journal of technical analysis (jota). issue 05 (1979, may)

Market Technicians Association

JOURNAL

MARKET TECHNICIANS ASSOCIATION JOURNAL

Issue 5 '

May, 1979

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

Direct inquiries to:

William DiIanni Market Technicians Association Journal c/o Wellington Management Company 28 State Street Boston, Massachusetts 02109

Copyright 1979 by Market Technicians Association

MARKET TECHNICIANS ASSOCIATION JOURNAL

EDITOR:

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

ASSOCIATE EDITOR:

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

EDITORIAL ASSISTANT:

Ms. Cheryl'$tafford, Wellington Management Co.

Thanks to Market Technicians Association members for their

part in the creation of this issue are owed to:

James D. Anderson Walter Deemer Francis E. James Jr.i Ph.D. Steven C. Leuthold Ian M. T. McAvity John McGinley, Jr. John A. Mendelson

INDEX

MARKET TECHNICIANS ASSOCIATION JOURNAL - May 1979

Page

EditorsNotes................... . . . . . . . . . . 4

Letters To and Through The MTA Journal . . . :. . . . . . . . . . . . 6

May Seminar Program. . . . . . . . . . . . . . . . . . . . . . . . . . 7

Indicator Analysis

Stock Market Analysis With Industry Groups . . . . . . . . . . . . . . 9 by Roger Williams, Ph.D.

Non-Member Short/Specialist Short Ratio . . . . . . . . . . . . . . . . 15 by John R. McGinley and Walter R. Deemer

General

Reinvestment Averaging - An Unexplored Factor in Portfolio Management . 23 by Francis E. James, Jr., Ph.D.

Does The Tail Wag The Dog? . . . . . . . . . . . . . . . . . . . . . . 33 by D. Bruce McMahan and F. Martin Koenig

Bottom Fishing With Relative Strength . . . . . . . . . . . . . . . . . 45 by Steve Leuthold

Statistically Significant

One Aspect of the Popular "4" Year Cycle . . . . . . . . . . . . . . . 51 by Ian McAvity

Interest Rates/Stock Prices . . . ; . . . . . . . . . . . . . . . . . . 57 by James D. Anderson

Commentary On The Relationship Between Recessions and The Stock Market 65 by John A, Mendelson

EDITOR'S NOTES

The technical alert bemoaned in my last commentary has hopefully passed.

The issue of concern, our Journal, has shown renewed vigor. We all want

to see a continuing good pattern unfold for our very special publication.

I can only remind you it requires help from the entire MTA membership.

Please send a note to the Editor indicating what you will contribute.

It has been my oleasure to be Editor of our Journal for its first two

years. This is my last issue as Editor, although I certainly hoDe to

stay involved. At least one task remains, that of further promoting

readership of the Journal in general and following through on Plans

underway for a subscription advertising program for the Journal alone.

The Journal will be in good hands with its new Editor, Bill DiIanni,

and his very capable Editorial Assistant, Cheryl Stafford. They have

made tremendous contributions to date, and I know they have strong

expectations for next year. Readers who are attending the Fourth Annual

Seminar should make a point of contacting Bill or Cheryl to show

support for the ongoing Journal effort.

Fred R. Gruber

P.S. The Journal takes another step forward with this issue - it is being printed professionally. You thought the previous issues were also. No, they were done in Boston as a labor of love by some dedicated members of the MTA.

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Market Technicians Association Membership and Subscription Information

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

Receives the Journal, the frequent 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 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 fee.

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

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

are available for: $10 to regular members or subscribers $15 to non-members or non-subscribers

The Market Technicians Association Journal is intended to be published three times each fiscal year, in approximately November, February and May. An Annual Seminar is held each Spring.

Inquiries for membership, subscription or single issues should be directed to:

William DiIanni or Cheryl Stafford Wellington Management Co. 28 State Street Boston, Massachusetts 02109 (617) 227-9500

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LETTERS TO AND THROUGH THE M T A JOURNAL

IS ANYONE USING THE FORMULA?

A line or two of thanks, appreciation and support for the "Journal". Issue #4 came yesterday and it has already been devoured. Possibly not quite as dynamite as #3 with its ST1 article by McGinley and Changes in Traditional Stock Market Stats by West & Murphy, I still think it great. The "Journal" is a window for outside creative thinking that I don't get exposed to any other way. The '74 article on Short Interest was particularly enlightening. I know its much easier asked than done; could you get Stan Zawadowicz of Data Lab, Inc., Box 292, Haverford, Pa. 19041, (215) 667-1640 to do something on the Options world he's involved in?---Maybe something on Options gyrations around expiration time? I'm using his Options Analyst and T. I.59 handheld calculator. Or, could someone do a little something on Federal Funds Rate as a short term forecaster?

Changing the subject somewhat, do you know anyone using the late Henry Wheeler Chase, Supply/Demand Corp. (of Greenwich, Conn.) formula? It is now owned, promoted and sold by Larry Williams of Montana fame, and I'm now a devotee of it. Would certainly like to "rap" with anyone who has knowledge of the formula, either at the upcoming seminar or otherwise.

J. Kevin Hughes Denver, Colorado

Editor:

We are contacting Data Lab, Inc. Does anyone have thoughts on the other subjects mentioned. Please contact Mr. Hughes with a copy "through" the MTA Journal.

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THURSDAY, MAY 3 May 306,1979

4: 00 pm-Registration

630 pm-Cocktails

736 pm-Dinner

9:00 pm-KEYNOTE SPEAKER William O’Neil, Chairman William ONeii 8 Co, Incorporated

FRIDAY, MAY 4

7:30am-&Breakfast

9:OC am-STUDIES IN VOLUME

Panelists: David Bostian, President Bostian Research Associates

Paul Desmond, President Lowry’s Reports, Inc.

10:3Dam-Coffee Break

7 0:45 am-ELLIOT WAVE: PURE FORM

Panelists: William Difanni, Vice President Wellington Management

A. J. Frost, Dean of Elliott Wave Theory

Robert Prechter, Vice President Merrill Lynch, Pl;Brce, Fenner 8 Smith

12:30 pm-Lunch and Free Time

3:OO pm-GROUP SELECTION TECHNIQUES

Panelists: David Diamond, Vice President Boston Company

Steven Leuthold, Vice President, Director Funds, Inc.

David Upshaw, Vice President Drexel Burnham Lambert. Inc.

439 pm-Coffee Break

r ,r 7

1976 1977 I978 1979

4:46 pm-THE CHANGING NATURE OF SUNDAY, MAY 6 TECHNICAL ANALYSIS

Speaker: Stan West, Vice President, Business Research

730 am- Breakfast

New York Stock Exchange 9:OO am -OPTIONS

7:3D pm-Dinner

9:00 pm-MTA Annual Award

Presentation

SATURDAY, MAY 5

730 am-Breakfast 1 :OCl pm-Lunch

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

Speaker: Anthony Tabell, Associate Delafield, Harvey, Tabell Division of Janney, Montgomery, Scott

lo: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%) Noon-Lunch and Free Time

6:30 pm-Cocktails

730 pm-Dinner

9:00 pm-“IS THE WORLD COMING ‘i-0 AN END?”

Alan Abelson, Managing Editor Barron’s

Panelists: Mike Epstein, General Partner, Trading Cowen a Co.

Gary Knight, Member Chicago Board Options Exchange

Morrfs Propp, President Cygnet V Securities

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

‘Registrants are encouraged to submit strategies employing the Shorbfem Trading Index that they would like to see tested. Please submit any testable strategy along with your registration form.

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STOCK MARKET ANALYSIS WITH INDUSTRY GROUPS

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

Considerable attention has been given to beta analysis, sensitivity of stock prices to changes in general market averages. However, little or no attention has been devoted to sensitivity of stock prices to changes in bond prices (the inverse of bond yields). This paper partially rectifies that imbalance. In our analysis we have used industry stock price groups as prepared by Standard and Poor's,

In reviewing historical experience, we have used monthly data for the Standard and Poor's 500 from 1945 to date, with stock market peak and trough dates as noted in the accompanying table, including January 1945 as an arbitrary beginning trough date, and August 1978 as an updating (but not conclusive) peak date.

Table I

STOCK MARKET HISTORY

Peaks

May 1946

June 1948

January 1953

July 1956

JOY 1959

December 1961

January 1966

December 1968

January 1973

September 1976

August 1978

Troughs

January 1945

May 1947

June 1949

September 1953

December 1957

October 1960

June 1962

October 1966

June 1970

December 1974

March 1978

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For bond prices we have used new issues of high grade corporate bonds as reported in Business Conditions Digest. Bond price lows are equivalent to bond yield highs, and bond price peaks are comparable to bond yield troughs. December 1978 has been inserted as an updating (but not conclusive) bond price trough date. Table II notes the cyclical peak and trough dates for bond prices.

Table II

BOND MARKET HISTORY

Peaks (bond prices) Troughs (bond prices)

April 1946 September 1946

April 1947 December 1948

April 1950 June 1953

March 1954 June 1957

June 1958 October 1959

January 1963

February 1967

January 1972

December 1976

September 1966

June 1970 .

September 1974 I"

December 1978

Our objective has been to determine which industry groups respond most sensitively to changes in the Standard and Poor's 500, (from peak to trough and trough to peak) and which groups respond most to changes in bond prices. In both cases, we have measured industry group stock price response relative to performance of the Standard and Poor's 500 during particular periods as a whole. In beta language, any sensitive group will have a beta value exceeding one. Our study indicates that a precise numerical beta for industry groups is an illusion. We are interested in whether the industry group usually has a beta value exceeding one or not, and we indicate the proportion of times that it has historically had a beta value exceeding one.

Bond prices decline when interest rates rise, and rise when interest rates fall. We have tested to see which industry groups decline most when bond prices fall, and which industry groups rise the most when bond prices increase. We have

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calculated no average beta figure, but indicate merely how consistently a particular industry has responded in a sensitive manner to bond price changes.

Table III lists those industry groups which have been most sensitive to rising and falling stock market periods, including the proportion of times that they have acted in this way.

Table III

STOCK MARKET SENSITIVITY

Best Industry Groups

Aerospace

Aluminum

Auto . ..Trucks

Coal

Electrical Household Appliances

Machinery.. .Construction and Materials Handling

Machine Tools

Metal Fabricating

Oil . ..Crude Producers

Oil . ..Integrated Domestic

Paper

Publishing

Textiles..Synthetic Fibers

Truckers

Vending Machines

Additional Stock Market Sensitive Groups

Air Transport

Autos

Conformity Scores

Rising Markets Falling Markets

7 out of 11 6 out of lo

8 out of 11

8 out of 11

7 out of 11

7 out of 11

10 out of 11

8 out of 11

8 out of 11

7 out of 11

7 out of 11

7 out of 11

7 out of 11

7 out of 11

7 out of 7

5 out of 8

6 out of 11

6 out of 11

Building..Heating, Plumbing 6 out of 11

Copper 5 out of 11

Home Furnishings 6 out of 11

Machinery..Agricultural 6 out of 11

7 out of 10

8 out of lo

6 out of lo

6 out of lo

9 out of 10

8 out of lo

6 out of IO

4 out of 10

6 out of lo

7 out of 10

j out of 10

8 out of lo

6 out of 7

5 out of 7

7 out of 10

7 out of 10

7 out of 10

6 out of lo

7 out of 10

7 out of 10

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Table III (continued)

STOCK MARKET SENSITIVITY

Additional Stock Market Sensitive Groups

Conformity Scores

Rising Markets Falling Markets

Metals . ..Miscellaneous 6 out of 11 6 out of 10

Radio, TV Broadcasters 6 out of 11 5 out of 10

Rail Equipment 5 out of 11 7 out of 10

Rails 6 out of '11 7 out of 10

Steel 5 out of 11 7 out of 10

Textiles . ..Apparel 6 out of 11 7 out of 10

Textile Products 5 out of 11 7 out of 10

Table IV lists those industry groups which have been most sensitive to rising and falling bond prices, including the share of times that they have acted in that sensitive manner.

Table IV

BOND PRICE SENSITIVITY

Best Industry Groups

Banks..New York City

Building..Cement

Building . ..Roofing and Wallboard

Chemicals

Finance

Finance..Small Loans

Insurance..Property and Casualty

Natural Gas Distributors

Retail.. Food Chains

Savings and Loan Assoc.

Utilities..Electric

Conformity Scores

Rising Bond Prices Falling Bond Prices

3 out of 8 6 out of 9

51/2 out of 8 6 out of 9










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Table IV (continued)

BOND PRICE SENSITIVITY

Additional Bond Market Conformity Scores

Rising Bond Prices Sensitive Groups

Falling Bond Prices

Banks . ..Outside New York City 6 out of 8 5 out of 9

Containers...Metal and Glass 5 out of 8 5 out 0r 9

Insurance...Life 6 out or 8 4 out 0r 9

Natural Gas Pipelines 5 out 0r 8 4 out 0r 9

Soaps 7 out 0r 8 ’ 4 out of 9

Telephone except ATT 6 out or 8 5 out of 9 Telephone 4 out 0r 8 4 out 0r 9

Industry group analysis can provide a special review of recent stock market history. In Table V, below, we have listed the relative price action of our selected industry groups for mid- 1977, late 1977, mid 1978, late 1978 and mid March of 1979. Relative price action for those periods has been established through looking at the Mansfield industry group charts. We have listed + for favorable relative price action, 0 for neutral, and - for unfavorable relative price action.

Table V

RECENT INDUSTRY GROUP HISTORY Mid

Mid 1977 Late 1977 Mid 1978 Late 1978 March 1973 Stock Market Sensitive Groups +

Best Groups 0

+

Total Groups 0

Bond Market

Sensitive Groups +

Best Groups 0

+

Total Groups 0

3 2 8 2 4 4 8 4 5 9 8 5 3 8 2

3 6 15 4 8

9 15 4 9 14

17 8 10 16 7

5 4

2

10

5

3

2

5 4

4

10

4

0

4

7 1

6

11

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Another way of examining the present position of the market is to examine those industry groups which have the clearest and strongest relative price action patterns as of mid March of 1979. The stock market sensitive groups which have recent favorable relative price action are aluminum, oil..crude producers, oil, . . integrated domestic, and metals..miscellaneous. Unfavorable relative price action has been demonstrated by air transport, home furnishings, machines.

rail equipment and vending This gives a neutral picture.

Among bond market sensitive industry groups, none of the clear trend groups have favorable relative price action. Five groups which have unfavorable price action include banks . ..New York City, finance...small loan, banks...outside New York City, containers...metal and glass, and insurance.. life. This picture comes out on the negative side.

Our various industry groups are behaving better than they were at the end of 1978, but their current mid March reading comes out about neutral. The most consistent stock market sensitive groups are slightly favorable, and the most consistent bond market sensitive groups are neutral, and the clearest bond market groups are unfavorable. Overall, the industry group rating of the stock market is approximately neutral, with no clear trend in either direction.

Technical analysis of industry groups which are sensitive to the stock market and to the bond market can be helpful for overall market analysis. It can also be helpful in establishing the character of the market and in making industry group selections for buying, selling or holding.

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

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Non-Member Short/Specialist Short Ratio

bY

John R. McGinley and Walter R. Deemer

John McGinley: Some time ago, Bob Prechter of Merrill Lynch and I were discussing the changed parameters of the

Specialists Short Sales Ratio in recent years. Decrying the lack of history for these parameters to assist us, I wondered aloud if there was not something else which could give us a handle on these important numbers. Bob referred me to his associate, Hans Schueren, who felt the solution could be found in the Non-member Shorts to Specialists Shorts Ratio.

Hans believed the two series had changed relatively equally, one to the other,thus preserving historical strategy parameters. He had folLowed the ratio for years but had nothing in chart form. We hope to get him to describe some of his techniques in a future article.

Norman Fosback, while praising the Non-member Short to Total Short Ratio by itself in his excellent work, Stock Market Logic*. agrees that "this (P/S Ratio) treatment eliminates from consider- ation the short selling activity of members trading off the floor for their own accounts, which can be influenced by non-speculative arbitrage transactions and option hedge strategies." Fosback has given us some rough guidelines for the individual weekly readings.

Over 1.0 Great! .70 Good .45 Average .30 Bad Under.20 Terrible!

I tracked the raw figures by hand for two years and came up with a strategy which had miraculous results. For example: Sell Aug. 29, 1977, Buy March 13, 1978, Sell June 5, 1978, Buy Dec. 6, 1978! Not only that, it gave these signals 4 weeks in advance!! I called Hans to see if the guidelines I had developed made any sense to him over a longer period, i.e. going back more than two years. His "definitely not!" still rings in my ears. "The numbers vary all over the lot," he said. Dismayed, I called Walter Deemer for solace and to see if he had any experience with this indicator.

* Institute for Econometric Research, 3471 North Federal Hwy, Ft. Lauderdale, Fla., 33306, $20.

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Walter Deemer: When John McGinley mentioned to me that he had been working on something called the "Public/

Specialist Short Sales Ratio", I told him I had not heard of this indicator before: but John's analysis sounded interesting enough tomethat I suggested we ask Tony Tabell to run a chart of it, using his awesome technical data base and computer plotting ca- pabilities, so we could see what it looked like. The results, using an eight-week moving average, are shown in the accompanying charts (remember that high readings are bullish and low ones bearish).

The rationale behind the “P/S Ratio" is simple: It compares short selling activity of an "uninformed' class of investor (the public) with that of anninformed" ists).

class of investor (NYSE special- When public short selling is high and/or specialist short

selling is low, a high ratio is obtained; conversely, when specialist short selling is high and/or public short selling is low, it results in a low ratio. John discusses the statistical in- tricacies of the indicator in the following part of this article. It is worth noting that this indicator should be much less dis- torted by option-related activity than some others.

John McGinley: Walter and I are fully aware that our rationale for this indicator is open to the critisism that

the specialist is only responding to orders he sees, theoretical- ly, and is not as free to act as is the non-member: he is required to go against the trend, but then he does not require an uptick. There would seem to be compensating factors.

Be that as it may, a glance at the chart verifies its aston- ishing accuracy, especially at bottoms. Because of the logarith- mic nature of ratios, the data gets "bunched up" at market tops, i.e..as the indicator approaches zero. There are not the dramatic swings one sees at the other end of the spectrum. A future project will be to look at the logs of the actual readings and/or to plot the raw data on log paper, as suggested by Bob Prechter. This may "tame the wide swings", to quote Arthur Merrill.

To lend statistical credence to this joint effort, I devised 3 buy/sell strategies -with 20-20 hindsight-and fed the results to Arthur Merrill for testing. My initial strategy had been to create a 4-week ModMA* of the weekly data and to post it on the chart of the market four weeks ahead! The action points were to be greater than -55 for buys and less than .45 for sells. Work- ing with the back data, I found that .40 was better for sells. That then became Strategy Xl. I then attempted to sharpen up the buy side by moving the action point to .60 and called it Strategy x2. Finzilly, we had Bob Simpkins run an 8-week normal moving average for us (see charts). (His computer back posts the data two weeks to when the trading actually occurred, rather than when the data was released. Our action points are figured from the release dates, the first time one can act on the information.)

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* ModMA refers to the Modified Moving average described in the April MTA Newsletter. Yesterday's MA is subtracted from today's item, the result divided by 4 (the length of the MA) and then added to yesterday's MA.

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Strategy $3 , involved.

the &week moving average, is a little more Using the normal 8-week MA, posted when released, buy

alerts are reared when the average rises above .60. occur when the average drops below

Sell alerts .35. Action points are then the

second week the actual reading occurs-below (above for sells) the current MA, even though this might be several weeks or months later. The buy/sell dates and Arthur Merrill's comments on the test results are appended. phases

Xhile it does not participate in all -intermediate swings- of all markets, those in which P/S

does participate have a major bite taken out of them. *

Norman Fosback observes that the ratio "... is greatly influenced by recent market behavior and an even more refined guide to future market performance can be derived by adjusting . . . recent market trends." for

Lance Rembar, also of Nerrill Lynch, who has followed this ratio since 1970, vjholeheartedly agrees, but adds, "what indicator couldn't?" i4e have yet to attempt adjusting this ratio for the mar?tet and would be greatly interested in hearing from anyone who has. Another future project!

<Ialter Deemer: That there is something useful in this data seems ObViOUS. But our intention here is not to hand

the reader a fait accampli, approaches. John and I

rather to suggest the beginnings of

elementary level. feel our analysis is still on a fairly

As John has suggested, we are now testing various modifications and refinements of the basic analysis you see here. Eiowever , enough

we thought the results thus far were interestix to share Mth you and hope that others can build from this

basic analysis to make the indicator even more useful. tically, this work also shows that,

Parenthe- contrary to popular myths,

market technicians can and do work together in developing new analytical tools.

* Ian XcAvity suggests it's better to lose capital!

opportunity than

T?alter Deemer Jo'hn bfcGinley

with thanks for the assistance of

Sob Prechter Hans Schueren Tony Tabell Bob Simpkins Xorman Fosback Arthur Xerrill Lance Rembar

April 1979

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Appendix 1

1965. The dataweused for the three strategies began on July 23,

VYe have subsequently obtained the actual data from 1946 to the end of January 1979. included therein are total shorts, member shorts, specialists shorts, the the DJIA, and the date.

.E/S, the moving average, Copies may be obtained by writing Xalt

Deemer at Putnam Xanagement Co., 265 Franklin St., Doston, ;&?A 02110 and enclosing $3 for mailing and copying costs.

2. Stratecv 7T 3 (8-wk KA, using .35 & -60 as alerts, etc.)

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Bullish

? 10-29-65 11-11-66 4-21-67 4-5-68 7-3-68 8-29-69 12-5-69 6-19-70 5-14-71 7-23-73 11-9-73 5-24-74 7-3-75 10-10-75 3-12-76 3-23-78 6-16-78 l-5-79 ?

Dearish

Stratecv %l (4-wk ModMA, posted 4 T+lks ahead, using -40 EC .55)

? 10-8-65 10-14-66 3-3-67 3-22-68 6-14-68 a-18-69 6-20-69 8-29-69 12-5-69 5-l-70 3-26-71 l-7-72 2-4-72 6-8-73 10-12-73 3-22-74 5-2-75 9-26-75 2-27-76 12-23-76 10-14-77 2-24-78 6-9-78 12-8-78 ?

With these signals, one should remember there is advance notice of a month in lghich to act or not,happily. Should the average turn around in that time, one has the luxury of ignoring the message in the "fortune cookie"!

Strategy ++2, though a good one, seemingly, renders far fewer signals. It has taken the most points, short and long, out of the DJIA, but, for instance, has said nothing since its sell of 6-9-78. It, too, made a bad call in the spring of '74, but like- Mse PIas smart enough to hold on for more than a year and sell profitably in 1975!

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Appendix II

Arthur Merrill's Test Results

The relative success of the indicators reported in Technical Trends is periodically checked by this method:

1) Each week in a test period is labeled a good buying week or a good selling week.

2) Indicators are then tested for correctness each week.

3) The number of correct weeks is then calcue lated as a percent of the total.

8-Wk MA t.35 6r.60)

Successful Weeks 467

Incorrect Weeks 216

Total Weeks 683

% Accuracy 68.4%

Chi2 91.5

4-WkModMA 4-Wk ModNA t.40 L.55) t.40 L.60)

433 479

253 206

686 ' 685

63.1% 69.9%

46.7 108.0!

Arthur A. Merrill

For perspective, the highest Chi2 he had previously tested was his Member Trading Index which came in at 70.7.

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-._

-- --- G- Q 5-- a-- l- i- L - \ 2 - -- 4

-.

- . . .._ .__ _- __ -+.. .-_ _

.---..L.- -.-

--

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REINVESTMENT AVERAGING--AN UNEXPLORED FACTOR IN PORTFOLIO MANAGEMENT?

Francis E. James, Jr., Ph.D. President, James Investment Research, Inc.

What is Reinvestment Averaging?

Over the past several years, the main thrust of many publications appears to have turned from the random walk hypothesis of stock price movement to problems of portfolio management. Various attempts have been made to define efficient portfolio performances in terms of risk and return. One factor in portfolio performance, of interest to portfolio mangers as well as academicians, deserves closer attention at this time. It is signif- cant and of considerable importance to market practitioners of all types, but especially those who manage large portfolios. The effect, which I call "Reinvestment Averaging," was first described in a Ph.D. dissertation in 1967.l It has recently been supported by a variety of theoretical and empirical analysis and research. A brief description of the effect follows:

If taxes and commissions are neglected, and within subsets of randomly selected securities, the practice of periodically selling a few securities selected at random, and reinvesting the proceeds into a few other randomly selected securities, will result in a significantly larger expected return than the practive of "buying and holding" the same securities.

How Was it Discovered?

This effect was discovered somewhat by accident. A research project was underway which was designed to examine monthly stock closing prices for evidence of nonrandomness. The University of Chicago tape of NYSE stock price relatives was used to generate month-end closing prices for 233 securities which had been continuously listed from 1926 through 1960. Dividend payments had been added back into the prices in order to fully account for the yield to the investor. A number of experiments had been performed, each randomly selecting 12 securities, simulating buy and sell activities every three months according to a predetermined decision rule based upon the movement of the stocks, and then comparing results at the end of the time period against an unmanaged portfolio that merely bought and held the securities. A number of highly successful trading rules were demonstrated. In order to ensure that the results were not just chance occurrences, the experiments were replicated many times, each time comparing results of a managed portfolio against a "buy and hold" portfolio. An average value of the difference in results was computed, along with other statistics such as sample variances. These permitted statistical tests to be performed. The tests indicated that it was highly unlikely that such favorable results had been achieved by chance.

The final experiment, which hardly appeared necessary at the time, was to have been an experiment in which random buying and selling (without the use of a mechanical trading rule) results were compared with a "buy and hold" portfolio. Twelve securities were randomly selected. An initial investment of $100 was assumed invested into each of the securities in January 1927. Each three months thereafter, 3 of the 12 securities were randomly selected. If the portfolio was holding the securities at that time, a sale was assumed, and the funds were reinvested (in equal dollar amounts) in three other randomly selected securities. Portfolio results were compared at the

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end of the time period (Dec. 1960). The experiment was replicated 20 times on the same set of securities. The results:

Buy and hold portfolio final value = $21,374 D = $29,263 n = 20 s/v% = 9,118 t = 3.2092

The practice of randomly selling three securities at the end of each quarter, and reinvestment proceeds into three other randomly sleeted securities, would have yielded an average of $29,263 more gain than just holding the same 12 securities until the end of the time period. An analysis of the results indicated that the "buy and sell at random" technique was superior to "buy and hold" 16 out of the 20 trials. The "t" statistic above indicates that results this favorable could have occurred by chance fewer than 5 times out of 1000.

Discussants, at the time of this work, were quick to suggest that some type of error had been made in the experiment. After all, they reasoned, if securities were selected completely at random, it seems logical that no reason existed to suspect that (in the long run) the securities selected to be bought would have better future prospects than the ones just sold. This proposition appeared to be so intuitively obvious that the experiment was deemed by some to be a waste of time.

The experiment described above used only one set of 12 securities and the test was replicated only 20 times. Another experiment was designed to permit a broader test of the proposition. In this second experiment, a new portfolio was randomly selected after each trial, and the est was replicated 120 times. The results:

- . . .

D= $12,200 s/Jn = 5,119 n = 120 t = 2.3829

The experimental results indicate that the practice of randomly selling three securities out of a randomly selected portfolio of 12 securities, and reinvesting the proceeds into three other randomly selected securities, would have yielded an average of $12,200 more gain than just holding the 12 securities until the end of the time period. The "t" statistic indicates that results this favorable could have occurred by chance less than 1 time out of 100.

This somewhat surprising outcome initiated further investigation during which the causes and necessary conditions were identified. These are outlined below, along with a review of certain current literature pertain- ing to the effect, and suggested implications for the academician and the market practitioner.

-24-

What Causes the Reinvestment Averaging Effect?

Over some period of time, the total appreciation of a portfolio is composed of the sum of various incremental increases. Understanding of the reinvestment averaging effect will be simplified if we examine only a limited segment of security price time series. The expected profit (or loss) from the random buying and selling is a function of sets of prices within three time periods. The first period establishes the base price. Within this time period are associated probabilities that securities are held in a long position. (Except for the initial period during which securities were purchased, the portfolio may or may not hold a long position in any given security, depending upon actions in previous periods.) The second period establishes prices to be used for switching securities. The third period establishes prices to determine portfolio value prices from time period three determine the outcome from actions taken in period two. Thus, for explanatory purposes, it may be instructive to consider the time series as a number of "links" in a chain. Each "link" consists of a subset of three arrays, the prices at periods during which the random switching process either starts, ends, or a transaction occurs.

A very simple numerical example may illustrate this point. Suppose a portfolio is to consist of three securities only. We will consider only one "link", beginning with the initial time period. For expository purposes, beginning and ending prices will be considered identical for all securities. The prices are depicted below:

Prices for Securities A B C

Time Period 1 1 1 1 Time Period 2 1 5 10 Time Period 3 5 5 5

We will assume that an investment was made (in equal amounts for all securities) in time period one. Random switching activity involving selling one security and buying one other occurs in time period two. In our example, we will use prices in time period three to evaluate portfolio performance. The model that was earlier tested would, of course, continue the switching actions down through a number of time periods--the second "link" would begin in time period two, another random switching operation would occur in time period three, and so forth.

We wish to calculate the expected, or average, value of the portfolio in the third time period. Suppose $100 is put into each security in time period one. At the end of the third time period, the value of the "buy and hold" portfolio (BAH) would be $1,500. The average value or the "buy and sell at random" portfolio (BSR) is determined by six equally likely switching transactions in the second time period:

A B A C B A B C C A C B

-25-

The reader may verify that these transactions would lead to a terminal portfolio value of $1100,$1050,$3500,$1250, $6000, or $2000. Since each of these are equally likely, the average value of a BSR portfolio managed according to these rules is $2483.33.

This example shows how considerable profits may be generated by randomly swapping stocks, even though starting and ending prices for all of the securities are identical. The BSR terminal portfolio value would have been greater than the BAR terminal value in three cases, and less in three other cases. However, the profitable cases so heavily outweighed the losing cases that the expected difference was positive.

The process is a good deal more complicated than this example suggests, of course. At the end of each "link", the expected number of shares held of each of the securities will not necessarily be the same. It is easy to demonstrate that more shares will be held of the securities whose price has been temporarily depressed. But in spite of its simpli- fications, the model is useful for explanatory purposes.

Large profits are generated by two factors: (1) Selling securities that have temporarily advanced faster than the others. (2) Reinvesting funds into securities that are temporarily depressed. The funds will purchase more shares when a security's price is temporarily depressed, so the end result is that a tendency exists for more shares of relatively profitable securities to be held than relatively unprofitable ones. In the example presented above, much of the profits were generated by the second factor. However, in the following example, the larger profits of BSR are due mostly to the first factor:

Prices for Securities A B c

Time Period 1 1 1 1 Time Period 2 1 5 10 Time Period 3 1 5 5

It is interesting to note (and the reader may wish to verify for himself) that the greater profits from buying and selling at random are not dependent upon a secular uptrend in prices. In the two examples above, prices for time period one and three may be interchanged, and the result is still favorable for the buy and sell at random model. What is necessary, however, is that somewhere in the "links" a degree of price irregularity exists. If, for example, prices show some types of consistently smc -h uptrends or downtrends, the BSR model may yield the same expected results as a BAH model.

This point may easily be illustrated by the following examples, which suggest price arrays for portfolios consisting of only two securities.

Prices for Securities

ABC D EF Time Period 1 12 2 1 41 Time Period 2 243 4 24 Time Period 3 484 8 1 10

-26-

Average terminal value for portfolios using securities A and B will be identical, regardless of whether BAH or BSR rules are followed. Average terminal portfolio values for portfolios using securities C and D are $1000.00 (BAH) and $916.66 (BSR), thus indicating the inferiority of the "buy and sell at random" procedure when price arrays are well behaved, prices follow clearly discernable trends, and reversals are not present (the mathematically inclined will notice that the necessary conditions of equation 2 in the appendix are not met). Where price arrays follow clearly discernable trends but move in opposite directions, as do securities E and F, results are again likely to be inferior; here, average terminal value of BSR was $675, BAH $1000. Market traders have long noted the tendency of stock prices to movetogetherand this has been confirmed by careful computer statistical studies.2 Apparently, price movement of extensive numbers of securities in clearly discernable trends in opposite directions is very much a rarity.

Are Results Confirmed by Other Studies?

The reinvestment averaging effects described above have been confirmed by a number of observers. For example, in 1968 Evans described a series of experiments using a trading strategy.3

"fixed investment proportion maintenance" This strategy involved periodic buying and selling of

securities such that the dollar value of each holding was maintained in equal proportions. Semiannual prices for 470 securities during the period 1958-1967 were used to construct 23,870 portfolios of differing sizes. The "fixed investment proportion maintenance strategy" results were consistently superior to a buy and hold strategy. Evans later attributed this result to the fact that 1( . ..the investor will periodically be led to purchase more shares of securities whose prices have fallen, and generally to sell shares of securities whose prices have risen-IV4

In 1971, Cheng and Deets reported the use of the 30 Dow Jones Industrials Stocks weekly prices from 1937 to 1969 to make further tests of the "fixed investment proportion maintenance" stretegy.5 Portfolios of different sizes were established, using rebalancing frequency intervals from 1 through 90 weeks. Results confirmed that the buy and hold strategy was overwhelmingly inferior to rebalancing. In addition, and as our earlier discussion of reinvestment averaging would lead one to suspect, more frequent rebalancing led to greater profits. The largest profits were obtained with one-week rebalancing intervals; the least with ninety week periods. Another interesting finding was that the greatest superiority from the periodic buying and selling activity occurred when the portfolio was large. Again, our discussion above would lead one to suspect that a larger portfolio would

-lead to a higher probability that securities with highly irregular price trends would be included, and these are the securities which are the greatest "money makers." Where rebalancing was infrequent, the size of the portfolio seemed to have little correlation with profits.

What is the Extent of Gain that May Be Achieved?

My initial reinvestment averaging research described above, in which the experiment was replicated 20 times on the same set of securities, achieved an average result $29,263 more favorable than the $21,374 value of the BAH portfolio. Although this is a highly favorable result, it should be noted that the results are only 2.7% per year (average annual

-27-

gain) superior to the "Buy and Hold" strategy. The second experiment, involving 120 replications on different sets of securities, achieved an average $12,200 more favorable than the $32,811 average value of the BAH portfolio. This broader and much more representative experiment yielded results which were 1% per year superior to "buy and hold."

Evan's 1968 study, using 470 listed securities in a 1958-1967 time period, showed an average advantage of 3.04% of the "fixed investment proportion" strategy over the "buy and hold" strategy for portfolios of lo-40 securities. 6 His later (1970) study pointed out that the method of calcul- ating "buy and hold" profits could have been erroneous, and that the results were open to question.' This subsequent study indicated a "fixed investment proportion" superiority of approximately 0.6% per year over "buy and hold." Evans found that this superiority was not sufficient to overcome costs of commissions and taxes, except for substantial portfolios (lower commission costs) with low investment tax rates.

In 1971, Cheng and Deets tested the "fixed investment proportion" strategy using the 30 Dow Jones Industrial stocks from 1937-1969.' They found that $1.00 invested in 1937 would have grown to $9.51 by 1969, under a "buy and hold" philosophy; however, weekly switching would have increased the $1.00 to $22.76. The margin of superiority here was more than 4%; the stocks were appreciating at a 10.7% average annual rate, and weekly switching increased this figure to 15.3%. These authors found, as Evans did earlier, that large portfolios and frequent switching of stocks were more profitable than portfolios of fewer securities with less activity.

What are the Implicatons of the Reinvestment Averaging Effect?

Some of the more interesting implications may be the following:

(1) Academicians will be interested in the effect in regard to statistical experiments and other research efforts. Many tests today contrast "buy and sell according to some decision rule" against "buy and hold." Obviously, if buying and selling at random will generate a positive profit, the fairer test would be "buy and sell according to some decision rule" against "buy and sell at random." This writer's experiments, for instance, which involved testing various trading rules, were reaccomplished contrast- ing results against random switching results. The trading rules remained highly successful and statistically singificant, but the margin of superiority was decreased.

(2) Those who believed in the random walk hypothesis of stock price changes will be heartened by disclosure of the reinvestment averaging effect, for it casts light upon an element which has mystified them. The reinvestment averaging phenomenon shows how stock traders might be able to make a very tidy profit, even without being able to forecast the future of stock prices.

For members of stock exchanges and others who may be able to trade stocks with little or no commissions, the implications are obvious. A periodic random exchange of securities will generate a positive profit, over and above the secular appreciation in securities noted over the past 50 or so years. And, the larger the portfolio, and the more switching, the greater the profits will tend to be.

-28-

(3) Managers of large portfolios who are not exchange members will appreciate the profit potential offered by the realization of this effect. Random buying and selling activities among portfolios selected at random will not, in general, produce returns sufficient to offset commissions and other transfer costs. However, the careful investor who selects a portfolio of stocks conducive to this effect is likely to find his results appreciably increased. For example, note that this writer's initial reinvestment averaging experiment which replicated buying and selling activities with only one set of securities just happened to include securities whose price patterns were conducive to profitable application of the effect. The results of this test were 2.7% per year superior to buy and hold activities, and were considerably more profitable than the 1% superiority of the larger set of experiments. This points to the advantage that may accrue from initial selection of highly suitable stocks.

(4) By examining the causes of this effect, the skillful portfolio manager may be able to do a great deal better at the timing of his buying and selling actions than random activities. Proper attention to timing can be accomplished while using only those securities he prefers to hold.

(5) The effect has much less practical relevance for small portfolios, but it is interesting that a slightly modified version of the reinvestment averaging effect is effective for even single security portfolios. That is to say, the practice of periodically selling a security and, after a random period of time, reinvesting the proceeds back into the same security, will often result in a larger expected return than holding the security, if taxes and commissions are ignored. For securities which pay no dividends, and during time periods during which the market does not enjoy the secular uptrend of prices, the practice will result in a larger expected return. (If transaction costs are ignored, an investor who sells at any price, say 10, will improve his position, on the average, if he can later repurchase at either 8 or 12, with probability.Jg

(6) The relative strength concept of stock selection has many ad- herents. However, it should be noted that the reinvestment analysis effect appears, at least on the surface, to contradict relative strength. The analyst who attempted to insert judgmental factors into portfolio operation might well select the weakest security to be sold and the strongest to be bought. This kind of procedure would, of course, work in a direction opposite to the reinvestment averaging effect."

-29-

APPENDIX

To illustrate necessary conditions for the reinvestment averaging effect, one may first consider price arrays of only two securities:

Time Period 1

Time Period 2

Time Period 3

SECURITY

X Y X0 YO

Xl Yl

x2 ,. y2

Let Z = The fixed investment made in each portfolio at the start of the experiment.

YPOT= The ending value of the "Buy and Hold" portfolio. XPOT = The ending value of the "Buy and Sell at Random" portfolio.

YPOT= zx, + zy2 = z X2 + y2

--

( >

- X0 YO x0 yo

2 E (XPOT) =[ (z/x.) (xl/YJ + Z/Y.] y2 +

[(Z/Ye) (Y1/xl) + z/x0] x2’ (1)

After combining and rearranging terms:

2 E (XPOT) = Z

1

(;+?$A) +z (; + 22)

For "buy and sell at random" to yield results superior (in the long run), it is necessary that YPOT < E (XPOT). This implies:

This reduces to the necessary condition that:

X2 + y2 X1 y2 + Yl X2

- --< - x0 Yo x0 Y, Yo Xl (2)

-3o-

The necessary condition essentially revolves about the per cent changes from one time period to another.

VP The quantity x1y2/xay1 is nothing

more than the ratio of thesecondperiod price of one security over its first period price, multiplied by the ratio of the third period price of another security over its second period price.

Time Period 1 Time Period 2 Time Period 3

Prices for Security W X Y

WO X0 YO w1 x1 Yl w2 x2 y2

YPOT=Z

t x,/x0 + YJYO + w&30

3 6 E (XPOT) = Zxl + 2 (y2) + Zw, +

( xoYl J w, ( EL+ i-)(-,) +

+(;: g-' 'I ( g,'y4 +'

=y2

55x2

(3) X0

zx2

x0

After comgining terms and rearranging, a positive difference is:

the condition necessary for

Yl wp + Wl x2 + Wl Y2 (4)

Yo Wl wo x1 wo Yl 1

It is again appropriate to point out that the condition of irregularity in price movements is most conducive to the achievement of a significant positive difference. The method of extending this investigation to portfolios containing four, five, and mOre securities is obvious.

-31-

FOOTNOTES

1. James, Francis E. Jr., "The Implications of Trend Persistency in Portfolio Management,* a Ph.D. disseration completed at Rensselaer Polytechnic Institute, June 1967.

2. King,

3. EVaIlS,

Benjamin F., "Market and Industry Factors in Stock Price Behavior," Journal of Business, 39 (Jan 19661, P. 139.

John L., "The Random Walk Hypothesis, Portfolio Analysis and the Buy-And-Hold Criterion," Journal of Financial and Quantitative Analysis, Vol. III, No. 3 (Sep 19681,p. 327.

4. Evans, John L., "An Analysis of Portfolio Maintenance Strategies," Journal of Finance, Vol, XXV, 'No. 3 (jun 19701, p. 562.

5 * Cheng, Pa0 L., and Deets, M. K., "Portfolio Returns and the Random Walk Theory," Journal of Finance, Vol. XXVI, No. 1, (March 19711, p. 11.

6. EVEUlS,

7. Evans,

op. cit. (1968) P. 340

op. cit. (1970) P. 565

8.

9.

Cheng and Deets, op. cit.

The investor who sells at price X ,, and repurchases the same security later at price X0 + e or X, - e, with equal probability of either event, will generate an expected gain. However, the "loss" of dividends and the drift of prices upward offset this tendency (reduce the probability of repurchasing at X0 - e) to the extent that it is doubtful that the investor will do better than buying and holding single security portfolios.

10. The contradiction is more apparent than real. Techniques of combining the two concepts exist and may be highly profitable.

-32-

DOES THE TAIL WAG THE DOG?

By Line

D. Bruce McMahan, a partner of Bear Stearns, is developer of the technical concepts of the premium pool and option premium levels as they are used here and heads up the options marketing effort for his firm. F. Martin Koenig is Vice President and Manager of Option Investments for Chase Investors Management Corporation. Mr. McMahan and Mr. Koenig have collaborated for more than three years in an attempt to refine and quantify certain relationships that exist between option premiums, individual securities, and the overall market.

-33-

DOES THE TAIL WAG THE DOG?

Shortly after listed options trading began on the Chicago Board Options Exchange in the spring of 1973, market practitioners became fascinated with the prospect that option premiums may contain valuable information concerning price movements in the underlying securities. The academic community has also become involved, developing a plethora of black boxes with which to predict the fair value of options. Most of these models key off price movements in the underlying security for predicting option fair values. The authors have attempted to look at things the other way around. Given option prices, can anything be said about price expectations in the underlying security?

Whichever way one locks at the question, the advent of exchange traded options has had a profound impact on the way traders and investors behave. Today, the hedging of risk and optimization of returns, are the watch word of trading and investment strategies. Increasingly, the investment community has focussed on the movement of securities in one market in an attempt to forecast what might happen in the other market. Since most would agree that predicting movements in the underlying security is far more important than predicting option premium levels, we have chosen to examine a few commonly held beliefs that purport to have predictive value.

Certain generalized relationships have cropped up, and have been accepted as self evident by many practitioners. One commonly held belief goes something like this: "when the market is high, premiums are low" or conversely,'when the market is low, premiums are high." Both of these axioms are well documented. A casual look at figure 1 - Market Level Versus Premium Level-illustrates the foregoing relationship.

More specifically, in the first quarter of 1974 when the S&P 500 was trading around the 99 level, six month, at-the-money call premiums were trading at 10.7%. About eight months later in the fall of 1974, the S&P 500 had dropped to 70, and six month, at-the-money call premiums were 18%. We all know the market rallied substantially after that, and a little less than two years later, in September 1976, the S&P 500 was trading at 105 and six month, at- the-money call premiums had dropped to 8.5%. Post 1976, the market entered a prolonged decline.

Look at figure 1 again. If these relationships are valid, they should have some predictive value , and certain collaries would logically follow. After all, the market did decline in 1977 did it not? One such collary might be: "when premiums are low, the market is high," or "when premiums are high, the market is low." Quite simply, the problem with such generalizations

Copyright @ 1979, D. Bruce McMahan and F. Martin Koenig, all rights reserved. No part of this publication may be reproduced without the prior wirtten consent of the authors.

-34-

is that they are not true.

In December of 1975, option premiums had just recorded a new all time low, and we all know what the market did in the first quarter of 1976. Look again at figure 1. The practitioner who assumed that "if premiums are low, the market must be high" and acted adcordingly, would have lost an awful lot of money on the short side. Had he been a more conservative investor and raised cash, or written calls on his whole portfolio, opportunity losses would have been quite substantial. In December of 1975, the S&P 500 stood at 87. By October of 1976, the market had climbed to 107, a 20 point move in ten months. This computes to a 23% opportunity loss. So much for that theory!

Money Rates Versus Premiums Level

Since options provide leverage to the buyer and risk transfer to the seller, (in a sense, the buyer is borrowing from the seller), one might expect that there would be a decent correlation between changes in interest rates and changes in option premiums. In fact, the Black Scholes model (used to compute the supposed fair value of options from stock price data and other information) uses an explicit interest rate variable as an important part of the model. Obviously, interest rates, volatility of the underlying securities, dividend rates, and most importantly future price expectations, have profound and noticeable impact on option prices. Yet, if we look at interest rates alone, there appears to be a rather neat correlation.

Figure 2 - Correlation of Money Market Rates With Option Premiums Lagged Four Months - displays the relationship between 90 day CD's and 90 day at-the-money option premiums. The correlation is almost too good. Today, with interest rates over lo%, one might argue that option premiums should be much higher than the 7-8% level recorded in late 1978, much less the 6% premiums that existed only last month. Admittedly, given the current level of interest rates, combined with the pickup in stock market volatility experience in 1978, premiums should move up sharply from their recently depressed levels. In fact most models (including Black Scholes), generally show options to be undervalued. Does this mean that one should go out and buy calls at today's market levels, because calls are cheap? Possibly, but that depends on whether the market goes up, down or sideways from here.

Maybe calls are cheap for a good reason! The question of whether calls are cheap relative to current money market rates, or cheap in terms of stock market volatility, or cheap in terms of various black box computations, is totally irrelevant. What is relevant, is whether stocks go up or down from here.

Copyright @ 1979, D. Bruce McMahan and F. Martin Koenig, all rights reserved.

-35-

What is Relevant

It doesn't really matter whether premiums are low, or whether premiums are high, or whether interest rates are low or whether interest rates are high, or whether stock market volatility is low or high. What matters when attempting to gauge what one should do with one's money, is whether or not the probabilities are in favor of a long, short or hedged position! As option practitioners, the authors generally prefer to hedge, but not always. Hedges do not have to be neutral either. They can be skewed to a bullish or bearish posture as well. When adjusting positions, we rarely move 100% in or 100% out of the market, but prefer to scale, making meaningful moves at the margin. Guts, intuition, and a few key indicators generally tell us when to hedge and when to unwind a position.

When analyzing financial markets , academic and investment professionals have tended to build models that rely heavily on repetitive circumstances to trigger certain action signals. The authors also view repetitive circumstances as essential to market forecasting. However, there always has and there always will be a certain amount of "art" required in making reliable forecasts of future market behavior.

Accordingly, our methods are not strictly mechanical, we do not profess to have found an end all panacea, and lastly, analysis of key variables frequently requires subjective determinations on the part of the user. Stock market forecasting is no simple matter. It cannot be reduced to a simplistic model using a handful of variables.

Notwithstanding the foregoing, indicators,

the authors have developed a series of which have proven useful in optimizing the risk/return trade offs

inherent in certain buy/sell decision rules. certain intuitive aptitude.

The decision rules require a Without this aptitude, the model will fail.

Buy/Sell . . . . . Can the Options Market Tell You When?

Looking at charts 3, 4, and 5 - Option Premium Cycle Index for All Listed Options" even the most casual observer is sure to notice that when a bulge occurs in the premium pool (plotted across the top of the page) the equity market inevitably flattens out or turns down in the seven to ten weeks following the bulge. In 1976 (figure 31, bulges occurred in January, February, June/July, September, and December. These were high points for the market. This phenomena occurred again in April/May/June, and August/ September of 1978 (figure 4). More recently (figure 51, a bulge occurred in January and again in late March of 1979. Conversely, buying opportunities have consistently occurred when the premium pool is at very low levels.


-36-

Before going much further, a few terms need defining:

Option Premium Pool - aggregate total funds flowing through the option market premium structure, this time series is plotted using the upper left hand scale.

S&P 500 - This is plotted directly below the option premium pool and is the second line from the top using the upper right hand scale.

Highest Value - This is the third line from the top (about the middle of the page), and is an average of the highest value for each stock's premium cycle, calculated over the previous nine months.

15 Day Moving Average - of the current index value.

Current Index Value - at the money premium, normalized to fourteen week expiration.

Lowest Value - This is an average of the lowest value for each stock's premium cycle, calculated over the previous nine months.

Premium Levels as a Forecaster

Option premium levels when used alone are not terribly reliable in forecasting future price movement. However, when analyzed in conjunction with the option premium pool and what is happening in the overall market, the results have been quite good. The degree to which these three variables accelerate and decelerate or whether confirmation/divergence is observed, is key in determining whether one should buy, sell or hedge.

Major sells generally occur under the following conditions: (1) a high or bulging premium pool, (2) a market that has recently risen, or is still rising, (3) the current index value is relatively high when compared to the recent past and is well up in the premium trading range between the highest and lowest value. Major buys generally occur during periods when the premium pool is very low and premium levels are also low, acting to confirm a market which has been drifting lower in the recent past.

Major buys and major sells are marked on figures 3, 4, and 5 with an M either above or below the arrow. In 1976 there were major sells indicated in February and December. In 1978 one occurred in January with three occurring in the May/June period, followed by a number of sell signals throughout August and September. One also occurred in November when premiums were at an all time recovery high of 8% for fourteen week, at-the-money options. This was the highest premiums had been since February of 1976. There was another signal in late December. No major sells have been registered thus far in 1979.


-37-

Looking again at figures 3, 4, and 5, major buys were recorded in January, April, May, August, September, October and November of 1976. In 1978, there were four major buys in February, March, July and December. In 1979, there have been three major buys , one in late January about a week before an overbought condition and a minor sell, the second in February and the third in March.

Other buy/sell signals are merely indicated with an arrow, and while not termed major buy or sell, they are still quite meaningful within the overall context of short term trading decisions. The batting average has been reasonably consistent and quite high. The buy/sell signals indicated in figures 3, 4 and 5 represent the concensus of a collaborated effort between broker and client. The signals do not necessarily represent all the broker interpreted signals nor do they represent all client interpreted signals either. What you see is a concensus of key buy/sell decisions arrived at independently, but using the same information. Not‘surprisingly, there were only a few instances where broker and client disagreed.

Summary and Conclusion

When using option premium information , one must take into account variations in momentum, as well as confirmation/divergence of the premium pool, the market itself, and the current index value. Acceleration and confirmation among these variables means one thing. High acceleration and divergence may mean another. Deceleration and confirmation may mean something totally different. Deceleration and divergence may mean another. There are essentially three variables plotted on figures 3, 4 and 5, with 6 time series derived from these variables. The interrelationship among these six time series is complex. It is the understanding of this total interrelationship however, that is key to successful forecasting.

Moderation is the watch word, as with most technical indicators. The risk of whipsaw is ever present, and scale tactics, making meaningful moves at the margin will generally be rewarded. With covered call writing and variable hedging, the selling of a wasting asset has generally served to optimize the trade offs, between risk and reward. This does not mean, however, that option buying strategies cannot produce a similar pattern of risk/reward optimization. The purchase of puts to protect long positions can serve as an excellent hedge. Similarly, the maintenance of a large reserve position combined with the purchase of calls has proved rewarding , as risk is limited to the premium paid, while rewards are open ended. More sophisticated hedges, including combination straddle hedging (short one put/call combination, while long another) can produce a high probability of return while operating at a reasonably low level of risk.

In sum, if you have a reasonably good handle on where the market is heading, appropriately skewed hedges can beset up to minimize the risk of whipsaw, hopefully producing a risk/return profile that is consistent with investor objectives.


-38-

Market Level vs Premium Level 6 Month percent

Option Premiums *

18

6 -1

i

.

-

0 lq 2q 3q 4q lq 2q 3q 4ql 2q 3q 4q

1974 1975 1976 *nomalized at- ths-nmrraay % %wm

Copyright @. 1977, F. Marlin Koenig. all rights re3mm

T Stock Index,

G

T-

S&P 500

-80

60

FIGURE I

Correlation of, Money Market Rates with

Option Premiums Lagged Four Months

90 Day CD Rate

I \-90 Day Option Premiums \ ,,,,‘g”‘N~@~ ,,,,

6 \ 0

--- I . -‘-’ 1974 ---- I 1975 --- l -- 1976 ,---.I--- -- 1977 .--.-I---. 1978 _ .___ m.I____

Cof)yright @ 1978, D. Bruce McMahan and F. Martin Koenig, aIt rights reserved FIGURE 2

J J I / J 1 J 1 1 J )

; :

: : : ! !

:

: : : : ; ! 5 i : : s

' ,,,,,,,,,// I,,/, , ///////N///Nlr "t I

Option Premium Cycle Index for all Listed Options Option Premluins*

p-pa’c;f7

G

% I

I I I ,l I , , I I , I I I ,

or$kdIe covered calls U.J

I Sell

t BUY or$$ver Previously wriuen ~oei~~onef&&fl~/~

1” 1 Maj4 Sell/Major Buy’respectlvely- , ’

I R I

.

rCurren1 Index Value 1 ’ t v

*lS Day Moving Average

AUG SEPT OCT NOV DEC

+ no!%% 1 ited at-the-money Premiums 1978

*9 Aggregate total funds llowing through the oplion market premlum struclure

Copyrlght 0 1979, D. Bruce McMahan and k Martln Koenig, all rights reserved. FIGURF 4

b W I

Option Premium Cycle index for all 1Asted Options 14 Week Option Premiums * $ Pool Millions r)c;k

‘-loo

00

-


-44-

BOTTOM FISHING WITH RELATIVE STRENGTH

Over the years relative strength has been one of t tools, applying the concept to the various averages and individual stocks. In the 1960’s relative strength app simple, at least with groups and individual issues. We for a clear uptrend to develop and climb on board.

he most useful technical indices, groups and

lication was relatively could sit back, watch

One hardly ever bought stocks near their lows with this approach but since the periods of positive relative strength sometimes ran for several years, what difference did it make? The proof was in the pudding, it made money. Then when relative strength began deteriorating or stagnated for several months, it was a simple matter for the technician to change horses.

Bob Levy, the academic-economist-statistician, convincingly and academically demonstrated the validity of relative strength as applied to 200 individual Issues, 1960-1965. His book, The Relative Strength Concept of Common Stock Forcasting, was one of the first serious studies supporting the validity of technical analysis. But, in the late 1960’s and early 1970’s the world began changing for the relative strength techn i ci an. Those long extended runs of better than market performance for groups and individual stocks became rarer and rarer. Cycles were too compressed.

The Ball Game Changes

in the early 1970’s technicians applying the longer term relative strength approaches of the past were often finding that by the time a strong relative strength uptrend was clearly established and obvious, it was also about over. Long extended periods of superior relative performance, the ones that lasted for years, were being replaced by five to eight month periods of superior performance. The course was getting tougher and the methods, such as Levy’s designed to take advantage of the longer time frames of the 1950’s and the first half of the 1969’s, no longer worked very well. A common complaint heard in technical circles was “by the time I recognize and buy the move, I’m buying at the top.”

This writer, an admitted relative strength devote)e, was having this same problem back in the early 1970’s. It was getting embarrasing. We made a series of runs using 320 stock groups (the Piper, Jaffray Micro loups) and confirmed that the cycles of positive relative performance were indeed becoming shorter. Why? Well, maybe it was the result of increased institutional market domination and more efficient transmittal of positive information. Maybe these big buyers were recognizing the good stories at close to the same time, bidding them up aggressively in a shorter period. Thus, the potential buying power that used to be spread over say a year, was now spent in a few months. Or perhaps these shorter periods of positive relative strength were only the result of the increased volatility

-45-

of the market itself. Then aga in , maybe it was only the perverse nature of the market itself. Now that many of us had discovered an approach that really seemed to work, one whose past effectiveness could actually be “proven,” now maybe it was time for the market gods to change the rules. As one old timer used to say: “Once you finally dlscover the key to the market, some some of a bitch comes along and changes the locks.”

But, whatever the reason, by the 1970’s most of the technical fraternity was dfscovering that the relative strength approaches to successfully applied in the past were not working very we1 1 anymore.

Here is the approach we developed in the early 1370’s to more effectively deal with this cycle compression. its primary advantage is that It gets us into a group move very early, very close to the low point.

Bottom Fishinq For Groups

Ilarket success often comes from buying the groups and stocks that are out of vogue..... “buy them when they hate them,” as an old broker friend of mine used to say. The biggest problem with this philosophy is that an investor can be very premature. Nobody has really come up with a formula to determlne how low is “low.”

Within our publication and also in managing portfolios we have come to employ a bottom fishing technique for groups that seems to have worked pretty well over the last five or. six years. The technique, using relative strength as a key tool is known

. as “The intriguers, lagging groups that could become leaders.” It, of course, does not work al 1 the time. Sometimes it is premature in isolating group relative strength - bottoms. But, our experience indicates that things do work out right about 70% of the time. And, in the 30% of instances where it does not work out, the damage seems to be quite 1 imited, since the groups we buy have al ready been underperforming the market for at least twelve months, Thus, it is virtually impossible to buy, just as a group is in the process of taping out. Also, since the group has already been declining for twelve months by the time we buy it, even if we are wrong, a good portion - of the decline is behlnd us. There is not as far to fall.

Our experience with this approach is limited to the 310 stock groups included in Piper Jaffray’s group service, The MicroGroup Project but it would seem the same approach should work with almost any group base. At th?s point we have not, on a highly organized basis, applied this disciple to individual stock relative strength.

Briefly, it works like this. Here are the steps we follow.

1. Isolate all groups that have been performing significantly worse than the market for at least twelve months, This is done visually, looking at the charts and applying judgement.

2. Fundamentally cull and divide this list of laggers and losers. We attempt to eliminate industries where economic survival is questionable (buggywhlp industries) and we subdivide the list into a listing of groups that could conceivably be appropriate for most institutions and a list of groups that are clearly speculative or very aggressive. (Note that a pure technician might eliminate this step completely, but we live in the real world of institutional money management so this step is a necessity.)

-46-

3. Then a monitoring procedure begins, looking for indications of stabilization. Stabilization to us means a period of at least four weeks, but usually eight or twelve, in which the group is no longer performing worse than the market. Again this is judgement, dependent primarily on chart reading. However, in the past year or so some purely quatitative techniques have been developed to supplement our j udgemen t . Note in this phase the relative strength need not be rising. It is enough that it-is moving sidewise. Also factor approximate group Beta differentials into your thinking. (At one time we actually calculated Beta adjusted relative strength, but this was too expensive, so it has been replaced by judgement.) Also, of course, consider any individual group contra market characteristics (gold group, utilities, etc.).

4. Once a group has achieved this “stabilization” status it must demonstrate a short period of superior relative strength action (again mentally adjusting for the factors discussed in the preceding step). We like to see at least two or three weeks, preferably carrying the relative strength line above a preceding minor high, be it ever so minor. This puts the group in the tenative “Active Buy” status.

5. Before awarding a group full fledged “Active Buy” status, we examine the component stocks of the group, looking for warps. Was the short term group relative strength improvement the result of one stock? A tender offer? A rummored buy out? An oi 1 discovery by a paper company? Or, was the relative strength improvement found in several of the group component companies? If the strength comes from a one stock warp, don’t buy the group, but keep monitoring it closely.

6. In our discipline, we remove a group from our intriguer list once it moves up 25% from its actual low. Of course, the group may st i 11 be attractive at this point but by our standards it no longer qualifies as “depressed .I’ Al so, if the relative strength line move up within 8% of a previous cyclical peak, the group no longer qualifies as “depressed . I’ And, when more than nine months has elapsed from the time of the latest new low in relative strength, the group is viewed as “matured,” no matter what price action has occurred, and is also removed from the list.

The principals involved in this whole procedure are not new. The quatitative standards set are not magtc numLers; others may have developed more sophisticated ways to play this same kind of rame. There are no magic formulas and room is left for judgement and the lessons of experience. Here are, in my opinion, the most important aspects of what has been described here:

- If the tools you have been using don’t seem to be working anymore, analyite and modify. If they change the locks try and find the new key. Don’t stubbornly keep trying to force the old one.

- Group analysis can be a very rewarding approach to portfolio management and stock selection.

-47-

- Quantification and the computer have limitations. Judgement, common sense, experience and flexibility are also necessary.

- Bottom quessing techniques as described here, having worked quite well for five or six years now, may become increasina less Droductive in coming years. Watch out! They’ may change the loiks aga’in .

TAKEN FROM APRIL 1979 PERCEPTION FOR THE PROFESSIONAL ---PJH

INSTITUTIONAL INTRIGUERS

% Down \

from % Above Months Techni- 1975-78 1978-79 Under Stabili-

CORE INDUSTRIAL Steel, Primary Chemicals, Primary 8+ Machinery,Construction & Mng. 6-

CONSTRUCTION Construction Mat.,Div., Pri. lO+

*Mobile Homes 20 CONSUMER GOODS

Consumer Conglomerates 15 NEW Food Products, Div. 15

Processors, Soy & Feed 17- *Brewers, National 20-

Tires, Original Equipment ll- Textile Manufacturing 7 Major Appliances 18 Small Appliances lO+ Home Electronics 19

NEW Housewares 19 Diversified Leisure 12

UTILITIES Electric, Large Metropolitan 20-

NEW Electric, Northeast 19- Electric, Midwest 19- Electric, North Central 19- Electric, Hydro, Northwest 18- Electric, Southwest 16- Electric, South Central 18- Electric C Gas, East 19- Electric c Bas, Midwest 18- Gas, Northeast 17- Gas, Midwest 15- Gas, West 13 Pipelines, Primary 5 Pipelines, Secondary 6-

TRANSPORTATION Trucking, Primary 12

grade** High

8+

Active Buy?

-34 -37 -16

LOW Performing zation

+19 +14 +22

37 38 34

Yes Yes Yes

--

Yes PP

-11 +18 23 Yes Maybe -48 +5 37 No --

-12 +7 16 Yes -10 +6 41 No -17 +8 38 Yes -50 +6 49 Yes -34 +13 38 Yes -6 +21 37 Yes -15 +8 13 Yes -16 +16 13 Yes -19 +5 36 No -22 0 37 No -20 +16 27 Yes

-- -- -- -- --

Yes --

Yes mm

-18 0 14 Maybe -12 +2 13 &Yb -21 +3 17 No -12 +3 16 No -14 +3 16 No -7 +4 15 Maybe -12 +4 51 Maybe -11 +3 17 No -19 +1 17 No -8 +4 16 Maybe -13 +6 17 Yes -9 +12 13 Yes -3 +23 15 Yes -4 +20 20 Yes

--

-- --

-- -- -- -- --

--

Yes Yes

-27 +15 36 Yes Maybe

-48-

% Down from % Above Months

1975-78 1978-79 Under Stabili- Active High Low Performing zation Buy?

Techni- srade**

FINANCIAL Banks, Money Center 19

NEW Banks, Mid Atlantic, Pri. 18 CONSUMER DISTRIBUTION & SERVICES

Department Stores, Secondary 16 Department Stores, Primary 19

NEW Hospital Supplies 20

-23 +5 48 No -- -14 +3 15 No --

-33 +6 37 Maybe -- -31 +4 39 No -- -19 +5 14 Maybe -- PP

AGGRESSIVE/SPECULATIVE INTRIGUERS

BASIC ENERGY 10 -22 +24 20

13

Maybe -- Uranium Mining CORE INDUSTRIAL

NEW Machinery, Const. & Mining, Set CONSUMER GOODS

*Sugar Beets *Seed Suppliers

Automobile Tires, Replacement Cosmetics, Secondary Toys, Games & Pets

-- PP

Yes -- -- --

Yes

SW

--

--

-- PP

. lo+

8 15

9+ 13

4+

-18 +20 Yes

-42 +24 45 Yes -43 +12 53 Yes -16 +17 19 Yes -22 +20 61 Yes -19 +23 37 Yes

UTILITIES NEW Water Services

TRANSPORTATION Maratime Shipping

FINANCIAL New Banks, Mid Atlantic, Sec.

8

16

10

-7 +5 13 Maybe

-30 +10 Yes

-8 +3 No CONSUMER DISTRIBUTION & SERVICES

Hospital Supplies, Secondary 15+ -21 +12

20

12

17 Yes

* Su: ‘r Depressed (Down 40% from 75-78 high) ** Technigrade is a weighted intermediate relative momentum reading combining 26

weeks of readings compiled by Piper's Keith Blaich. It is a new tool, but has been tested back four years. A Technigrade of "1" indicates a MicroGroup is in the top 5% of Technigrade ratings , while 20 indicates the bottom 5%

PP Primary Productivity Play

P Productivity Play (Secondary1

-49-


-5o-

ONE ASPECT OF THE POPULAR "4" YEAR CYCLE

BY: IAN CAVITY, EDITOR, DELIBERATIONS

Canada is best known in the United States for the almost nightly comment in the weather forecast, which typically announces another cold front blowing in from the north. The Canadian stock market providesa similar service for students of the 4% Year Cycle in the stock market.

Perhaps you have noticed that an increasing number of market letters are putting more and more Canadian issues on their buy lists....the oil and gas stocks have been extraordinarily popular, and more recognition seems to be falling towards majors like Alcan, Canadian Pacific, Into, and other inter-listed majors.

This is essentially a cyclical phenomenum, not seen since late 1973, or in the prior cycle, the spring of 1969. To refresh memories, October 1973 saw a Bear Market rally top out in New York, as did May 1969. Those two months witnessed the Canadian markets posting their cycLLca.!Z pe&, from which they joined New York on the downside through the subsequent cyclical bottoms in May 1970 and Oct/Dec 1974.

In the April 5, 1976 issue of BARRoN'S, in an article entitled BAY STREET VS. WALL STREET - Canadian SXach6 May Be PaLed to CaXch Up, I outlined a study of the relative behaviour of the Canadian Markets (vs the S&P 425 Industrials) over the past five completed market cycles from 1953 through 1974.

In each cycle, the Canadian underperformed New York quite dramatically for the first 16 to 18 months following a cyclical bottom in New York; and then, frequently commencing from an intermediate low (like Nov'71, Mar'68 or Oct'60) the Canadian Market would change in character, and go on to OUTperform New York for a period of 26 to 28 months.

The study was based on visual observation of a relative strength value which was derived from dividing the Toronto Index by the S&P Industrials on a month to month basis. Thus the RSV would rise whenever Canada went up ma&e, or dotin Lua than New York. The chart from that original study is reproduced here as CHART II as it appeared in April 1976.

Across the bottom, there is a momentum plot which simply identifies 12 month rate of change in that Relative Strength Value, smoothed with a front weighted moving average. At that time, the momentum was recording the weakest relative performance by Canada in two decades, but it was decelerating.

The subsequent sell off later in 1976 (actively exagerated by the election of the Separatist Government in Quebec) made my case for Canada premature by some six months; but the following 28 months have borne out the theory - with Canada's markets dynamically outperforming New York from November 1976 to date.

Stepping back a moment, CHART I, provides a pictorial history of the past thirty years in LONDON, NEW YORK, TORONTO, and more recently TOKYO. The cyclical bottoms are illustrated on NEW YORK, but you can see that they appear elsewhere in much the same fashion, and they tend to be roughly coincident.

-51-

I 481 1 I Ir2i 1 I Iwi 1 I lbol 1 I itul 1 I lrel 1 i I721 1 I- 1761 1 i h301 1 i i84

9 9 9 9 9 9 9 9 9 5 5 5 6 6 7 7 7 8 0 4 8 2 6 0 4 8

500 N. i2 500

.-

/

1

2000 I !

-1500

I

’ / ,ooo

.

.* 800

,,, 600, L

_ 1

-52-

t III1 Ill Ill IllI I I 11 11 I I I I[

I1 mnnls I ’

1 I

* .

CHART 111

9s4l I I )19sal I I I I i )i%d i I J197d I I I 19741

NEW YORK

Once again resorting to 12 month rates of change, smoothed, CHART III provides the cyclical cardiogram of the LONDON, NEW YORK and TORONTO markets since 1953. The relationships between the three markets are remarkably similar.

CHART III provides an important illustration of the @m or relative behavioural characteristics of Canada's markets in relation to New York. Note that New York's bullish phase appears to have two positive humps - with the first hump reaching higher than the second. (Or, to put it another way, the bull market peak tends to occur with a lower peak in momentum).

Toronto on the other hand, does the opposite....with its second peak invariably rising above the first one. The little arrows illustrate this fact.

In my opinion, the relative behaviour of Canadian markets over the past twelve months, in contrast with New York, adds an element of historical perspective which suggests that the Spring bottom in 1978 will prove to have been an int- emediate bottom, which suggests that the nominal "4" year cycle from 1974's lows is running long in time, this go around.

It is not unreasonable to presume that the Bull Market which came out of the ashes of 1973174 - the worst Bear Market in a generation - could indeed turn out to be longer and stronger than its inmediate predecessors. Up to, and including, the occurence of TWO intermediate bottoms, where the two previous cycles had only shown one.

Index relative to New York; CHART 1970/1974 cycles, and the picture as it stood when this chart was published in DELIBERATlUNS back in June 1978.

Gettins back to the "form" of the cycle. as illustrated bv the Toronto IV providei a weekly profile of 'the 1966/1970,

CHART iv

The Inferior phase, and the subsequent Superior phase of Canada/New York relative performance reveals the cyclic "form" which I consider to be significant; and it also illustrates the inconsistency of elapsed time.

In my opinion, this particular cyclical form can add great perspective to the exploitation of the widely popular "4" year cycle.

To crystalize the "theory" of Canadian relative behaviour, as well as putting it into a current perspective, CHART V on the next page tells a rather strong story.

The "Theory" portion is in fact the average of the five completed cycles between 1953 and 1974.

-54-

CHART v

100 - The relationship between the Toronto Composite Index and the NYSE Composite Index at the Bear Market Bottoms

The theory model is based on FIVE completed Market Cycles. 1953/57, 1957/62, 1962/66. 1966/70 and 1970/74. The more recent cycles have shown greater relative performance by Canada in the latter stages, which explains why the weighted moving average rises significantly above the arithmetic average.

. The arrows identifying 1970, 1966, 1957, 1974 and 1962 fllustrate the point at which those bottoms occurred, in terms of the number of months from bottom to bottom - with October 1974 as the reference point.

In constructing the "Theory" model, I show an arithmetic average in which each of the five cycles is equal; and a front weighted average that gives greater emphasis to the more recent experiences.

The "Fact" portion of CHART V is the actual experience from October 1974 to date. Both models take the Relative Strength Value which is the Toronto Index divided by the New York Index, as being equal to 100 at the Bear Market Bottom. For comparative purposes, the "Theory" model is illustrated here in terms of the current time period - starting from October 1974, with the arrows (dated) identifying the point in time at which the In the 15 months since next cyclical low occurred. market troughs were reached

In my original study of the 1953/1974 period, in Toronto and New York late in 1974, the Toronto Stock Ex-

I looked for, bti could not @id, any exchange rate factor change Industrial index has which might have played a role in Canada's relative form. risen less than half as much as In fact, I could not identify ANY significance to the C$ New York (measured by var-

exchange rate in US$ terms, in so far as stock markets ious popular indices). The lessons of history suggest that

were concerned. this performance is--perfectly normal. Moreover, if the past be prologue, the TSE index should outperform New York from the second quarter of 1976 through the third quarter of 1978.

Below, CHART VI, shows the current picture, index to index terms, AND with an adjustment for the decline which the C$ has suffered since 1976. On the adjusted basis, we are witnessing an almost perfect instant replay of 1972/73....with the current levels VERY close to where they were when the 1973 top was being recorded by Canada (as New York was topping out in a Bear Market Rally....in October 1973).

The reason Canada's relative performance continues strong AFTER the actual top stems from a "low-beta" or volatility characteristic of the Canadian Market. Simply put, it doesn't fall as fast as New York in the early stages of a Bear decline . . ..but it tries to catch up on the downside later on.

To conclude with a return to my opening analogy to the weather forecasts. When Canada is having its cyclical "moment of glory"....it is also warning of an imminent cold front in the Stock Market Cycle. Canada - Caveat Empto/r I!!

. zg US8

At the moment, however, Bay Street investors are openly skeptical about the out- look for the Canadian stock market. Indeed, Toronto’s poor relative performance vs. New York over the past 15 months, coupled with the un- certainties created by Cana- da’s anti-inflation program. have created widespread belief here that the only game in town lies south of the border. In my view, the herd of Cana- dian investors now migrating south is abandoning a greener pasture for a well-trodden one.

3 23- .lv’\I P’I

i’ ’ lconverId to USUI c 16

1971 , 1972 : 1973 ( 1974’ ‘, 1975 , 1976 ‘, 1977 , 1978 l 1979

I I I I I I I I I lllllll IIIIIIIIIIIl III I_

-

-56-

INTEREST RATES/STOCK PRICES

by James D. Anderson

The following outline is an historical study of corporate bond interest rate trends,

yield differential comparisons of various quality instruments, inverted yield curve

analysis, and the predictive value of these trends in determining future stock price

movement and likely swings in interest rates. The reference material dates back to

1919 and encompasses sixty years of valuable data encased in American history. Out

of this information, some definite conclusions regarding today's investment environ-

ment can be made.

To begin, a brief overview of interest rate trends during this period is essential

to understanding our current dilemma. Interest rate history directly after World

War I was dominated by high levels of inflation as the Nation used large quantities

of raw materials to fight that war, and prices were steadily advancing. The peak in

long Aaa Corporate Bond yields occurred in June of 1920 at a level of 6.40%. During

the following 26 years, the trend in these instruments declined (higher bond prices)

with two brief interim periods (mid-1928 to late 1929 and third quarter of 1931 to

mid-1932). This latter period was brief and primarily involved a panic situation

brought about by .illiquidity, bank closings, and an economic depression already

visibly in sight;'... It is also noteworthy that during this period (mid-1932) the lower

credits (Baa) were severely hit with selling pressure as investor questions regarding

the viability of these instruments became paramount. Peak levels were 11.63% and

were recorded in May of that year. This compares to the 1921 peak level at 8.56%.

As previously stated, the high credit ratings did not penetrate their yield levels

of mid-1920; and, after the panic, yields settled once again and the primary trend

remained down until mid-1946. In total, Aaa yields declined 394 basis points to 2.46%,

Since this date, interest rates have been on an ever-increasing yield curve with

each subsequent peak higher than the preceding peak. We have listed these periods

below.

Moody's Aaa Corporates

April 1946 2.46% January 1948 2.86 June 1953 3.40 September 1957 4.12 September 1966 5.50 June 1970 8.48 October 1974 9.27

Low Peak Peak Peak Peak Peak Peak

Two segments of the corporate bond market are detailed in this study--Aaa/Baa. One

characteristic which has developed consistently during interest rate peaks is that a

divergence of trend will occur between these quality ratings. High grade bonds

-57-

typically peak from one to three months before the lower credits. We regard this as

typical investor concern which manifests itself during irrational market periods.

This relationship is documented below.

Peak Aaa

June 1920 June 1932 January 1948 June 1953 September 1957 September 1966 June 1970 October 1974

6.40% June 1921 8.56% 5.41 May 1932 11.63 2.86 February 1948 3.53 3.40 September 1953 3.88 4.12 November 1957 5.09 5.50 December 1966 6.18 8.48 August 1970 9.44 9.27 January 1975 ' 10.62

Peak Eaa Lag Time

12 mos. (1 mo.)

1 mo. 3 mos. 2 mos. 3 mos. 2 mos. 3 mos.

The one period which did not follow the pattern (1932) was dominated by volatile

investment bahavior. In particular, the lower credits (Baa) leading up to this peak

had been under tremendous selling pressure and yields had increased 448 basis points

in the preceding 12 months. In hindsight, this market had already overcompensated

for the reality of the times.

The next phase of our study deals with yield spreads between the quality ratings

(Baa/Aaa). In order to determine the yield curve differential, we measure bond yields

of Baa quality to those of Aaa quality. The yield differential line is based on a

percentage difference--Baa yield divided by Aaa yield. Currently, it is at an histori-

cally low range of 9.0%. Here we are measuring psychology of the bond investor. Once '

again, a definite pattern seems to unfold and represents the typical response to a

given environment. A closer examination of the charts reveals that during periods lead-

ing up to interest rate peaks, a widening of the yield curve appears and in some

instances this pattern may continue for a period after the highest levels have been

achieved. Narrowing yield spreads derive from periods of stable economic growth.

They represent an increasingly favorable view by the bond investor toward the lower

credits. Corporate profits tend to be good, and the immediate prospects are for

generally continued tranquility. Declining interest rates are also very apparent dur-

ing the early stages of narrowing yield spreads.

Since the panic of 1932 when Baa yields were 116% higher than Aaa yields (11.63% vs.

5.41%), yield spreads have been narrowing as the progression of economic stability

has surfaced in America. The current differential of 9% represents an historically

-58-

narrow range and one from which an investor must exercise a higher degree of caution

with regard to his lower credit rating bond investments. The initial reversal of

this differential line is just now becoming apparent.

The final comparative analysis deals with the relationship of short-term interest

rates (go-Day Treasury Bills/Finance Paper) and long high grade corporate bond yields.

Here our particular emphasis deals with an inverted yield curve--short rates higher

than long rates. Short rates tend to be much more volatile than long rates. In

recent years, this volatility has quickened; and, after periods of sustained economic

growth, demand factors for credit multiply and this, combined with a general deterior-

ation in overall liquidity, propels these interest rates sharply higher. The table

below lists the periods when an inversion of rates occurred and the subsequent peak

in long rates. On balance, you can see that rates tend to peak out long after the

inversion process has resulted. In-the last three cycles, the exact timing has been

prolonged and the degree of increase in rates has been progressively more negative.

Inversion . . - . . Dec. 1919

- . June 1928

Oct. 1959 Jan. 1966 June 1969 June 1973 Oct. 1978

Long-Term Int. Rates

@ 5.73% @ 4.57 @ 4.52 @ 4.74 : 7.37 6.98

@ 8.87

Peak in Long- Term Int. Rates

Increase In Basis

Points

June 1920 @ 6.40% 67 Sept. 1929 @ 4.80 23 Jan. 1960 @ 4.61 9 Sept. 1966 @ 5.50 76 June 1970 @ 8.48 150 Oct. 1974 @ 9.27 190

Time of Inversion to Int. Rate Peak

6 mos. 15 mos.

3 mos. 8 mos.

12 mos. 16 mos.

Based on the preceding analysis, we have not witnessed the peak in long-term interest

rates. The pattern established since 1946, whereby each cyclical peak in interest

rates is higher than the preceding peak, does not appear to have been broken in the

latest cycle. Yield spreads remain very narrow after a prolonged contraction lasting

almost four years. Past history reveals that these spreads will begin to widen before

the eventual peak and as this occurs, rates will continue to trend higher. We are

just beginning to witness this disparity. A continuance of this trend will likely

become more visible as we progress into 1979. In addition, the yield curve inversion

recorded last October (1978) indicates that pressures are beginning to mount in these

markets. Once again, based on historical precedence, it is premature to believe we

have witnessed the final blowoff phase in the interest rate pattern for this cycle.

Finally, we have not detected a divergence in trend between the various quality

rankings.

-59-

To use simple averages based on the preceding six cycles, we should not expect a peak

in long rates until August 1979 and yields on long Aaa quality bonds could approach

9.75% or about 50 basis points higher than currently exist. A more severe case can

be projected by simply extrapolating the recent historical trends. Under this scen-

ario, interest rates may not peak until the first half of 1980 with high quality

interest rates approaching 10.75%-11%. This seems a bit harsh in our estimation, and

we would lean to a more moderate view placed somewhere between these two outlines.

These conclusions would also seem to fit the background established by the Federal

Reserve Board and their policies regarding credit creation during this cycle. It is

our observation that business cycles evolve around credit expansion and it is not

necessarily high interest rates which create economic recessions but, more precisely,

the unavailability of credit accompanied by a rundown in liquidity trends throughout

the various segments of the economy. Although a greater degree of restraint is now

apparent when examining various monetary aggregates (Ml, M2), the key monetary base

indicator continues to expand at relatively high levels suggesting that credit avail-

ability remains if the borrower is willing to pay the higher interest rate fee. Thus

far in the credit cycle, there has not been a great degree of restraint. This phase

is still ahead of us, further suggesting that peak rates have not been achieved.

Typically, rates peak after a downturn in business activity occurs. As the avail-

ability of credit becomes crucial, rates are bid up as a variety of users seek to

improve their own liquidity. These periods are particularly hazardous for the marginal

borrower.

Let's turn now to the stock market. To begin, several observations seem apparent

when correlating the bond and stock markets. Initial periods of disinflation (lower

interest rates) have a favorable effect on stock prices (1920-29). True deflation,

once in full motion, is the absolute worst enemy of stock prices. Relative stability

accompanied by low inflation of 1%-3% is the best environment for stocks. The period

from 1942-1966 was such a period. For much of that time span, interest rates were

consistently moving higher with each cyclical peak. The stock market (DJIA) went from

96 to 1000. Since 1966, inflationary forces have gathered steam and a giant trading

range of 600-1000 has evolved for the DJIA. A more severe effect has been realized

by a majority of stocks during this period.

Yield spreads are a measure.of the bond investors' psychology. Quite typically,

declining spreads are generally bullish for the stock market while widening yield

spreads are generally bearish for stock prices. These comparisons are good to a

-6O-

certain degree; but at key turning points, these investors become overly optimistic

or pessimistic, and they are usually wrong. Bull market peaks occur after yield

spreads have narrowed for a long period. The 10% differential has been a key turning

point in recent history. Bear market bottoms occur after yield spreads have been

widening. Currently, we have experienced a four-year cyclical decline in yield

spreads with the current ratio less than 10%. It now appears that a somewhat more

cautious feeling is beginning to pervade the bond investor as a marginal widening is

becoming noticeable. It is still early in this cycle, so this change of investment

perception has a ways to go and would suggest we have not seen the end of this bear

market.

The next relationship involves an inversion of the yield curve. Here we are measur-

ing yields on long high-grade corporate bonds and short-term Treasury Bills/Finance

Paper. During the reference period, we have documented six cycles where this tempor-

ary phenomenon occurred. The stock market direction in each case proved to be un-

satisfactory. The one period that lagged was 1928, and this proved to be a speculative

blowoff prior to the ensuing collapse into 1932. Last October, we witnessed the

seventh inversion of this yield curve study. With history as our guide, we believe

investors are bucking the odds when they remain fully invested at this juncture in

the market cycle.

Our interest rate scenario, based on this data, continues to call for higher rates as

we move into the new year--perhaps 100 basis points. An examination of past bond/

stock relationships reveals that equity prices have a difficult time bucking these

bond trends, particularly at such lofty levels.

-61-

4 .I. INVERTED YIELD CURVE

200

100

60

8.0

I z I 6.0

4.0

90

50

30

1920 1925 1930 1935

1 1 ) I

5oc

3oc

200

100

4.50

d\ w I 3.50

3.00 Las

- - I I/ ”

;f INVERTED YIELD CURVE

1000

800

600

101

H 8 I

6

4

202

10

I

DJIA

Yield Dif zrential.

1960 1965 1970 1975

) 1 1 I ) I

COMMENTARY ON THE RELATIONSHIP BETWEEN RECESSIONS

AND THE STOCK MARKET

By John A. Mendelson

Wall Street is waiting for a recession. The hope is that it will alleviate the rate of inflation and bring down interest rates. Everyone knows that each recession in our history has led to a bull market...so the bulls say "bring on the recession". A study of the relationship between the beginning of recessions since 1900 and the bull markets of those periods produces some sobering statistics. First of all, it has been our view that the low of this market cycle has not been seen. If the March 1978 lows of the Dow Jones Industrial Average or the other major averages were indeed the final low of this cycle, the 1978 low would have preceded the start of a recession by at least 12 months if a recession began today. The attached table shows that only twice in the seventeen recessions of this century has the market bottomed before the beginning of a recession. These exceptions occurred in 1926 when the market bottomed seven months before the recession and in 1945 when the market reached its low three months before the event. I gather some economists question the official view that a recession did occur in 1945, but, for the purpose of our table, it is listed as a recession year. Therefore, if March 1978 was the low, it developed at least twelve months prior to the start of a recession and thus would be (1) only the third time in eighteen recessions this occurred, (2) the first time since the end of World War II, and (3) it would be the longest dis- counting of the start of a recession in this century by at least five months. (The longest lead-time to date was the seven months of 1926.)

What has happened if you bought three months before the start of a recession? A comparison of columns on the left side of the table would imply you lost money. There have been only four occasions in the seventeen recessions that the Dow Jones Industrials moved up by more than a point between the period three months before the recession and its actual beginning (1902, 1918, 1929, and 1945). What has happened if you bought three months before and held on until you were three months into the recession? This strategy has been profitable only three times in the seventeen recessions and in one of these cycles your gain was one point (1918, 1945, and 1953). Now you have the answer . ..you buy when the recession starts (if you can guess right) and hold on for six months into the recession. Sorry old boy! . ..this strategy has produced only four profitable periods out of seventeen when the Dow moved higher by at least a point and one of them was again in 1945 which economists question as a true recession. (1918, 1926, 1945, and 1953)

-65-

The question remains: "When do you buy?" The column on the right side of the table indicates the lag time between the start of each recession and the eventual stock market low. The average lag time for the seventeen recessions was 7.6 months. Since the end of World War II the average lag time has been 5.8 months. Perhaps of greater significance is the average decline of the Dow Jones Industrial Average from the start of a recession to the eventual market low. In the table I measured the Dow for a fixed period of six months after the start of recession, but the time span of the actual low varied a good deal. For the seventeen recessions the average decline from the start of the recession to the actual low in the Dow Jones Industrials was 20.7%. If the year 1929 was excluded to present a more normal series, the average decline from the start of the recession to the eventual low in the Dow Jones Industrials was 16.5%.

Sources for attached Table:

The Dow Jones Averages 1885-1970 Ed. byM=e L. Farrell, Dow Jones Books

Business Conditions Digest U. S. Department of Commerce - June 1978

Note: Dow Jones Industrial prices are last trading day of month except for actual low column on right side.

March 9, 1979

Originally published at Morgan Stanley & Co., Incorporated

Reprinted with permission.

-66-

DJI THREE MONTHS BEFORE MONTH

START OF RECESSION RECESSION BEGAN

64.31

90.54

99.07

90.71

78.08

118.92

103.90

160.47

297.41

187.30

147.33

181.71

274.75

504.93

622.62

813.09

887.57

Sept.1902

May 1907

Jan. 1910

Jan. 1913

Aug. 1918

Jan. 1920

May 1923

Oct. 1926

Aug. 1929

May 1937

Feb. 1945

Nov. 1948

July 1953

Aug. 1957

Apr. 1960

Dec. 1969

Nov. 1973

17 RECESSIONS Since 1900

6 RECESSIONS Since 1946

DJI AT START OF

RECESSION

66.15

78.10

91.91

83.72

82.84

103.82

97.53

150.38

380.33

174.71

160.40

171.20

275.38

484.35

601.70

800.36

822.25

TIME SPAN DJI DJI SIX BET\JEEN

THREE MONTHS MONTHS AFTER START OF ACTUAL AFTER START START RECESSION AND DJI OF RECESSION RECESSION MARKET LOW LOW

64.29 63.64

72.28 58.41

86.20 76.48

78.54 78.48

81.13 84.81

93.54 86.85

93.46 92.34

156.41 164.21

238.95 271.11

177.41 123.48

168.30 174.29

173.06 171.53

275.81 292.39

449.87 439.92

616.73 580.36

785.57 683.53

860.53 802.17

+ 14 Months 42.15

+ 5 Months 53.00

+ 6 Months 73.62

+ 5 Months 72.11

+ 6 Months 79.15

+ 19 Months 63.90

+ 5 Months 85.76

- 7 Months 135.20

+ 35 Months 41.22

+ 10 Months 98.95

- 3 Months 145.60

+ 7+'Months 161.60

+ 2 Months 255.49

+ 2 Months 419.79

+ 6 Months 566.05

+ 5 Months 631.16

+ 13 Months 577.60

AVERAGE + 7.6 MONTHS

AVERAGE + 5.8 MONTHS

journal of technical analysis (jota). issue 05 (1979, may)

Economy & Finance

mta journal

new editor

ongoing journal effort

new jersey associate

state street boston

issue of concern

pine street new york

mcavity john mcginley