Journal of Technical Analysis (JOTA). Issue 04 (1979, February)

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Market Technicians Association

JOURNAL ISSUE 4 FEBRUARY 1979

IMARKET TECHNICIANS ASSOCIATION JOURNAL

Issue 4

February, 1979

PUBLISHED BY: MARKET TECHNICIANS ASSOCIATION 70 PINE STREET NEW YORK, NEW YORK 10005

Direct inquiries to:

Fred R. Gruber, Editor Market Technicians Association Journal c/o United Jersey Bank 210 Main Street Hackensack, New Jersey 07602

Copyright 1979 by Marke t Technicians Association

MARKET TECHNICIANS ASSOCIATION JOURNAL

EDITOR:

Fred R. Gruber, C.F.A. United Jersey Bank 210 Main Street Hackensack, New Jersey 07602

ASSOCIATE EDITOR:

William DiIanni Wellington Management Company 28 State Street Boston, Massachusetts 02109

EDITORIAL ASSISTANT:

Ms. Cheryl Stafford, Wellington Management Co.

Thanks to Market Technicians Association members for their

part in the creation of this issue are owed to:

Robert Farrell Howard Hebert Stan Lipstadt Arthur A. Merrill Robert R. Prechter, Jr. John Schulz David L. Upshaw

INDEX

MARKET TECHNICIANS ASSOCIATION JOURNAL - FEBRUARY 1979

Editor's Notes . . . . . . . . . . . . . . . . . . . .

MTA Fourth Annual Seminar Program . . . . . . . . . .

Indicator Analysis:

Stock Market Forecasting through the Interrelating of Bond Prices and Stock Prices By Roger Williams, Ph.D. . . . . . . . . . . . . . .

The Short Interest Ratio and Its Component Parts By Thomas J. Kerrigan . . . . . . . . . . . . . . . .

General:

Portfolio Management By Howard Hebert. .

Smoother is Sharper By David L. Upshaw.

by Robot: The Ultimate Put-Down . . . . . . . . . . . l . . . . .

. . . . . . . . . . . . . . . . .

A Twenty-Year Business Slump? Not a Ghost of a Chance. By John Schulz. . . . . . . . . . . . . . . . . .

Statistically Significant:

Fifty Years of Market Volatility By Robert R. Prechter Jr. and Robert J. Farrell .

Percent Change in One Year - S&P 400 and D.J.I.A. By Arthur A. Merrill. . . . . . . . . . . . . . .

Funds - Cash Position By Arthur A. Merrill. . . . . . . . . . . . . . .

. .

. .

. .

. .

Book Reviews:

Elliott Wave Principle - Key to Stock Market Profits Reviewed by Willlam DiIanni . . . . . . . . . . . . .

Pages

4

5

7 - 12

13 - 17

19 - 23

24 - 28

31 - 33

35 - 36

37 - 38

39 - 40

41 - 43

EDITOR'S NOTES -

Technicians beware, I see signs of loss of momentum, or at the

very least consolidation in an issue. Its uptrend has been broken,

but hopefully the issue will simply go through a test here, find

new support and go on with renewed strength to new highs, and

with increased distribution besides. That's not an inconsistent

use of technical analysis descriptors when you realize that the

issue in question is the Market Technicians Association Journal

itself.

The smaller current issue again reflects the work of very few

contributors, many of whom were the mainstay of our past efforts

as well. There are no"Letters To and Through the MTA Journal"

this time - weren't there any reactions to past articles, or isn't

there furtherwork to be communicated on those subjects? If you've

considered our Journal to be worthwhile reading, how about preparing

your own contribution ? Let's make our May issue, for the Fourth

Annual MTA Seminar, special. (See page 29.)

For the first time we are showing subscription information within

our Journal. Pass it along to an interested party and help our

distribution. And again, even more importantly, send us a chart,

a report, a market letter or something you've produced or seen

recently which we can use in your Journal--the only publication .

of its sort that I know of in the United States.

Fred R. Gruber

May 3-6,1979 THURSDAY, MAY 3

4:00 pm-Registration

10:30 am-MARKET LETTER WRITERS

Moderator: Abe Cohen, President Chartcraft, Inc.

Panelists: John Goddess, Editor The Master Indicator

Ian McAvity, Editor Deliberations

Stan Weinstein, Editor Professional Tape Reader

12:oO Noon-Lunch and Free Time

150

100

50

0

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-100

.* 50

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6130 pm-Cocktails

7:30 pm-Dinner

9:00 pm-KEYNOTE SPEAKER William O’Neil, Chairman William O’Neii & Co., Incorporated

6130 pm-Cocktails FRIDAY, MAY 4

7:30 pm-Dinner 7:30 am-Breakfast

9:OC am-STUDIES IN VOLUME

Paneiists: David Bostian, President Bostian Research Associates

Paul Desmond. President Lowry‘s Reports, Inc.

9:00 pm-“ IS THE WORLD COMING TC AN END?”

Alan Abelson, Managing Editor Barron’s

IO:30 am-Coffee Break 4:45 pm-THE CHANGING NATURE OF TECHNICAL ANALYSIS

Speaker: Stan West, Vice President. Business Research New York Stock Exchange

SUNDAY, MAY 6

7:30am-Breakfast

9:00 am -OPTIONS

Panelists: Mike Epstein, General Partner, Tradrng Cowen & Co.

GaFy Knight, Member Chicago Board Options Exchange

Morns Propp, President Cygnet V Securities

Steven Shobin. Assistant Vice President Merrill Lynch, Pierce, Fenner 8 Smith

10:45 am-ELLIOT WAVE: PURE FORM

Panelists: William Dilanni, Vice ?resident Wellington Management

A. J. Frost, Dean of Elliott Wave Theory

Rooert Prechter. Vice President Merrill Lynch. Pierce, Fenner & Smith

7:30 pm-Dinner

9:00 pm-MTA Annual Award

Presentation

12:30 pm-Lunch and Free Time

3:00 pm-GROUP SELECTiON TECHNIQUES

Panelists: David Diamond, Vice President Boston Company

Steven Leuthold, Vice President. Director Funds. inc.

David Uoshaw, Vice President Drexel Burnham Lambert. Inc.

SATURDAY, MAY 5

7:30am-Breakfast 1 :OO pm-Lunch

9:00 am-WORKSHOP: SHORT-TERM TRADING INDEX- APPROACHES AND RESULTS’

Speaker: Anthony Tabeli, Associate Deiafield, Harvey, Tabell Division of Janney, Montgomery. Scott

I ’

‘Registrants are encouraged to submit slrategies employing the Shorr-Term Trading index !hat they would like t9 see tested.

: Please submit any testable strategy I I

along with your registration form.

.-

4:30 pm-Coffee Break

SEE OVER FOR REGISTPATION FORH

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

SUBSRIBER STATUS - $50 per year plus $10 one-time application fee

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

Single issues of the MTA Journal (including back issues) are available for: $5 to regular members or subscribers

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The Market Technicians Association Journal is intended to be published three times each fiscal year, February and May.

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STOCK MARKET FORECASTING THROUGH THE INTERRELATING

OF BOND PRICES AND STOCK PRICES

by Roger Williams, Ph.D. St. John's University

There has been considerable discussion of bond yields, stock yields, interest rates and stock prices in the past. For some purposes, it may well be better to compare bond prices and stock prices directly. Bond yields and stock prices are unlike objects, whereas bond prices and stock prices are comparable. Looking at matters this way also focuses on possibilities for capital gains and losses in both vehicles. For our purposes, we have found it appropriate to use the Standard and Poor's 500 Composite Index as the measure of common stock prices, and Standard and Poor's Index of Prices per $100 of High Grade Corporate Bonds for fixed income.

The long-term trend of stock prices has been generally upward, while the long-term path of bond prices has usually been downward since World War II. Tables I and II present major cyclical swings in monthly stock prices and bond prices during the period 1945-1978, with peak and trough dates as selected by the author. Stock prices have shown more numerous cyclical swings than bond prices during the 1945-1978 period.

Stock price peaks with no bond price counterpart were clearly demonstrated in 1961 and 1968. With other stock price peaks, bond prices led the way downward, but the length of the lead was highly variable and sometimes very long. When leads are extremely long, they are often of very limited use. Despite these various qualifications, bond price movements are useful in identifying stock price peaks. During our review period, stock price peaks always occurred when the general trend of bond prices was downward.

Again comparing Table I and Table II, there were stock lows in 1947 and 1962, with no low in bond prices. The recovery of bond prices lagged by one month in 1970 and five to eight months in 1974-1975, but in five other cases, bond prices led on the way up. When bond prices move up, there is a very favorable signal for stock prices, and the lead has always been under a year, and usually much shorter.

Another way of looking at bond prices and stock prices is to note periods when they move in the same direction and when they move in opposite directions. In Chart I, we have scored +2 when both prices are rising on a month to month basis, +l when stock prices alone are rising, -1 when stock prices alone

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are falling and a -2 when both stock prices and bond prices are falling. Identification of stock market peaks is not always clear, but they are often preceded by two or more monthly scores of +2. Seven out of nine peaks have been followed very quickly by two or more readings of -2, the exceptions being 1953 and 1961-1962.

Stock market lows have typically been marked within two months by a sharp improvement from negative numbers to positive numbers. The present position of the market looks favorable, since there was a sharp move from -2 in November 1976 to a +l in December of 1978, and January numbers add further confirmation.

Chart II presents a ratio of bond prices divided by stock prices, a measure of relative price action. We have inverted the scale so that increases indicate favorable relative action for stock prices and declines represent unfavorable relative price action for stocks. Market peaks have been typically preceded by a rather long period of rising relative price action, but this method does not provide a good method for quickly identifying market peaks. There is normally a rather clear descent towards market lows and there is a distinct change of direction when the market passes from decline to recovery. The bond price/stock price ratio is a very valuable ratio in identifying major stock market lows.

Narket history since the stock market peak in late 1976 clearly points to a major stock market low in March 1978. Recovery of the bond price/stock price ratio since then has proceeded in a traditional manner, and the S & P 500 is still well below its earlier peak.

Bond price lows have been most useful as an advance indicator for stock market lows. A rise in bond prices is very favorable for the stock market and the lead has usually been much shorter - than a year. The ratio of bond prices divided by stock prices (inverted) is also a valuable clue, with increases (favorable relative price action for stocks) suggesting upward movement for the stock market. The most unfavorable sign for the stock market would be a sharp switch from both bond and stock prices moving up (a +2) to both moving down (a -2). The most favorable sign would be a sharp switch from a negative (-2) to a positive (+2).

Author's Note: I wish to thank Natasha Spearman-Isip for assistance in the preparation of this paper.

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Peaks

May 1946

June 1948

January 1953

July 1956

July 1959

December 1961

January 1966

December 1968

January 1973

September 1976

Peaks

Table I

STOCK ?RICE CYCLES (Standard and Poor's 500)

Troughs

May 1947

June 1949

September 1953

December 1957

October 1960

June 1962

October 1966

May 1970

December 1974

March 1978

Table II

BOND PRICE CYCLES (Standard and Poor's High Grade Corporate Bonds)

March, April 1946

January, February, March 1950

April 1954

January 1958

February 1963

February 1967

January 1972

December 1976

Troughs

August, September, October, November, 1948

June 1953

September 1957

January 1960

September 1966

July 1970

May, August 1975

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CH.A-?T 1 DIRECTION OF BOND PRICES AND STOCK PRICES -

+2 Both prices moving up on a month to month basis i-1 Only stock prices moving up -1 Only stock prices moving dct;n -2 Bond prices and stock prices both moving down ?= peak T= trough All scales are equal for each period

-

T-trough

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aRRr3 EKNDPIiIcEs

P = peak, stock prices '@ trough, stock prices

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Originally published in the Financial Analysts Journal November/December 1374

lieprinted with pe,mLssion

by Thomas J. Kerr&n

First National Sank of Boston

The Short Interest Ratio, published monthly in Barron’s, is considered a reliable indicator of future market direction by most members of the technical school of security analysis. It is computed by dividing the number of shares sold short on the .New York Stock Exchange as of the fifteenth of the month (or before if the fifteenth falls on a non-business day), by the average daily volume of shares traded for the month ending on that same day. The number of shares shoned total is released by the Exchange three business days later. Barron’s, which is published weekly, com- putes and publishes the ratio in the issue following the Exchange’s re!ease of the shares shorted total.

Technicians claim that, for the market as a whole as well as for individual stocks, the foilowing are bullish:

1) a large number of shares shorted; 2) a rising trend in shares shorted; 3) a relatively high Short Interest Ratio; 4) a rising trend in the Short Interest Ratio.

Conveneiy, the following are bearish:

1) a small number of shares shorted; 2) a failing trend in shares shorted; 3) a relatively low Short Interest Ratio; 4) a falling trend in the Short Interest Ratio.

Studies of the predictive value of short interest figures relative to individual stocks have produced negative results. 1.2 In addition, Barton Biggs claims

1. Barton M. Biggs, “The Shon Interest-A False Proverb,” Financial Analyszs kurnal, July/August 1966. pages 111-116.

2. Randall D. Smirh. “%on Interest and Stock Market Prices,” Financial ,dnalysrs Journal, Yovem-

beaDecember 1968. pages 15 I- 154.

that a iailing trend in shares shoned should iogically coincide with a rise in the stock in that the excess of short covering over short selling would create a condition of demand exceeding

supply. To evaluate these conflicting claims. [he author

analyzed 300 monthly Short Interest Ratios riom October 1952 to May 1969 (see Tabie A). The 200 Shon interest Ratios were ranked according to the numeric difference between the rario snd the ratio one, two. three and four months later. The period showing the greatest drop in the Shorr Interest Rario was ranked one, and the period showing the greatest rise in the Short Interest Ratio was ranked 200. The 200 rankings were then grouped into declles.

The price action for the Standard and Poor’s 500 Stock Average during the two periods was compared with the Short Interest Ratio changes in two ways. In the fira, an arithmetic average of the corresponding S&P’s 500 change-s was computed for each decide. These were then ranked from one to ten. In the second computation, changes in the S&P 500 for the individual periods were ranked from one to 200, and the average rank for each decile computed. These were also ranked from one to ten. These ranks were then correfared with the Short Interest Ratio change ranks. (The same methodology was used in Tables C, D and E.)

As can be seen from the table, the average of the 20 top ranked one-month Short Interest Ratio changes was -0.4 11. The average S&P 500 change for this top decile was +2.95 per cent. Using the S&P 500 ranking method we find that the average rank for this decile was 59.3. Both the average S&P 500 change ( + 2.95 per cent) and the average rank oi S&P 500 changes (59.3) ranked this decile first in terms of market performance in the first month. In the two, three and four month columns of the table the top ranked S&P 500 changes once again

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coincided with the top ranked average Short In- terest Ratio differences. After four months the only Short Interest Ratio deciles that corresponded to S&P 500 losses were deciles nine and ten. The disparity between Standard and Poor’s Averages for deciles one and ten grew from 1.94 per cent after one month (2.95 to 1 .Ol per cent) to 11.74 per cent after four months [ ( + 10.27 per cent) - (- 1.47 per cent) J. The ascending degrees of rank correlation from one to four months would appear to contradict the technicians’ claim that a falling ratio is bearish.

The preceding is of no value, however, unless one can anticipate the future direction of the Short Interest Ratio. Table B is an analysis of the 200 Short Interest Ratios and the ensuing changes in them one, two, three and four months later. In this table the starting values for the ratios are ranked from one to 2Oa with the highest 20 ratios assigned to the top decile. In this case, the average starting value for the top 20 ratios was 2.003. In the table both the average change occurring for each Short Interest Ratio decile one, two, three and four months later and the ranks of the average change are ranked from one to ten. Thus the top decile group of Short Interest Ratios shows drops of 0.211, 0.293. 0.312 and 0.398 for one, two, three and four months respectively. Because these drops are the largest for any decile, they all rank one. Examining the tenth decile of starting ratios, we find a steady rise from a starting average ratio of 0.827 to an average ratio four months later of 1.126. The high coefficients of rank correlation, particularly in the two, three and four month figures, indicate that the ratio displayed a strong tendency to move toward its average value (1.325).

Market Prediction At this point we can draw two conclusions:

1) Movements of the Short Interest Ratio correlate with corresponding movements of Standard and Poor’s Stock Average.

2) The future direction of the Short Interest Ratio can be predicted, based on the rela- tionship of the current ratio to the average ratio.

Using conclusions 1 and 2, can we not predict future market direction based on the level of the Short Interest Ratio? Table C indicates that indeed we can. Once again, as in Table B, the short interest ratios have been ranked from high to low

and grouped into deciles. This table shows a strong correlation between Short Interest Ratio levels and ensuing S&P 500 changes. Examining the top decile of short interest ratios we find that S&P’s 500 average advanced 2.62, 4.07, 6.48 and 8.31 in one, two, three and four months respectively. These advances, as well as the average ranks of the advances, all ranked first in the ten decile rankings. At the other end of the scale the tenth decile Short

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r Interest Ratios usually ied to tenth defile S&P 500 changes. As in TCie A, :he spread between S&P’s 500 percentage gam jioss) for dedes one and :en steadily widens. The percentage differences are 3.20, 4.33, 6.02 and 9.49 ior one, two, three and four months respefzively. Once again rhe coeti- clents of rank coneiation rise to high Ieve!s aiter three and four months.

Thus there is some compatibility between the claims oi the technicians and Biw’ bindings. The :echnicians’ assenion that a hi& Short Interes: Ratio is bullish and 3 low ratio bearish is jup- ported by Tabie C. However. this is trJe oniy because high ratios do not stay high long, and as they drop the market :ends to rise. This, of course, supports Bigs’ claim.

Trends in the ratio are only apt to develop. however, when the ratio is at 1 retatively high or low level. Trying to predic: the dire&on of the ratio by means of trends atone appears to be folly. For example, if Ihe ratio rises for three consecutive months from a low of 1 .OO to 1 .SO the chances oi it continuing to rise the foilowing month are !ow due to the fact that ir has become too high. .A study of month-to-month Trends in the ratio <or the 100- month period produced more reversals of trends than continuations.

The Components of the Short Interest Ratio Often overiooked is the fact that average daily

volume has a role in [he Shon Interest Ratio equal in importance : o rota1 shares sold short. For example, if the number oi shares honed and average

daily volume rose an equal percentage. the ratio would remain the same. To discover the relative importance of shares jnorted versus average daily volume, the data from Table ,A was broken down in Tables D and E.

Table D is an analysis of the etiect of changes in total shares jold short on rhe performance of Standard and Poor’s 500 Stock Average. Table X indicated a strong correlation between changes in the Short Interest Ratio and changes in the S&P 500, with drops in the Short Interest Ratio accompanied by above average gains in Standard and Poor’s 500 Stock Average, leading us to the preliminary conclusion that a drop in shares shorted

should be bullish. Thus, in Table D, which has iso- lated the numerator of the Short Interest Ratio, a drop in shares sold short would also cause a drop in the Short Interest Ratio uniess the denominator of the ratio (average daily voiume) dropped by a greater percentage than the numerator.

In Table D the 10 months having the great:st percentage drop in shares shorted are ranked in the tint deciie and those displaying the larges: percentage increase in shares shorted are ranked in !he tenth deciie. As might be expected, the 10 months showing the largest three-month increase in shares shorted (+ 38.32 per cent), coincided with the poorest performing S&P 500 decile (-0.68 per

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cent). However, the whole table does not fare as well. For example, reading across the top decile for one through four months (i.e., those 20 months having the largest percentage drop in shares shorted) the decile ranks of the S&P 500 average only a mildly favorable 3.87. The top ranked Standard and Poor’s decile corresponded to shares shorted deciles five, five, three and four for months one, two, three and four respectively. The only im- pressive rank correlation coefficient is the four- month rank of average S&P’s 500 gain or loss (+0.88 per cent).

Table E analyzes the effect of volume changes on the performance of Standard and Poor’s 500 Stock Average. Note that a rise in average daily volume would raise the denominator of the Short Interest Ratio, thus causing the ratio to fall (unless offset by a percentage rise in the numerator at least as great as the percentage rise in the denominator). Thus, advances in average daily volume were considered bullish and the 20 periods for each time in- terval (one, two, three and four months) with the greatest percentage increases in average daily volume were placed in the first decile. As can be seen in the two. three and four month columns of the table. there is a wide disparity between both the stock averages and the average ranks for deciles one and ten. After four months the percentage change disparity exceeds 10 per cent [ ( + 8.94 per cent) - (- 1.41 per cent) 1. In Table D the corresponding disparity is only 2.72 per cent (4.34 - 1.62 per cent). The four month average rank difference for Table E is 92.4 (47.3 - 139.7) versus only 6.5 for Table D (91.1 -97.6). Comparing Tables D and E on a month-by-month basis we find only one occasion out of eight where the correlation coefficient in Table D is higher than its counterpart in Table E, with the rank correlation coefficients in Table E 0.335 higher than the corresponding coefficients in Table D on average.

Conclusions I) During the period of this study the Short In-

terest Ratio proved to be an excellent tool for forecasting the future direction of the market.

2) Although the number of shares sold short is one of the components in computing the Short In- terest Ratio, its contribution to the predictive value of the ratio during the period of this study is minor.

3) The ratio’s past effectiveness is due mainly to the tendency for volume to be relatively high during bull markets and relatively low during bear markets.

4) For the Short Interest Ratio to perform as well in the future as it did during the period of this study, the volume patterns of future bull-bear cycles must strongly resemble those of the past-something for which, unfortunately, we have no guarantee. 8

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A PAGE FOR NOTES

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PORTFOLIO MANAGEMENT BY ROBOT: THE ULTIMATE PUT-DOWN

Howard Hebert - Newhard, Cook & Company

Few will disagree with the fact that the last decade has brought more change to the professional investment field than any other time in living memory. Much of the change has been caused by some serious questioning of the traditional methods employed in stock selection, portfolio management, market timing and the art of successful investing in general. With each new thread of truth brought to light by one camp came a reciprocal put-down to another. Consider the following hypo- thetical commentaries and their inferences :

Efficient market academician to the fundamental analyst: “Stock prices fully reflect all available information at any given time. New information, therefore is discounted too quickly in the market place to be acted upon profitably.”

Translation: “Four times earnings and a ten percent yield you say. I wonder if anyone else is aware of this ? Ho Hum. ”

Random walk theorist to the technical analyst: “In moving toward equilibrium, a securities price movement is completely inde- pendent of all previous movements.”

Translation: “You people are an arcane bunch of weirdos practicing an amusing yet futile form of tarot reading.”

Fund sponsor to bank trust department: “After considerable deliberation, the board has decided to instruct you to index our plan.”

Translation: “If your =.gg of MBA’s, CFA’s, economists, et. al. could pick stocks as well as the kid in our shipping department, we wouldn’t have to be going through this falderal.”

Modern portfolio theorist to anyone within earshot of ivory tower: “Alpha, beta, R2, correlation coefficient and extra market covariance. I’

Translation: “You poor pitiful simpletons. How can you expect to gain a modicum of success while wallowing down there in your quagmire of ignorance. ”

Not to be outdone in this intimidation game, we have decided to enter our robot portfolio manager, Phil Stone (short for Philosopher’s Stone - you won’t find the term in your MPT manual), into the foray. As you will see, Phil will succeed in putting down in one fell swoop all of the above contestants by means of an ancient and mysterious science that somehow has been largely overlooked in the investment field. Phil’s secret weapon is . . . . . . . . . . . arithmetic.

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Although Phil is not as cute as Star War’s R2D2, he is however endowed with an incredible memory and a way with numbers that is dazzling.

To explain Phil’s portfolio management technique it is necessary to raise a term for discussion that may not be entirely familiar to all. The term is percentile strength. It’s not a complicated subject and can be easily understood and utilized by all of us who have survived Jr, High School math.

PERCENTILE STRENGTH: THE COMMON DENOMINATOR OF STOCK PRICE MOVEMENT

The best way to approach this subject is to exercise your imagination for a moment and visualize a huge wall chart upon which is posted in graphic form, the price action of hundreds or even thousands of stocks over a given time frame. Do you get the picture ? A sea of squiggly lines that may be a delight to the chartist but to everyone else a scene of ocular chaos.

Instead of the above, perhaps a different method of presentation that would sort this unruly gang of stock prices into an understandable order would serve some useful purpose.

Suppose first we list these stocks by degree of price change over the given period. After performing the necessary arithmetic let’s say we find that Acme Electronics had advanced 250% and this was the greatest gain re- corded by any. We would place Acme at the top of our list and then go on to discover what stock was the second best performer and position it directly below and so on until the entire collection was correctly arranged in descending order of performance. Now by bracketing the list in percentile ranks an accurate label of current performance value can be affixed to each stock. If the universe was comprised of say 4000 stocks, the top 40 would be called 99’s, performing better than 99% of the constituents and the bottom 40 would be in the zero percentile, performing better than none. There would be 40 stocks in each of the remaining 98 slots and the average strength of all would of course be 50.

Now advance the time frame by one week and repeat the entire pro- cedure. We may now find that Acme was replaced in the 99th percentile by some other stock. This means that Acme was forced to a lower number simply because everybody has to be someplace. Although many individual stocks may have changed positions, the average of all would still be the same . . . . 50.

This sort of work performed on your pocket calculator every week would obviously drive you crazy. Luckily the information can easily be obtained from several computerized sources. Besides ourselves, a number of advisory services and some brokerage houses produce this type of data. All are based on different time frames with varying sized universes and of course the actual com- putations of the stren,gth figures are somewhat more complicated than the above simplification. But you get the main idea: an accurate measurement of relative price action where average performance is always described at the mid-field 50 yard line.

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Though this ongoing process of percentile strength ranking has considerable practicai value by itself, some other tri&s can be employed to im- prove the output. One, by making a couple or more passes at the raw data and skewing the arithmetic a little bit to give more or less emphasis to the most recent prices, a determination can be made as to the current direction in strength each stock is trending. Stocks that are making unusually rapid moves through the ranks can be filtered out and identified. In our work we simply call these “I? stocks (accelerating rapidly Qward in strength) or “D” stocks (accelerating rapidly Downward in strengtt. ) -

Another benefit can be obtained by fooling the computer a little bit. Computers in many ways are pretty dumb machines. They’ll believe anything you tell them to believe. We told ours for instance that a dollar bill was in fact a stock and as such it’s cllrrent quotation ($1.00 always) should be included right along with all the other data. The value of this exercise is *that the exact strength of dormant cash, now related to stock prices, is always spelled out. If ‘he strength of cash is greater than 50, then the majority of stock prices must be in downtrends. If the stren,@ of cash becomes greater than the average strength of the stocks in my portfolio, I must be in trouble, etc.

We also tricked our computer into believing the S & P 500 composite average was a single stock. Because the S & P is Ehe decreed standard to which all of us are ultimately compared, it is e-xtremely important to know what this index is doing when compared to the real world of stock price movement. If the S & P were really depicting ‘Lhe price action of the typical stock, it’s percentile strength of course would be a constant 50. But this is seldom the case and many times it is not even c 10s e. So, when the S & P’s strength is less than .50, it should be easy to overperform and vice-versa.

Xow back to Phil, the robot portfolio manager.

The objectives we laid down for Phil’s portfolio were simple enough. These were:

Objective 32: Appreciate in value.

Objective #3: Beat the S & P. Objective 41: Realize objectives 82 and $3.

Because of objective +3 and also to restrain Phil from going rampant in low priced super beta stocks, we thought it only fair to restrict his selections to those 500 stocks that make up the S & P Composite.

13 stocks were to be held when fully invested. This was just an arbitrary number on our part and could have been considerably greater. The efficient market people tell ils that if a portfolio exceeds a dozen or so issues it should “correlate” with the market. The implication being that good or bad luck is sufficiently neutralized through adequate diversification.

Perhaps this is a good time to e,xpose Phil’s portfolio management logic. This can best be done with a flow chart diagram.

- 21 -

I

N N

I

3. I5 stocks.

4. ‘1’11~ Iowcst perccntl le strength fwlcling. -. .-

Now for the results of this dehumanized experiment. We gave Phil an assumed one million dollars to ply his magic with as of 3-7-74. As it turns out this date produced the most disappointing “whipsaw” buy signal ever generated by our work and provided the acid test of worst possible starting conditions: fully invested in a crashing market.

As of this date, l-3-79, our robot’s portfolio is worth $2,037,7 92. A gain of 1040/o! You’ll have to agree that this is a very good record when compared to his approved list and bogey, the S & P 500 which has advanced 3%.

The question that usually arises at this time is turnover. Surely Phil Stone must be churning the account with an incredible amount of short term trades, right ? Not so. Phil’s average of 54 transactions over the nearly five year period produced a realized gain of 30.8% and was held 55 weeks. Furthermore, sub- stantially all of Phil’s significant gains were long term while the majority of his losses were short term.

And there you have it. If Phi l’s performance were monitored by the experts he surely would have been persistently in the top decile of equity managers. To carry this one step further, if total ego decimation has not been complete, it is interesting to note the things that Phil doesn’t know and can not do when compared to his intelligent and experienced human counterparts.

1. Phil can’t read. All of the wisdom available in the Wall Street Journal, Barrens, Pensions & Investments and other scholarly pub- lications is completely out of reach for Phi 1.

2. Phil doesn’t know the meaning of price-earnings ratios, interest rates, dividend yields, cash flow, etc.

3. Phil can’t perform any of the contemporary technical analysis functions. He doesn’t lmow a head and shoulders formation from a Kansas plain.

4. He is unaware of the current political climate or for that matter if World War III has come to pass.

And yet, one can’t help but wonder what would have occurred if Phil were the portfolio’s slave rather than its’ master. What if Phil was not allowed to respond to all of the minor strength fluctuations of cash equivalent and the S & P in such a knee jerk fashion ? What if the robots’ yes-no bullish/bearish market mentality were tempered to a degree by some sound objective economic reasoning? Or maybe augmented to include some standard technical analysis ? What if Phil’s approved list were humanly screened to include only fundamentally logical consider- ations rather than a sterile, unchanging list of 500 stocks.

What if . . . . . . . . . . . . . . . . . . . ?

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SMOOTHER IS SHARPER

Moving Averages Add Another Dimension To Point-and-Figure Charts

Introduction by David I,. Upshaw

Technicians and investors who are interested in technical analysis use a variety of charts in a variety of ways. Nany chart users admire the compactness and ease of posting offered by point-and-figure charts, but they also like the moving-average smoothing techniques that can be applied to daily, weekly, or even monthly bar charts.

It is possible to compute moving averages for point-and-figure charts and to apply the same kinds of analysis to those averages that are applied to bar-chart moving averages. This article tells how.

The Why and How of Moving Averages

Security prices and some other kinds of data that are used in technical analysis can change suddenly. We use averages of prices over various time periods to smooth out those short-term fluctuations and reveal long-term patterns. For example, derstood average,

a commonly used and widely un-

tions, which is printed in several security chart publica-

is the 200-day moving average. (A simpler version is an average constructed from the latest 30 weekly closing prices, or the 30- week moving average.)

The titles of these averages: ing average," and others,

"200-day moving average," "30-week mov-

and-q' all specify a time period. Because a point-

&igure chart depends on the direction of price movement and reversals in that direction rather than on the passage of time for its pro- file, moving-average-analysis techniques might not appear to apply. But they do. Point-and-figure chart users, who also like the smoothing effects of moving averages, can combine both approaches.

For starters let's review one way of constructing a conventional, time- based, moving average and then transfer figure chart.

that technique to a point-and- Let us assume that we would like to derive a 5-week

average of the price of XYZ stock. for

The closing prices of the stock the last 5 weeks are as follows:

week 1 21.500 (five weeks ago) 2 21.625 3 20.375 4 20.750 5 22.500 (latest week)

SUKI 106.750

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The S-week average

When the next week

average = 106.75 + 5 = 21.350

price is 21.350.

's closing price becomes available, it is added t0 the j-week total, and the price of 5 weeks ago is deducted from that figure. The new total is then divided by 5 to obtain 5-week average figure.

the current Assume the new price is 23.30.

old total ' 106.750 plus: new price 23.000 minus: price 5-weeks ago 21.500 equals: new total 108.250

new average = 108.250 d 5 = 21.650

Point-and-Fisure Chart Moving Averages

The same technique is used to compute a moving average for a point- and figure chart, with one more stew. chart has no time basis and, therefore,

Because a point-and-figure no dailv or weeklv closing

prices, we need to find substitutes 2

substitute prices are the average for those closing xrices.

Carithmetic mean) prices of highest and iowest values posted. in each column of the ooint-a u-e chart. Instead of time periods, averages.

columns are used to compu

and so on. Thus we speak of a j-column averaue, a lo-col:&mn av

Note carefully that a j-week moving average is not same thing as a j-column moving average. A column of Frices point-and-figure chart can take a few days, weeks, complete, the stock's volatility and

or even mon depencing on

Those the .nd-ficr- .te 'erage,

the

upon which the chart is based. the reversal

In a ths to

unit

A moving average of any desired number of columns .:an be computed a point-and-figure chart as follows:

for

thereby ending the posting of when a price reversal occurs,

prices the low price of

in a column, the high price and the now-completed column are added, then divided by

two to derive the average (arithmetic mean) orice of & that example: a 3-point reversal chart

column. An

from 50 to 56. of a $50 stock shows an advance

low--50 A reversal to 53 "closes" the 50 to 56 column.

--is The

added to the high--56. The sum--106--is divided by 2, and the mean price--53--can be used in the construction of moving averages of any desired number of columns. For a 5-coluinn average, 5 most

the recent column means are averaged. For a lo-column average, the

10 most recent column means are averaged, and so on.

Bow To Use The Moving Averages

The application of rnoving averages to Doint-and-f -igure price data is

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limited only by the inventiveness of the user, as is true of moving averages applied to bar-chart data. This section outlines two methods of using the moving averages, both of which are taken from bar- chart moving-average analysis techniques.

The first and simplest method is the plotting of the desired average or averages directly onto the point-and-figure chart. On the charts of the Dow industrials on the last page that illustrate this article, a 20-column moving average is plotted. through the point-and-figure postings.

It is the heavy line that runs "Buy" and "sell" signals can

be generated by the crossings of these averages just as they are from bar-chart moving averages. The criteria for such signals, such as the amount of penetration of the average and the trend of the average at the time of its penetration, of the technique.

are decisions best made by each user

Remember that the moving average is always posted one column behind, or to the left of, because the

the column that contains current price postings, final mean price of a column can't be computed until that

column is closed by a price reversal that moves the price plots to the next column of the chart. Thus, be crossed by current price action,

a moving average can't literally but that is of no practical con-

cern, particularly if a 20-column or 30-column moving average is used. These values change relatively little from one column to the next.

T:he second technique, illustrated by the lower part of the Dow charts, involves the computation of percentage spreads between two or more moving averages, and plotting these spreads on the chart beneath the price plots. For this analysis, I compute a 5-column average, a lo- column average, and a 20-column average. (Only the latter is posted on the chart shown here.)

Three percentage differences between these averages are computed and posted on the chart under the heading "Moving Average Spreads." The percentage spread between the 5- and lo-column averages-is labeled U5/lo.ti The spread between the lo- and 20-column averages shows as a line marked "10/20," and a third line, identified as "5/20," shows the percentage spread between the 5- and 2C-column averages.

The general purposes of these moving average spreads are to give indi- cations of overbought and oversold conditions and to reveal increasing/ decreasing rates of price change. There are no hard-and-fast rules for the interpretation of these oscillators: analvsts who use this technique will apply their own expertise or define their own "rules." The same techniques you may now be apolying to bar-chart moving averages can be applied to point- and-figure-chart moving averages. Some of the patterns that I look for are described in the following para- graphs.

I think of the lo/20 moving average ratio, shown as a solid line, as a sort of "major trend" indicator. I interpret the four possible

- 26 -

trends of this line as =‘oliows:

lo/20 ?osition Interoretation

3elow zero and rising Above zero and rising Above zero and falling Below zero and falling

Rate of price decline slowing Rate of price advance increasing Rate of price advance siowing Rate of grice decline increasing

The lo/20 line can also be used as an overbought/oversold indicator. Each st,ock or average has its own pattern, but f 0 r the DCW, reversals of the lo/20 line from -5% or lower and +59 or hi-her have orovided some good

a--> clues to major trend changes. On the charts, theLDoints

numbered 1, 2, 3, and 4 show where k-7 L,,e -j% or lower. Point 2 was

LO/20 lixe turned up >rom the continuation of the 1373-1374

bear market; followed by

the otlher three points provided gocd clues to be&' L;er marktt action. Points that are lettered A, 3, C, and D show where t .n P -a-i 10/2C line turned down from levels of +5 or ihig.her. The dcwn- C-drnS from above +3 have led market Desks by longer time periods than the upturns from -3 have led market iows.

The j/l0 line, drawn as a dashed line, tends to lead the turns of the IO/20 l>ecause it is based on the shorter moving averages. "he j/20 line (dotted line! shows the widest range of the three lines because it depicts longest.

the spread between the shcrtest moving average and the Notice the extremeiy depressed readings reached by the Y/23

line near t,he major market lows. Xotice , too, a

that near points 3 and - I the 5/20 line's action diverged from the price action 0 f the Dow

by Y efusinq to cjo to new lows falling.

even though the averace itself was still The principles of divergence and non-confirmation that you

may now be using can also be applied to this technique.

December 4, 1978 Drexel Burnham Lambert

Reprinted With Permission

Acknowledgment

In 1968 I met a technician named Gilbert Foster, who was then working and who still works in Denver. Gil was t5e first _3ersonl an-d so far the only person I know of, to apply moving averages to ooint-and-fic- . d ure charts. I am indebted to Gil for the method of constructing the moving averages described in this article. The methods of analyzing the averages outlined here are ones I have used for several years in working Smith bar-chart moving averages.

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. B f

P f

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Use this page to advise the MARKET TECHNICIANS ASSOCIATION

JOURNAL of what you can do to help make the next issue

special.

Send to: Fred R. Gruber, Editor c/o United Jersey Bank

210 Main Street Hackensack, New Jersey

07602

I will do the following:

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This page intentionally left blank.

-_

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Originally published in Dun's Review, November 1978

Reprinted with permission of the author, an NTA member.

A Twenty-Year Business Slump? Not a Ghost of a Char,ce.

JOHN SCHULZ

The ghost of Xkolai Dimitrievich Kon- dratieff haunts many an economist and businessman these days, carrying warn- ings that the United States is about to enter upon an economic slump that will last twenty years. Like all ghosts, Kondratieff s doesn’t stand close inspection, but it frightens people nonetheless.

Take this year’s annual report of the Bank for International Settlements- headquartered in Basle, majority-owned by the central banks of the leading in- dustrial nations and thus presumably a bastion of card-carrying conservative opinion. Viewing deep-rooted problems in its constituents’ economies. the B.I.S. declares that “such maladjustments suggest the possibility of a slowdown of the Kondratieff-type after several decades of virtually uninterrupted growth.”

Or take Jay W. Forrester. professor of management at Massachusetts Institute of Technology and a “believer.” His new computer model of the U. S. economy indicates (to him) that the peak of a “Kondratieff wave” has been passed and that, without new planning policies, we face a lengthv period of economic doldrums. Simrlarly, 77~ New Yorker magazine, always ready to take a sophis- ticated, literate swipe at free enterprise, joined the parade with a lengthy article by economist Robert L. Heilbroner as- serting that only an “institutional” shift to economic planning can give a new measure of life, “albeit a limited one,” to the capitalist system.

Push for Planning

Perhaps not surprisingly, The New Yorker article displays a predilection for citing Marx, John Kenneth Galbraith, David Gordon (“a leading young Ameri- can Marxist scholar”), Branko Horvath (“a widely known Yugoslavian economist”) and Paul Erdman (The Crash o/ ‘79). Somewhat remarkably, Gordon the Marxist shares concepts that led Stalin

John W. Schuiz, veteran rrockbroker and mon-

ey manager, is a senior vice presidenr of Brean

.Murray. Fosrer Securities Inc.. (I .Vew York

Srock Exchange member firm.

to send Kondratieff to perish in Siberia. In short, it seems that quite a few of the “best and the brightest” want to push this country toward centralized planning, brandishing a long Kondratieff downswing as a weapon of persuasion. And -the ultimate ‘irony-economist Walt W. Rostow, another believer, proposes centralized planning to deal with the dangers of a Kondratieff upswing.

Who was Kondratieff and what did he say? A professor at the Soviet Agricultur- al Academy and director of the Business Research Institute of Moscow. he published in 1925 a paper captioned “The Major Economic Cycles,” which appeared the following year in a German translation. It was not until 1935 that Harvard’s Review ~j- Economics and Statistics made the text available in Eng- lish under the title of -‘The Long Waves in Economic Life.” Kondratieff wrote: “There is. .reason to assume the existence of long waves of average length of about lifty years in the capitalist economy.” and he presented statistics to

show that these waves tended to consist of upswings and downswings having roughly equal durations. Kondratieff as- serted that these waves and their component swings are attributable to the in- herent mechanism of a capitalist economy. That landed him in Siberia. Or- thodox Marxism holds that capitalism is bound to self-destruct; hence. any theory claiming it would survive and flourish in the wake of recurrent crises had to be “reactionary.” Thus. Kondratieff s theory was literaily the death of him.

Here is the core of Kondratieff s thesis (in his own words, translated into English from the 1926 German version): “The relevant data which we were able to quote cover about 140 years. This period com- prises two-and-one-half cycles. .The following limits of these cycles. .can be presented as being the most probable:

“First !ong wave- I. The rise lasted from the end of the 1780s or the beginning of the 1790s until 1810-17. 2. The decline lasted from 1810-17 until 1844-51. conrinued on page 135

Schulz: Believers in the K-wave want to push the U.S. toward central planning

- 31 -

“Second long wave- 1. The rise lasted from 1844-51 until 1870-75. 2. The de-

“Third long wave-l. The rise lasted cline lasted from 1870-75 until 1890-96.

from 1890-96 until 1914-20. 2. The decline probably begins in the years 1914-20.”

People promptly were-and still are- fascinated by the pattern that Kon- dratieff thus revealed. True. he gave himself five-to-seven years leeway at each of his long waves’ peaks and troughs. But his assertion that these waves had an “average length of about f i f ty years” stuck and soon became dogma to his followers. The implications of regular periodicity and forecasting capabilities seemingly were irresistible. What’s more. by the time Kondratieff could be read in English (1935), the Great Depression appeared to confirm his theory. It had begun ten years after the last K-peak. much like the two previous long and deep

depressions, which began in late 1825 and late 1873. Both had come relatively early

What, therefore, could be more rztion- al than to conclude that the next long

in their respective K-downswings.

K-wave would peak near 1970 and be followed by a K-downswing, including a characteristically severe and prolonged business contraction in its earlier stages, a multi-year doldrum pertod in its later phase and a final long-wave trough near the year 2000? That. at any rate. is the party line as plugged by today’s Kon- dratieff fans. with the “ultras” predicting a vicious deflationary collapse as a prr- requisite for the next K-upswing.

Scanty Data

Kondratieff s theory sounds im- pressively simple, scientific and plausible. There is? perhaps fortuntately. only one thing wrong with it: It won’t stand up to careful examination. A lot of work

was done on its underlying data and assumptions during the two decades after Kondratieff first went public. Most of it concluded that the existence of the long K-waves could not be factually documented as an economic phenome- non recurring with predictably regular periodicity. But that work of thirty-to- forty years ago is now buried in library stacks, and latter-day Kondratieffniks carefully refrain from dusting it off.

The first and most glaring trouble with Kondratieffs theory is the paucity of data on which he based his conclusions. He could use only four series of statistics to define the upswing of his first wave and only three more to date the downswing. For the timing of the second wave and the upswing of the third wave, he eventually had 25 series. In other words, at the time he published the theory, the first long K-wave was poorly documented and the downswing of the third wave

could not yet be documented at all. That left only one-and-a-half waves for whtch there was a seemingly plausible case- certainly not an acceptable basis for a sweeping, long-term economic theory.

In-depth research done since the 1920s -much if not most of it under the aegis of the National Bureau of Economic Research-has yielded no support for Kondratieff s dating of long-wave peaks and troughs. Thus, former Federal Re- serve Chairman Arthur F. Burns and Wesley Mitchell, co-authors of the massive Measuring Business Cycles (1946). noted the dearth of data before 1860 and examined literally hundreds of statistical series for the vears since then. They found it “impossible to come to serious grips with the problem whether business cycles tend to move in cycles within Kondratieff s periods.” Research after 1946 seems to have shed httle or no additional light.

The most detailed critique of Kondratieffs theory yet to appear was done by George Garvey. then with the National Bureau, and ran in the Novem- ber 1943 issue of Harvard’s Review of Economics and Statistics. Garvey. re- garded by many as the foremost author- ity on the subject, also found himself unable to verify Kondratieff s dating of long-wave peaks and troughs. What’s

more. he accused Kondratieff of. in .ef- feet. cooking the data to fit his theory: “Less arbitrariness. .and closer con- formity to his own rules for the determination of turning points would have resulted in a much less uniform picture than the one Kondratieff presented.”

“Decomposing” Statistics

Garvey also pointed out that different accepted methods of”decomposing” any given series of statistics (that is, making adjustments to uncover basic trends) will yield different results and. furthermore. that the use of moving averages-Kon- dratieff used a nine-year movmg average -provides no reliable proof of cyclicali- ty. because different moving-average periods will produce different periodicities. Garvey concluded flatly: “The theory offered by Kondratieff to explain the cyclical recurrence of long cycles has no empirical foundation.”

Another major problem with the theory is that the long K-waves are not visible to the naked eye-for the simple reason that. as you may now suspect. they don’t rea$ exist, at least in overall business actrvuy. Take a look at a graph of real U.S. Gross National Product since late in the eighteenth century. What you see is a long upward sweep. noticeably inter- rupted only during the very early 1800s.

the Civil War years and the early 1930s: no regular periodicity here. Instead, real GNP was significantly greater at each trough registered in the Kondratieff cycle than it was at the preceding K-peak- notwithstanding numerous shorter-term recessions, a good many crises and several deep and lengthy depressions. Even in Kondratieffs time, it must have been plain to any other observer that his “downswings”-one running from 1810-17 to 1844-51 and the other from 1870-75 to 1890-96spanned decades of enormous economic growth.

Capping it all. the theory’s forecasting record to date has been conspicuously, though not surprisingly, lousy. In 1926. Kondratieff had to place his third-wave peak as “probably” in 1914-20. Ten years later. it was plain that any third K-wave peak had to be dated 1929-and thus any subsequent K-trough could be expected in the late 1940s or in the 1950s.

Unfortunately, World War I1 in- terfered. setting off a real wave of economic expansion that began in the late 1930s and has not visibly ended yet, some sixty years after tbe last “official” K- peak. At any rate. some modern Kon- dratieff followers insist on placing “ide- al” wave peaks m 1814. I864 and 1920. with troughs in 1843. 1869 and 1940.

continued .

- 32 -

I f there is one area in which Kondratiefrs long waves may have had some validity, it’s.in rhe fluctuations of wholesale prices. Here, long-term peaks and troughs did coincide roughly with Kondratieifj dating from the early 1800s

to the eariy 1900s. But the long downswings m prices did not inhibit ongoing, longer-term economic growth. In fact, dtspite the impact of two mammoth wartime inflations (the War of 1512 and :he Civil War). wholesale prices were lower at the end oirhe nineteenth century rhan at its beginning, while real GNP grew more than a hundredfoid.

Although {here is evidence that pros- perity phases tend to be iengthier when prices are rising than when they are failing, the postwar price deflation5 ofthe nineteenth century mostly tended to pro-

mote vigorous business expansion by making a steadily growing volume of goods and services increasingiy ac- cesslble to a ra?,idiy grswing population.

Thus, the pnct derlation forecast by today’s Kondratieffniks for the rest of this century need not be a threat to economic we&being-ii it does indeed materialize. To be sure, some of the severe business crises of the past 200 years are traceable to rapid and drastic contractions in the money supply, which could account for failing prices-even

the 1929-33 Great Depression can be attributed in the main to a disastrously deflationary Federal Reserve policy.

But similar “errors” are almost c:rtain to be avolded. If 50, what rational basis is left for expecting a severe K-down- wave in economic activity stretching over the next twenty years’? In any case, as far as prices are concerned, Kondratieff’s :heory has now gone far off the track: Sixty years after the latest K-peak in wholesale prices. there is still no end to rising prices anywhere in sight.

An Awesome Gamble

What’s in Kondrarieff’s theory for rhe business planner and the investment strateqst? Probabiy nothing much, 2x- cept the remote chance of being phenomenally right for the wrong reason -an awesome gamble of the kind that Sewell Avery of Montgomery Ward fame took and lost thirty years ago when he hoarded his company’s cash and refused to modernize in anticipation of a postwar collapse that was, at the time, widely expected but that never materialized.

Very long-range forecasting and pian- ning may be the “in” thing, but it’s a risky way to go. Remember those ultra-long- term planners, the institutional portfolio managers who hoarded “one-decision” growth stocks, the kind you only bought

and never had to sell? Well, :hey came to gr:ef when no one was isft to keep buying :he stocks at ever-rising prices. Today, many of the same money managers are playing Sewetl Avery’5 game, explicitly or !mpiicitly betting on a K- type deflation and warehousing cash instead of buying equities at historicaily modest vaiuations.

Few men. proiessors included, have had the genius to envisage the shape of things X-to-50 years ahead with anv tolerable degree of error. Kondracieif certainly was not one of them; his view of the past-as-prologue is not reconcii- able with demonstrable reaiity, and :Ime has just about run out on his theory of the future. It’s unsettling that today’s inteiiigentsia should seek to revive and invoke Tim in what is beginning to look like a broadening power-play promotion for Planned Capitalism. Maybe they just have no sounder Tremises.

It’s tough enough to cope with the shorter-term business and investment cycles, :hose reckoned in years rather than decades or generations, without trying to figure out which professor, dead or aiive, or whose computer program has the right game plan for the next quarter- century. Besides, long before you can know the answer, it’ll be your job or your money That’s on the tiring line. --END

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A PAGE FOR NOTES

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FARXET ANALYSIS REPORT

Reprinted with Denission OrlgFklly published 5/d/78 Xerrill Lynch

FIFTY YEARS OF MARKET VOLATILITY

by Robert R. ?rec”+ar, ;r. - .*a-. Harket Specialist

and Robert J. Yarre11 Vice President and yanager

The volatility of the stock market, as measured by the monthly average of the daily percentage range in the S&P 500 stock index, was the subject of a recent study published in the Statistical Bulletin of the Securities and gxchange Commission. On the accompanying chart, ;re have those volatility readings plotted against a chart of the montihly average of the daily closing prices for the S&P 500 index in order to assess the character of the current market in terms of volatility.

Some preliminary observations can be made on the basis of a general inspection of the data. First, the 1973-74 decline was accompanied by the highest volatility since 1946. Second, the market decline in 1938 was the last decline previous to 1973-74 to register two peaks of more than 3.0 on the volatility scale, indicating that the 1973-74 bear market was the most volatile decline in 35 years.

Xost important to us, however, iS that several declines since 1928 were accompanied by very low volatility (below 1. j) , which is contrary to the normal character of declining markets. ‘Je found that market behavior in each of those iow volatility periods of decline followed a similar pattern (see table below). First, the market experienced a severe, highly volatile decline such as occurred in the bear markets of 1929-32, 1937-38, 7946

the low in the market was followed by a’ and 1973-74.

In each of those cases, recovery phase -- 7932-34, 1938-39, 1947-48 and 1975-76 -- in which the market dispiayed fairly high volatility compared with that in most advances. The I1 t e s t ” declines following those recovery periods -- 1934-35, 1939-42, 1948-49, and 1977-78 -- always were characterized by low volatility, when unpleasant memories of the preceding bear market were reEdled and stoc’ks became one of the least favored investment vehicles. Those periods are marked with straight dark lines on the chart. In the history of these data, such declines presented buying opportunities for the long term during periods of low valuation for stocks.

1929-1932 1932-1934 1934-1935 1937-1938 1938-1939 1939-i942 1946 1947-1948 1948-1949 1973-1974 1975-1975 1977-1973

SL?!MARY

The present market resembles those periods since 1928 during which stocks declined sluggishly following a rebound from a major bear market low. if we take a long-term view, three precedents in terms of volatility indica%e t’ha t the stock market appears currently to be in a basebuilding phase prior to the eventual resumption of a secular bull market.

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- 36 -

Cspyright 1973 @ Xrhur A. Merrill

{-,V’tiip this mai? &* - rial is zrotecred ‘by copyright, I x-5 do not object to quotation ii a name-and- aderess credit 52-e is inc!udeci: Art’zur A.

Mexill, 30x 223, Chappaqua NY !03!-1)

13 09 78

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Copyright 1978 @ Arthur A.Merrill 1 FUNDS-CASH POSITION 1

(While this material is Trotected by copyright, we do not object to quotation if a name-and-address credit line is included: Arthur A. Merrill, Box 228 Chappaqua NY 10514)

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ELLIOTT WAVE IRINCIPLE Key to Stock Market Profits

by A.J. Frost and Robert Prech-ter

Published by New Classics Library 1978

Reviewed by William DiIanni, V.P. Wellington Management Company

To date there haven't been many books of any real importance written on the Elliott Wave Principle. But even so, this book by A.J. Frost and Robert Prechter is by far the most useful and comprehensive for both the beginner and the veteran. The beginner will find Elliott's theories clearly delineated in principle and flawlessly diagrammed. The more knowledgeable reader will find many nuances and interpretations which will sharpen his own convictions, whether the reader agrees with the authors' personal interpretations or not.

The book is divided into two logical parts: Part I, Elliott Theory; and Part II, Elliott Applied. Theory is "basic Elliott", from its simple and complex concepts of impulse and corrective waves to their perplexing Fibonacci measurements. The rules are clearly stated and potentially confusing areas adequately explained. Reading Elliott in the original can be difficult and somewhat confusing, since Elliott rarely used repetition or many graphic examples where one diagram should do. Application runs the gamut from ratio analysis of time and amplitude to much longer cycles, as supercycle, grand super cycle and even a millennium cycle; also commodities, gold and individual securities.

The Wave Principle by R.N. Elliott in 1938 was an original landmark work of tremendous magnitude. But original theories in any field carry within them the seeds of pervasiveness. In other words, the genius of the originator rushes to apply them to literally every facet of the subject, and sometimes to things beyond. The theories are meant to transcend everything to a unified manner without exception and without limitation. This was true of many momentous theories, as those of Aristotle, Newton, Darwin, Einstein and many others of lesser light. At times it can be done. But sometimes the object becomes too far removed from the scope of the theory; or is actually beyond the reach of the source; or is in reality a new entity.

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Elliott waves, as a "reflection of the mass psyche", extend their influ- ence over all categories of human activity. The authors, however, caution against against strict use when Elliott 's theories are applied to individual issues. "'When to make a move in the investment field is more important than what issue to trade. Stock selection is of secondary importance compared to timing. It is relatively easy to select sound stocks in essential industries if this is what one is after, but the question always to be weighed is when to buy it." This is especially true of options.

Further on they say: "The progress of general business activity is well reflected by the Wave Principle, while each individual area of activity has its own essence, its own life expectancy and a set of forces which may relate to it alone."

The interplay of investors' general knowledge and human psychology is key to the wave patterns generated in the broad market averages. Here is where Elliott and Dow overlap. As Charles J. Collins observes in the foreward: "Elliott . . . incorporated what Dow discovered but went beyond Dow's theory in comprehensiveness and exactitude. Both men had sensed the involutions of the human equation that dominated market movements -but Dow painted with broad strokes of the brush and Elliott in detail, with greater breadth."

Moreover, Charles Dow in formulating his principles, did not suggest that the interaction of the Industrials and Transports be used primarily as a fore- caster of the stock market, but rather as an economic barometer. However, its application to the better understanding of the stock market was its necessary corollary. Elliott would not disagree with that at all, but went a step further in isolating the degree. "The foremost aim of this wave classifica- tion is to determine where we are in the stock market cycle."

But when it comes to individual stocks, "basic textbook technical analysis" should be used rather than "forcing the stock's action into an Elliott count that may or may not exist." This is not to say that its application to individual issues is unreliable, but that the "fuzzy" ones should be left to traditional technical studies.

Furthermore, theories are sometimes more comfortable in the abstract. For instance, their application to large secular cycles can be downright starry, and at first blush, even fatalistic. But the authors are quick to point out that "the Elliott Wave Principle is a law of probability and relative degree, not a law of inevitability". Thank God for that. Yet the section suggesting that all larger waves are likely to reach a peak around 1983, even from a millennium viewpoint, is alarming. This is especially true when one overlays Benner's cycles, and others not mentioned in this book, as various sunspot cycles and the fact that all planets will be horizontally lined up in one direction around that time in sort of a perfect linear least squares fit. The probability of extensive earthquakes and the risks of other terrestial havoc will increase. Hopefully, the leveraged gravitational pull exerted on our planet will not be in the direction the wave count suggests , for the market.

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Ehtt Waves in Descending Magniivde

1983! /

19a3z i983Z / I

J Grand Supercyde

Millennium Cycle

I I

197%51/ r4

,Y

I978

Cycle

hot to scale)

In sum, this book is extremely well done. It is clear, brief and bold. It should stimulate activity in the use of the Xave Principle by other market analysts previously not too well acquainted with it. As a devotee myself, Z sincerely hope the book elevates interest to a h.igh plateau of study ar,d respectability, and that its impact will be more than fleeting.

It is obvious that the authors spent much time and effort on the book. It is equally obvious that Robert Prechter supplied the entlhusiasm of :7Out:?,

and the dean, A.J. Frost, the experience and wisdom of age. The blending or' these qualities was perfection itself, and worthy of Francois Xauriac's dictum: "To write is to hand oneself over."

Indeed, the book should be at the elbow of avery marlcet analyst. The r'ibonacci cost of $21 could be logarithmically spiralled 'lo a modest fortxe. L; -= not in dollars, tl?en in knowledge.

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A PAGE FOR NOTES

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Economy & Finance

Journal of Technical Analysis (JOTA). Issue 04 (1979, February)