journal of technical analysis (jota). issue 16 (1983, november)

!Fllll:~~IANS ASSOCIATION

JOURNAL Issue 16 November 1983

MARKET TECHNICIANS ASSOCIATION JOURNAL

MTA Journal/November 1983 1

MARKET TECHNICIANS ASSOCIATION JOURNAL Issue 16 November, 1983

Editor: James M. Yates Bridge Data Company 10050 Manchester Road St. Louis, Missouri 63122

Contributors: Roger G. Clarke Arthur A. Merrill John J. Murphy Henry 0. Pruden David L. Upshaw

Publisher: Market Technicians Association 70 Pine Street New York, New York 10005


0 Market Technicians Association 1983


MTA JOURNAL - NOVEMBER, 1983

TABLE OF CONTENTS

Title Page MTAOFFICERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

MEMBERSHIP AND SUBSCRIPTION INFORMATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

STYLE SHEET FOR SUBMISSION OF ARTICLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

MTA LETTER FROM THE EDITOR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . James M. Yates

9

THE USE OF INTRA-DAY PRICE CHARTS FOR STOCK INDEX FUTURES . . . . . . . . . . . . . . . . . . . . . John J. Murphy

11

A DISCUSSION OF APPLIED MODERN PORTFOLIO THEORY: ITS FUNDAMENTAL AND TECHNICAL ASPECTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Roger G. Clarke 23

FOUR NEW INDICATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Arthur A. Merrill

PRICEVOLUMEDIVERGENCE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Henry 0. Pruden, Ph.D.

KEEPING SCORE ON INFLATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 David L. Upshaw, CFA


1983-84 MARKET TECHNICIANS ASSOCIATION

PRESIDENT Fred Dickson Millburn Corp. 212398-8489

OFFICERS

SECRETARY Gail Dudack Pershing & Co. 212/902-3322

VICE PRESIDENT John Greeley 212i747-1520

VICE PRESIDENT (SEMINAR) Richard Yashewski Butcher & Singer 516/627-l 600

TREASURER Robert Simpkins Delafield Harvey Tabell 609/924-9660

COMMITTEE CHAIRPERSONS

PROGRAMS John Greeley 212/747-l 520

NEWSLETTER Robert Prechter 404/536-0309

JOURNAL James Yates 314/821-5660

CERTIFICATION Charles Comer 2128254367

MEMBERSHIP Cheryl Stafford 617/227-9500

LIBRARY Ralph Acampora 212l747-2355

ETHICS & STANDARDS/PUBLIC RELATIONS Tony Tabell 609/924-9660

PLACEMENT John Brooks 404/266-6262

COMPUTER SPECIAL INTEREST GROUP John McGinley 203/762-0229

FUTURES SPECIAL INTEREST GROUP John Murphy 212/724-6982

SAN FRANCISCO TECHNICAL SOCIETY SPECIAL INTEREST GROUP

Henry Pruden 415/459-1319


MEMBERSHIP AND SUBSCRIPTION INFORMATION

REGULAR MEMBERSHIP - $50 per year plus $10 one-time application fee.

Receives the MTA Journal, the monthly MTA Newsletter, invitations to all meetings, voting member status, and a discount on the Annual Seminar fee. Eligibility requires that the emphasis of the applicant’s professional work involve technical analysis.

SUBSCRIBER STATUS - $50 per year.

Receives the MTA Journal and the MTA Newsletter, which contains shorter articles on technical analysis. The subscriber receives special announcements of the MTA meetings open to The New York Society of Security Analysts and/or the public, plus a discount on the Annual Seminar fee.

ANNUAL SUBSCRIPTION TO THE MTA JOURNAL - $35 per year.

SINGLE ISSUES OF THE MTA JOURNAL (including back issues) - $15

The Market Technicians Association Journal is scheduled to be published three times each fiscal year in approximately November, February, and May.

An ANNUAL SEMINAR is held each Spring.

Inquiries for REGULAR MEMBERSHIP and SUBSCRIBER STATUS should be directed to:

Membership Chairman Market Technicians Association 70 Pine Street New York. New York 10005


MTA Editorial Policy

The Market Technicians Association Journal is published by the Market Technicians Associ- ation, 70 Pine Street, New York, New York 10005 to promote the investigation and analysis of price and volume activities of the world’s financial markets. The MTA Journal is distributed to individuals (both academic and practitioner) and libraries in the United States, Canada, Europe and several other countries. The Journal is copyrighted by the Market Technicians Association and registered with the Library of Congress. All rights are reserved. Publication dates are February, May, and November.

Style for the MTA Journal

All papers submitted to the MTA Journal are requested to have the following items as pre- requisites to consideration for publication.

Short (one paragraph) biographical presentation for inclusion at the end of the accepted article upon publication. Name and affiliation will be shown under the title.

All charts should be provided in camera ready form and be properly labeled for text reference.

All tables should be properly labeled and in camera ready form.

Paper should be submitted typewritten, double-spaced in completed form on 8% by 11 inch paper. If both sides are used, care should be taken to use sufficiently heavy paper to avoid reverse side images. Footnotes and references should be put in the end of the article.

Greek characters should be avoided in the text and in all formulae.

One submission copy is satisfactory.

Manuscripts of any style will be received and examined, but upon acceptance, they should be prepared in accordance with the above policies.


The MTA Journal is meant to be a chronicle of the information derived from the activity of the financial markets in which the collective capital of the world is invested. No part is safe from the inspection of the marauding technicians. Technicians of the markets have the liberty to inspect any compendium of information. These lucky people have only the discipline of results, the discipline of the wizard wh6 must make sense of the unexplainable, and the discipline of those who search with no predetermined rules. Indeed, market technicians must have the discipline to examine a dynamic arena where rules can and do change.

It’s no wonder that people question the technicians’ efforts. It’s no wonder that there are fewer technical analysts than their fundamental cousins. It’s no wonder that the technicians themselves have a difficult time grappling with the subject of qualifying one of their own. Or how is it that you identify ingenuity in relating information and test for common sense? How is it that you make reference to the ability to discern representative patterns?

This is not to say that the technicians are undisciplined. In fact, the most successful are the most highly disciplined analysts. It is the seeming inconsistency of the insatiable appetite for new data and new ways of examining that data with the dogmatic stance of maintaining and examining a favorite indicator the same way regardless of the situation that proves the rule. The question is, “What is the rule?” The answer is, of course, “There are no rules.”

Instead of the centerfold, we have this month the interfold. Several charts, some explained, some not, are interspersed among the work. Feel free to contribute your most interesting examples for future issues.

Please note the inclusion of a style sheet designed to improve the professional presentation of the MTA Journal. It will be extremely helpful if contributors to the Journal follow the simple rules in this style sheet.

In order to make a previous point, we will break the above rule with the February, 1984 Journal. The February issue will contain every Market Letter’s market prediction for 1984 that we are given permission to print. We would like to include at least 50 of these, one page for each. They will be reproductions of the actual Market Letters, not necessarily in their entirety, but the salient portions relative to the predictions for the market or individual securities. Everyone’s assistance in contributing or recommending contributors is appreciated.

As with all MTA Journals, this one would not have appeared without the brave souls who spent the time to write down a coherent examination of an interesting market item. In addition, special thanks to Pam Hollrah, who again typed every word; Sheldon Hoffman, who continued to improve the text-editor-to-typeset program; Fred Zaegel, who again applied ink to the paper with perfection; and most of all, to Sally Ruppert, who once again made it all work together.

James M. Yates Editor


This page left intentionally blank for notes, doodling, or writing articles and comments for the MTA Journal.


THE USE OF INTRA-DAY PRICE CHARTS FOR STOCK INDEX FUTURES

John J. Murphy, JJM Technical Advisors

Presentation to the 8th Annual Market Technicians Association Seminar, Amelia Island Plantation, Amelia Island, Florida.

May 15,1983

Since this is a technical audience, I’m sure you’re aware of the need to “close gaps”. I would like to take about a minute of my allotted time to close a rather large gap in the biography that was handed out to you.

While it is true that I began as a stock market technician in 1968 and while it is also true that I went out on my own in 1981 as an independent commodity trading advisor, I would like to assure you that I did do some work in the intervening 13 years.

Actually, I made the transition to commodities in 1970 with Merrill Lynch’s Commodity Division where I spent most of the next ten years. I spent about half of that time in the research area, during which time I served as director of Merrill’s Commodity Technical Analysis Department. I then made the switch from research to the “real” and more difficult world of trading and be- came a managed-account trading advisor for the last few years with that firm. Therefore, I have worked as both a stock and commodity technician and have done both research and trading.

Since I also teach a course on Commodity Technical Analysis at the New York Institute of Fi- nance, I am often asked if the principles of technical analysis are the same for both stocks and commodities. That’s actually a difficult question to answer. I would say that the basic concepts are the same. We use the same charts and rely on most of the same tools and indicators. How- ever, there are some very profound differences. Perhaps the most profound are the time dimension and the nature of the futures contract itself. Since all futures trading is done on margin, which is usually less than 10% of the value of the underlying contract, leverage becomes an extremely important factor. Leverage, of course, is a double-edged sword. It can work for or against you very quickly This is why it is possible to either make or lose large sums of money in a very short period of time.

This high leverage factor has some important implications for the use of technical analysis in the futures markets. First, timing becomes extremely important. It is not enough to be right on the general direction of a given market. It is quite common to be right on the direction of a market and still lose money. The specific timing of entry and exit points is absolutely critical to successful futures trading. Therefore, futures technicians have been forced to fine tune their technical tools to a very fine edge. We deal of necessity in a very short time dimension that would probably surprise most stock market traders.

Another implication is that timing is almost purely technical. In futures trading, more so than in stocks, some knowledge of technical analysis becomes absolutely essential at some point in the decision-making process.

Just as an aside here, I should mention that we no longer like to be called “commodity” traders. We’re now “futures” traders. With the tremendous growth in financial futures, including interest rates, foreign currencies and stock index futures, the shift in emphasis has been away from the traditional image of commodities such as corn, soybeans or porkbellies. The term “futures” is much broader in scope and is the preferred usage in the futures industry today.


The subject of this panel presentation is “Using Stock Market Futures.” I realize that the audience here today is mainly stock market oriented, and that the concept of futures trading is new and somewhat intimidating to most of you. I have had the very strong impression in my dealings with MTA members since the introduction of stock index futures about a year ago that there is a great deal of concern, and almost alarm, as to how to deal with the shorter time dimension, the higher leverage and increased volatility of stock index futures. I hope that my presentation here today will shed some light on the subject.

What I propose to do is to show you one of the ways that we as futures traders deal with the short-term trading by the use of intra-day price charts. The charts that I will show you have been taken from the ADP Comtrend-Videcom system which is a very widely used video re- trieval system in the futures industry

Figure 1 shows the standard daily high, low and closing bar chart that we’re all most familiar with. I have chosen to use the June Standard & Poor’s contract for my examples since it is by far the most actively traded stock index futures contract as measured by volume and open interest.

Most analysts and traders are familiar with the bar chart on a daily basis. I am, therefore, beginning with the chart we are most familiar with, which shows the past 90 days of trading activity for perspective. The table in Figure 1 shows that is is possible to move into different time di- mensions depending on what the trader is interested in.

One of the most important things to realize when moving from one time dimension to another is to always begin with the longer term view and move to the shorter term. It does not work very well in the other direction. We’re going to look at three different bar charts starting with Mode 39 showing 90 days, then Mode 37 showing the most recent five days, and then Mode 36 showing only one day Figure 1 shows the last 90 days. Notice the last 5 trading days marked off by the box. These 5 days are as of two weeks ago, from May 2nd to the 6th. Not too much detail is shown except for a small dip early in the week and new highs later in the week.

Now let’s look at Figure 2 where we will zero in on those 5 days. Figure 2 is a high, low and last bar chart with each bar representing fifteen minute intervals. Notice the increased detail. The near term selloff on Monday, the “double bottom” upside reversal on Tuesday, the trian- gular consolidation on Thursday and resumption of the uptrend on Friday. Suddenly, support and resistance levels become clearer and chart patterns begin to appear. Trendline analysis becomes possible and can be shown to be very effective in identifying trading turns. To the technical trader, the timing of entry and exit points becomes a good deal easier.

Let’s zero in further and put Tuesday under the microscope. Since Tuesday was the day the corrective dip terminated, it is the most critical trading day of the week.

Figure 3 shows every 5 minutes of price action. Take note of how well this chart follows standard charting principles. Notice the almost perfect “double bottom” which was completed with the breakout over 16250 after 2:15. An even earlier “buy” signal was given about ten minutes sooner when prices broke through initial resistance at 16220. Notice the large pullback around 3:15 from 16330 which retraced almost exactly 50% of the previous runup and stopped just above the 16250 breakout level--all standard chart analysis. Elliott Wave advocates will notice a very clear five-wave advance from 12:15 to the end of the day.

Chartists who see these charts for the first time are often surprised to see how well chart analysis works on such a short term basis. As a matter of fact, if I didn’t tell you this was a one-day chart, you would never suspect it from the price action alone, since it could just as easily be a chart of six months’ action.


One of the most intriguing and often overlooked benefits of technical or chart analysis is its application to virtually any time dimension, from the very long-term to the very short-term. In my work, I usually advise stock market traders to shorten their time horizon especially if they are dealing with stock market futures, and commodity traders, who tend to become too short- term oriented, to lengthen their horizons for greater perspective.

The rest of the charts we will look at show the same price action, but in different formats. For example, Figure 4 shows Tuesday’s action on a “tic” chart. Note all the different Modes available in each different format. Figures 5 and 6 show “trendline” charts, which are just modifications of the tic chart which uses an exponential smoothing curve drawn through the tics. I personally prefer the trendline format. Since I do a fair amount of Wave Analysis, I feel that waves show up more clearly when the connecting lines are drawn.

The last chart, Figure 7, is an intra-day point and figure chart which I’m sure you’re all familiar with. Point and figure charts are especially popular among floor traders and those who trade on a very near term basis. If the trader wishes to plot his or her own charts on graph paper, another feature will print out the actual prices. The trader can specify any box and reversal size, and the machine will do the rest. Incidentally, one of the reasons that point and figure charting is not as widely used in futures trading is that the data is harder to obtain. There are no in- expensive, commercially-available services that provide the intra-day information. Therefore, traders are forced to rely on computer printouts which are more expensive and out of the reach of many individual traders.

What I have attempted to do here today is to discuss one of the most important features of stock index futures trading, namely the much shorter time horizon, and also to demonstrate to you one of the most useful tools at our disposal--intra-day price charts.

I will leave you with a couple of positive thoughts on the role of technical analysis as it applies to futures trading in general. The principles of technical analysis led themselves to virtually any trading medium, be it in stocks or futures, and to virtually any time dimension as well. With the proper tools, and sharpened reflexes, the chartist in stocks should be able to make the nec- essary transition to futures trading. Finally, because of the increased emphasis on timing of entry and exit points in the trading process, which is purely technical in nature, technical analysis is even more important in futures than it is in stocks.

All charts are courtesy of ADP Comtrend-Videcom, 25 Third Street, Stamford, CT 06905, (203) 357-l 611.


J

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BIOGRAPHY

John J. Murphy entered the investment field in 1968 as a technical analyst for CIT Financial Corp. Since 1981 he has worked as a consultant on commodity technical analysis under the name of JJM Technical Advisors. John publishes his own technical market letter specializing in financial futures, stock index futures, precious metals and energy futures. He is presently conducting a course on Commodity Technical Analysis at the New York Institute of Finance.


INTERFOLD CHARTS

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LAST 468.9655 ABOVE 62X 76%

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BELOW 38% 24% 3CE - Cal 1 Eouivaient Voiume Inoex

TOTALS 150 17431

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A DISCUSSION OF APPLIED MODERN PORTFOLIO THEORY:

ITS FUNDAMENTAL AND TECHNICAL ASPECTS

Roger G. Clarke

Modern portfolio theory has undergone a variety of changes since its foundations were laid in the early 1960’s. The first attempt of the theory was to simplify and aggregate investor expec- tations into a model giving a specific relationship between risk and return. Simplifications were obviously needed to achieve such an ambitious task. But under the assumptions outlined by Bob Vandell the CAPM (Capital Asset Pricing Model) was born -- expected return for an individual security was shown to depend on the relative price movement between the firm and the market as a whole or the security’s beta. Subsequently, many have tried to test the model to see if there was actually any detectable relationship between this measure of risk and the resulting returns. The results have been encouraging but not totally satisfying. There is some relationship on average but it is not perfect. Low beta stocks seem to do slightly better than predicted and high beta stocks seem to do slightly worse.

The investment implications of the initial theory when combined with the notion of efficient markets suggest that the investor should hold the market portfolio average of stocks and borrow or lend at the margin to achieve a desired level of risk. A risk averse investor would hold Treas- ury bills and a little of the market in a portfolio. The less risk averse investor would hold much more of the market or perhaps even borrow to invest. Though such a choice is theoretically simple, following that prescription is not very exciting for investors.

Fortunately for active investors and unfortunately for the theory, the conceptual model was not perfect. It was indeed an ambitious undertaking to try to explain the tradeoffs between risk and return in one simple package. The more testing that was done the more researchers discov- ered some unexplained anomalies in the theory between what was observed and what was expected.

For example, the simple theory did not allow for different marginal tax rates between individuals in the market or different tax treatment for dividends and capital gains. In practice not all investors were in the same tax bracket, and securities with the same before-tax return would not have the same after-tax return for all investors. Consequently, it may not be optimal for an investor to just hold the market portfolio and a riskless asset. The theory did not allow for such differences.

In addition, the simple theory required that information be freely available to all, that investors agree as to the risk and return for each security available and that all investors have uniform horizons for holding the assets. Here again the simple theory would break down when compared with the realities in the marketplace.

Furthermore, the theory was a static construct. All the information relevant for decision-making was known at the beginning of the time horizon. The marketplace was much more dynamic. New information was arriving continuously and not all investors would agree on the content and implications or adjust their portfolio at the same speed. Investors have a wide variety of psychological profiles and some need more information and assurance before they act.

Finally, the theory required that all assets be easily tradeable. Some individual assets are hardly tradeable at all. Markets are not always very liquid. Such restrictions have raised a great deal of controversy as to whether the “market” was well defined and what should be included in it.


Nearly all of the simplifying assumptions of the model are violated to some extent in the practical world of investments. Though there are problems with the simple theory, the real question is whether modern portfolio theory can contribute anything to portfolio and investment analysis. There are two primary ways in which the modern theory might be useful. FIRST, it may help us to understand market forces a little better. SECOND, it may provide a benchmark for us as we try for better relative performance.

In an effort to help us understand the market better adjustments can be made in the theory to allow for differences in the tax treatment of investment income and for different investor tax brackets. A variety of other attempts have been made to “fix” the theory in order to make it more realistic. Such modifications of the theory raise some problems, however. Many modifications can undo the critical underlying theory that holds the relationships together. What results often lack any notion of general price equilibrium or involve parameters that are not easily measurable.

Even if the theory were totally consistent and the parameters were well identified, there would still be some question as to whether good estimates of the important variables can be ob- tained. In particular, the theory calls for an estimate of beta. Experience has shown us that there is some noise in estimating this parameter. Estimation is sensitive to the length of the measurement period. Often 5 years of monthly data is used in the estimation techniques, but other periods of time could be used which would result in a somewhat different value. There is also the question of what historical data to use as a proxy for the market and the riskless rate. Should the S&P 500 be used as the market proxy or some other group? Should 30-day Treasury bills be used for the riskless rate or go-day Treasury bills? The static theory does not give much help in settling these questions.

Getting good estimates of the parameters is important because many of the investment strategies depend on screening firms with particular characteristics. For example, a market timing strategy which shifts funds between low and high beta stocks may not give very satisfactory results if the supposedly high beta firms as measured initially do not really have high betas.

The investor who uses mdoern portfolio theory confronts many of these measurement issues. An active program of trying to perform better than the market may look successful or unsuc- cessful depending on whether there are significant biases in calculating how the portfolio should have performed because the critical parameters are biased in their measurement or the “market” portfolio is not correctly specified. This raises the question of whether we can hope to do better than the “market” in risk adjusted terms if theory doesn’t give clear signals about what is important to consider and how those variables relate to performance? Or should we just look for something that seems to work even if only temporarily regardless of whether it has any the- oretical foundations? If the latter, can we depend on being right consistently or do we have to depend on being lucky?

Once we t-r-rove away from pure theory to practical applications in an effort to explain what works in the market, we confront many of the same issues a market technician sees. We are looking for understandable patterns and signals in data, whether it comes fundamentally from prices, earnings, dividends, etc.

Modern portfolio theory is an approach to organize this search for pattern recognition. It is not completely successful. There is a great deal of noise and uncertainty in the data used. It is not the final answer to investment analysis but depending on the analyst’s investment strategy and philosophy, it may be able to contribute some insights.


BIOGRAPHY

Roger G. Clarke is an Associate Professor of Finance at the Graduate School of Management at Brigham Young University. He holds several degrees, including an M.B.A. in Business Administration and a Ph.D. in Finance.


INTERFOLD CHART

TW TRANS WORLD CORPORATION VOLATILITY OVER 26 WEEKS

76.5 - - 42

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FOUR NEW INDICATORS

Arthur A. Merrill

A research analyst can understand why an explorer explores. Like a prospector for gold, he pushes into new territory. Usually he finds no gold, but occasionally he finds pay dirt.

This paper reports on four successful ventures; four new indicators are described.

Two parts (at least) of the descriptive material need explanation. If you are puzzled by any of the rest of the material, please write.

First, the exponential average is described by a ratio such as 0.67/0.33. The slash mark is merely a divider between two multipliers. To calculate an exponential for any week, multiply the average for the preceding week by the number in front of the slash mark. Then multiply the sta- tistic for the current week by the number following the slash mark. Then add the two results to get the average for the current week.

Second, the accuracy table needs description. The indicators were tested in every week from 1976 through 1982. The top line of the table reports on the success in forecasting the following week. The number of times right is in column R, the number of times wrong in column W, and the percent right in column % R. The last column is a measure of statistical significance. (chi squared with one degree of freedom.)

The second line reports on success in forecasting whether the Dow was higher or lower five weeks later. The remaining lines in the table report the longer range success. Did the indicator forecast the Dow 13 weeks later? 26 weeks later? 52 weeks?

The indicators follow:

SECOND HOUR INDEX Proposed by Arthur A. Merrill

Published weekly in TECHNICAL TRENDS

DEFINITION:

This is an index of the difference between the points change in the second hour of the trading day and the average points change in all hours of the day. It’s a weekly index, so the total points change in the second hour in a week is divided by the number of days in the week. To get the average hourly change for all hours, the closing price for the preceding week is subtracted from the closing price in the current week, and the difference is divided by the number of trading hours in the week.

To make the index MORE convenient, the average points per hour is multiplied by 1000 and rounded to the nearest integer. The final index is an exponential average (0.926/0.074) which approximates a 26 week average.


PARAMETERS:

Bullish: above +91 Bearish: below -350 These are 0.67xstd.deviation, to approximate the quartiles.

EXAMPLE:

Data for week ended 02/l 883: Total of 11 o’clock prices: 5449.40 (DJ Industrials) Total of noon prices: 5455.44 Average second hour = (5455.44~5449.40)/5 = 1.208 Average hour in week = (1092.82-l 086.50)/30 = 0.211 Index for week= 1000(1.208-0.211) = 997 Exponential index = 0.926x1 54 + 0.074x997 = 217

WEIGHTS IN BALANCE: (Indicator No. 88) 1 WK:O 5 WKS:4 13 WKS:7 26 WKS:9 52 WKS:lO

t500 I

ACCURACY RECORD

SECOND INDEX HOUR .926/.074,26 week O-l-2 FILE MT4 A7 Merrill Analysis Inc.

1971 to 1982 DJI R W % R CHI SQ

1 166 143 53.72 1.57 5 183 126 59.22 10.15

13 198 110 64.29 24.57 HIGHLY SIG 26 218 83 72.43 59.65 HIGHLY SIG 52 237 60 79.80 104.30 HIGHLY SIG


RESISTANCE INDEX: Proposed by Arthur A. Merrill


DEFINITION:

This index measures the difference between resistance to downward swings and resistance to upward swings. The resistance is measured in thousands of shares (NYSE) required to move the Dow one point. In order to make a high figure bullish and a low figure bearish, resistance to rises is subtracted from resistance ‘to declines.

To calculate this index, in each hour of the week calculate points change and not volume.

For all hours in which prices rose, total the points moved in one week and the volume. Divide thousands of shares total by points.

Do the same for all declining hours to get decline resistance.

To get net resistance, subtract rise resistance from decline resistance. The final index is an exponential average (0.86/0.14) which approximates a 13 week average.

PARAMETERS:

Bullish: above 230 Bearish: below -105 These are 0.67xstd.deviation, to approximate the quartiles.

EXAMPLE:

Data for week ended 01/l 883: 18 rising hours totaling 41.84 points and 219,120,OOO shares.

Thousands of shares per point = 5237 12 declining hours totaling 35.52 points and 177,010,OOO shares.

Thousand shares per point = 4983 Net resistance = 4983-5237 = 254 Exponential index = .86x20.7 + .14x254 = 17.7

WEIGHTS IN BALANCE: (Indicator No. 20) 1 WK:O 5 WKS:O 13 WKS:O 26 WKS:O 52 WKS:6


1 I ’

INOEX

I ‘I

@

ACCURACY RECORD:

RESISTANCE INDEX: .86/.14, 13 week Merrill Analysis Inc.

1971 to 1982 DJI R W % R CHI SQ.

1 127 132 49.03 0.06 5 115 144 44.40 3.03 *

13 130 129 50.19 0.00 * 26 134 116 53.60 1.16 * 52 149 83 64.22 18.21 HIGHLY SIG

VOLATILITY INDEX: Proposed by Arthur A. Merrill


DEFINITION:

This index measures volatility of the DJ Industrials in percent change per day. It’s a weekly index; daily changes for the week are averaged. To get a measure of the size of the move, rather than direction, all of the changes are considered positive. To make the index more convenient, percent change is multiplied by 1000 and rounded to the nearest integer. The final index is an exponential (0.67/0.33) which approximates a 5 week average.


PARAMETER:

Bullish: above 888 Bearish: below 537 These are 0.67xstd.deviation, to approximate the quartiles.

EXAMPLE:

Data for the week ended 01 /18/83 Average percent change per day multiplied by 1000:

= 1 000( + .976 + .365 + .519 + .136 + .359)/5 = 471. Exponential index = .67x975 +,.33x471 = 809

WEIGHTS IN BALANCE: (Indicator No. 16)

1 WK:l 5 WKS:2 13 WKS:5 26 WKS:4 52 WKS:O

cool I

, , , . . . . , . . .._ . . . . . 6

I I .(,’ I . . . . . I (

ACCURACY RECORD:

VOLATILITY INDEX: .67/.33, 5 week Merrill Analysis Inc.

1971 TO 1982 DJI R W % R CHI SQ.

1 161 127 55.90 3.78 5 163 125 56.60 4.75 PROB. SIG.

13 180 104 63.38 19.81 HIGHLY SIG. 26 163 109 59.93 10.33 SIG. 52 136 128 51.52 0.19 *


MEMBER/ODD LOT INDEX: Proposed by Arthur A. Merrill


DEFINITION:

This index compares the trading by members of the stock exchange with trading by the odd lot group. The ratio of purchases to sales by the member group is divided by the ratio of purchases to sales by the odd lot group. The sales by members is adjusted by deducting odd lot sales and adding odd lot purchases:

The resultant formula is:

weekly index = (1 OO%xAxD)/(Cx(B-D + C)) Where: A = member purchases

B = member sales C = odd lot purchases D = odd lot sales

The final index is an exponential average (0.67iO.33) which approximates a five week average.

PARAMETERS:

Bullish: below 189 Bearish: above 224 These are 0.67xstd.deviation, to approximate the quartiles.

EXAMPLE:

Data for week ended 04/08/83 Member purchases = 95816 Member sales = 100545 Odd lot purchases = 1867 Odd lot sales = 3321 Index for week = (100x95816x3321 )/( 1867x( 100545-3321+ 1867)) = 172 Exponential index = 0.67~222 +0.33x1 72 = 206

WEIGHTS IN BALANCE: (Indicator No. 89)

1 WK:O 5 WKS:O 13 WKS:O 26 WKS:l 52 WKS:O


350

‘1 @

250

ACCURACY RECORD:

MEMBER/ODD LOT INDEX: .67/.33,5 week Merrill Analysis Inc.

1976 TO 1982 DJI R W % R CHI SQ.

1 71 85 45.51 1.08 5 75 81 48.08 0.16 l

13 77 76 50.33 0.00 * 26 58 83 41.13 4.09 PROB. SIG. 52 55 75 42.31 2.78 *


BIOGRAPHY

Arthur Merrill was awarded the coveted MTA annual award in 1977. Art is the publisher of TECHNICAL TRENDS, a statistical stock market service. He pioneered in the study of seasonal patterns of stock prices, and is the author of the book BEHAVIOR OF PRICES ON WALL STREET, SEASONAL TENDENCIES IN STOCK PRICES, BEAR MARKET CHAR- ACTERISTICS, and MARKET INDICATORS AND GROWTH COMPANY EARNINGS. Among the indicators originated by Art is the ratio of ASE to NYSE volume, a device now used by many technicians as a gauge of speculative activity.


A study of twelve years of price and volume data which examines the validity and reliability of divergence as an early warning method for catching market turns.

Henry 0. Pruden, Ph.D.

The author wishes to acknowledge the valuable assistance of Mr. Bruce Fraser, Registered Representative, Dean Witter, who was formerly an M.B.A. student at Golden Gate University

BACKGROUND

A cardinal goal of technical analysis is to “buy low and sell high.” Fulfillment of this goal to its utmost degree requires some sort of a method for anticipating trend changes in the market so that buy and sell orders may be placed at or very close to turning points. One widely acknowl- edged method for anticipating market turns is divergence analysis.

Divergence has long been used as an anticipatory or early warning device for catching trend reversals as they develop. Within the tenets of the Dow Theory there has been the requirement of confirmation by both the Transports and the Industrials. It was long ago recognized by Dow Theorists that a non-confirmation of one average by the other was often the warning of an im- minent reversal of trend [Stansbury].

Anticipating trend reversals through divergence analysis has developed far beyond comparing the Dow Transportations to the Dow Industrials. Divergence studies now encompass confirmation/non-confirmations between the Industrials and the Advance-Declines, the Industrials and the Utilities, and especially the Dow Industrials and the New York Stock Exchange Volume. Finally, price/volume divergence has become the centerpiece of some popular technical systems [e.g., Granville].

SCOPE OF THIS STUDY

The purpose of this study is to present and interpret empirical data relating price to volume in an effort to answer the two following questions:

(1) Are turning points in the market foreshadowed by a divergence between price and volume?

(2) Does volume precede price?


The latter question is based upon the idea that just not any divergence is important, but that there exists a cause-and-effect or lead-and-lag relationship whereby volume invariably precedes price. Moreover, we are not talking about just any gross measure of volume; rather, we are focusing on a special treatment of volume, known as on-balanced volume [Granville].

The idea that on-balanced buying and selling of shares as an indicator of “smart money” ac- cumulation or distribution has a fine pedigree. Jesse Livermore and the other old-time pool operators knew all about manipulating a stock through buying and selling of shares on-balance. Livermore would mark up a stock by making it active on rallies for the purpose of attracting a public following. He would accumulate shares on-balance to spur surges in price and volume. He would then sell on rallies and buy back on reactions, carefully accumulating on-balance until he started a campaign of distribution as on-balanced selling at the top, which he would then continue on the way down [Lefevre, pp. 244-2501.

To study on-balanced volume in the strict sense of Mr. Granville’s practice or in the usage of the old-time pool operators is beyond the scope of this study. What is within the scope of this study is to use an indicator which belongs to the specie of on-balanced volume. In no sense should the results of this study be interpreted as a scientific test of the Granville method of on- balanced volume.

METHOD

Data Collection

Data for this study were collected from the Stock Market Institute [SMI].* Daily price and volume data were extracted from SMI archives for the period July 1968 to April 1980. The data were the Wyckoff Wave Index, which is the Institute’s proxy for the New York Stock Exchange’s price movements. Also collected for the same time period were data for the Optimism-Pes- simism Index which, for the purposes of this study, will be the indicator of on-balanced volume.

Definitions

Wyckoff Wave: A weighted price index of eight stocks deemed by the Institute to reflect market leadership.

Around 1968, the components and weights of the Wyckoff Wave were:

Stock Multiplier

Chrysler 6.0 General Electric 4.0 International Business Machines 2.0 Penn Central 5.2 Standard Oil of New Jersey 4.0 Union Carbide 6.0 UAL, Inc. 6.0 U. S. Steel 8.0


in January, 1982, the components and weights of the Wyckoff Wave were:

Stock Multiplier

General Motors 6.0 General Electric 8.0 International Business Machines 8.0 Exxon 10.0 Merrill Lynch 6.0 Union Carbide 6.0 UAL, Inc. 6.0 Pepsico 4.0

Optimism-Pessimism Index (O-P): This is an index which portrays the volume transacted during each buying and selling wave of the Wyckoff Wave recorded during the day. Below is the official SMI procedure for calculating the O-P Index.

The O-P is determined by adding the UP volume and subtracting the DOWN volume. This volume is added or subtracted with the decimal point placed after the millions column, and the final zero is eliminated. Therefore, the volume column will be changed as follows to determine the O-P Index:

I II III IV V WAVE TIME DUR PRICE CHN

OPENING 2762-l 14

1. 10:20 2. 10:35 3. 10:50 4. 1l:lO 5. 11:20 6. 11:30

;: 1140 11:55 9. 12:lO

10. 12:25 11. 12:35 12. 12:55 13. 1:30 14. 1:50 15. 2:oo

20 2773-5/8H 15 2757-314 15 2770 20 2755 10 2765 10 2754-l l2L 10 2767-l /4 15 2756-l I8 15 2768 15 2756-518 10 2766-314 20 2756 35 2764 20 2755-518 10 2759-518

+15-l/8 1430 593.91 H - 15-718 810 593.10 +12-l/4 740 593.84 -15 940 592.90 +lO 700 593.60 -10-l/2 500 593.10 + 12-3/4 360 593.46 -11-l/8 540 592.92 +ll-7/8 610 593.53 -11-318 640 592.89 +10-l/8 300 593.19 - 1 o-314 660 592.53L +8 1000 593.53 - 8-318 670 592.86 +4 750 593.61

TOTAL VOLUME

VI VOL

10650

VII O-P VOLUME O-P

+1430 +1.43 - 810 - .81 + 740 - .74 - 940 - .94 + 700 + .70 - 500 - .50 + 360 + .36 - 540 - .54 +610 +.61 - 640 - .64 + 300 + .30 - 660 - .66 +lOoo +l.OO - 670 - .67 + 750 + .75

The Figures now contained in the O-P column are then added or subtracted from the O-P In- dex of the PREVIOUS wave. Hence: the Optimism-Pessimism Index for Wave 1 is:

592.48 (previous day's final O-P) + 1.43 ( an UP wave) = 593.91


The O-P for Wave 2 (a DOWN wave) is 593.91 - 81 = 593.10. The remainder of the O-P indexes for these Intra-Day Waves 3 to 15 are as follows:

593.10 + .74 = 593.84 593.84 - .94 = 592.90 592.90 + .70 = 593.60 593.60 - -50 = 593.10 593.10 + .36 = 593.46 593.46 - .54 = 592.92 592.92+ .61 =593.53 593.53 - .64 = 592.89 592.89 + .30 = 593.19 593.19 - .66 = 592.53 592.53 + 1 .oo = 593.53 593.53 - .67 = 592.86 592.86 + -75 = 593.61

The O-P Index for the last wave is the final O-P Index for the day, and is the figure which is used to chart the O-P Index on the vertical line chart of the Wyckoff Wave.

The volume data for calculating the O-P Index is total New York Stock Exchange volume.

Procedure

All Wyckoff Wave movements of 5% or greater were examined to see if the move was preceded by a divergent relationship between the Wyckoff Wave and the Optimism-Pessi- mism Index. What was noted was whether the divergence was caused by volume failing to confirm price, or by price failing to confirm volume, or if the turn was preceded by a joint confirmation of price and volume.

Somewhat more difficult was an effort to capture instances where divergences did occur but were not followed by the predicted 5% rise or fall in the price index. Albeit hard to ac- complish, an effort was made to find and report these whip-saw divergence signals.

Divergences were determined by comparing closing values for price and volume. So long as they both jointly made a high or a low in an uptrend or a downtrend they were reported as nondiverging or confirming. When one index or the other moved onto a higher or lower closing value while the other refused to do so, an upside or downside non-confirmation would be reported. Considerable leeway was needed in making divergent judgments since there were sometimes multiple divergences, and sometimes immediately alternating or double divergences, and sometimes such extreme inharmony between the speed of the movement of the two indices that an essentially divergent relationship was established even though a strict non-confirmation was missing.

DATA ANALYSIS

An assembly of the pertinent data items is reported in the Appendix. Please note that there were 80 observations taken over the approximately twelve year period from July 1968 to April 1980. Answers to the research questions were sought by cross-classifying the data found in the Appendix. The results are in Tables 1 and 2.


TABLE 1

ARE TURNING POINTS IN THE MARKET ANTICIPATED BY DIVERGENCES?

Price/Volume Number of Cases

Turn No-Turn

Divergence I 48 I 7 I

Confirmation I 25 I I

Total number of cases = 80

Table Number 1 shows that most turning points were preceded by a divergent relationship between the Wyckoff Wave Price Index and the Optimism-Pessimism Volume Index. Di- vergences preceded market turns by a ratio of almost 2-1 over instances of turns which had no early warning from divergences. Moreover, when divergences did occur, the observer could have acted upon these signals with confidence. Only seven cases out of a total of fifty-five divergent relationships proved to be whip-saws or spurious predictions; good signals outweighed bad signals by a ratio of about 7-1, which were very favorable odds.

In general, the data in Table Number 1 tend to give an affirmative answer to the question: “Are turning points in the market foreshadowed by divergence between price and volume?” The data show divergence preceding turns on a much more than chance basis, though some analysts may be disappointed because the odds were not overwhelming.

TABLE 2

DOES VOLUME PRECEDE PRICE?

Divergent

Price precedes volume

Volume precedes price

Confirmed

l-

Bull: Turn

UP

12 cases

5 cases

19 cases

Bear: Turn Down

10 cases

21 cases

6 cases

No Turn

I 6 cases

1 1 case

Total number of cases = 80

In Table 2, one can observe an about even split between price, as measured by the Wyckoff Wave, preceding volume, as measured by the Optimism-Pessimism Index, and on the other hand, volume preceding price...there were 22 and 26 instances respectively. So from these


data we cannot simply accept the assertion that volume precedes price without qualifica- tion. However, upon closer examination we can discern some distinctive lead-lag relationships. As the data in Table 2 show, bottoms in the market are often composed of joint lows by price and volume. What mostly happened over the period studied was for spike or V- bottoms to find both indices plunging together and then, rising in tandem. The second most common sort of bottom saw price preceding volume. Here we saw the price index refusing to be pushed into lower ground despite heavy on-balanced volume selling pressure. At bottom, when turn was preceded by a divergence (45% of the time), it was twice as likely for price to lead volume (12 cases) than for volume to lead price (5 cases).

Top turning points did support the hypothesis that volume precedes price. Indeed, a pattern of a higher closing Wyckoff Wave Price Index unconfirmed by the Optimism-Pessimism Volume Index was a very reliable guide to anticipating downturns in the market. Not only did volume non-confirmations (21) outpace price non-confirmations (lo), but also there was only one instance where an upside non-confirmation by the O-P gave a false signal. Con- trast this last relationship to the six instances where non-confirmations by the price index resulted in spurious turn signals. An even closer scrutiny of the data showed that these spurious price-precedes-volume signals were almost all false bottom signals. So while volume leadership was not universally valid, it did seem much more reliable than price leadership.

CONCLUSIONS

If one cared to generalize based upon the limited sample and restricted scope of this study, the following tentative conclusions could be drawn:

(1) Divergence as a method for anticipating market turns works about sixty percent of the time.

(2) Price/volume divergence works best at tops; divergence signals tops about 80% of the time, while at bottoms divergence is present less than 50% of the time.

(3) In about 40% of the cases there will be no advance warning of a turn emanating from a divergence between price and volume. Rather price and volume will reconfirm an ex- isting trend, then just reverse together.

(4) Calling bottom turning points is a treacherous undertaking:

(a) About 50% of the time there will be no advanced, divergent signal.

(b) Among the divergent signals, it will be price that more often gives the downside non- confirmation.

(c) But about 30% of the price signals at bottoms are liable to be whip-saws.

(5) “Volume-precedes-price” is a special case of divergence; volume-precedes-price is a divergent relationship frequently found at top turning points, but seldom at bottom turning points.

(6) Volume-precedes-price, while not universally valid, seems more reliable than price leadership because it flashes fewer false signals.

(7) Divergence is a highly elastic, variable method for comparing price with volume. Antic- ipating turning points via price/volume divergence is a lot trickier than trend following.


APPENDIX

DATA ON THE WYCKOFF WAVE (PRICE) AND THE OPTIMISM-PESSIMISM INDEX (VOLUME)

Dates of Wyckoff Price Level of Wave Price Movement Wyckoff Wave Divergence Preceding Turn

Divergence Non-Confir- Non-Confir- mation by mation by

Start End Start End Confirmation Wyckoff Wave O-P Index

7168 a/68

10168 l/69 2169 3169 5169 7169

3170 3170 5170 6170 7170 7170

at70 10170

10170 4171 a/71 9171

7168 3044 X X at68 3044 2762 X

10168 2762 3068 X l/69 3068 2784 X 2169 2784 2904 X 3/69 2904 2648 X 5169 2648 2851 X* 7169 2851 2407 X a/69 2407 2548

(Whipsaw signal given in August 1969 by a dow:side non-confirmation by price.) 3170 2068 2167 X 5/70 2167 1633 X 6/70 1633 1856 X 7170 1856 1625 X 7/70 1625 1788 X 8170 1788 1682

(Along the way up to October high would have occurred a spuriots sell signa1.A small upward non-confirmation of volume by price took place between 8129 and 914170.) 10/70 1682 2034 X lo/70 2034 1925 (Whipsaw signal. False bearish upside non-confrmation by the index.) 4171 1925 2594 X at71 2594 2144 X 9171 2144 2450 X

11171 2450 2136 X

MTAJournaVNovember1983 41


Start

11/71 5172 2136 2752 5172 7172 2752 2504 X 7l72 ai72 2504 2698 X 6172 9172 2698 2508 9172 12172 2508 2784

12172 12172 2784 2632 X 12/72 l/73 2632 2818

l/73 9173 2818 2210 9173 1 O/73 2210 2544 X

10173 12173 2544 2106 12173 1 I74 2106 2304

l/74 2174 2304 2084 X 2l74 3174 2084 2316

3174 5174

6174 7174 7l74 9174 9174

10/74 1 O/74 12174

3175 4175 5175 6i75 7175

End Start End Confirmation

Divergence Non-Confir- Non-Confir- mation by mation by Wyckoff Wave O-P Index

X

* x X*

X X

X X

X (Whipsaw buy signal given by a downside non-confirmation by the price index.) 5174 2316 2020 X 6l74 2020 2212

(Whipsaw buy sig;;L;iven by idownside non-confirmation by price.) 7174 2212 7174 1960 2140 X 9174 2140 1600 X 9174 1600 1776 X*

10174 1776 1542 X 10174 1542 1864 X* 12/74 la64 1560 3175 1560 2220 X 4175 2220 2095 5175 2095 2384 X 6175 2364 2224 7175 2224 2404 X 9175 2404 2188



Start

9175 1 o/75 12i75

3176 4176 7176 8176 9176

11176

1 I77 1 l/77

11177 3178 6178 7/78 9178

1 l/78 1 I79 2179

3179 7179

End


Start End Confirmation Wyckoff Wave O-P Index

10175 2188 2404 X 12175 2404 2280 X 3176 2280 2880 X 4176 2880 2740 X 7176 2740 2960 X 8176 2960 2752 X 9176 2752 2948 X

11176 2948 2618 X l/77 2618 2848

(Whipsaw buy signal given in February 1977 by downward non: confirmation by the price index. The Wyckoff Wave failed to rally by 5%.)

(Whipsaw buy signal in June by downside non-confirmation by price.)

(Whipsaw buy sell given in August by downside non-confirmation by price.) 1 l/77 2484 2178 X 11177 2178 2302 (Whipsaw buy signal given by a downside non-confirmation by tXhe price index in December 1977.) 3178 2302 2068 X 6/78 2068 2372 X 7178 2372 2200 X* 9178 2200 2596 X

1 l/78 2596 2156 X l/79 2156 2412 X 2179 2412 2242 X 3179 2242 2424

(Whipsaw buy signal in May 1979 given by a doinward non-confirmation by price.) 7179 2424 2240 X 9/79 2240 2432 X




Start End Start End Confirmation Wyckoff Wave O-P Index

9179 1 l/79 2432 2108 X 1 l/79 2180 2108 2432 X

2180 4180 2432 1894 X

TOTALS 25 22 26

l Cases with double divergence and/or inharmonious action judged to be so close to divergent action that it was classified as a divergence.

REFERENCES

1. Joseph E. Granville, GRANVILLE’S NEW STRATEGY OF DAILY STOCK MARKET TIMING FOR MAXIMUM PROFIT (Englewood Cliffs, NJ, Prentice-Hall, Inc., 1976).

2. Joseph E. Granville, Editor, THE GRANVILLE MARKET LETTER.

3. Edwin Lefevre, REMINISCENCES OF A STOCK OPERATOR (Burlington, Vermont: Books of Wall Street, A Division of Fraser Management Associates, 1980. First published 1923 by George H. Doran Company, New York.)

4. Charles B. Stansbury, THE DOW THEORY EXPLAINED: HOW TO USE IT FOR PROFIT (New York, NY: Richard Russell Associates, 1960).

5. THE RICHARD D. WYCKOFF COURSE IN STOCK MARKET SCIENCE AND TECHNIQUE, Volume Two (Wyckoff Stock Market Institute, Inc., 1968).

FOOTNOTES

l The author wishes to thank Mr. Craig Smith, Director of Research and the staff of the Stock Market Institute for generously providing these data.


BIOGRAPHY

Dr. Pruden is a member of the MTA, a past president of the Technical Securities Analysts Association of San Francisco, a Lecturer at Golden Gate University, and a private investor.


INTERFOLD CHART

cIMD 1,623-

1,427-

1,231-

1,035-

ADVANCED MICRO DEVICES INC SHARE LIRUIDITY FOR 26 UEEKS - 36

* * * *

* * St* ** ' ',"I*$ - 28

I'* I,$ t

I I

’ ‘I - 20

******* 839-

+ 1982 t

1~492 HIGH 967 LOU 1~177 LAST

- 4

1983


KEEPING SCORE ON INFLATION

David L. Upshaw, CFA

SUMMARY

This report is about industry group index movements during six periods of rising and failing rates of inflation from 1965 to 1983. The report shows that the S&P 400 performed better during periods of disinflation than during periods of inflation. It demonstrates that knowledge of price performances in two previous periods of inflation and two periods of disinflation would have been helpful in selecting groups to own during a subsequent period of inflation and a subsequent period of deflation. Some conventional wisdom about which groups “benefit” from inflation/disinflation is confirmed here. There are also several interesting surprises in the data. Finally, some suggestions about using these data in forming portfolio strategies are offered.

U.S. CONSUMER PRICE INDEX

Annual Ranges of 12-Month Rate of Change

From 1959 Through August 1983


OVERVIEW

You read it many times each month: “We think that disinflation beneficiaries should do well in the present market environment” or, at other times, perhaps, “In this unsettled climate, we advise overweighting in groups that usually do relatively well during periods of rising rates of inflation.” Sometimes these kinds of statements are followed by specific recommendations; sometimes the writer leaves it to the reader to come up with investments to match the stated opinion.

A lot of people spend a lot of time trying to figure out precisely which groups or issues will perform relatively well during periods of inflation and disinflation. Usually these studies are based on economic theory and on the way different industries are impacted by the acceleration or deceleration of the rate of inflation.

This report takes a different approach. It details, for six different periods of inflation and disinflation, the actual price performance of 56 S&P Industry Groups and the S&P Short Maturity Government Bond Index. The 56 industry groups account for over 80% of the value of the S&P 600. Some of the results appear to mesh with conventional wisdom as to what groups SHOULD perform the best during inflation and disinflation, but there are some surprises in the data, too. For example, Gold Mining is supposedly the prime beneficiary of an inflationary period. In fact, the Gold Mining group did outperform the S&P 400 during two of the three inflationary periods covered by this study. The surprise is that Gold Mining also outperformed the S&P 400 during two of the three disinflation periods in the study

Using data generated by price performances during the first two inflation periods, a portfolio was selected which should have outperformed the S&P 400 during the third inflation period. It did.

Using data generated by price performances during the first two disinflation periods, a portfolio was selected which should have outperformed the S&P 400 during the third disinflation period. It did. In the aggregate, past performance during periods of inflation and disinflation did provide valuable information about future performance.

With the results of three inflation and three disinflation periods in this report, readers now have some objective data to go along with what economic theory says should happen. No claim is made here that changes in the rate of inflation actually caused the price movements reported. All the report shows is how groups actually performed during various periods of changing rates of inflation. And the reader must still decide on which side to model his or her portfolio; nothing in this report predicts when a period of inflation or disinflation will begin or end. That task is altogether different from the topic of this report, and will be addressed in the near future.

THE SIX PERIODS STUDIED

Conventional wisdom, as I understand it, contains several things about stock prices and the rate of inflation, some of them contradictory:

1. over the long term, stocks outpace inflation.

2. inflation means high interest rates, and the market does not do well against high returns from fixed income investments.


3. a lessening in the rate of inflation (if it doesn’t turn into deflation) is good for stocks.

You can add other pieces of wisdom to this list, I’m sure. During the period of this study, De- cember 1965 - July 1983, the stock market did better during disinflation periods than during inflation periods. Table 1 illustrates these tendencies quite clearly

The six periods studied are shown on the charts of the S&P 400 which follow. Disinflation period 3, 1980-1983, is subdivided into three periods, A, B, and C, as shown on the chart.

Montthy Av&age ‘Price,

-.i, :.,

/ II 59 1 IU sd / 6’ I I 6i , 63 64 65 66 67 66 69 70 ,u7, , ;,72 / 1.73


I began the study with December 1965 because the rate of inflation was on the threshold of going above 2%. In my opinion, inflation rates of less than 5% to 2% between 1959 and 1965 did not have any appreciable impact on the stock market.

TABLE 1

THE SIX INFLATION/DISINFLATION PERIODS

Inflation 1 Inflation 2 Inflation 3

Means

Disinflation 1 Disinflation 2 Disinflation 3

Means

Rate of Overall Overall Time Number Inflation % Change, % Change,

From To of Months From To CPI S&P 400

1265 02/70 E

1.9% 6.3% + 19.4% - 2.0% 06/72 12/74 2.9 12.2 +24.3 -38.1 12i76 03180 39 4.8 14.7 +37.6 + 2.7

----

--;2O?&

-____ ---mm- -----_

39.7 11.1% +27.1% - 12.5%

02/70 06/72 28 6.3 2.9 + 9.8 + 26.2 12/74 12/76 24 12.2 4.8 + 12.2 + 55.5 03/80 07183 40 14.7 2.4 + 24.8 + 58.4

---- ____- -___ ---mm- -----_

30.7 11.1% 3.4% +15.6% + 46.7%

INFLATION PORTFOLIO

It is December, 1976. You know that a period of disinflation is ending and that a period of inflation is beginning. Armed with that perfect foresight and the knowledge of which groups outperformed the S&P 400 during each of the two previous inflation periods, you put together a portfolio which you will hold until the inflation period ends. Table 2 shows your groups, how they performed, and their mean percent change. On an equally-weighted basis, your groups gained 8% against a 3% gain by the S&P 400.

True, you probably could have earned a lot more than 8% by rolling over Treasury bills from December 1976 to March 1980, but this report is about inflation, not asset allocation or market timing. In the aggregate, knowledge of past performances during inflationary periods resulted in better-than-market performance.


TABLE 2

PORTFOLIO FOR INFLATION PERIOD 3

Composed of Groups Which Outperformed The S&P 400 During Inflation Periods 1 and 2

Group % Price Change

From 12/76 to 03/80

Distillers Coal, Bitum Containers, M + G Copper Drugs Instrumentation Semiconductors Forest Products Hospital Supplies Mist Metals Oil Well Eq Paper Soaps Tobacco NG Pipelines NYC Banks Banks Outside NYC

+ 35% -35 -12 +38 -4 +52 +13 -20 - 7 +30 +93 -25 -28 +4 +48 -25 -18

Mean + 8% S&P 400 + 3%

DISINFLATION PORTFOLIO

It is March, 1980. Having successfully weathered the latest attack of inflation, you now know that a period of disinflation is beginning. You also know which groups outperformed the S&P 400 during each of the last two disinflation periods. You build the portfolio shown in Table 3. From March, 1980 through July, 1983 (the lowest year-to-year rate of inflation so far in the period) your portfolio gained 115% versus a gain of 58% by the S&P 400. Once again, an ac- curate forecast of the direction of the rate of inflation, and knowledge of past performance has resulted in great, not to say astonishing, performance.

Because disinflation period 3 included the last leg of a bull market, a bear market, and the first leg of another bull market, I show in Table 4 the action of the portfolio during subperiods A, B, and C. During the last leg of a bull market (3/80-l l/80) the portfolio lagged behind the S&P 400, + 24% vs + 30%. In the 1980-l 982 bear market, the portfolio was outstanding. It gained 1% while the S&P 400 was losing 22%. In the first leg of the current bull market (8/82-7/83) the portfolio gained 75%, vs a 56% gain by the S&P 400.

Table 5 shows the action of all the groups studied, not just the portfolio, between 3180 and 7/83. The groups are listed alphabetically, and their performance rank is also shown.


TABLE 3

PORTFOLIO FOR DISINFLATION PERIOD 3

Composed of Groups Which Outperformed The S&P 400 During Disinflation Periods 1 and 2

Group % Price Change

From 03/80 to 07183

Aerospace Autos ex GM Soft Drinks Cosmetics Elec Equip Major Electrical Household Furn Ap Instrumentation Semiconductors Agri Mach Constr Mach Newspapers Radio TV Restaurants Dept Stores Gen Mdse Chains Air Transport Banks Outside NYC

+ 56 +124 + 72 + 20 + 77 +114 +216 +153 +123 - 19 - 5 +196 +157 +182 +231 +161 +137 + 81

Mean 7 15% S&P 400 + 58%


TABLE 4

THE THREE MARKET SWINGS DURING DISINFLATION 3

Percent Changes A B C

3/80-l 1 I80 1 l/80-8/82 8182-7183

Aerospace Autos ex GM Soft Drinks Cosmetics Elec Equip Major Electrical Household Furn Ap Instrumentation Semiconductors Agri Mach Constr Mach Newspapers Radio TV Restaurants Dept Stores Gen Mdse Chains Air Transport Banks Outside NYC

Means S&P 400

+ 27% ‘-18 +lO +21 +29 +29 +32 +44 +52 +27 +25 +35 +24 +31 +23 +4 +22 +18 ___ + 24% + 30%

- 30% 0

+35 -26

0 +4 +31 -12 -28 -60 -41 +5 +14 +45 +35 +22 +5 +lO ___ + 1% - 22%

+ 76% +172 + 16 + 35 + 38 + 59 + 84 +lOl +105 + 59 + 29 +107 + 82 +48 +100 +106 + 85 + 47 ____ + 75% + 56%


TABLE 5

GROUP 3180 - 11180 11180 - 8182 8182 - 7183

% CNG RANK % CNG RANK % CNG RANK

S&P 400 + 30.47 21 IND DIGEST + 40.46 11 SHORT GOVTS + 4.51 57 AEROSPACE + 26.97 26 ALUMINUM + 18.47 42 AUTOMOBILES - 4.70 59 AUTOS EX GM - 17.96 60 BREWERS + 30.65 19 DISTILLERS + 30.61 20 SOFT DRINKS + 10.20 52 BLDG MATLS + 26.80 27 CHEMICALS + 18.41 43 COAL BITUM +25.17 30 CONT MET&GL + 15.98 47 COPPER + 7.26 54 COSMETICS +21.10 36 DRUGS + 28.29 25 ELEC EQUIP + 28.62 24 EL MAJOR CO + 28.90 23 HSLD FURN AP +31.58 17 INSTRUMENTN + 43.67 10 SEMICONDUCT + 52.07 6 FOODS + 14.07 48 FOREST PROD + 9.59 53 GOLD MNG +71.14 1 HOSP SUPPL + 38.42 13 MACH AGRI + 26.54 28 MACH CONSTR + 24.70 31 MACH INDUSTR + 62.19 4 METALS, MISC + 32.65 16 COMP & BUS EQ + 18.56 41 COMP EX IBM + 18.00 45 OIL CRUDE + 51.60 7 OIL DOM + 53.88 5 OIL INTL + 25.98 29 OIL WELL EQ + 69.26 2 PAPER + 20.47 39 PUBLISHING + 38.50 12 NEWSPAPERS + 35.39 15 RADIO-TV + 23.95 32 RESTAURANTS + 31.20 18 RETDEPTSTR + 22.79 33 RET FOOD CHN + 13.53 49 RET GEN MDSE + 3.57 58 SOAPS + 10.33 51 STEEL + 22.05 35 TIRES + 46.58 8 TOBACCO + 43.82 9

-22.23 37 + 4.51 20 + 2.03 24 -29.78 43 -38.61 46 - 6.25 28 + 0.27 25 +48.23 1 -17.05 33 +35.07 4 -27.67 41 -22.59 38 -46.04 54 -16.46 32 -17.20 34 -26.22 40 + 3.12 23 - 0.27 26 + 4.12 21 +30.70 5 -12.08 30 -28.43 42 +28.52 7 -32.69 44 -59.57 58 +27.69 8 -59.59 59 -40.55 50 -48.64 56 -39.82 49 -19.84 35 -42.65 52 -47.30 55 -49.91 57 -41.25 51 -61.86 60 -23.32 39 +11.69 15 + 5.26 18 +13.75 14 +44.96 2 +35.10 3 +25.92 9 +22.38 11 +18.44 12 -39.50 48 +16.58 13 + 3.59 22

+ 56.12 28 + 87.30 12 + 5.21 60 + 75.50 17 + 59.98 21 + 90.74 10 +171.80 1 + 44.14 42 + 49.81 36 + 15.72 58 + 64.20 20 + 52.13 34 + 33.47 50 + 54.76 29 + 57.82 24 + 34.64 49 + 31.76 53 + 37.67 45 + 59.38 22 + 83.60 15 + 100.69 7 +105.30 5 + 33.26 51 + 57.77 25 +137.12 2 + 36.69 47 + 59.32 23 + 28.81 55 + 45.06 40 +103.32 6 + 86.96 13 + 88.13 11 + 74.98 18 + 54.36 30 + 39.65 43 + 57.36 26 + 56.14 27 +iOO.Ol 8 +107.43 3 + 82.32 16 + 48.27 37 + 99.60 9 + 51.37 35 +106.05 4 + 28.85 54 + 36.88 46 + 52.99 32 + 21.13 57


3180 - 11 I80 GROUP %CNG RANK

ELEC UTIL + 6.55 55 NG DISTRIB +29.34 22 NG PIPELINES +35.87 14 TELEPHONES + 5.18 56 AIR TRANS +22.08 34 RAILROADS +67.66 3 NYC BANKS + 12.30 50 BANKS OUR NY + 18.15 44 LIFE INS +18.58 40 MULTI-LN INS +20.97 37 PROP CAS INS + 16.35 46 DJIA +20.80 38

11180 - 8182 %CNG RANK

+23.45 10 -34.33 45 -43.82 53 + 8.52 17 + 4.95 19 -39.11 47 + 9.89 16 -20.78 36 +28.66 6 - 1.28 27 - 7.67 29 -15.49 31

8182 - 7183 %CNG RANK

+ 13.33 59 + 32.08 52 + 52.30 33 + 21.68 56 + 85.03 14 + 74.69 19 + 47.01 38 + 46.32 39 + 36.06 48 + 38.21 44 + 53.42 31 + 44.97 41

WHAT ABOUT NOW?

Table 6 shows the scores generated by each group during the six periods in the study. You may be surprised, as I was, to learn that INSTRUMENTATION and SEMICONDUCTORS are the only groups to beat the S&P 400 during all six periods. Truly, these two groups have been all-weather groups for many years now.

Table 7 combines the scores from Table 6 just as a matter of interest. I suppose one could say “If I have no opinion whatsoever of the direction of the rate of inflation, I should just buy, and hang on to, groups rated 6, 5, and possibly 4, in Table 7.” That is certainly a possible strategy, but I don’t think you need to have a perfect forecast of the direction of inflation in order to use the data in Table 6. The inflation/disinflation trends covered in this report lasted from 24 to 50 months. Even if you are several months late in recognizing a change of trend (and most of you probably will be late), the data contained in Table 6 should be of some value to you. There’s no need for a compromise, know-nothing, portfolio, which is really what is listed in Table 7.

The two portfolios shown earlier could not have been exactly duplicated in the real world. They were shown to illustrate that some knowledge of performance during four inflation/ disinflation periods would have been useful during two subsequent periods. I hope that these data, from six periods, will be useful to you in the future.

Note: Standard & Poor’s Corp. has recently renamed two group indexes. The old “Office and Business Equipment” has become “Computers and Business Equipment.” “Office and Business Equipment excluding IBM” is now “Computers and Business Equipment excluding IBM.” In this report, the old names are used except in Table 5.


TABLE 6

THE NUMBER OF TIMES EACH GROUP OUTPERFORMED THE S&P 400

(3 = Highest possible score)

Three Inflation Periods Three Disinflation Periods

Distillers Copper Instrumentation Semiconductors Mist Metals Oil Well Eq Tobacco NG Pipelines

Aluminum Bldg Matls Coal, Bitum Containers, M + G Drugs Elec Equip Forest Prod Gold Mining Hosp Suppl Industrial Mach Oft Eq ex IBM Oil, Domestic Oil, lntl Paper Newspapers Radio - TV Soaps NG Distrib Railroads NYC Banks Banks Outside NYC Multi-Line Ins

Indicator Digest Short Govts Aerospace Brewers Soft Drinks Chemicals Cosmetics Household Furn Ap Foods Agricultural Mach Constr Mach

z 3 3 3 3 3 3

2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

1 1 1 1 1 1 1 1 1 1 1

Autos ex GM Soft Drinks Elec Equip Major Electrical Household Furn Ap Instrumentation Semiconductors Newspapers Radio TV Restaurants Dept Stores Gen Mdse Chains Air Trans

Indicator Digest Aerospace Autos Brewers Distillers Cosmetics Drugs Foods Gold Mining Agri Mach Constr Mach Publishing Soaps Tires Tobacco Banks Outside NYC Prop Cas Ins

Aluminum Bldg Matls Chemicals Coal, Bitum Forest Prod Hosp Suppl lndust Mach Mist Metals Office Eq Crude Oil lntl Oil

3 3 3 3 3 3 3 3 3 3 3 3 3

2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

1 1 1 1 1 1 1 1 1 1 1


Three Inflation Periods Three Disinflation Periods

Office Eq Crude Oil Publishing Restaurants Dept Stores Food Chains Gen Mdse Chains Steel Tires Telephones Prop Cas Ins DJIA

Autos Autos ex GM Major Electrical Elec Util Air Trans Life Ins

1 1 1 1 1 1 1 1 1 1 1 1

Oil Well Eq 1 Paper 1 Food Chains 1 Steel 1 Elec Util 1 NG Distrib 1 NG Pipelines 1 Railraods 1 NYC Banks 1 Life Ins 1 DJIA 1

Short Govts Containers, M + G Copper Oft Eq ex IBM Domestic Oil Telephones


TABLE 7

COMBINED SCORES FROM TABLE 6 SHOWING

THE TOTAL NUMBER OF TIMES EACH GROUP OUTPERFORMED THE S&P 400

(6 = highest possible score)

Instrumentation 6 Semiconductors 6

Distillers Elec Equip Newspapers Radio TV Tobacco

Soft Drinks Drugs Household Furn Ap Gold Mining Mist Metals Oil Well Eq Restaurants Dept Stores Gen Mdse Chains Soaps NG Pipelines Banks Outside NYC Multi-Line Ins

Indicator Digest Aerospace Aluminum Autos ex GM Brewers Bldg Matls Coal, Bitum Copper Cosmetics Major Electrical

5 5 5 5 5

4 4 4 4 4 4 4 4 4 4 4 4 4

3 3 3 3 3 3 3 3 3 3

Foods 3 Forest Prod 3 Hosp Suppl 3 Agri Mach 3 Constr Mach 3 Industrial Mach 3 lntl Oil 3 Paper 3 Publishing 3 Tires 3 NG Distrib 3 Air Trans 3 Railroads 3 NYC Banks 3 Prop-Cas Ins 3

Autos 2 Chemicals 2 Containers, M + G 2 Office Eq 2 Office Eq ex IBM 2 Crude Oil 2 Domestic Oil 2 Food Chains 2 Steel 2 DJIA 2

Short Govts Elec Util Telephones Life Ins


DETAILS OF EACH PERIOD

Those who are interested in individual group performances will find the details in this sec- tion. For each of the six periods, there is a page showing group performances listed in al- phabetical order and in rank order. These pages were used to compile the scores shown in Table 6.

A recent list showing the components of each industry group index is at the end of this sec- tion. It is not completely up-to-date but will serve as a guide to readers who may not be completely familiar with the S&P universe.


BASED ON ABSOLUTE PRICES OVER THE 50 MONTHS FROM 12/65 TO 02/70

GROUP % CNG

S&P 400 - 1.98 IND DIGEST - 7.89 SHORT GOVTS - 10.57 AEROSPACE - 55.10 ALUMINUM - 11.65 AUTOMOBILES - 34.66 AUTOS EX GM - 35.84 BREWERS + 64.96 DISTILLERS + 38.74 SOFT DRINKS + 76.90 BLDG MATLS + 37.81 CHEMICALS - 48.22 COAL BITUM +118.96 CONTMET&GL + 7.26 COPPER + 10.25 COSMETICS + 121.08 DRUGS + 52.20 ELEC EQUIP + 10.47 EL MAJOR CO - 22.45 HSLD FURNAP + 5.61 INSTRUMENTN + 53.75 SEMICONDUCT + 35.14 FOODS - 2.46 FOREST PROD + 104.08 GOLD MNG - 8.18 HOSP SUPPL + 354.35 MACH AGRI - 35.73 MACH CONSTR - 20.20 MACH INDUSTR - 18.85 METALS, MISC + 13.22 OFFICE EQUIP + 98.83 OFC EQX IBM + 68.04 OIL CRUDE - 15.74 OIL DOM - 19.29 OIL INTL - 25.81 OIL WELL EQ + 70.97 PAPER + 7.04 PUBLISHING - 24.43 NEWSPAPERS + 8.51 RADIO-TV + 4.58 RESTAURANTS + 6.29 RET DEPT STR + 10.20 RET FOOD CHN - 15.37 RETGEN MDSE + 3.00 SOAPS + 34.71 STEEL - 30.12 TIRES + 6.81

INFLATION 1

RANK

34 36 38 SO 39 55 57

9 12

6 13 59

3 25 21

2 11 20 48 29 10 14 35

4 37

1 56 45 42 18

5 8

41 43 50

7 26 49 24 31 28 22 40 33 15 53 27

RANK ORDER % CNG

1 HOSP SUPPL + 354.35 2 COSMETICS +121.08 3 COAL BITUM +118.96 4 FOREST PROD + 104.08 5 OFFICE EQUIP + 98.83 6 SOFT DRINKS + 76.90 7 OIL WELL EQ + 70.97 8 OFC EQ X IBM + 68.04 9 BREWERS + 64.96 10 INSTRUMENT + 53.75 11 DRUGS + 52.20 12 DISTILLERS + 38.74 13 BLDG MATLS + 37.81 14 SEMICONDUCT + 35.14 15 SOAPS + 34.71 16 PROP CAS INS + 22.45 17 NYC BANKS + 20.62 18 METALS, MISC + 13.22 19 MULTI-LN INS + 10.91 20 ELEC EQUIP + 10.47 21 COPPER + 10.25 22 RET DEPT STR + 10.20 23 BANKS OUT NY + 9.35 24 NEWSPAPERS + 8.51 25 CONT MET&GL + 7.26 26 PAPER + 7.04 27 TIRES + 6.81 28 RESTAURANTS + 6.29 29 HSLD FURN AP + 5.61 30 TOBACCO + 5.28 31 RADIO-TV + 4.58 32 NG PIPELINES + 3.11 33 RET GEN MDSE + 3.00 34 S&P 400 - 1.98 35 FOODS - 2.46 36 IND DIGEST - 7.89 37 GOLD MNG - 8.18 38 SHORT GOVTS - 10.57 39 ALUMINUM - 11.65 40 RET FOOD CHN - 15.37 41 OIL CRUDE - 15.74 42 MACH INDUSTR - 18.85 43 OIL DOM - 19.29 44 NG DISTRIB - 20.04 45 MACH CONSTR - 20.20 46DJIA - 20.96 47 TELEPHONES - 21.74



INFLATION 1 (continued)

GROUP

TOBACCO + 5.28 30 ELEC UTIL - 28.49 52 NG DISTRIB - 20.04 44 NG PIPELINES + 3.11 32 TELEPHONES - 21.74 47 AIR TRANS - 45.69 58 RAILROADS - 28.42 51 NYC BANKS + 20.62 17 BANKS OUT NY + 9.35 23 LIFE INS - 32.46 54 MULTI-LN INS + 10.91 19 PROP CAS INS + 22.45 16 DJIA - 20.96 46

% CNG RANK RANK ORDER % CNG

48 EL MAJOR CO - 22.45 49 PUBLISHING - 24.43 50 OIL INTL - 25.81 51 RAILROADS - 28.42 52 ELEC UTIL - 28.49 53 STEEL - 30.12 54 LIFE INS - 32.46 55 AUTOMOBILES - 34.66 56 MACH ARGI - 35.73 57 AUTOS EX GM - 35.84 58 AIR TRANS - 45.69 59 CHEMICALS - 48.22 60 AEROSPACE - 55.10



GROUP % CNH RANK

S&P 400 - 38.08 34 IND DIGEST - 61.94 53 SHORT GOVTS - 5.25 6 AEROSPACE - 45.55 39 ALUMINUM - 18.42 13 AUTOMOBILES - 58.68 51 AUTOS EX GM - 56.45 45 BREWERS - 70.75 59 DISTILLERS - 34.35 30 SOFT DRINKS - 62.10 54 BLDG MATLS - 58.21 50 CHEMICALS - 24.86 21 COAL BITUM - 10.88 9 CONT MET&GL - 21.91 19 COPPER - 6.21 7 COSMETICS - 68.0 58 DRUGS - 18.93 14 ELEC EQUIP - 54.28 43 EL MAJOR CO - 57.05 47 HSLD FURN AP - 64.30 57 INSTRUMENTN - 33.15 29 SEMICONDUCT - 25.64 24 FOODS - 32.25 28 FOREST PROD - 12.02 10 GOLD MNG +115.34 1 HOSP SUPPL - 36.12 31 MACH AGRI - 7.45 8 MACH CONSTR - 26.36 25 MACH INDUSTR - 21.23 17 METALS, MISC - 25.51 22 OFFICE EQUIP - 49.83 41 OFC EQ X IBM - 57.16 48 OIL CRUDE - 46.35 40 OIL DOM + 31.86 3 OIL INTL - 26.88 26 OIL WELL EQ + 46.79 2 PAPER - 16.68 11 PUBLISHING - 63.86 56 NEWSPAPERS - 59.58 52 RADIO-TV - 58.20 49 RESTAURANTS - 62.64 55 RET DEPT STR - 55.55 44 RET FOOD CHN - 30.10 27 RET GEN MDSE - 57.00 46 SOAPS - 22.52 20 STEEL - 1.97 4 TIRES - 52.01 42

INFLATION 2

RANK ORDER % CNG

1 GOLD MNG +115.34 2 OIL WELL EQ + 46.79 3 OIL DOM + 31.86 4 STEEL - 1.97 5 TELEPHONES - 4.55 6SHORTGOVTS - 5.25 7 COPPER - 6.21 8 MACH AGRI - 7.45 9 COAL BITUM - 10.88 10 FOREST PROD - 12.02 11 PAPER - 16.68 12 NG DISTRIB - 17.98 13 ALUMINUM - 18.42 14 DRUGS - 18.93 15 RAILROADS - 20.26 16 NYC BANKS - 20.34 17 MACH INDUSTR - 21.23 18 NG PIPELINES - 21.28 19 CONT MET&GL - 21.91 20 SOAPS - 22.52 21 CHEMICALS - 24.86 22 METALS, MISC - 25.51 23 TOBACCO - 25.60 24 SEMICONDUCT - 25.64 25 MACH CONSTR - 26.36 26 OIL INTL - 26.88 27 RET FOOD CHN - 30.10 28 FOODS - 32.25 29 INSTRUMENTN - 33.15 30 DISTILLERS - 34.35 31 HOSP SUPPL - 36.12 32DJIA - 36.63 33 BANKS OUT NY - 37.80 34 S&P400 - 38.08 35 PROP CAS INS - 39.44 36 LIFE INS - 42.19 37 ELEC UTIL - 44.24 38 MULTI-LN INS - 45.10 39 AEROSPACE - 45.55 40 OIL CRUDE - 46.35 41 OFFICE EQUIP - 49.83 42 TIRES - 52.01 43 ELEC EQUIP - 54.28 44 RET DEPT STR - 55.55 45 AUTOS EX GM - 56.45 46 RET GEN MDSE - 57.00 47 EL MAJOR CO - 57.05



INFLATION 2 (continued)

GROUP

TOBACCO - 25.60 23 ELEC UTIL - 44.24 37 NG DISTRIB - 17.98 12 NG PIPELINES - 21.28 ‘18 TELEPHONES - 4.55 5 AIR TRANS - 74.73 60 RAILROADS - 20.26 15 NYC BANKS - 20.34 16 BANKS OUT NY - 37.80 33 LIFE INS - 42.19 36 MULTI-LN INS - 45.10 38 PROP CAS INS - 39.44 35 DJIA - 36.63 32

% CNH RANK RANK ORDER % CNG

48 OFC EQ X IBM - 57.16 49 RADIO-TV - 58.20 50 BLDG MATLS - 58.21 51 AUTOMOBILES - 58.68 52 NEWSPAPERS - 59.58 53 IND DIGEST - 61.94 54 SOFT DRINKS - 62.10 55 RESTAURANTS - 62.64 56 PUBLISHING - 63.86 57 HSLD FURN AP - 64.30 58 COSMETICS - 68.10 59 BREWERS - 70.75 60 AIR TRANS - 74.73



GROUP % CNG

S&P 400 + 2.67 IND DIGEST + 20.65 SHORT GOVTS - 24.89 AEROSPACE +116.20 ALUMINUM + 39.54 AUTOMOBILES - 37.12 AUTOS EX GM - 39.16 BREWERS - 27.45 DISTILLERS + 35.14 SOFT DRINKS - 23.27 BLDG MATLS + 9.54 CHEMICALS - 26.39 COAL BITUM - 35.47 CONT MET&GL - 11.72 COPPER + 37.59 COSMETICS + 22.93 DRUGS - 3.75 ELEC EQUIP + 3.28 EL MAJOR CO - 7.48 HSLD FURN AP - 44.49 INSTRUMENTN + 51.70 SEMICONDUCT + 12.75 FOODS - 23.08 FOREST PROD - 20.23 GOLD MNG + 167.51 HOSP SUPPL - 6.71 MACH AGRI - 9.18 MACH CONSTR - 14.90 MACH INDUSTR + 8.38 METALS, MISC + 30.40 OFFICE EQUIP - 8.02 OFC EQX IBM + 7.90 OIL CRUDE +115.19 OIL DOM + 62.26 OIL INTL + 51.44 OIL WELL EQ + 93.49 PAPER - 24.78 PUBLISHING + 39.89 NEWSPAPERS + 19.87 RADIO-TV + 17.06 RESTAURANTS - 2.72 RET DEPT STR - 30.47 RET GOOD CHN - 20.64 RET GEN MDSE - 54.35 SOAPS - 28.15 STEEL - 42.34

INFLATION 3

RANK

26 17 46

2 10 55 56 51 12 44 21 49 54 35 11 42 28 25 30 58

6 20 43 39

1 29 33 36 22 13 32 23

3 5 7 4

45 9

18 19 27 53 40 59 52 57

RANK ORDER % CNG

1 GOLD MNG + 167.51 2 AEROSPACE +116.20 3 OIL CRUDE +115.19 4 OIL WELL EQ + 93.49 5 OIL DOM + 62.26 6 INSTRUMENTN + 51.70 7 OIL INTL + 51.44 8 NG PIPELINES + 48.28 9 PUBLISHING + 39.89 10 ALUMINUM + 39.54 11 COPPER + 37.59 12 DISTILLERS + 35.14 13 METALS, MISC + 30.40 14 MULTI-LN INS + 28.97 15 RAILROADS + 25.52 16 NG DISTRIB + 22.49 17 IND DIGEST + 20.65 18 NEWSPAPERS + 19.87 19 RADIO-TV + 17.06 20 SEMICONDUCT + 12.75 21 BLDG MATLS + 9.54 22 MACH INDUSTR + 8.38 23 OFC EQX IBM + 7.90 24 TOBACCO + 3.77 25 ELEC EQUIP + 3.28 26 S&P 400 + 2.67 27 RESTAURANTS - 2.72 28 DRUGS - 3.75 29 HOSP SUPPL - 6.71 30 EL MAJOR CO - 7.48 31 PROP CAS INS - 7.86 32 OFFICE EQUIP - 8.02 33 MACH AGRI - 9.18 34 LIFE INS - 10.63 35 CONT MET&GL - 11.72 36 MACH CONSTR - 14.90 37DJIA - 17.29 38 BANKS OUT NY - 17.60 39 FOREST PROD - 20.23 40 RET FOOD CHN - 20.64 41 AIR TRANS - 22.44 42 COSMETICS - 22.93 43 FOODS - 23.08 44 SOFT DRINKS - 23.27 45 PAPER - 24.78 46 SHORT GOVTS - 24.89


BASED ON ABSOLUTE PRICES OVER THE 39 MONTHS FROM 12176 TO 03180

INFLATION 3 (Continued)

GROUP

TIRES - 55.86 60 TOBACCO + 3.77 24 ELEC UTIL - 27.24 50 NG DISTRIB + 22.49 16 NG PIPELINES + 48.28 8 TELEPHONES - 25.26 48 AIR TRANS - 22.44 41 RAILROADS + 25.52 15 NYC BANKS - 24.99 47 BANKS OUT NY - 17.60 38 LIFE INS - 10.63 34 MULTI-LN INS + 28.97 14 PROP CAS INS - 7.86 31 DJIA - 17.29 37


47 NYC BANKS - 24.99 48 TELEPHONES - 25.26 49 CHEMICALS - 26.39 50 ELEC UTIL - 27.24 51 BREWERS - 27.45 52 SOAPS - 28.15 53 RET DEPT STR - 30.47 54 COAL BITUM - 35.47 55 AUTOMOBILES - 37.12 56 AUTOS EX GM - 39.16 57 STEEL - 42.34 58 HSLD FURN AP - 44.49 59 RET GEN MDSE - 54.35 60 TIRES - 55.86


BASED ON ABSOLUTE PRICES OVER THE 28 MOTNHS FROM 02/70 TO 06/72

GROUP % CNG

S&P 400 + 26.19 IND DIGEST - 0.11 SHORTGOVTS + 7.50 AEROSPACE + 29.84 ALUMINUM - 30.18 AUTOMOBILES + 18.61 AUTOS EXGM + 46.14 BREWERS + 62.67 DISTILLERS + 30.54 SOFT DRINKS + 68.04 BLDG MATLS + 9.94 CHEMICALS + 64.51 COAL BITUM + 19.50 CONT MET&GL - 21.35 COPPER - 33.02 COSMETICS + 26.97 DRUGS + 33.69 ELEC EQUIP + 52.34 EL MAJOR CO + 44.21 HSLD FURN AP + 87.93 INSTRUMENTN + 31.58 SEMICONDUCT + 42.44 FOODS + 4.63 FOREST PROD - 18.64 GOLD MNG + 82.30 HOSP SUPPL + 5.77 MACH AGRI + 32.74 MACH CONSTR + 52.46 MACH INDUSTR + 59.00 METALS, MISC - 21.99 OFFICE EQUIP + 17.23 OFC EQ X IBM + 25.16 OIL CRUDE + 97.95 OIL DOM + 22.66 OIL INTL + 22.63 OIL WELL EQ + 126.19 PAPER - 5.98 PUBLISHING + 2.29 NEWSPAPERS + 112.27 RADIO-TV + 53.16 RESTAURANTS + 203.31 RET DEPT STR + 47.59 RET FOOD CHN + 4.77 RET GEN MDSE + 74.93 SOAPS + 73.75 STEEL - 4.24

DISINFLATION 1

RANK

30 50 44 28 59 39 20 14 27 11 43 12 38 57 60 29 24 18 21

6 26 22 48 56

7 45 25 17 15 58 41 31

5 33 34

2 53 49

3 16

1 19 46

8 10 52

RANK ORDER % CNG

1 RESTAURANTS + 203.31 2 OIL WELL EQ + 126.19 3 NEWSPAPERS +112.27 4 TOBACCO + 105.43 5 OIL CRUDE + 97.95 6 HSLD FURN AP + 87.93 7 GOLD MNG + 82.30 8 RET GEN MDSE + 74.93 9 AIR TRANS + 74.55 10 SOAPS + 73.75 11 SOFT DRINKS + 68.04 12 CHEMICALS + 64.51 13 PROP CAS INS + 63.86 14 BREWERS + 62.67 15 MACH INDUSTR + 59.00 16 RADIO-TV + 53.16 17 MACH CONSTR + 52.46 18 ELEC EQUIP + 52.34 19 RET DEPT STR + 47.59 20 AUTOS EX GM + 46.14 21 EL MAJOR CO + 44.21 22 SEMICONDUCT + 42.44 23 BANKS OUT NY + 34.92 24 DRUGS + 33.69 25 MACH AGRI + 32.74 26 INSTRUMENTN + 31.58 27 DISTILLERS + 30.54 28 AEROSPACE + 29.84 29 COSMETICS + 26.97 30 S&P 400 + 26.19 31 OFC EQ X IBM + 25.16 32DJIA + 24.41 33 OIL DOM + 22.66 34 OIL INTL + 22.63 35 NYC BANKS + 21.58 36 MULTI-LN INS + 21.48 37 RAILROADS + 19.57 38 COAL BITUM + 19.50 39 AUTOMOBILES + 18.61 40 LIFE INS + 17.31 41 OFFICE EQUIP + 17.23 42 NG PIPELINES + 16.74 43 BLDG MATLS + 9.94 44 SHORT GOVTS + 7.50 45 HOSP SUPPL + 5.77 46 RET FOOD CHN + 4.77



DISINFLATION 1 (Continued)

GROUP

TIRES - 1.75 51 TOBACCO + 105.43 4 ELEC UTIL - 6.40 54 NG DISTRIB + 6.40 47 NG PIPELINES + 16.74 42 TELEPHONES - 13.28 55 AIR TRANS + 74.55 9 RAILROADS + 19.57 37 NYC BANKS + 21.58 45 BANKS OUT NY + 34.92 23 LIFE INS + 17.31 40 MULTI-LN INS + 21.48 36 PROP CAS INS + 63.86 13 DJIA + 24.41 32


47 NG DISTRIB + 4.63 48 FOODS + 4.63 49 PUBLISHING + 2.29 50 IND DIGEST - 0.11 51 TIRES - 1.75 52 STEEL - 4.24 53 PAPER - 5.98 54 ELEC UTIL - 6.40 55 TELEPHONES - 13.28 56 FOREST PROD - 18.64 57 CONT MET&GL - 21.35 58 METALS, MISC - 21.99 59 ALUMINUM - 30.18 60 COPPER - 33.02


BASED ON ABSOLUTE PRICES OVER THE 24 MONTHS FROM 12174 TO 12/76

GROUP % CNG

SP 400 + 55.48 IND DIGEST + 87.92 SHORT GOVTS + 7.10 AEROSPACE +130.11 ALUMINUM + 87.64 AUTOMOBILES + 127.55 AUTOS EX GM + 87.26 BREWERS + 5.65 DISTILLERS + 6.76 SOFT DRINKS + 68.77 BLDG MATLS + 106.61 CHEMICALS + 50.01 COAL BITUM + 89.56 CONT MET&GL + 45.32 COPPER + 15.91 COSMETICS + 58.12 DRUGS - 5.52 ELEC EQUIP + 68.36 EL MAJOR CO + 71.32 HSLD FURN AP + 109.88 INSTRUMENTN + 63.36 SEMICONDUCT + 55.80 FOODS + 67.11 FOREST PROD + 95.49 GOLD MNG - 17.00 HOSP SUPPL + 17.15 MACH AGRI + 59.28 MACH C~NSTR + 82.01 MACH INDUSTR + 36.71 METALS, MISC + 49.46 OFFICE EQUIP + 52.75 OFC EQX IBM + 26.71 OIL CRUDE + 40.95 OIL DOM + 47.20 OIL INTL + 66.50 OIL WELL EQ + 40.87 PAPER + 98.77 PUBLISHING + 162.19 NEWSPAPERS + 112.69 RADIO-TV + 135.03 RESTAURANTS + 94.62 RET DEPT STR + 76.41 RET FOOD CHN + 45.87 RET GEN MDSE + 58.79 SOAPS + 21.64 STEEL + 66.79

DISINFLATION 2

RANK

36 12 56

3 13

4 14 58 57 21

7 39 11 44 55 33 59 22 20

6 28 34 23

9 60 53 31 16 49 40 37 51 47 42 25 48

a 1 5 2

10 19 43 32 52 24

RANK ORDER % CNG

1 PUBLISHING + 162.19 2 RADIO-TV + 135.03 3 AEROSPACE +130.11 4 AUTOMOBILES + 127.55 5 NEWSPAPERS + 112.69 6 HSLD FURN AP + 109.88 7 BLDG MATLS + 106.61 a PAPER + 98.77 9 FOREST PROD + 95.49 10 RESTAURANTS + 94.62 11 COAL BITUM + 89.56 12 IND DIGEST + 87.92 13 ALUMINUM + 87.64 14 AUTOS EX GM + 87.26 15 TIRES + 82.86 16 MACH CONSTR + 82.01 17 AIR TRANS + 80.62 la MULTI-LN INS + 76.59 19 RET DEPT STR + 76.41 20 EL MAJOR CO + 71.32 21 SOFT DRINKS + 68.77 22 ELEC EQUIP + 68.36 23 FOODS + 67.11 24 STEEL + 66.79 25 OIL INTL + 66.50 26 BANKS OUT NY + 65.05 27DJIA + 63.39 28 INSTRUMENTN + 63.36 29 ELEC UTIL + 60.42 30 NG DISTRIB + 59.99 31 MACH AGRI + 59.28 32 RET GEN MDSE + 58.79 33 COSMETICS + 58.12 34 SEMICONDUCT + 55.80 35 NG PIPELINES + 55,71 36 S&P 400 + 55.48 37 OFFICE EQUIP + 52.75 38 TELEPHONES + 50.29 39 CHEMICALS + 50.01 40 METALS, MISC + 49.46 41 PROP CAS INS + 48.94 42 OIL DOM + 47.20 43 RET ~00~ CHN + 45.87 44 CONT MET&GL + 45.32 45 RAILROADS + 45.16 46 LIFE INS + 44.39




GROUP % CNG RANK RANK ORDER % CNG

TIRES TOBACCO ELEC UTIL NG DISTRIB NG PIPELINES TELEPHONES AIR TRANS RAILROADS NYC BANKS BANKS OUT NY LIFE INS MULTI-LN INS PROP CAS INS DJIA

+ 82.86 15 + 31.27 50 + 60.42 29 + 59.99 30 + 55.71 35 + 50.29 38 + 80.62 17 + 45.16 45 + 45.16 54 + 65.05 26 + 44.39 46 + 76.59 18 + 48.94 41 + 63.39 27

47 OIL CRUDE + 40.95 48 OIL WELL EQ + 40.87 49 MACH INDUSTR + 36.71 50 TOBACCO + 31.27 51 OFC EQX IBM + 26.71 52 SOAPS + 21.64 53 HOSP SUPPL + 17.15 54 NYC BANKS + 16.44 55 COPPER + 15.91 56 SHORT GOVTS + 7.10 57 DISTILLERS + 6.76 58 BREWERS + 5.65 59 DRUGS - 5.52 60 GOLD MNG - 17.00


BASED ON ABSOLUTE PRICES OVER THE 40 MONTHS FROM 03/80 TO 07183

GROUP % CNG

S&P 400 + 58.41 IND DIGEST + 174.94 SHORT GOVTS + 12.19 AEROSPACE + 56.47 ALUMINUM + 16.34 AUTOMOBILES + 70.42 AUTOS EX GM + 123.58 BREWERS + 179.14 DISTILLERS + 62.30 SOFT DRINKS + 72.26 BLDG MATLS + 50.60 CHEMICALS + 39.44 COAL BITUM - 9.85 CONT MET&GL + 49.94 COPPER + 40.17 COSMETICS + 20.29 DRUGS + 74.32 ELEC EQUIP + 76.59 EL MAJOR CO +113.89 HSLD FURN AP +215.75 INSTRUMENTN + 153.49 SEMICONDUCT + 123.45 FOODS + 95.36 FOREST PROD + 16.38 GOLD MNG + 64.06 HOSP SUPPL + 141.62 MACH AGRI - 18.52 MACH CONSTR - 4.50 MACH INDUSTR + 20.83 METALS, MISC + 62.30 OFFICE EQUIP + 77.67 OFC EQX IBM + 27.32 OIL CRUDE + 39.80 OIL DOM + 18.99 OIL INTL + 3.37 OIL WELL EQ + 1.59 PAPER + 44.23 PUBLISHING + 209.39 NEWSPAPERS + 195.61 RADIO-TV + 157.06 RESTAURANTS + 181.99 RET DEPT STR + 231 .I 2 RET FOOD CHN + 116.40 RET GEN MDSE + 161.14 SOAPS + 68.38 STEEL + 1.08 TIRES +161.42

DISINFLATION 3

RANK RANK ORDER % CNG

34 1 RET DEPT STR +231.12 7 2 HSLD FURN AP + 215.75

53 3 PUBLISHING + 209.39 35 4 NEWSPAPERS + 195.61 51 5 RESTAURANTS + 181.99 27 6 BREWERS + 179.14 14 7 IND DIGEST + 174.94

6 8 TIRES +161.42 33 9 RET GEN MDSE + 161.42 26 10 RADIO-TV + 157.06 36 11 INSTRUMENTN + 153.49 43 12 HOSP SUPPL + 141.62 59 13 AIR TRANS + 137.06 37 14 AUTOS EX GM + 123.58 41 15 SEMICONDUCT + 123.45 48 16 RET FOOD CHN + 116.40 25 17 EL MAJOR CO + 113.89 24 18 LIFE INS + 107.58 17 19 FOODS + 95.36 2 20 NYC BANKS + 81.41 11 21 TOBACCO + 80.46 15 22 RAILROADS + 78.32 19 23 OFFICE EQUIP + 77.67 50 24 ELEC EQUIP + 76.59 31 25 DRUGS + 74.32 12 26 SOFT DRINKS + 72.26 60 27 AUTOMOBILES + 70.42 58 28 SOAPS + 68.38 47 29 MULTI-LN INS + 65.06 32 30 PROP CAS INS + 64.81 23 31 GOLD MNG + 64.06 46 32 METALS, MISC + 62.30 42 33 DISTILLERS + 62.30 49 34 S&P 400 + 58.41 55 35 AEROSPACE + 56.47 56 36 BLDG MATLS + 50.60 40 37 CONT MET&GL + 49.94

3 38 ELEC UTIL + 49.07 4 39DJIA + 48.00

10 40 PAPER + 44.23 5 41 COPPER + 40.17 1 42 OIL CRUDE + 39.80

16 43 CHEMICALS + 39.44 9 44 TELEPHONES + 38.89

28 45 BANKS OUT NY + 36.96 57 460FC EQX IBM + 27.32

8 47 MACH INDUSTR + 20.83


BASED ON ABSOLUTE PRICES OVER THE 40 MONTHS FROM 03108 TO 07/83


GROUP % CNG RANK RANK ORDER % CNG

TOBACCO ELEC UTIL NG DISTRIB NG PIPELINES TELEPHONES AIR TRANS RAILROADS NYC BANKS BANKS OUT NY LIFE INS MULTI-LN INS PROP CAS INS DJIA

+ 80.46 21 + 49.07 38 + 12.18 54 + 16.25 52 + 38.89 44 + 137.06 13 + 78.32 22 + 81.41 20 + 36.96 45 + 107.58 18 + 65.06 29 + 64.81 30 + 48.00 39

48 COSMETICS + 20.29 49 OIL DOM + 18.99 50 FOREST PROD + 16.38 51 ALUMINUM + 16.34 52 NG PIPELINES + 16.25 53 SHORT GOVTS + 12.19 54 NG DISTRIB + 12.18 55 OIL INTL + 3.37 56 OIL WELL EQ + 1.59 57 STEEL 1.08 58 MACH CONSTR

T 4.50

59 COAL BITUM - 9.85 60 MACH AGRI - 18.52


STOCKS IN THE S6P 500 PRICE INDEX

- 400 INDUSTRIALS -

AEROSPACE-Boemg. General Dynamrcs. Grumman. Martm

Marretta, McDonnell Douglas, Raytheon Rockwell lntl Unded

Technologres.

ALUMlNUMdlcan Alummum. Aluminum Co of Amer. Karser

Alummum; Reynolds Metals

AUTOMOBILE-Amer Motors: Chrysler. Ford: Gen Motors.

AUTO F’ARTS(Afk?r Market&Champron Spark Plug. Echlrn Kfg

Genuine Parts; Sealed Power Corp

AUTO PARTS (Original Equip.&Dana. Eaton: Lrb -Owens-Ford.

TRW Inc., Trmken Corp.

AUTO TRUCKS 6 PARTS-Cummrns Engrne: Fruehauf: Paccar

IIIC

BEVERA6ES (BREWERS)-Anheuser-Busch. Coors (Adolph):

Hedeman (G) Brewmg: Pabst Brew

BEVERA6ES tOISTILLERS~Brown-Forman Drstrllers, Nab Dust.:

Seagram Ltd.: Walker.

BEVERIIGES (SOFT ORlNKStCoca-Cola: Or Pepper. General Cinema: PepsrCo Inc : Royal Crown Cos

BUILDING MATERIALS -American Standard. Crane: Fedders: Ideal Basrc, hm Walter: Karser Cement; tone Star Ind Masco:

Masomte: Nat? Gypsum; Dane: U.S Gypsum.

CHEMICAL&Dow: Du Pont (E.I.): Hercules, Monsanto: Stauffer

Chem ; Umon Carbrde.

CHEMICALS tMISC&AJhed Corp. Amencan Cyanamrd. Celanese Corp.: FMC Corp.: Grace (WR.1 &Co.; PPG. Inc Rohm & Haas

CW(BITUMlNOUS&Eastem Gas & Fuel. No Amet Coal: Pdtston.

Westmoreland.

COMMUNICATION~E6UIC/MFRS.-M A-Corn Inc Northern Tefecom.; Rolm Corp.: Screntrfrc Atlanta.

COMPUTER SERVICELAutomahc Data: Computer Sciences:

Electromc Data Systems: lymshare.

CONGLOMERAlE~GuIf & Western: IC lndus Int’l Tel & Tel..

Litton Indus., Northwest lndus, Teledyne; Tenneco Inc Textron

CONTAINERS (METAL & 6USStAmer. Can, Contl Group, Crown

Cork: Natl. Can: Owens-Ill.

CONTAINERS (PAPERtBemrs Co : Stone Contamer: Federal,

Maryland Cup.

COPPER-ASARCO Inc.. Newmont Mrmng: Phelps-Dodge

COSYEllC%Afbertc&lver: Ibon: Chesebrough-Fond’s: Faberge

Inc.: Intl. Flavors & Fragrances: Revlon.

ORU6S-Amer. Home; Bristol-Myers: Ldly (El0 Merck: Pfizer.

Schenng-Plough; Searte (G. 0.1: SmrthKhne Beckman Corp.

Squibb Corp.; Sterhng; UpJohn Co.: Warner-Lambert.

ELECTRICAL EPUIPMENT-Emerson Electrrc: General Instrum.. Grainger tW W,): McGraw Edrson, Square D: Thomas & Betts

ELECTRONICS MAJOR COS.--Gen. Elec.; RCA. Westinghouse Elec

ELECTRONICS (IN6lRUMENlAllONJ-Gould Inc.: Hewlett-Packard;

Perkin-Elmer: Tektronix.

ELECTRBNIS (SEMlCONOUCTORS/COMWNENTS&AMP Inc : Intel

Corp.: Motorola. Nat’1 Semiconductor: Texas Instruments

ENTERTAINMENT-Drsney (Walt). MCA MGMUA Entertamment

Co.; Warner Communications.

FERTILIZER~Beker Inds.; Frrst Miss. Corp : Intl. Mmerals &

Chem.; Wdliams Cos.

FOODS-Amstar Corp : Archer-DameIs-Mrdland: Beatnce Foods, Borden; CPC Int’l.; Campbell Soup: Carnatron. Consohdated

Foods: Dart & Kraft Inc.; Gen. Foods: Gen Mills: Gerber Prod.;

Hemz (HJ.); Hershey Foods: Kellogg: Nabtsco Brands Inc: Morton Simon; Pillsbury; QuakerOats: Ralston Rrrna. Stokely-

Van Camp; Wrigley (Wm.).

FOREST PRODUCT&Bofse Cascade: Champron lntl : Evans Products: Georgra-Pacrfrc: Loursrana-Pac., Potlatch Corp

Weyerhaeuser.

t6AMlN6 COS.-Bally Mfg.: Caesars World: Resorts Int’l (Cl. Al:

Webb (Del. E.T.

HOMEBUILUlN6-Centex Corp.: Kaufman & Broad: U.S. Home Corp.

6010 MININGASA Ltd ; Campbell Red Lake; Dome. Homestake

Mming.

NOSPllNl YANlGEYENT-Amer. Med. Int’l; Hosprtal Corp. of

Amer.: Humana Inc.: Nat’1 Med. Enter.

HOSPITALSUPPLIES-Abbott Lab. Amer Hosprtal: Bard (C R J. Baxter Travenol tab Becton. Drckrnson. Johnson & Johnson

HOTEL-MOTEL-Hrlton Hotels, Hohday Inns: Ramada Inns

HOUSEHOLO FURNISHING 6 APPLIANCES-Bassett Furndure

ind Maytag. Roper Corp Mohasco Corp Whrrlpool, Whrte Consolrdated lnds Zemth

LEISURETIME-AMF Inc. Brunswrck. Coleman Co Handleman. Outboard Manne

MACHINE TOOLS-Acme Cleveland, Brown & Sharpe. Cmcrnnatr Mrlacron. Cross & Trecker. Monarch Machrne Tool

MACHINERY ~A~RICULTURAL~AIIIS Chalmers, Deere, Intl. Har- vester, Massey Ferguson

NACHINERY (CONSTRUCTION 6 MATERIALS tMNOLlN6~Bucy~us- Erie: Cater. Trac Clark Equrp Hyster Co. Rexnord Inc

MACtNNERVDNDUSTRIAL’SPEClALTV~Br~ggs & Stratton. Chrcago Pneumatrc. Combustron Eng Cooper Indus.. Ex-Cell-O. Foster

Wheeler. Ingersoll-Rand. Joy Mfg.

MEIALS MISC.-Amax Inc : Hudson Bay Mng ; INCO Ltd. Phibro

Salomon Inc.

MISCELLANEOUSARA Servrces. AT&T. Apple Computer: Armstmng

World: Black & Decker, Borg-Warner, Cornmg Glass. Eastman

Kodak, Esmark. Fluor Corp. Grllette. Harris Corp. Honeywell Inc MCI Commumcahons. Mrnnesota Mmmg, Owens-Coming.

Polarold: Shemrn-Willlams. Srgnal Cos.. Smger. Snap-on Tools:

Stanley Works: Tandy

MOBlLEHOME~Fleetwood Enterprrses. Redman Inds.: Skyhne.

OFFICE & BUSINESS EtlUIPMENT-Burroughs. Control Data. Data General. Datapornt Corp : Drgrtal Equrp.. lntl Bus Mach :

NCR Corp Pdney-Bowes. Sperry Corp. Storage Tech. Wang

Lab Cl B. Xerox Corp

OFFSHORE DRILLING-Global Marme. Readrng & Bates, SEDCO;

Western Co of North America.

OIL (CRUOE PROOUCERSttoursrana Land & Exploratron; Mesa

Pet, Pennzorl Co, Superror 011. Texas 011 &Gas

OIL (INTEGRATED-OOMESTlCtAtl. Rrchfreld. Get@ 011. Occrdental

Petroleum, Phrlhps. Shell, Stand 011 Ind Standard 011 Ohio:

Sun Co, Umcal Corp

OIL (INTEGRATED-INTERNATIONAL&Exxon Corp Gulf. Mobrl

Corp.. Royal Dutch. Stand Or1 Calrf. Texaco.

SCANAOIAN OIL 6 61s EXPLORATlOtCDome Petroleum. Gulf of

Canada. Husky 011. lmperral 011 ttd

OIL WELL EtlUIPMENT AN0 SERVICES-Baker lntl Dresser:

Hallrburton: Hughes Tool, McDermott Int’l.: NL Industries:

Schlumberger

PAPER-Crown Zell.. Int‘l Paper: Krmb-Clark, Mead; St Regrs.

Scott, Umon Camp: Westvaco

POLLUTION CONTROL-Brownmg-Ferns: Peabody Int’l : SCA

Servrces. Waste Management Inc.: Zurn Ind

PUBLISHINGDun & Bradstreet: Harcoud Brace lovanovrch.

Macmdlan. McGraw-Hrll. Meredrth. SFN Co : Time Inc

PUBLISHING (NEWSPAPERS&Dow Jones: Gannett Co.. Kntght Rrdder Newspapers. Trmes Mrrror

RAOIO-TV BROAOCASTERtAmerrcan. CBS Inc.. Caprtal Crtres

Comm.. Cox Commumcatron Corp.: Metromedra. Taft.

RAILRMO EBUIPMENT-%F Ind., Amsted lndus : Gen. Srg.

RESTAURANTS-Church’s Frred Chrcken: Denny’s Inc. Marrrott.

McDonald’s Corp Wendy’s Int’l.

RETAIL STORES tOEPI SlORES&-Afhed Stores: Assocrated: Carter

Hawley Hale Stores; Dayton Hudson: Federated: Macy: May

Dept Mercantde Stores.

RETAIL STORES (ORUGbEckerd (Jack): Revco D.S Inc Rrte

Ard: Walgreen Co.

STEEL-Armco: Beth Inland. Interfake, Natronal: Republrc: U S.

Steel: Wheehng-Prttsburgh.

RETAIL STORES (FOOD CHAINS)-Amer. Stores Co.: Great A.&P: Jewel Compames. Kroger: Lucky Stores, Safeway; Wmn-Drxre

RETAIL STORES f6EN. MDSE. CHAINS)-K mart; Penny (1.C.h

Sears. Wal-Mart Stores; Woolworth

SHOELBrown Group: Genesco: Interco; Melvdle Carp

SUAP~Clomx: Colgate-Palmohve; Procter & Gamble: Undever

N.V.

TEXTN.ES (APPAREL MFRS&Blue Bell: Cluett Rabody: Hartmarx Corp.: Jonathan Logan: Levr Strauss: V.E Carp


TEXTILE PROOUCT~Burhngton lndus Colhns. Cone Mrlls

Lowenstem Sprrngs lndustrres Inc Stevens. West Pmnt- Pepperell

TIRES 6 RUBBER 600O~Fnestoce Gcodnch. Goodyear. Unnoyai

TOBACCO-Amer Brands Inc Phrhp Morns, Reynolds lndus

TOYLColeco Inc Mattel Inc Mrlton Bradley. Tonka Corp

- 40 PUBLIC UTILITIES - ELECTRIC POWER-Amer El. Pwr. Balt G & E.. Cent & So

West. Corp Comm Ed : Con Ed : Detroit Ed Duke Power. Fla Power & Lrght. Middle So Utrl New Eng Elec Sys,

Niagara Mohawk. No. States Pwr. Ohro Ed., Pat G & E., Phrla

Elec Pub. Serv E. & G.. Publrc Servrce of Indrana. So. Cahf Ed Southern Co., Texas Utrls.: Va. E. & P: WISC El. Pwr

NATURAL 6AS DISTRIBUTOR~Bklyn Umon: Columbra. Consol- rdated Natural, ENSERCH Corp., Oneok Inc.. Pat Lrght. Peoples

Energy

NATURAL 6115 PIPE LINELAmer Natural Resources: El Paso

Co InterNorth Inc.: Panhandle Eastern: Sonat Inc Texas East

Corp Texas Gas Trans

TELEPHONE--‘AT&T: Centel Corp : Contl. Tel.: GTE Corp.. Unded

Telecommumcatrons

- 20 TRANSPORTATION - AIR FREIGHT -Emery Arr Frerght. Federal Express. Trger inter-

natronal

AIR TRANSPORT-AMR Corp.: Delta. Northwest. Pan Am. UAL.

Inc

RAILRMDS-Burhngton Northern Inc. CSX Corp : Norfolk Southern

Carp, Santa Fe industries. So Pac. Umon Pat Corp

TRUCKERS-Consol Frerghtways. Overmte Transportatron.

Roadway Servrce: Yellow Frerght Sys.

lRANSPORWION fMISCELLANEOUSJ4easeway Transportatron.

Ryder System

- 40 FINANCIAL - BANKS (NEW YORK ClTVbBankers Trust New York. Chase Man-

hattan Chemrcal. Cdrcorp: Manufacturers Hanover: Morgan

f1.P) & Co

BANKS fOUlSIOE NEW YORK ClTV&BankAmenca; Bank of Boston Corp : Cont‘l Ill. Corp.. Frrst Chrc. Corp.; hrst Interstate Bancorp..

Frrst Penn., InterFirst Corp. Mellon Nat1 : NCNB Corp.. Northwest

Corp

LIFE INSURANCE-Capkal Holdmg: Jefferson Pilot; Lmcoln National

Corp., USLIFE Corp.

MULTI-LINE INSURANCE&tna Life & Cas.: Amencan Int’l Gmup:

American General: CIGNA Corp.: CNA Financral. Travelers.

PROPERTY-CASUALTY INSURANCE-Chubb Corp.. Contrnental

Corp.: St. Paul: Safeco Corp : USF E G Corp.

SAVINGS 6 LMN HOLOING COS.-Ahmanson (H.0 Frrst Charter.

Great Western.

PERSONALLMN~Benefrcral; Household Int’l Inc

FINANCIAL-MISC.-Amencan Express; Heller (Walter E ): Merrill

Lynch; Transamenca Corp.

l *BRONERA6E FIRM6-Donaldson Lufkm Jenrette; Edwards fA.G.1;

Hutton fE.F) Group, Paine Webber, Inc.

**INVESTMENT COMPANIES-Adams: Gen. Amer: Lehman:

Madrson, Tri-Cont.

*‘INVESTMENT COS. (Bond Funds)-Amerrcan General Bond;

lntercaprtal Inc. Sec.: John Hancock Inc Sec.; Masshlutual Inc. Inv.. Montgomery Str. Inc. Sec.

“REAL ESTATE INVEST-Frrst Union Real Estate, Lomas &

Nettleton Mtge. Inv.; Mass-Mutual Mtge & Realty: Mony Mtg..

Wells Fargo Mortge. & Equdy

tNot included rn 400 Industrials. ‘Not mcluded m Utddy composde.

**Not mcluded m Financial composrte.

tSupplementary Groups and Changes on Preceding Page)

David Upshaw is a Vice President of Waddell & Reed, Inc., a Kansas City-based financial services firm. He is the firm’s Director of Portfolio Strategy Research. David is a Founding Member of the MTA and served as its fourth President. He is a Chartered Financial Analyst, and belongs to the Kansas City Society of Financial Analysts and the New York Society of Security Analysts, Inc.


journal of technical analysis (jota). issue 16 (1983, november)

Economy & Finance

mta meetings

mta letter

cfa mta journalnovember

monthly mta newsletter

journal james yates

merrill john

group john murphy

pine street new york