk periods, obviously it can be equally valuable to position traders who can use stop-reverse strategies for either a long-neutral strategy or a long-short strategy. Written in August 1996.
UPDATE – ONE YEAR LATER
Updating the model from the report’s initial publication in August 1996, we find that no further sell signals have been issued since the June/July 1996 signal that captured that sell-off so well. While the indicator E/I did not issue a sell signal going into the April 1997 correction, a more subtle warning was evident in that a bearish divergence occurred at the final high leading into the correction. This reinforces my point that the value of E/I as an indicator is not limited to a buy/sell algorithm, but rather that traditional technical analysis can be performed just as would be appropriate for an advance decline line for example. Since the correction in April ’97 was so short lived, in retrospect the failure of E/I to issue a sell signal probably worked out for the better. Since the April 14th low, the indicator has been making new highs, thereby confirming the bullish price action. August 18, 1997.
REFERENCES
- Paper written by Paul Montgomery for 1996 MTA seminar where he was the featured speaker
- John Murphy, Technical Analysis of the Futures Markets
- CQG, Inc.
- Welles Wilder, New Concepts in Technical Trading Systems
The Story of the Three Stock Market Bottoms
by Ken Safian
About the Author | Ken Safian
Ken Safian, the president of SIR, is a graduate of the Wharton School at the University of Pennsylvania. He started his career at Dreyfus & Co. where the legendary Jack Dreyfus served as his early mentor. Ken has served as a director of the NY Society of Security Analysts, as a member of the National Association of Business Economists and is currently on the Executive Committee of Edward Jones and Co. He was a major shareholder and investment policy director for Regent Investor Services, which managed $3 billion and was sold in the early 1990s to Alliance Capital.
The most unique aspect of this stock market that many investors may be telling their children or grandchildren is the three distinct stock market bottoms that have occurred since March 2000. As page 7 illustrates, more than 50% of the Standard & Poor’s 500 Index groups reached new 52-week lows at the 1987 and 1990 bottoms. Just under 50% reached new lows in 1998. In April 2000, 50% of the groups reached new lows as our Technology Average had its final advance. Investors, therefore, dramatically reduced their more conservative holdings and heavily purchased technology company shares. This was the larger sector bottom for the market since more groups reached their lows at that time.
The second bottom occurred in October 2000 when worse economic statistics were released and investors heavily sold their cyclically sensitive issues. At that time, 25% of the Standard & Poor’s 500 Index groups reached new lows. This sector low was discounting unfavorable economic conditions and the liquidation was for fundamental rather than psychological reasons as was the case in the earlier bottom. Finally, the technology issues reached their lows this March when the media declared Lucent and some other corporations being close to bankruptcy. Fifteen percent of the S&P 500 Index groups hit new 52-week lows at that time. This was a larger psychological bottom due to short selling, but a smaller actual bottom since fewer groups reached new lows. These stocks were no longer as important to the total market because they had already declined so much in dollar values. The media focused on this bottom as being “the” bottom because of the interest in technology issues.
The table below shows the performance of some industry groups during these time periods. These different bottoms in price can also be seen for the breadth series we maintain for our averages (see charts 10 to 14).
This perspective brings up some interesting points. First, the Federal Reserve eased dramatically at the end of 1999 and the beginning of 2000 fearing a year 2K problem could occur. Additional funds were available in the system and investors pushed up the prices of more aggressive (technology) stocks compounding the “bubble.” A year-over-year gain of more than a 150% occurred for our Technology Average in early 2000 while industrial production for technology industries grew at a peak annual rate of gain of 60%. Prior to that, both series grew about the same. It is noteworthy to re-emphasize that most S&P 500 Index groups reached new lows at the same time that our Technology Average reached its peak.
The diversity within the economy, the fiscal drag created by the large budget surplus of our government during the mid-to-late 1990s, and the raising of interest rates by the Federal Reserve when the business conditions were “too strong” also strengthened the dollar. These conditions were quite unfavorable for commodity cyclical industries. Despite those trends, the price of energy was able to rise due to the energy policies of our government and those comprising OPEC. Given these trends, why should there not have been diversity within the economy and stock market and why should they not continue? Finally, if all groups reached their lows, had their good bounces, and the first bottom occurred over one year ago, why should there be an urgency to rush out and buy stocks generally? The technology sector may rally further since that group reached its low most recently. However, most groups backed off after the rally from their bottom was over and we would expect the same situation for technology stocks once their rally is exhausted. Additionally, the rebounds in groups following their lows were about 45% and our Technology Average has rallied that percentage.
The graphic section of our recent study highlights the current technical and fundamental environment. More technical indicators suggest an approaching overbought condition. For example, while more groups were oversold than overbought several weeks ago, there is now an equal number if both the intermediate and long term categories are included. Most recent oversold conditions have been offset by overbought conditions indicating a neutral environment. Investor sentiment data have generally moved to more optimistic attitudes but they are not yet at dangerous levels. Mutual Fund data clearly reflect the divergent trends discussed earlier in this report. There were relatively large net conversions out of aggressive growth funds in February and March, but growth and income funds were getting net inflows. Money managers were also net buyers of stocks and net sold securities other than common stocks which did not indicate bearish attitudes by the mutual fund managers. Net flows into growth and income funds continued in March 2001. From a fundamental point of view, March inventories of technology products still seemed high and new orders of technology products fell below year ago levels for the first time since 1991. The data for the Purchasing Managers’ Survey seemed mixed and may suggest some stabilization. Employment data for April seemed more diverse than generally expressed in the media. For example, the percentage of industries that recorded a greater number of workers on a month-to-month basis has stabilized over the past three months. Structural changes seem to be taking place in our labor force since the number of women workers are falling and men are rising slightly. Additionally, there have been large declines in employment in the personnel agencies category.
We continue to believe the government is and will be the major determinant of economic and sector trends. Congress is now in the process of trying to pass a budget resolution and the Republican leadership must compromise in order not to have that resolution defeated in the Senate. A defeat of a budget resolution in the Senate would mean that future budget resolutions could be filibustered. It seems the government monetary and fiscal stimulus may abort the recession signal given by our Composite Forecasting Index and related data in August 2000 and that greater inflationary pressures should unfold. Our investment policy is unchanged. We would be more diversified but concentrate more in those companies that will benefit from increased government fiscal stimulus and somewhat higher inflation rates. Portfolios should be structured in a similar manner as our Suggested Equity Portfolio for Large Institutional Accounts.
SECTOR ANALYSIS
Sector analysis is an approach that Ken Safian and Ken Smilen (who died several years ago) formally developed in the early 1960s. They developed the Dual Market Principle which first divided the stock market into two major groups – traditional growth and cyclical – and several satellite sectors which included primarily regulated companies or ones strongly influenced by the government such as airlines, utilities, defense, oil and gas. They maintained many fundamental and technical series for these two major groups just as technicians and analysts kept them for the entire market or economy: price, volume, breadth, short interest, odd lot series, dividend yields, P/ E’s, valuation measures, etc. Some of these indicators can no longer be maintained because data are either unavailable or no longer relevant. However, other series and relationships are available and are maintained.
In the mid-1960s when increased government stimulus and coming financial speculation, seemed probable an aggressive growth average started, due to a slowing economy. This index proved to achieve extraordinary price gains almost equaling those of the late 1990s (see table). That average was discontinued because there were so many mergers and restatements of earnings.
In 1971, when President Nixon instituted wage and price controls, it appeared there would be a distinct difference in earning and price performances between consumer related companies and capital goods companies. Two new averages to track these sectors were immediately started. The performance between the Consumer Related Average and the Capital Goods Average was tremendous in 1973: The former average was down more than 38% and the Capital Goods Average was up 22%. Divergences between sectors are nothing new. In 1957, our Cyclical Average declined more than 20% while the Traditional Growth Index increased almost 15%. In our judgement, the current period is a magnification of the sector work started by our firm many years ago and the great degree of change has been caused by the transition within our economy. Our firm now has about 50 individual sector averages for which prices, volume, breadth and other related series are maintained. Our Technology Average data were extremely helpful in detecting the deteriorating technical conditions in early 2000.
Breadth of the stock market can be kept in a number of ways, but the most common method is to merely compute the difference between the number of advances and declines, on a daily or weekly basis and cumulate those figures. If the trend in these breadth series vary from price or the direction of that trend changes, investors can detect transitions within the stock market. Breadth series for most of our sector averages have been very helpful in detecting weaker or stronger technical conditions for individual groups of stocks.
CONCLUSION
The important question regarding the recent, unique occurrence of the differing bottom periods for groups of stocks is whether this will develop again. Will it become a more common technical condition at both market tops and troughs? We believe the answer is: “probably so.” As economic conditions become more complex and world business characteristics differ, we believe there are increased chances for major disparities within the stock market to occur. Furthermore, as more funds for the stock market are in retirement accounts, there are reduced probabilities for these savings to be withdrawn from the stock market, as are regular savings that can go toward the purchase of a house or a car. Therefore, money stays in these accounts and the money managers move funds from one group or type of stock to another. Given these factors, we think varied sector trends will become an increasing probability and should be a major part of technical analysis.
Please see over for the Breadth Series Charts
Exploiting Volatility to Achieve a Trading Edge using an Average-True Range (ATR) Second Filter
by Jeffrey Morton, MD, CMT
About the Author | Jeffrey Morton, MD, CMT
Bio Coming
by Randi Schea, M.D.
About the Author | Randi Schea, M.D.
Bio Coming
ABSTRACT
Purpose: Previously, we have shown that the theoretical returns for a simple non-directional option strategy initiated after a sudden and significant volatility implosion of an underlying stock has a positive expectation with an average return per trade of 4.25%. This study was designed to evaluate whether the addition of a second entry signal based on the average-true-range (ATR) of the daily stock prices could improve the theoretical returns or decrease the drawdowns experienced in the first study.
Methods and Materials: The 30 Dow Jones Industrial Average stocks from November 1, 1993 through May 30, 1998, were chosen for this study. Delta neutral/gamma positive straddle options positions were initiated on the opening price of the stock after two sequential signals were satisfied. The first signal was generated when the near-term historical volatility of the stock had significantly imploded relative to its longer-term historical volatility. The second signal was generated when the daily ATR of the stock began to increase. Any signals generated in the same stock before the 6-week termination date of a prior trade were ignored. On the date of calculation, the options prices were determined with the actual implied volatility using the Black-Scholes model, assuming moderate slippage. All trades were equally weighted. The value of the options positions were calculated based on the closing stock price at the 2-, 4-, and 6- week periods respectively. Two trading systems were evaluated. In the first system (time based system), time was the sole determinant used to determine when the option positions would be closed out. In the second trading system (money management system), simple money management rules were added to reduce drawdowns and to “lock-in” profits in profitable trades. Given the wide variability of brokerage fees, the results are presented without commission costs deducted.
Results: A total of 230 trades were generated between 11/1/93 and 5/30/98. For the time-based trading system (trading system 1), the 2-week, 4-week, and 6-week cumulative return was +88%, +255%, and -151% and the average return per trade was +0.38%, +1.11%, and -0.65% respectively. For the money management trading system (trading system 2), the 2-week, 4-week, and 6-week cumulative return was +219%, +979%, and +1470% and the average return per trade was +0.94%, +4.26% and +6.39% respectively. The use of a simple money management system significantly reduces the drawdowns of the system.
Conclusions: The addition of a second entry filter, ATR, did not improve the theoretical returns of a simple time-based volatility trading strategy that previously had been shown to produce a positive return for positions held four weeks. The addition of the ATR filter did, however, significantly decrease the drawdowns that precluded the original system’s viability as a useful trading strategy in its own right. As in the original study, the addition of some simple money management rules had a dramatic impact on the results. The addition of the ATR filter in combination with some very simple money management rules significantly improved the theoretical returns while simultaneously decreasing the drawdowns when compared to the original study. This improved volatility-based, market-neutral, deltaneutral (gamma positive) trading strategy yielded a very substantial positive return across a large number of large-cap stocks and across a broad 5-year period. These results demonstrate the potential positive returns that can be obtained from a market-neutral/delta-neutral strategy. The benefit of a market-neutral strategy as demonstrated here is of significant importance to institutional portfolio managers in search of non-correlated asset classes.
INTRODUCTION
For options-based trading, the price action of any freely-traded asset (e.g., stocks, futures, index futures, etc.) can be grouped into three generic categories (however defined by the trader): (a) bullish price action; (b) bearish price action; (c) congestion/trading range price action.
Specific options-based strategies can be implemented which results in profits if any two out of the three outcomes unfold. For example, the purchase of both call and put options on the same underlying asset for the same strike price and same expiration date is termed a “straddle” position (e.g., buying XYZ $100 strike March 1999 call and put options = XYZ $100 March 1999 straddle). This straddle position can be profitable if either (a) or (b) quickly occur with significant magnitude (i.e., price volatility) prior to option expiration. In this sense, a straddle trade is non-directional since it can profit in both bull and bear moves.
Price volatility can be described by several common technical indicators including average-true-range (ATR), average-directional index (ADX), standard deviation, and statistical volatility (also called historical volatility). Volatility has been observed to be “mean-reverting.” Periods of abnormally high or low short-term price volatility are followed by price volatility that is closer to the long-term price volatility of the underlying asset.(1,3) A short-term drop in price volatility (volatility implosion) can be reliably expected to be followed by a sudden volatility increase (volatility explosion). Connors, et. al. have shown that multiple days of short-term volatility implosion is a predictor of a strong price move.(1,2)
The volatility implosion does not predict the direction of the impending price move, but only that there is a high probability that the underlying asset is going to move away from its current price and by a significant amount. In a previous study(4) we showed that a simplestraddle, options-based strategy designed to exploit a sudden implosion of a stock’s volatility, combined with a simple money-management strategy, with time as the only existing criteria produced superior returns and, therefore, could be used as the basis to develop trading strategies capable of producing superior returns without the need to correctly predict the direction of a given stock, commodity or market being traded. However, the volatility implosion does not predict when (how quickly) the explosion price move will develop. Further analysis of the previous study indicated that volatility can remain low and even continue to decrease for several weeks. Thus, not infrequently, the trade was stopped-out just before the volatility exploded. It appeared that we were successful at defining periods of low volatility but needed a way of better predicting when the period of low volatility was ending. In this study we investigated the use of a second entry filter based on the average-true-range (ATR) of the recent daily prices as a way for trying to better define the “end of the low period of volatility” and thereby improve the overall returns obtained using the basic option straddle strategy. At PRISM Trading Advisors, Inc., this strategy has been successfully implemented to generate superior returns at lower risk than traditional investment portfolio benchmarks.
METHODS AND MATERIALS
System 1 (Time-Based Strategy): This strategy was tested from November 1, 1993 through May 31, 1998 using the stocks that make up the Dow Jones Industrial Average as a representative sample of the broader market. They were chosen because they are a well-known group of stocks that have been designed to represent the market at large. Volatility is defined by the price statistical volatility formula:
s.v. = s.d.{log(c/c[1]),n} * square-root (365); where:
s.v. = the statistical volatility.
s.d. = the standard deviation.
c = the closing price of the stock on that day.
c[1] = the closing price of the stock of the previous day.
Statistical (or historical) price volatility can be descriptively defined as the standard deviation of day-to-day price change using a log-normal distribution and stated as an annualized percentage. Detailed information on statistical volatility is available from the references.(1,2,3)
Another measure of volatility is the average-true-range (ATR). It is the average of the true-range (TR) of the daily prices over a specified period of time. True-range (TR) is defined as the greater of:
- the difference between today’s high and today’s low,
- the difference between yesterday’s close and today’s high,
- the difference between yesterday’s close and today’s low.
The rules to initiate a trade were as follows:
- Rule 1: 6-day s.v. is 50% or less than the 90-day s.v.
- Rule 2: 10-day s.v. is 50% or less than the 90-day s.v.
- Rule 3: Both Rule #1 and Rule #2 must be satisfied to trigger completion of the first trade signal.
Thus in this study, the first signal, a volatility implosion, occurred when the 6-day and 10-day historical volatilities were 50% or less than the 90-day historical volatility.
- Rule 4: Rule #3 must be satisfied before proceeding to Rule #5.
- Rule 5: The trend of the 14-day ATR, when the first trade signal is triggered, must be flat or in a downtrend.
- Rule 6: The 14-day (ATR) today must be greater than the 14-day ATR yesterday.
- Rule 7: The 14-day (ATR) yesterday must be greater than the 14- day ATR two days ago to initiate the trade.
Thus the second signal, the beginning of an increase in volatility, occurred when the 14-day ATR increased for two consecutive days.
When these conditions were met, a signal to initiate a straddle position was taken the following trading day. The Black-Scholes model was used to calculate the options prices that were used to establish the straddle positions. The opening price of the stock, the actual implied volatility, and the yield of the 90-day U.S. Treasury Bill were used to calculate the price of the options. The professional software package, OpVue 5 version 1.12 (OpVue Systems International), was used to calculate the options prices assuming a moderate amount of slippage. For the purposes of this analysis, it was assumed that each trade was equally weighted and that an equal dollar amount was invested in each trade. Based on the closing stock price, the value of the option straddle positions were then calculated using the same method described above after 2-weeks, 4-weeks, and 6-weeks respectively. Any trading signals generated in a stock with a current open option straddle position before the end of the 6-week open trade period were ignored. To minimize the effect of time decay and volatility, options with greater than 75 days to expiration were used to establish the straddle positions. The positions were closed out at the end of the 6-week time period with more than 30 days left until expiration. To further minimize the effect of volatility, options were purchased “at or near the money.” Given the current large variability of brokerage fees, the results were calculated without deducting commission costs.
System 2 (Money-Management Strategy): As in the original study, a second trading strategy was explored. It was identical to the first trading strategy above except that a set of simple money management rules were added. The rules were designed to 1) cut losses short, 2) allow profits to run, and 3) lock in profits.
- Rule #1: A position was closed immediately if a 10% loss occurred.
- Rule #2: If a 5% profit (or greater) was generated, then a trailing stop of one-half (50%) of the maximum open profit achieved by the position was placed and the position closed if the 50% trailing stop was violated.
- Rule #3: If neither Rule #1 or #2 was violated then the position was closed out after either four weeks or six weeks.
RESULTS
System 1 (Time-Based Strategy): A total of 230 trades were generated between 11/1/93 and 5/30/98. Numerous parameters of the 230 trades were analyzed. The results are summarized in Table 1. The 2-week, 4-week, and 6-week cumulative returns were +88%, +255%, and -151% respectively and are shown in Chart 1. The return of the DJIA over the same time period was +242% (3680.59 to 8899.95). The maximum drawdowns for the 2-week, 4-week, and 6- week series were, -143%, (8/24/94 – 3/10/94), -249% (9/1/94 – 3/13/94), and -640% (12/29/93 – 1/26/95). The maximum draw-ups for the 2-week, 4-week, and 6-week series were, +312% (3/10/94 – 11/25/95), +557% (3/13/94 – 1/30/96), and +561% (1/26/95 – 4/24/96). The results of the current study are compared with the results of the prior study in Charts 3 and 4.
System 2 (Money-Management Strategy): A total of 230 trades were generated between 11/1/93 and 5/30/98. Numerous parameters of the 230 trades were analyzed. The results are summarized in Table 2. The 2-week, 4-week, and 6-week cumulative returns were +251%, +979%, and +1470% respectively and are shown in Chart 2. The return of the DJIA over the same time period was +242% (3680.59 to 8899.95). The maximum drawdowns for the 2-week, 4-week and 6- week series were -132% (8/24/94 – 3/10/95), -112%, (9/1/94 – 1/19/95) and -125% (9/1/94 – 12/30/94). The maximum draw-ups for the 2-week, 4-week and 6-week series were +223% (3/10/95 – 11/24/95), +666% (2/7/95 – 4/24/95) and +939% (12/20/94 – 4/24/96). The results of the current study are compared with the results of the prior study in Charts 5 and 6.
DISCUSSION
It has been observed that short-term volatility will have a tendency to revert back to its longer-term mean.(1,3) Connors et.al.(1) have published the Connors-Hayward Historical Volatility System and showed that when the ratio of the 10-day versus the 100-day historical volatilities was 0.5 or less, there was a tendency for strong stock price moves to follow.
In our previous study at PRISM Trading Advisors, Inc., we confirmed the phenomenon of volatility-mean reversion by presenting the first large-scale, option-based analysis while maintaining a strict market-neutral/delta-neutral (gamma positive) trading program(4). We showed that a significant price move occurred 75% of the time following a short-term volatility implosion (as defined in the Methods and Materials section).
In the previous study, we chose a relatively straightforward strategy of purchasing a straddle. A straddle is the proper balance of put and call options that produce a trade with no directional bias. A straddle is said to be “delta neutral” and will generate the same profit whether the underlying asset’s price moves higher or lower. As the asset price moves away from its initial price, one option will increase in value while the other opposing option will decrease in value. A profit is generated because the option that is increasing in value will increase in value at a faster rate than the opposing option is decreasing in value. The straddle is said to be “gamma positive” in both directions, because one is both long the call option and long the put option.
This option strategy has a defined maximum risk that is known at the initiation of the trade. This maximum risk of loss is limited to the initial purchase costs of the straddle (premium costs of both put and call options). There is no margin call with this straddle strategy. There is an additional way that this strategy can profit. Because the options are purchased at the time there has been an acute rapid decrease in volatility, one should theoretically be purchasing “undervalued” options. As the price of the asset subsequently experiences a sharp price move, there will be an associated increase in volatility which will increase the value of all the options that make up the straddle position. The side of the straddle which is increasing in value will increase at an even faster rate, while the opposite side of the straddle which is decreasing in value will decrease in value at a slower rate. So as to not further complicate the analysis, the exit strategy for the first system (time-based strategy) for this study was even more basic; using a time-stop exit criteria.
In the previous study we showed that a 4-week exit produced a positive return over the study period (335%). However, the drawdowns precluded its use as a stand-alone system for real-time trading (-451%). In that study, a simple set of money management rules were added to the original system tested. These money management rules were designed to close-out non-performing trades early before they could turn into large losses and kept performing positions open as long as they continued to generate profits. These goals were accomplished by closing out any position if its value decreased to 90% of it’s initial value (i.e. a 10% loss). A position with open profits had a 50% trailing stop of the maximum open profit achieved by the position at any time open profits exceeded 5%. If neither of these two conditions occurred, the position was closed-out at the end of six weeks. As predicted, the 6-week money-management strategy produced both a significantly greater total return (1189%) with a significantly smaller drawdown (-246%) than the 4-week non-money-management strategy. By closing positions when a loss of 10% had occurred, we were able to significantly decrease the amount of losses.
Further analysis of the previous study indicated that volatility can remain low and even continue to decrease for several weeks. Thus, not infrequently the trade was stopped out just before the subsequent and anticipated volatility exploded. It appeared that we were successful at defining periods of low volatility but needed a way of better predicting when the period of low volatility was ending. It has also been shown that unusually high volatility generally indicates that a sustainable trend is underway. Price-range expansion, after a period of unusually low volatility, indicates that a new sustainable trend is beginning. In this study, we investigated the use of a second entry filter based on the average-true-range (ATR) of the recent daily prices as a way for trying to better define the “end of the low period of volatility” and the “beginning of a reversion of volatility back towards its mean.” It was hoped that the ATR filter would improve the overall returns obtained using the basic-option-straddle strategy, while simultaneously decreasing the drawdowns experienced by the original study.
In the original study, the 4-week time-stop yielded the best results since it was felt that the 2-week time-stop did not allow for sufficient time for the anticipated price move to fully develop; total return of +335% versus -191%. The 6-week time-stop allowed for the adverse effects of time-decay, volatility, and price regression back towards the stock’s initial starting price that eroded the value of the straddle position; total return of +335% versus -84%. Since the addition of the second ATR filter was intended to delay the entry into the trade until
the period of low volatility had ended, we were concerned that the use of the same 4-week time-stop might experience some of the same problems encountered in the original study with the 6-week timestop. This is in fact what was seen; the 2-week time-stop produced significantly better results while the 4-week time-stop produced slightly worse results when compared to the original study. If one compares the time-based systems from the original study with the current study (Table 3), one finds that for the 2-week time-stop the total return (- 191% vs. +88%), the average return-per-trade (-0.60% vs. +0.38%), and the maximum drawdown (-424% vs. -143%) were significantly improved. For the 4-week time-stop (Table 4), the total return (+335% vs. +255%) and the average return-per-trade (+1.20% vs. +1.11%) were slightly worse. The maximum drawdown again, however, was significantly improved (-451% vs. -249%). It was, therefore, concluded that the addition of the second ATR filter had a significant positive effect on the original trading system.
As in the original study, the application of a simple set of moneymanagement rules was again explored in the study. Once again, as in the original study, the money-management rules dramatically improved the overall returns while simultaneously decreasing the drawdown experienced in the time-based strategy. The combination of the money-management rules with the addition of the ATR filter further improved the results (Tables 5 and 6). For the 6-week time-stop plus money management, there was a 24% improvement in total returns (1187% vs. 1470%), a 50% improvement in average return-pertrade (4.25% vs. 6.39%), and a 51% reduction in the magnitude of the maximum drawdown (-246% vs. -125%).
The current study also continues to suffer from several limitations. Although moderate slippage was used in all the calculations, the robustness of this study might have been improved if access to real-time stock option bid-ask prices were available for all of the trades investigated. Unfortunately, such a large, detailed database is not readily available. Given that the real-time bid-ask prices were not available, the use of the Black-Scholes formula with the known historical inputs (stock price, implied volatility, 90-day T-bill yield) is a acceptable alternative thereby minimizing any pricing differences between the actual and theoretical option prices systematically throughout the time period used in the study.
The current study revealed that the addition of a second ATR filter to a simple straddle options-based strategy designed to exploit a sudden implosion of a stock’s volatility with time as the only existing criteria, yielded superior results when compared to the same strategy without the second ATR filter. Although improved, this strategy with the second ATR filter continues to produce drawdowns that preclude it as a viable trading strategy. The addition of some simple moneymanagement rules dramatically improved the overall returns while simultaneously decreasing the excessive drawdowns that plagued the original trading strategy, thereby transforming it into an applicable trading system for everyday use. This volatility-based, delta-neutral strategy also is independent of market direction. A market-neutral strategy and portfolio may be considered as a separate asset class by portfolio managers in the efficient allocation of their investment portfolios to boost returns while simultaneously decreasing their risk exposure.
In conclusion, this is the second large-scale, trading-research study to be shared with the trading public that clearly demonstrates how the phenomenon of price-volatility, mean-reversion can be exploited by using an options-based, delta-neutral approach. By adding a second filter based on ATR to signal the end of the “low volatility period,” the results were significantly improved. Price, time and volatility factors using options-based strategies to further maximize positive expectancy continue to represent active areas of real-time trading research at PRISM Trading Advisors, Inc. These results will be the subject of future articles.
REFERENCES
- Connors, L. A., and Hayward, B.E., “Investment Secrets of a Hedge Fund Manager,” Probus Publishing, 1995.
- Connors, L. A: “Professional Traders Journal.” Oceanview Financial Research, Malibu, CA. March 1996, Volume 1, Issue 1.
- Natenberg, S., “Option Volatility and Pricing. Advanced Trading Strategies and Techniques,” McGraw Hill, 1994.
- Morton, J. D.: “Exploiting Volatility to Achieve a Trading Edge: Market-Neutral/Delta-Neutral Trading Using the PRISM Trading Systems.” The MTA Journal, Issue 54, pp. 9-12, 2000.