journal of technical analysis (jota). issue 27 (1987, may)

MARKET TECHNICIANS ASSOCIATION

JO Issue 27

URNA May 1987

i!l?umP !lTunuIcIAnzs xxmA!rIm a7wmAL Issue 27 May 1987

RiitXX: Henry 0. Pruden, Ph.D. Adjunct Professor Golden Gate University San Francisco, CA 94105

t&itmmriptm: Arthur T. Dietz, Ph.D. Professor of Finance Graduate School of Business Administration, -2-y University Atlanta, Georgia

h-ederick Dickson Portfolio Manager Millburn Corporation New York, New York

Richard Orr, Ph.D. Vice President for Research John Gutmn Investment arpration New Britian, Connecticut

David Upshaw, C.F.A. Director of Portfolio Strategy Research Waddell and Reed Investment Management Kansas City, Missouri

Anthony W. Tabell Technical Analyst Delafield, Harvey, Tabell Princeton, New Jersey

Robert T. Wood, Ph.D. Associate Professor of Finance Pennsylvania State University State College, Pennsylvania

PKiZlter: Golden Gate University 536 Mission Street San Francisco, CA 94105

Market Teihnicians Association 70 Pine Street New Yo>k, New York 10005

1

KA Jv 1987

Ml'A OFFICEl?SAND~Il'I!EE~IRP~S. . . . . . . .

MEMBERSHIP AND SUBSCRIBERIWRMATION. . . . . . . . .

S!PYLESHEETE0RSVBMISSICi'JOFARI'I~. . . . . . . .

ARIXLES:

UNLOCKING THE MYSTERIES OF THREE SHO- INDIcxmRs Loren E. Flath and Joseph F. Kalish . . . . . . .

THE IMPAC'TOF!l!HEcRB INDEXONEIWIAL-S John J. Murphy. . . . . . . . . . . . . . . . . .

PROGRAM TRADING: A TIMEFoREaCTS JackSchmger . . . . . . . . . . . . . . . . . .

'IZliNICAL AIDS FOR ACTIVE PO-LIO MNA- Frederic H. Dickson . . . . . . . . . . . . . . .

i%RKEl' VOLATILITY: AN UPDATED SlWDY Iaszlo Birinyi, Jr. and H. Nicolas Hanson, Ph.D..

!m.xHNIcxL ANALYSIS: INSTITVTIOML TR?DIEK; ANDMON?iYELOWS Laszlo Birinyi, Jr. and Susan L. Field. . . . . .

EXPXTATIONS 1987: TRlWD & CYCLE IanS.Notley..................

TZHNICAL ANALYSIS OF THE FIXED-INCOME tW?KElS Steven Blitz. . . . . . . . . . . . . . . . . . .

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28

41

51

69

83

96

115

m.n iromN&w 1987

h’esident Gail M. Dudack S.G. Warburg 212/415-1869

VicxPresident-LmgRangePlanning Viu2President-Seminar Robert J. Sinpkins, Jr. David Krell Delafield, Harvey, Tabell New York Stock Exchange 609/987-2300 212/656-2865

Reasurer Cheryl Stafford Wellington Management 617/227-9500

-w Philip J. Roth E.F. Hutton 212/969-4501

Conmittee Chairpersons

Steven Shobin Merrill Lynch 212/637-2468

Nmsletter Robert Prechter New Classics Library 404/536-0309

J0UtTB.l Dr. Henry 0. Pruden P.O. Box 1348 415/459-1319

Accreditation Charles Comer Mosley Securities 212/558-0273

Donald Kimsey Dean Witter Reynolds 212/524-3516

mucatim Frederic H. Dickson Millburn Corporation 212/398-8489

Placemmt Anthony W. Tabell Delafield, Harvey, Tabell 609/987-2300

Ethics and s- Donald E. Benson Endowment Mgt. & Research 6171357-8480

Library Dennis Jarrett KidderPeabody & Co. 212/510-3751

-m~special~-~ John McGinley, Jr. Technical Trends Inc. 203/762-0229

mturesspecialInterest~ Bruce Kamisch MCM, Inc. 212/509-5800

KCA JOUMU&M 1987

ELIGIBILITY: REGULAR MEMBERSHIP is available to applicants "whose total professional efforts are spent practicing financial technical analysis which results in an identifiable research product that is either made available to the investing public or beclomes a primary input into an active portfolio management process. W (From revised Constitution)

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4 m-1987

MTA Editorial Policy

Zhe MARKET lEliNICIAKs ASX3ATXN JUllWAL is published by the Market Tech- nicians Association, 70 Pine Street, New York, New York 10005 to promote the investigation and analysis of price and volume activities of the world's financial markets. The MTA Journal is distributed to individuals (both academic and practitioner) and libraries in the United States, Canada, Europe and several other countries. The Journal is copyrighted by the Market Technicians Association and registered with the Library of Congress. All rights are reserved. Piublication dates are February, May, and mvember.

Style for the Mw JoumaZ

All papers submitted to the MTA Journal are reguested to have the following items as prerequisites to consideration for publication:

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

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

3. Paper should be submitted typewritten, double-spaced in completed form on 8 l/2 by 11 inch paper. If both sides are used, care should be taken to use sufficiently heavy paper to avoid reverse side images. Footnotes and references should be put at the end of the article.

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Mail your manuscripts to Henry 0. Pruden, Ph.D., Editor, MTA JOURNAL, P.O. Box 1348, Ross, California 94957.

by Ioren E. Flath and Joseph F. Kalish

This paper was originally prepared for a wxkshop a~ short-term indicators cmducted by Ned Davis at the 1987 annual Ml?A Seminar.

Sentiment indicators, overbought/oversold oscillators, and trend detec- tors are allpartof the serious market technician's arsenal of tools for gauging the short-term outlook. Since every bullmarkethasitscorrec- tions, just as every bear market has its rallies, it is comforting to know that a diverse bag of short-term indicators is available to help the analyst make the right decisions. This paper is intended to test one representative short-term indicator from each of the following categories: sentiment, overbought/oversold, ard trend-following. Since all of these indicators are easily misinterpreted, we present a simple method that will help to clarify what they are telling us. The results are surprising.

In general, sentiment indicators measure swings in investor psychology, whereas overbought/oversold indicators measure whether the market itself has moved too far too fast in either direction. We like to call sentiment and overbought/oversold indicators "should be" indicators; when an extreme is reached, the market "should be" poised for a reversal. Trend-following indicators, on the other hand, confirm what has already happened -- the direction of the trend. Trend indicators follow turns in the market like a caboose following a train through the n-ountains.

All three types of indicators have their share of problems. Trend- following indicators can produce whipsaws and are notoriously late whereas sentiment and overbought/oversold indicators tend to get one in and out early on big moves. Consequently, traders who have religiously adhered to signals from "should be" indicators, have probably been burned more than once, but a few burns doesn't necessarily mean that these indicators "should be" removed from the recipe. The prudent market technician should of course use these indicators in combination with other timing-tools so that the overall blend is properly seasoned.

As with most indicators that measure extremes, one needs to find what levels a particular indicator must reach in order to define an extreme. A standard method for doing this is to compute the mean (or average) and standard deviation of the data series of interest and to define the upper extreme (or bracket) as the mean plus the standard deviation, and the lower extreme (or bracket) as the mean minus the standard deviation. (The standard deviation is a measure of dispersion about the mean. One standard deviation on each side of the mean encompasses about 67% of the observations in a normal distribution.) Presumably, anything outside of these brackets

6

represents true nonconformity thereby setting the stage for the decision making process.

Many technicians change the extremes in their sentiment and overbought/ oversold indicators as often as they change their shorts. This is the major problem we find with "should be" indicators; they seem to work differently under different market conditions. Ignoring markets that go nowhere, we can safely say that there are two basic kinds of markets: bull markets and bear markets. In the case of sentiment ard overbought/oversold indicators, extreme levels of bullishness or bearishness will differ over the short-term, based on whether the overall environment is bullish or bearish. When the primary trend is up, it should take very high levels of optimism (or an extreme overbought market condition) to generate a sell signal an3 only moderately low levels of pessimism (or a moderately oversold condition) to generate a buy signal. Conversely, under bear market circumstances, extremely low levels of optimism (or a mildly overbought market) should be needed to generate a sell and very high levels of pessimism (or an extremely oversold market) to produce a buy.

We can examine trend-following methods in the same light as sentiment indicators and overbought/oversold oscillators. If a bull market is underway, a slight improvement in trend should generate a buy, while a much greater downside move should generatea sell. When the primary trend is down, the opposite situation would apply: a small downside move should generate a sell signal and a more substantial increase in trerd should produce a buy.

Four main data series were used in the study. We used the Advisory Service data from Investors Intelligence to develop the sentiment indicator. Overbought/oversold data, also from Investors Intelligence, consisted of the percentage of stocks on the NYSE above their lo-week moving average. Trend- following methods were applied to the Value Line Composite Index. 'Lb define the background environment, a 26-week rate-of-change in the S&P Short-Term Government Bond Index was used. It has an excellent correlation with the primary trend. When short-term government bond momentum was above 2.9%, the monetary environment was defined as positive (probable bull market), and when this momentum fell below -0.3%, the monetary environment was define3 as negative (probable bear market). When the 26-week change in short-term government bonds was between -0.3% and 2.9%, the previous valid condition was assumed (Chart 1).

KI!AJoOMb#M I387 7

aart 1.

Value Line Comoos i te Wkly Data J/c)49 - 2/28/8? (Log Scale)

256 222

7 1¶3 i

168 . 146 - 127 - 110 - 96 -

Y3 .

f i

h ? ’ i

i

256 222 193 169 146 127 110 96

J 83 - 73

63 - i -I B . - 63 5s - - 5s 49 . - 41 - ?

49 - 41

i

IS

12 BullIth Environamt

9

6

3

0

-3

-6

-9

-12 Soar 4th Gwl ronamt

T!YL ~~~~

- 1s

I - 12

9

6

3

m-1 26 Week Rate Of Change In Short-Term Government Bond Momentum

WAWM!IE'RIEIN)1QIm-- IND1cxmRs1QimIs

All analyses were backtested on a weekly closing basis from l/3/69 to 2/20/87. Tb test the indicators, a variety of trading measures were evaluated. These included gain per winning trade, loss per losing trade, average gain per trade, growth of an original $10,000 investment, and gain per annum. Extremes in the sentiment ati overbought/oversold indicators were established, and the Value Line Composite was bought, sold, and sld short when the indicators reached these brackets. Based onboth long and short positions, the results of each trade from an original $10,000 hypothetical investment were continuously reinvested. For example, when sentiment reached or exceeded abearish extreme, a short position was covered and a long position initiated. When sentiment reached or exceeded the opposite extreme, the long position was closed and a short position initiated. All open positions were closed on 2/20/87 so that the results could be included in the statistics. The trend analyses differed from the bracket analyses only in the way signals were generated. "Slope signals" were produced when the Value Line Composite moved up from a bottom by a specific percentage (buy) or down from a top by a specific percentage (sell).

I

8 HA DJRN?WN 1987

All analyses and graphics were done cn a Hewlett-Packard 320 technical workstation using TECHNALYZER, a software package designed for, and used ex- clusively by, Ned Davis Research, Inc.

Four strategies were evaluated ti test the sentiment and overbought/ oversold indicators. The first two evaluated extremes in terms of fixed brackets over the entire time period while the last two employed variable brackets. In strategy one, we used the mean plus or minus one standard deviation to define the two extremes. Strategy two was a fine-tuning of the brackets determined in strategy one. Rather than employing fixed brackets over the entire time period in strategies three and four, the brackets were shifted based on the nature of the monetary environment as defined above. When the monetary background was positive, the brackets were shifted in ane direction, and when it turned negative, they were shifted in the opposite direction. Strategy three, analogous to strategy one, used a separate mean and standard deviation for each of the two environments. The fourth and final strategy was a fine-tuning of strategy three.

Three basic strategies were used to evaluate our trend-following method. Strategy one used a fixed percentage move in the Value Line Compo- site togenerate both buy and sell signals. The second strategy explored the possibilities of using a different percent move to generate a buy other than that used to givea sell. These first two strategies were performed under all market conditions while the third strategy used the monetary background to fine-tune strategy two.

A favorite indicator among technicians is derived by dividing the number of advisory services that are outright bullish by the sum of those bullish services plus the outright bearish services -- Bulls/(Bulls +Bears). This covers the senrices that have a definite opinion m the stock market. The theory holds that when this ratio is high, indicating the majority of advisors to be bullish (so-called euphoric optimism), it's time to sell. A low ratio indicates that optimists are too few in number among the experts, implying that it's time to buy.

Table 1 below summarizes the various statistics for this indicator over all time periods included in the study, as well as under different monetary circumstances. The mean differs according to conditions: under positive monetary conditions, the mean is shifted up, whereas under negative monetary circumstances the mean is shifted down. This shifting of means involves a shift in the corresponding brackets as defined by the standard deviations, and they are in the directions that we would expect based cn the Mture of the indicator.

Table 1. Basic statistics on Bulls/(Bulls + Bears) for the period l/3/69 to 2/20/87. ALL TIME PERIODS refers to all data. MONETARY POSITIVE refers to Bulls/(Bulls + Bears) only during periods in which weekly S&P Short-Term Government Bard momentum was above 2.9%. MONETARY NEGATIVE refers to Bulls/(Bulls + Bears) only during periods in which Short-Term Government Bonj momentum was below -.3%.

BULlX/(BUIU+BEARS) N MEAN-SD MEAN+SD

ALL TIME PERIODS 947 57.9 41.8 74.1 MONEZARY POSITIVE 357 65.5 51.3 79.6 MXEXARYNIZATIVE 590 53.4 37.8 69.0

The results of the four strategies using Bulls/(Bulls+Bears) are sum- marized in Table 2 an3 the signals for the best and worst of the four strategies are presented in Appendix Tables 1 and 2, and Charts 2 and 3. Our first strategy, the worst of the four, had a total of 10 trades with an average loss per trade of 0.8% and a negative gain per annum. Our original $10,000 tumbled to $4,840. Although the system worked adequately for the buys in 1977, 1978 and 1984 and for the sells in 1971, 1978 and 1983, the mistakes were indeed disastrous, the most notable being the short signal in 1984. In fine-tuning this strategy as best we could, strategy number two managed to run $10,000 up to $14,329 for a 2% gain per annum which brought us even with a buy-and-hold stragegy. Not much help. Adjusting the indicator brackets for the monetary environment produced results a little more palatable. In strategy three, which used brackets based cn the mean plus or minus one standard deviation of Bulls/(Bulls+Bears) for ea& of the two monetary conditions, our $10,000 grew to $33,462, a 7% gain per annum in 14 trades. Only one trade, a buy in 1969, proved to be a disaster.

Table 2. Results for four strategies based a-~ extremes in Bulls / (Bulls+ Bears) for the period l/3/69 to 2/20/87. All results are based on buying and selling thevalue Line Composite on a weekly basis. Buy and hold for the Value Line Composite was 2% per annum. Brackets represent buying and selling points respectively. Strategies three and four include two sets of brackets: pluses refer to brackets used under positive monetary conditions and minuses refer to brackets used under negative monetary conditions. See text for descriptiorr; of strategies.

10

Value Line Composite Qrart 2. kkly Data 1mm - zmfe7 (Log Scale)

257 .- - 257 230 - - 238 207 - Buy &en Bullr~(Bullr + Bears) ( 41.B - 207

Sell When Bullt/(Bullr + Bears) ) 74.1 - 186

- 167

- 150 - 17s

- 121 - 109 - 98 - 08 - 79

71 - - 71

63 - - 63 57 - - 57 51 - - 51

m-2 Bulls/(Bulls+Bears~ - Strategy 1 J

Value Line Compcsite 2/28/87 (Lo6 6cal.I

I - 3. lhkly Data VW69 -

t : -1 263 263 253

i tlonrtrry Potlttvr

227 Buy lYlrn Bul ls/(Bullr + bars

203 se1 1 Hhen Bui Ir~(Bullt l Bears ? - - 283 181 1

- 162 - 14s - 138 - 116 - 104 - 93 - 83 - 74

Monetary Noart IV. l 66 Buy Hhen Bullr~(Bullr + &art) < 32 - 59 kll Hhn &Ilt~(Bullr + Bmrrt)S 56 - 53

‘1 4e

181 162 14s 130 116 104

93 83 - 74 - 66 -

ii - 48 -

42 - 42

40 :...I i . . . . . . . . . A?!#.: l-f :.; L.?. jL..+..-; ‘8-y L..-...

70

Bullfrh

m-3 Bui ls/(Bul Is+Bears) - Strategy 4 J

KI% JalFWL&= 1987 11

The best of our four strategies was strategy four, the fine-tuned version of strategy three (Chart 3). In this case, our $10,000 became $171,290 for a whopping gain per annum of 16.9%. The most notable difference between this strategy and the rest was in the total number of trades: 27. Although the trades increased significantly, the gain per trade also increased, from the 11.5% of strategy three to 12.3% (Appendix Table 2). The number of trades for this strategy might be too few to categorize this indicator as short-term, but it still managed to identify a few good short- to intermediate-term moves, especially the short-term action in 1969 and the more intermediate-term action in the 1978 to 1981 period.

Our next indicator was the percentage of stocks cn the NYSE above their lo-week moving average. As with the advisory service sentiment, shifts in the means and standard deviations occurred under different monetary back- grounds (Table 3). Performance of this indicator was also dramatically improved by adjusting it for monetary conditions (Table 4).

12

Table 3. Basic statistics on the lo-week overbought/oversold oscillator for the period l/3/69 to 2/20/87. ALL TIME PERIODS refers to all data. MONE- TARY POSITIVE refers to overbought/oversold only during periods in which weekly S&P Short-Term Government Bond momentum was above 2.9%. MONETARY NZATIVE refers to overbought/oversold only during periods in which Short- Term Government Bond manentum was below -.3%.

OVERE?OUGHT/OVEZGOLD N MEAN-SD MEAN+SD

ALL TIME PERIODS 947 50.5 26.6 74.5 MONETARY POSITIVE 357 63.2 43.2 83.1 MON?Tl'ARY NEGATIVE 590 42.9 20.1 65.8

Strategy one produced dismal results. Although over half of the trades were profitable, the $10,000 dwindled to $1,602 (Appendix Table 3). Strat- egy two was equally unimpressive. These two strategies clearly reveal the problems with using fixed levels for an overbought/oversold indicator in all types of markets. In this case, we found that both strategies got us into bear markets and out of bull markets too early. In particular, this indicator was too early in the 1969-1970 bear market and flashed a sell signal too quickly during the ensuing rise. Similar behavior was noted in the 1974-75 period. The bull markets of 1980, 1982, and the powerful rise in 1985, also lead to premature sell signals (Chart 4). With strategies three and four, the indicator brackets were adjusted for monetary conditions. Strategy three, an improvement over the first two, still showed significant losses, so it was not much help either (Table 4).

Table 4. Results for four strategies based on overbought/oversold extremes for the period l/3/69 to 2/20/87. All results are based an buying and selling the Value Line Composite on a weekly basis. Buy and hold for the Value Line Composite was 2% per annum. Brackets represent buying and selling points respectively. Strategies three and four include two sets of brackets: pluses refer to brackets and used under positive monetary conditions and minuses refer to brackets used under negative monetary conditions. See text for descriptions of strategies.

13 MI’A JCXBM&AY 1987

chartI. Meekly Data l/03/69 - 2/2g/g7 (Log Scale)

Value Line Composite r I a ,

230 ilsI I -

208 188

- f -

170

S 154 -

:+-+4

I)

139 126k -I?*

93 I I 94 V” =

76

- 139 - 126

- 114

- 103

- 93

- 94

- 76 , 69

62

56

51

90 - - 90

e0 - - 80

70 - - 70

60 - - 60

50 - - 50

40 - - 40

30 - - 30

20 -

10 -

m-4 % Of Stocks Above Ten Heck Moving Average - Strategy 1

chart 5. Herkly Oata VW69 - 2/2Wg7 (Log Scale)

Value Line Composite

270 - 270 Hrmctary Positive

' When % Of Stocks Rbove 10 Week t!R ( 52 d - 242

-I 218

60 Plonet rry Negat i ve - - 60 54 Buy idhen X Of Stocks Above 9 - - 49

!&II When X Of Stocks Above 10 Ckek r(A 94

) 52 - - 49

43 - t - 43

- 19s - 176 - 158 - 142 - 127 - 114 .--

m-5 Y Of Stocks Flbove Ten E,-ck Moving Average - Strategy 4

MTA JOURNAL/MAY 1987

Faced with such disappointing results , we were about to give up on this indicator. But as with advisory sentiment, we fine-tuned strategy three and uncovered a bonanza. We turned a losing indicator into a superb winner; $10,000 would have grown to $105,565 (Chart 5, Appendix Table 4). It is interesting to note how the character of this indicator changes after taking the monetary environment into consideration. By coincidence, the lower (buy) bracket in the positive monetary environment doubles as the upper (sell) bracket in a negative monetary environment. In other words, we would buy when this indicator dropped below 52 (moderately oversold) in a positive environment, and sell when it climbed above 52 (moderately overbought) in a negative environment.

Closer inspection of the problems in the previously troublesome periods shows impressive improvement (Chart 5). A buy signal was flashed right before the bottom of the 1969-1970 bear market. We still got out too quickly in 1970, but with short-term government bond momemtum improving, we got back in right after the first correction. In 1974, we again got out too soon, but with the monetaryadjustmentquickly reversed our positon. The 1980 sell signal was delayed by several months. Finally, the action in 1982 almost identical to 1974.

We have seen how two indicators have been dramatically improved by adjusting for monetary conditions. Now let's turn to our old friend, the trend, our third and final indicator, to see if it can use any help. It has long been our philosophy to stay in harmony with the major trend.

One simple method of determining the trend is to take a fixed percentage move from a high or low on an index like the Value Line Composite. We call this technique taking the slope of an index.) For example, one popular heuristic with the Value Line Composite is to take a 4% slope. In other words, one would buy stocks (or go along the Value Line) when the index increased by 4% from its most recent low. Conversely, one would sell stocks (or short the Value Line) when it decreased by 4% from its most recent high.

Our analysis revealed that a 3.6% slope was optimum. This would have produced a tremendous gain of over 16% per annum compared to only 2% for a buy-and-hold strategy (see Table 5 and Chart 6). Although almost half of the trades would have been losers, $10,000 would have ballooned to over $150,000. We still are amazed that such a simple indicator could produce these spectacular gains (Appendix Table 5).

Of course, in our constant quest for even better indicators, we did not stop there. Using a fixed percentage for the upside and the downside seemed somewhat naive since bear markets tend to unfold much more quickly. We therefore tested different percentage thresholds for the upside and the downside. Also, we decided that a move less than 1% was unrealistic for the average investor's participation , so we limited ourselves to movements of 1% or more. Our analysis showed that a 1% slope from a top and a 2.9% slope

15 Ml74 JouHEE&M 1987

16

Value Line Composite Chnrt 6. Weekly Data l/83/69 - 2/28/W (Log Scale)

262 S

- Buy When Value Line Rises By 3.6%

- 262

243 - Sell When Value Line Falls By 3.6% - 243

225 '

L

- 225

208 208

193

179

I

1

193

179

166 1 1

i

166

153 t 153

142 - - 142

132 - - 132

122 - - 122

113 - - 113

105 - - 105

97 - - 97

30 - - 90

63 - - 83

77 - - 77

71 - - 71

66 - ? 66

61 c - 61

57 I - 57

52 t - 52 49 I- - 49

trrrz s z E m-6 s El - ?2 5

E k k z - 5 - s n 5 St - - = f g $ f f g ! j E

Weekly Data lAW69 - 2AXM7 (Log Scrlr)

Value Line Composite Chad 7.

253 - Monetary Positive

234 - Buy When Value Line Rises By 1.5%

Sell When Value Line Falls By 5.0%

216 -

200 -

- 158

- 146

- 13s

- 12s

- 11s

- 187

- 99

- 91

- 64

- 76

- 72

6011 When Value Line Falls By - 62

- 57

- 53

- 49


from a bottom produced good results (Table 5). The gain per annum increased by over 3%, but with more trades, the gain per trade fell. This is a natural trade-off.

Table 5. Results for three strategies based on slope signals i theValue Line Composite for the period l/3/69 to 2/20/87. All results are based on buying and selling the Value Line Composite on a weekly basis. Buy and hold for the Value Line Composite was 2% per annum. Slope parameters represent selling and buying points respectively. Strategy three includes two sets of slope signals: the plus refers to slope signals used under positive monetary conditions and the minus refers to slope signals used under negative monetary conditions. See text for descriptions of strategies.

STRATEGY

TOTAL YlWWIWC tAIY PER LOSS PER AVERAGE SlO,WO WIN PER

SLOPE X TRADES TRADES UINNlNC TRADE LOSING TRADE WIW EECAME AWNW

1 3.6% 89 46 10.5 3.7 3.6 s150,539 16.1

2 1.0/2.9 154 79 7.2 2.7 2.4 S259.749 19.7

3 + 5.0/1.5 95 55 10.7 3.0 4.9 SSn.329 25.6

- 1.0/4.5

With the impressive performance of strategy two, we wondered if we could improve the results by adjusting for monetary conditions. The answer, not surprisingly, was yes (Chart 7). We found that under a positive monetary environment, we needed only a 1.5% move from a bottom to buy but a 5% drop from a top to produce a sell. Under negative monetary conditions, we needed 4.5% from a bottom to buy, yet only 1% from a top to sell. These parameters are intuitively appealing. Underthetheorythatmoney moves markets, we want to enter the market quickly under easy Fed policy and retreat only if something else is drastically affecting the market. Under a restrictive Fed policy, we want to leave the market on any sign of weakness and enter only on extreme strength. These parameters mt only make sense, they work. The gain per annum increased to over 25%, turning $10,000 into $573,329, beating the already spectacular 3.6% simple slope by nearly four times. Although the number of trades nearly matched those of the 3.6% slope, the percent of profitable trades increased from 52% to 58% (see Table 5 and Appendix Table 6).

We started out by testing three short-term indicators in all market conditions and found that only the trend-following indicator can work prof-

17 KAJWRF&WW I987

itably without adjustments. The raw sentiment ard overbought/oversold indicators were failures. By adjusting for the monetary environment we demonstrated that it is possible to switch horses in mid-stream without falling off and being swept downstream. All three of the indicators that we tested showed dramatic improvement when the monetary background was considered.

Like most technicians, we use these indicators in combination with many other indicators relying on a weight-of-the-evidence approach. We would never make decisions based strictly on sentiment and overbought/oversold readings without confirmation from other key indicators. Thus, the problems with using these indicators muld be minimized.

As favorable as the results were, there maybe room for improvement. For instance, we may have paid a penalty for using weekly data. Since moves of 1% or more are commonplace in today's volatile market environment, the indicators may react too slowly to important moves starting at the beginning of a week. Using daily data might alleviate this problem.

Defining the background differently is another potential source for improvement. We used a simple 26-week rate-of-change of the Short-term Gov- ernment Bonds for our background, but just as easily could have used the yield curve, inflation, or some other more complex standard. We chose what we regarded as representative measures of the sentiment and overbought/oversold techniques. Different indicators from these areas may well work better, while others will not work as well.

Finally, let's not lose sight of the main point that the importance of using these indicators is whether or not they are telling us something: Is sentiment at an extreme? Is the market really overbought? Should a 4% drop in the Value Line Composite point toward the door? Clearly, the background environment makes a difference in how these questions are answered. After digesting the results of this 18-year study, these questions may be more easily answered, and decisions based QI these indicators may be less costly and more profitable.

Appendix Tables. The following tables summarize selected strategies for the three indicators tested. ‘lo fully understand the tables, two points need to be made. First, although we kept the date range consistent for all indicators, not all strategies produced signals on l/3/69. Hence, in several cases, the number of days used to calculate the gain per annum for one strategy may be different than the time used for a comparable strategy. Buy-and-hold was consistently calculated from l/3/69. The second point is that in each strategy, the last trade was closed although the verdict was not in. This was done to facilitate comparisonof the various indicators and techniques.

18

Appendix Table 1. Signal analysis for Bulls/(Bulls + Bears) using fixed brackets set at plus and minus one standard deviation (strategy one). This was the mrst of the four sentiment strategies.

&IRKET: Value Line Composite SIGNkLS : Bulls/Bulls+Bears Strat tl FRICTION: 0 Percent MARGIJ.': 100 Percent DATES: l/03/69 through 2/20/87 (Weekly)

ACTIOh' DATE

Long 3/07/69 Sh& ljOlj71 Low 6/08/73 Short 2;21;75 L0r.g 10/28/77 Short E/18/78 Long 11/03/78 Shcrt 2/25/83 Long 4/13/84 Short 11/16/84

PRICE

165.69 103.60

84.88 64.79 88.09

116.06 98.87

173.89 178.35 178.01

LOJ<G LOSSES GA’NS . Net

SHOR? LOSSES GAINS Net

TOTALS WSSES GAINS Net

Total Number Profit/ Number Profit/ Profit Trades Trade Days Annum

-61.33 3 -20.44 107.63 2 53.81

46.30 5 9.26 3374 1.07

-86.69 3 -28.90 32.88 2 16.44

-53.81 5 -10.76

-148.02 6 -24.67 140.51 4 35.13

-7.51 10 -.75

ACTION DATE

Sell l/01/71 Cover 6/08/73 Sell 2/21/75 Cover 10/28/77 Sell E/18/78 Cover 11/03/78 Sell 2/25/83 Cover 4/13/84 Sell 11/16/84 Cover z/20/87

PRICE PROFIT% DAYS s10,000

103.60 -37.47 665 6,253 84.88 18.07 889 7,382 64.79 -23.67 623 5,635 88.09 -35.96 980 3,609

116.06 31.75 294 4,754 98.87 14.81 77 5,459

173.89 75.88 1575 9,600 178.35 -2.56 413 9,354 178.01 -.19 217 9,336 263.74 -48.16 826 4,840

3185 -9.02

6559 -3.96

SUMMARY OF CLOSED TRADES

Profitable Trades: 40% ( 4 out of 10 )

(\Cain/%Gain+%Loss (48.78) SGain/SGain+SLoss (36.74) SGain/Loss (.6))

RESULTS OF ALL TRADES

510,000 became S4,840 in 6559 days (17.97 years). -4% per annum compounded annually.

BUY/HOLD is 2% per annum compounded annually for 6622 days (18.14 years).

19

I'flR JOCIFW@W 1987

20

Appendix Table 2. Signal analysis for Bulls/(Bulls + Bears) using fine- tuned brackets adjusted for the monetary background (strategy four). This was the best of the four sentiment strategies.

UARKET: Value Lint Compotite SIGNAL.!? : Bull*/Bulls+Beart Strat (4 FRICTION: 0 Ptrctnt XARGIN: 100 Ptrctnt DATES: l/03/69 through 2/20/87 (Weakly)

ACTION DATE PRICE ACTION DATE PRICE PROFIT% DAYS $10,000

Short l/03/69 Long 3/07/69 Sho;t 5)lS)SO Long 7/11/69 Short 10/31/69 Long 5;01/70 Short g/25/70 Long 2;01;74 Short 3/22/74 Long 6/28/74 Sho;t 11;15/74 Lms 12/13/74 Short 6j27;75 Long l/27/78 Short 6/16/78 Long 11/03/78 Short 3/30/79 Long 6)22;79 Short l/18/80 Long 3;14;80 Short 4/03/81 Long g/11/81 Short 6/03/83 Long g/26/85 Short 3/14/86 Lang g/26/86 Short l/23/87

LONG LOSSES GAINS Net

SHORT LOSSES GAINS Net

TOTALS LASSES GAINS Net

183.67 COVtr 165.69 Sell 171.82 COVtr 146.75 Sell 147.27 Cover 105.93 se11 loo. 97 Cover 79.31 SC11 81.29 COVtr 64.58 Sell 55.30 Cover 48.50 Sell 77.77 Cover 89.55 Sell

107.11 Cover 98.87 Sell

109.46 Cover 114.14 Sell 127.09 Cover 114.41 Sell 155.12 COVtr 137.33 Sell 200.69 Cover 189.04 Sell 238.92 Cover 222.86 Sell 247.32 COVtr

Total Number Profit/ Profit Trades Trade

-19.05 2 -9.53 227.65 11 20.70 208.60 13 16.05

-26.06 3 -8.69 148.42 11 13.49 122.36 14 8.74

-45.11 376.07 330.96 27

3/07/69 S/16/69 7/11/69

10/31/69 s/01/70 g/25/70 2/01/74 3/22/74 6/28/74

11/15/74 12/13/74 6/27/75 l/27/78 6/16/78

11/03/78 3/30/79 6/22/79 l/18/80 3/14/80 J/03/81 g/11/81 6/03/83 O/26/85 3/14/86 g/26/86 l/23/87 2/20/87

-9.02 17.09 12.26

165.69 9.79 171.82 3.70 146.75 14.59 147.27 .35 105.93 28.07 100.97 -4.68 79.31 21.45 81.29 2.50 64.58 20.56 55.30 -14.37 48.50 12.30 77.77 60.35 89.55 -15.15

107.11 19.61 98.87 7.69

109.46 10.71 114.14 -4.28 127.09 11.35 114.41 9.98 155.12 35.58 137.33 11.47 200.69 46.14 189.04 5.80 238.92 26.39 222.86 6.72 247.32 10.98 263.74 -6.64

63 70 56

112 182 147

1225 49

1:: 28

196 945 140 140 147 84

210 56

385 161 630 846 169 196 119 28

Numbor Profit/ Dayo Annum

2514 28.81

4108 10.24

6622 16.95

SUWARY OF CLC)SED TRADES

Profitable Trades: 81% ( 22 out of 27 )

(%Gain/%Gain+%Loss (89.38) $Gain/SGain+SIaas (88.68)


SlO,OOO became $171,312 in 6622 days (18.14 years). 174 per annum compounded annually.

10,979 11,385 13,046 13;093 16,768 15; 983 19,411 19,896 23,986 20,539 23,064 36,984 31,382 37,536 40,423 44,753 42,840 47,700 52,459 71,126 79,283

115,861 122,587 154,933 165,347 183,495 171,312

SGafn/Lors (7.7))

BUY/HOLD is 28 per annum compounded tnnually for 6622 days (18.14 yearr).

Appendix Table 3. Signal analysis for the percentage of stocks above their lo-week moving average usi@ fixed brackets set at plus and minus one standard deviation (strategy one). This was the worst of the four overbought/ oversold strategies.

MARKET: Valu. Line composite SIGNALS: \ Stka >lO UK UA Strat 1 FRICTION : 0 Percent MRCIN: 100 Percent DATES : l/03/69 through Z/20/87 (Weekly)

ACTION DATE PRICE AmION DATE PRICE PROFITI DAYS 510,000

Short tin9 Short Long Short Long Short I.-3 Short L=v Short L-4 Short Long Short Low Short Long Short L-3 Short Long Short Long Short Long Short Leng Shcrt Long Short Long Short bw Short L-4 Short Long Short Law Short Long Short

l/03/69 2/14/69

11/21/69 12/26/69

9/25/70 6/11/71 3/0?/72 a/04/72

12/06/?2 l/26/73 ?/27/73

11/09/?3 l/25/74 4/12/74 l/17/75 0/08/75 l/09/76 4/16/76 l/16/76

10/21/?7 11/25/77

l/13/78 4/21/?0

10;20;?6 l/12/79 5;la;79 e/10/79

10/12/79 12/14/79

j/07/80 5/23/80

12/12/60 3/27/01 ?/24/81 4/30/02 s/04/62 e/27/82 s/12/83 o/17/04 9/20/85

Il/l5/85 g/19/86 l/16/8?

183.67 Cover 2/14/69 178.83 2.64 178.83 Sell 11/21/69 139.95 -21.74 139.95 Cover 12/26/69 130.49 6.76 130.49 Sell 9/25/?0 100.97 -22.62 100.97 Cover 6/11/71 118.91 -17.77 118.91 Sell l/07/72 116.39 -2.13 116.39 Cover 0/04/72 114.04 2.01 114.04 so11 12/08/72 117.99 3.39 117.89 Cover l/26/73 109.02 7.52 109.02 Sell' 7/27/73 90.08 -17.37

90.08 Cover 11/09/73 87.46 2.91 87.46 SO11 l/25/74 79.67 -8.91 79.67 Cover 4/12/74 76.45 4.04 76.45 Sell l/17/75 56.75 -25.77 56.75 Cover 8/08/?5 71.28 -25.60 71.28 Sell l/09/76 75.?0 6.31 75.78 Cover 4/16/76 85.50 -12.83 85.50 Sell l/16/76 89.39 4.55 89.39 Cover 10/21/?7 88.18 1.35 88.18 Sell 11/25/?7 95.21 '1.97 95.21 Cover l/13/78 89.19 6.32 89.19 Sell 4/21/70 100.11 12.24

100.11 Cover 10/20/78 104.80 -4.68 104.80 Sell l/12/79 104.73 -.07 104.73 Cover 5/u/79 108.45 -3.55 108.45 Sell a/10/79 120.22 10.85 120.22 Cover 10/12/79 115.16 4.21 115.16 bell 12/14/?9 121.21 5.25 121.21 Cover 3/07/80 116.58 3.82 116.58 Sell 5/23/60 119.31 2.34 119.31 Cover 12/12/80 137.39 -15.15 237.39 Sell 3/27/81 152.72 11.16 152.72 Cover ?/24/01 149.11 2.36 149.11 Sell 4/30/82 130.44 -12.52 130.44 Cover 6/04/82 122.16 6.35 122.16 Sell 8/27/82 127.77 4.59 127.17 Cover a/32/63 195.40 -52.93 195.40 Sell 1)/3?/84 180.02 -7.87 380.02 Cover 9/20/85 190.79 -5.98 190.79 Sell 11/15/85 204.59 7.23 204.59 Cover 9/19/86 220.89 -?.S? 220.89 Sell l/16/87 247.51 12.05 247.51 Cover 2/20/6? 263.74 -6.56

35 273 259 210 210 126

l'ef 105

77 77

280 203 154

98 91

462 35

:t 182

04 126

84 63 63 84 77

203 105 119 280

35 a4

350 371 399

56 308 119

35

Total Number Prof lt/ Profit Trade6 Trade

IBDNG LQSSLS -119.00 9 -13.22 GAINS 07.94 12 1.33 Net -31.06 21 -1.49

SHORT USSES -153.03 10 -15.30 GAINS 50.30 4.19 Net -102.73 -4.67

TOTALS

IasSES -272.03 19 -14.32 GAINS 138.23 24 5.?6 Net -133.79 43 -3.11

LU?WARY Oi CUSED TRADES

Profitable TrEd.6: 56A ( 24 out of 43 )

Number Profit/

mY6 Annum

3129 -5.43

3493 -13.16

6622 -9.60

(#Gain/8Gain+8Lo66 (33.74) bGEin/$Gain+$Lo66 (27.28) (Gain/Lo66 (.4))


$10,000 became $1,602 in 6622 d6y6 (18.14 yoarc). -9.6b pm 6nnum compounded annually.

BUY/HOLD ic 2\ per annum compounded annually for 6622 days (18.14 years).

KI!A JOURtW&W 1987

10,264 8,032 8,575 6,635 5,456 5,340 5,448 5,631 6,055 5,003 5,149 4,690 4,880 3,622 2,695 2,865 2,497 2,611 2,646 2,857 3,038 3,410 3,250 3,248 3,133 3,473 3,619 3,809 3,955 4,047 3,434 3,817 3,907 3,418 3,635 3,802 1,790 1,649 1,550 1,662 1,530 1,714 1,602

21

22

Appendix Table 4. Signal analysis for the percentage of stocks above their lo-week moving average using fine-tuned brackets adjusted for the monetary background (strategy four). sold strategies.

This was the best of the four overbought/over-

HARKET : Value Line Composite SIGNALS: \ Stks al0 UK M Str6t 4 FRICTION: 0 Percent MARGIN: 100 Percent DATES : l/03/69 through 2/20/87 (Yorkly)

ACTION DA’SE

Short l/03/69 I-9 7/M/69 Short 10/24/69 Ung 5/29/70 Short B/21/70 tin9 11/27/70 Short l/22/71 tin9 6/04/71 Short S/27/71 L-4 12/10/71 Short 12/24/71 L-3 S/25/73 Short 7/20/73 Long 11/23/73 Short l/11/74 Lang 5/24/74 Short 10/18/74 L-3 12/13/74 Short l/31/75 Long 4/11/75 Short 6/27/75 Long 0/22/75 Short IO/l:/75 Long 4/02/76 Short f/09/76 Long 11/19/76 Short 5/20/77 Long 10/27/78 Short l/05/79 L-4 10/26/79 Short 11/30/79 L-9 I/14/00 Shcrt 10/24/SO Long 9/11/81 Short 5/14/82 Ung 7/23/02 Short 10/15/82 tin9 12/23/62 Short 6/03/83 Long 11/23/84

PRICE ACTION DATE PRICE PROFITI DAYS $10,000

183.67 Cover 7/18/69 144.40 21.38 144.40 Sell 10/24/69 140.22 2.65 148.22 Cover 5/29/70 95.36 35.66

95.36 Sell O/21/70 90.07 -5.55 90.07 Cover 11/27/70 94.34 -4.74 94.34 Sell l/22/71 111.13 17.80

111.13 Cover 6/04/71 120.35 -0.30 120.35 se11 S/27/71 116.05 -3.57 116.05 Cover 12/10/71 107.53 7.34 107.53 SO11 12/24/71 110.78 3.02 110.78 Cover 5/25/73 87.21 21.29

87.21 Sell 7/20/73 88.55 1.54 06.55 Cover 11/23/73 78.96 10.83 76.96 Sell l/11/74 76.66 -2.91 76.66 Cover 5/24/74 68.35 10.84 68.35 Sell 10/m/74 56.16 -17.83 56.16 Cover 12/13/74 48.50 13.64 48.50 Sell l/31/75 62.21 26.27 62.21 Cover 4/11/75 67.62 -0.70 67.62 Sell 6/27/75 77.77 15.01 77.77 Cover S/22/75 68.54 11.87 68.54 Sell 10/17/75 69.81 1.85 69.81 Cover 4/02/76 88.02 -26.09 88.02 Sell 7/09/76 89.00 1.11 89.00 Cover U/19/76 85.07 4.42 85.07 se11 5/20/77 93.30 9.67 93.30 Cover 10/27/78 97.44 -4.44 97.44 Sell l/05/79 103.19 5.90

103.19 Cover 10/26/79 109.05 -5.68 109.05 Sell 11/30/79 117.56 7.80 117.56 Cover 3/14/00 114.41 2.68 114.41 Sell 10/24/80 145.35 27.04 145.35 Cover g/11/51 137.33 5.52 137.33 se11 5/14/82 132.14 -3.78 132.14 Cover 7/23/82 122.19 7.53 122.19 Sell 10/15/82 145.33 18.94 145.33 Cover 12/23/62 157.17 -8.15 157.17 se11 s/03/03 200.69 27.69 200.69 Cover 11/23/84 178.77 10.92 178.77 Sell 2/20/87 263.74 47.53

196 98

217 e4 98 56

133 84

105

5::

1% 49

133 147

56 49 70 77 56

1%8 98

133 182 525

2:: 35

105 224 322 245

70 64 69

162 539 819

12,138 12,459 16,903 15,965 15,208 17,915 16,426 15,641 17,004 17,516 21,246 21,572 23,908 23,212 25,720 21,140 24,023 30,814 28,134 32,357 36,197 36,868 27,251 27.554 28,771 31,555 30,154 31,934 30,120 32,471 33,341 42,357 44,694 43,005 46,244 55,001 50,520 64,509 71,555

105,565

ZONG LQSSES GAINS Net

SHORT LOSSES GAINS Net

TOTALS LOSSES GAINS Net

Total Number Profit/ Number Profit/ Profit Trades Trade MY6 &mum

-33.65 215.83 182.16

1: 20

-6.73 14.39

9.11 2689 23.69

-66.08 163.91

97.82

-99.73 379.73 280.00

7

f i

if 40

-9.44 12.61

4.89

-8.31 13.56

7.00

3933 7.61

6622 13.87

Stl?MARY OF CtOSED TRADES

Profitable TrSde6: 7Oa ( 28 out Of 40 )

(8Gain/9Cain+\Lo66 (79.29) $Gain/$Cain+SLars (80.4%) SGSin/USS (4.1))

RESULTS OF ALL T'RADES

$10,000 kcamr $105,565 in 6622 day6 (18.14 years). 13.9) Per annum compounded annually.

BUY/HOLD is 2t per annum compounded l nnuslly for 6622 dsys (18.14 years).

Appendix Table 5. Signal analysis for the 3.6% slope signals on the Value Line Composite (strategy one). lowing strategies.

This was the worst of the three trend-fol-

MARKET: Value Line Composite SIGNALS: Trend - Strategy 1 PRICTION: 0 Percent HARGIN: 100 Percent DATES: l/03/69 through 2/20/87 (Weekly

ACTION DATE PRICE ACTION DATE PRICE PROFIT8 DAYS s10,000

Long l/03/69 183.67 Sell l/10/69 176.98 -3.64 Short l/10/69 176.98 Cover 5/02/69 170.73 3.53 Long 5/02/69 170.73 Sell 6/06/69 165.00 -3.36 Short 6/06/69 165.00 Cover 10/17/69 144.60 12.36 tong 10/17/69 144.60 Sell 11/21/69 139.95 -3.22 Short 11/21/69 139.95 Cover 2/27,/70 126.95 9.29 Long 2/27/70 126.95 Sell 3/20/70 121.75 -4.10 Short 3/20/70 121.75 Cover 5/29/70 95.36 21.68 Long 5/29/70 95.36 Sell 6/26/70 88.78 -6.90 Short 6/26/70 88.78 Cover 7/17/70 90.49 -1.93 Long 7/17/70 90.49 Sell a/14/70 87.45 -3.36 Short 8/14/70 87.45 Cover a/28/70 95.58 -9.30 Long a/28/70 95.58 Sell 10/23/70 97.52 2.03 Short 10/23/70 97.52 Cover 12/04/70 98.92 -1.44 Long 12/04/70 98.92 Sell 5/28/71 118.27 19.56 Short 5/28/71 118.27 Cover a/20/71 114.08 3.54 Long 8/20/71 114.08 Sell 10/15/71 111.55 -2.22 Short 10/15/71 111.55 Cover 12/03/71 105.92 5.05 Long 12/03/71 105.92 Sell 5/05/72 119.90 13.20 Short 5/05/72 119.90 Cover 11/03/72 111.98 6.61 Long 11/03/72 111.98 Sell 12/22/72 113.14 1.04 Short 12/22/72 113.14 Cover 7/13/73 84.48 25.33 Long 7/13/73 84.48 Sell a/10/73 85.85 1.62 Short 8/10/73 85.85 Cover g/07/73 86.87 -1.19 Long g/07/73 86.87 Sell 11/02/73 89.96 3.56 Short 11/02/73 89.96 Cover l/04/74 79.12 12.05 ung l/04/74 79.12 Sell 3/29/74 78.45 0.85 Short 3/29/74 78.45 Cover 6/07/74 71.31 9.10 Long 6/07/74 71.31 Sell 6/21/74 66.69 -6.48 Short 6/21/74 66.69 Cover g/20/74 53.20 20.23 Long g/20/74 53.20 Sell 10/04/74 49.86 -6.28 Short 10/04/74 49.86 Cover 10/11/74 55.73 -11.77 Long 10/U/74 55.73 Sell 11/22/74 52.68 -5.47 Short 11/22/74 52.68 Cover l/03/75 52.12 1.06 mng l/03/75 52.12 Sell 7/25/75 75.68 45.20 Short 7/25/75 75.68 Cover 10/24/75 70.70 6.58 ung 10/24/75 70.70 Sell 12/05/75 67.74 -4.19 Short 12/05/75 67.74 Cover l/02/76 71.62 -5.73 Long l/02/76 71.62 Sell 4/09/76 85.70 19.66 Short 4/09/76 85.70 Cover 6/18/76 86.53 0.97 fnw 6/18/76 86.53 Sell 8/20/76 85.77 0.88 Short a/20/76 85.77 Cover g/24/76 88.15 -2.77 Long g/24/76 88.15 Sell 10/08/76 84.54 -4.10 Short 10/08/76 84.54 Cover 11/26/76 86.51 -2.33 Long 11/26/76 86.51 Sell 4/08/77 89.96 3.99 Short 4/08/77 89.96 Cover 5/20/77 93.30 -3.71 ung 5/20/77 93.30 Sell 8/12/77 92.61 -.74 Short a/12/77 92.61 Cover 11/11/77 92.34 .29 Long 11/11/77 92.34 Sell l/06/78 90.97 -1.48 Short l/06/78 90.97 Cover 3/17/78 94.10 -3.44

7 112

35 133

35 98 21 to 28 21 28 14 56

1:: 84 56 49

154 182

49 203

28 28 56 63 84 70 14 91 14

7 42 42

203 91 42 28 98 70

4; 14 49

133 42 84 91 56 70

9,636 9,976 9,641

10,833 10,485 11,459 10,989 13,371 12,449 12,209 11,799 10,702 10,919 10,762 12,868 13,324 13,028 13,686 15,492 16,515 16,686 20,913 21,252 21,000 21,747 24,367 24,161 26,360 24,652 29,639 27,778 24,508 23,166 23,413 33,996 36,233 34,716 32,728 39,162 38,782 38,442 37,375 35,844 35,009 36,405 35,054 34,794 34,896 34,378 33,195

23

Mm JOUFWU&W 1987

Appendix Table 5 cant ‘d.

Short s/30/78 Long Y/28/78 Short 9/22/70 Long 12/00/70 Short 3/02/79 bnq 3/16/79 Short 10/12/79 Long 11/23/79 Short 2/29/80 bnq 4/11/80 Short g/26/80 bnq 11/14/80 Short 12/12/80 Long 12/26/80 Short 2/20/81 Una 3/06/81 Shoit 7jO2j81 Lanq 10/02/81 Shoti 1;oe;e2 Unq 3/26/82 Short S/28/82 mnq B/20/82 Short 7/29/83 Law 9/23/83 Short 10/21/83 Law 11/25/83 Short 2/03/84 Long 8/03/84 Shoti 11;16;84 Long l/11/85 Sho;t 3;15;05 L-3 5/17/85 Short 8/09/85 Low 11/01/65 Short 7/11/86 L-q E/15/86 Short g/12/86 L-q 10/31/86

LONG LDSSES GAINS Net

SHORT LDSSES WINS Net

TOTALS IDSSES GAINS Net

Total Profit

-82.25 289.07 206.82

104.11 Cover 108.84 sell 113.63 Cover 100.21 Sell 102.62 Cover 107.15 Sell 115.16 Cover 113.65 Sell 124.50 Cover 110.22 Sell 143.06 Cover 146.25 Sell 137.39 Cover 144.28 Sell 139.98 Cover 145.02 Sell 152.60 Cover 132.79 se11 136.03 Cover 125.15 Sell 124.88 Cover 121.32 Sell 199.38 Cover 202.56 Sell 194.10 Cover 197.30 se11 188.67 Cover 177.30 Sell 178.01 Cover 181.08 Sell 192.63 Cover 198.06 Sell 199.91 Cover 196.04 Sell 236.78 Cover 233.75 Sell 219.80 Cover 230.44 Sell

-78.36 21 -3.73 194.36 23 8.45 116.00 44 2.64 2878 13.76

-160.62 43 -3.74 483.43 46 10.51 322.82 89 3.63 6622 16.12

7/28/78 g/22/78

12/08/78 3;02;79 3/16/79

lOj12j79 11/23/79 2/29/80 r/11/80 g/26/80

11/14/80 ltilti80 12/26/80 Z/20/81 3/06/81 7/02/81

10/02/81 l/00/82 3/26/82 b/28/82 B/20/82 7/29/83 g/23/03

10~21;83 11/25/83 Z/03/84 8/03/04

11/16/84 l/13/85 3/M/85 5/17/85 S/09/85

11/01/85 7/11/86 S/15/86 g/12/86

10/31/86 Z/20/87

108.04 -4.54 113.63 4.40 100.21 11.81 102.62 2.40 107.15 -4.41 115.16 7.48 113.65 1.31 124.50 9.55 110.22 11.47 143.06 29.79 148.25 -3.63 137.39 -7.33 144.28 -5.01 139.98 -2.98 145.02 -3.60 152.60 5.23 132.79 12.98 136.03 2.44 125.15 8.00 124.88 a.22 121.32 2.85 199.38 64.34 202.56 -1.59 194.10 -4.18 197.30 -1.65 188.67 -4.37 177.30 6.03 178.01 .40 181.08 -1.72 192.63 6.38 198.06 -2.02 199.91 .93 196.04 1.94 236.78 20.78 233.75 1.28 219.88 -5.93 230.44 -4.80 263.74 14.45

28 56 77 84 14

210 42 98 42

168 49 28 14 56

1:: 92 98 77 63

3:: 56 28 35 70

182 105 56 63 63 04 a4

252 35 28 49

112

Number Protit/ Number Profit/ Trades Trade Days Annum

22 -3.74 23 12.57 45 4.60 3744 17.97

35,058 36,601 40,923 41,908 40,050 43,052 43,617 47,781 53,261 69,130 66,622 61,742 58,646 56,898 54,049 57,716 65,208 66,800 72,142 71,987 74,039

121,677 119,736 114,736 112,844 107,908 114,411 114,869 112,888 120,089 116,704 117,794 120,074 145,027 146,883 138,167 131,532 150,539

SU?OURY OF CLLlSED TRADES

Profitable Tradea: 52% ( 46 out of 89 )

(%Gain/&Gain+*Loss (75.18) SGain/SGafn+SLo8s (73.91) SGain/Lo+s (2.8))


SlO,OOO became SlSO,f39 in 6622 days (18.14 years). 16.12 per annum compounded annually.

BUY/HOLD is 2% per anmm compounded annually for 6622 days (18.14 years).

24 M!A J(XXNM&S 1987

Appendix Table 6. Signal analysis using variable slope percentages adjusted for the monetary background on thevalue LineComposite (strategy three). This was the best of the three trend-following strategies.

MARKET: Value Line Composite SIGNALS: Trend - Strategy 3 FRICTION: 0 Percent MARGIN: 100 Percent DATES: l/03/69 through 2/20/87 (Weekly)

ACTION DATE

Long 5/16/69 Short 5/23/69 Long 10/17/69 Short 11/14/69 Long 5/29/70 Short 6/12/70 Long 7/24/70 Short a/07/70 Long a/28/70 Short 10/16/70 Long 11/27/70 Short 6/11/71 Long a/20/71 Short g/17/71 Long 12/03/71 Short 3/24/72 Long 11/17/72 Short 12/15/72 Long 7/13/73 Short a/03/73 Long g/07/73 Short 10/19/73 Lang l/04/74 Short l/11/74 Long 2/01/74 Short 3/22/74 Long 6/07/74 Short 6/14/74

Long g/20/74 Short g/27/74

Long 10/11/74 Short 10/25/74 Long l/03/75 Short 7/25/75 Long 11/14/75 Short 11/21/75 Long l/02/76 Short s/28/76 Long 6/18/76 Short 7/30/76 Long 11/19/76 Short 5/20/77 Long 6/24/77 Short 7/29/77 Long 11/11/77 Short 12/09/77 Long 3/17/78

PRICE

171.82 169.97 144.60 145.66

95.36 92.37 91.00 90.22 95.58 99.86 94.34

118.91 114.08 115.32 105.92 122.52 113.65 115.74

84.48 87.62 86.87 94.59 79.12 76.66 79.31 81.29 71.31 69.80 53.20 51.44 55.73 54.63 52.12 75.68 71.31 70.29 71.62 84.28 86.53 87.47 85.07 93.30 94.90 93.41 92.34 93.16 94.10

ACTION DATE

Sell 5/23/69 Cover 10/17/69 Sell 11/14/69 Cover s/29/70 Sell 6/12/70 Cover 7/24/70 Sell a/07/70 Cover a/28/70 Sell 10/16/70 Cover 11/27/70 Sell 6/11/71 Cover a/20/71 Sell g/17/71 Cover 12/03/71 Sell 3/24/72 Cover 11/17/72 Sell 12/U/72 Cover 7/13/73 Sell a/03/73 Cover g/07/73 Sell 10/19/73 Cover l/04/74 Sell l/11/74 Cover 2/01/74 Sell 3/22/74 Cover 6/07/74 Sell 6/14/74 Cover g/20/74 Sell g/27/74 Cover 10/11/74 Sell 10/25/74 Cover l/03/75 Sell 7/25/75 Cover 11/14/75 Sell 11/21/75 Cover l/02/76 Sell 5/28/76 Cover 6/18/76 Sell 7/30/76 Cover 11/19/76 Sell s/20/77 Cover 6/24/77 Sell 7/29/77 Cover 11/11/77 Sell 12/09/77 Cover 3/17/78 Sell 5/26/78

m xmaa/hm 1987 25

PRICE PROFIT% DAYS $10,000

169.97 144.60 145.66

95.36 92.37 91.00 90.22 95.58 99.86 94.34

118.91 114.08 115.32 105.92 122.52 113.65 115.74

84.48 87.62 86.87 94.59 79.12 76.66 79.31 81.29 71.31 69.80 53.20 51.44 55.73 54.63 52.12 75.68 71.31 70.29 71.62 84.28 86.53 87.47 85.07 93.30 94.90 93.41 92.34 93.16 94.10

104.83

-1.08 14.93

.73 34.53 -3.14

1.48 9.86

-5.94 4.48 5.53

26.04 4.06 1.09 8.15

15.67 7.24 1.84

27.01 3.72

.86 8.89

16.35 -3.11 -3.46

2.50 12.28 -2.12 23.78 -3.31 -8.34 -1.97

4.59 45.20

5.77 -1.43 -1.89 17.68 -2.67

1.09 2.74 9.67

-1.71 -1.57

1.15 .89

-1.01 11.40

7 9,892 147 11,369

28 11,452 196 15,407

14 14,924 42 15,145 14 15,015 21 14,123 49 14,756 42 15,571

196 19,627 70 20,424 28 20,646 77 22,329

112 25,828 238 27,698

28 28,208 210 35,826

21 37,158 35 37,476 42 40,806 77 47,480

7 46,004 21 44,414 49 45,522 77 51,111

7 50,029 98 61,927

7 59,878 14 54,884 14 53,801 70 56,273

203 81,710 112 86,429

7 85,192 42 83,580

147 98,355 21 95,729 42 96,769

112 99,424 182 109,043

35 107,173 35 105,490

105 106,698 28 107,646 98 106,560 70 118,710

Appendix Table 6 cont'd.

Short 5/2b/?8 104.63 Cover t/26/76 106.64 -3.63 L-Kl ?/2a/?a 106.84 SC11 9/15/?6 117.36 7.63 Short g/w78 111.36 Cover l/05/79 103.19 12.07 Low l/05/19 103.19 8811 2/02/79 105.33 2.01 Short 2/02/79 105.33 Cover 3/23/19 106.69 -3.19 Long 3/23/19 108.69 8.11 5/11/79 107.10 -1.46 Short s/11/79 107.10 Cover 6/06/?9 112.00 04.56 L-g 6/08/?9 112.00 5811 s/14/79 123.59 10.35 Short g/14/19 123.59 Cover 11/30/19 117.56 4.66 Long 11/30/?9 117.56 se11 2/15/60 126.70 9.46 Short 2/15/(10 126.70 Cover 4/11/60 110.22 14.36 Long 4/11/00 110.22 Sal1 4/16/60 107.41 -2.15 Short 4/U/80 107.41 Cover 4/25/60 110.60 -3.16 Long 4/25/ro 110.80 8.11 10/24/80 145.35 31.16 ShOP, 10/24/00 145.35 Cover 11/26/80 146.91 -2.49 Long 11/26/60 148.97 Sal1 12/05/80 144.96 -2.69 Short 12/05/60 144.96 Cwor 12/26/60 144.26 .I7 Long 12/26/60 144.26 sol1 l/09/61 143.71 -.40 Short l/09/81 143.71 Cover 3/13/61 147.99 -2.96 Long 3/13/81 141.99 1.11 S/01/61 154.64 4.49 Short 5/Ol/Sl 154.64 Cover 10/02/61 132.79 14.13 Low 10/02/61 132.79 Cm11 10/16/61 135.71 2.20 Short 10/16/61 135.71 Cover 11/06/61 139.s3 -2.61 Iang 11/06/Sl 139.53 Sal1 l/15/62 131.60 e.54 Short l/15/82 131.60 Cover l/29/62 133.68 -1.43 Long l/29/02 133.66 1.11 3/05/62 123.05 -7.95 Short 3/05/62 123.05 Cover 3/19/62 122.S5 .41 ung 3/19/82 122.55 8.11 S/14/62 132.14 7.63 Short 5/14/62 132.14 Cover 7/23/62 122.19 7.53 Ipw 7/23/82 122.19 6811 6/06/62 115.02 -5.67 Short S/06/82 115.02 Cover E/20/62 121.32 -5.48 Low 6/20/62 121.32 so11 7/01/63 205.94 69.75 Short 7/01/83 205.94 Cover S/23/63 202.56 1.64 Lang g/23/03 202.56 0811 e/30/03 199.13 -1.69 Short 9/30/83 199.13 Cover l/06/64 200.31 -.59 Ung l/06/84 200.31 8811 l/20/64 196.22 -1.04 Short l/20/64 198.22 Cover 6/03/64 177.30 10.55 km a/03/04 177.30 Sell S/26/64 162.44 2.90 Short g/28/84 162.44 Cover 11/09/64 162.29 .08 Long 11/09/84 162.29 se11 12/07/64 173.28 -4.94 Short 12/0?/64 173.28 Cover 12/21/84 176.69 -2.06 Lw 12/21/84 116.69 se11 E/16/65 197.72 11.76 Short a/16/85 191.72 Cover 10/16/65 193.69 2.04 Long 1O/l6/65 193.69 se11 t/16/66 230.13 16.81 Short ?/la/66 230.13 Cover O/15/66 233.75 -1.51 Long a/15/66 233.75 SO11 9/12/66 219.66 -5.93 Short g/12/86 219.88 Cover 10/03/66 223.55 -1.67 Long lO/O3/66 223.55 SO11 2/20/61 263.74 17.96

UNG LoSSES GAINS Not

SHORT LDSSES GAINS Nat

TOTALS LQSSLS GAINS Nat

Total Number Profit Trader

Fvofif/ Trade

-56.65 20 -2.93 347.53 26 12.41 268.68 46 6.02

-60.66 20 -3.04 236.62 21 6.64 177.75 47 3.76

-119.53 166.15 466.62

2 95

-2.99 10.66

4.91

63

1:: 26 49

te9

5: 77 S6

7 7

162 35

7 21 14 63

1:: 14

3: 14 35 14

3: 14 14

315 64

7 96

1;: 616 42 26 14

236

2;: 26 20 21

140

Wumber bY8

Rof it/ Annwn

3165 32.62

19.14

b469 25.56

114,169 123,107 137.910 140,632 136,339 134,345 126,198 141,464 146,367 162,426 165,746 161,013 175,300 229,962 224,235 216,199 219,223 216,351 211.654 221,313 212,652 2S6,206 250,940 237,038 233,651 215,077 215,951 232,650 250,363 235,691 222,761 376,170 364,377 377,668 375,629 371,709 410,939 422,853 423,200 402,283 393,902 440,287 449,261 533,763 525,366 494,211 465,963 573,329

WY 01 CZQSLD TMDB

Rofittilo Trsdas: IS% ( I5 out of 95 )

(6Gain/6Gsin+9Lass (63.16) SG6in/SG8in+SLosr (77.18) SCsin/Lms (3.4))

RESULTS O? u TRADES

510,000 be&me 6573,329 in 6469 days (17.76 yure). 25.68 par annum compounded l nu4lly.

BUY/HOLD is 2k per mnum compounded l nu~lly for 6622 days (16.14 years).

26

MA JOUFWi#W 1987

Ioren E. Flath is manager of research and director of computer opera- tions at Ned Davis Research, Inc. He is also the editor of Techno-Fundamen- tal Ranks. --

Joseph F. Kalish, a research analyst with Ned Davis Research, Inc., is editor of the Bond Timer. He was the recipient of the MTA's first student research grantwhich resulted in the paper "Using Divergence Analysis To Technically Solve the Asset Allocation Problem" (MTA Journal, May 1986).

27

by John J. Murphy

On June 12 of last year, the New York Futures Exchange launched a futures contract on the CRB Futures Price Index, attracting new attention to the 30- year old commodity index.* The impact of the CRB Index on the traditional commodity markets has long been recognized. Because of its influence over all commodity markets, the CPB is used as the starting point in commodity market analysis in much the same way as stock averages are used in stock market analysis. The impact of the CFB Index on financial markets, however, is also quite impressive.

THFIMPORT74NCEOFINTERMARKGT RELATIONSHIPS

It has become increasingly clear that commodity prices (representing inflation), interest rates, equities (domestic and international) and the U.S. dollar (currencies) impact on one another. It is no longer possible or wise for an analyst or trader in one financial sector to ignore movements in other sectors. Commodity prices impact on bonds and stocks and, in turn, are themselves influenced by movements in the dollar. Commodity-related stock groups are impacted by commodity movements. Stock groups often lead turns in their underlying commodities thereby providing early trend signals to tie alert comnodity trader.

lXECFBINDEXMOVESINVEE?SELYl-OFINANCIAIS

The CFU3 index generally moves in the qposite directicxl of, and often leads, the financial markets. A falling CIB Index is bullish for bards and stocks (Figure 3). A rising CRB index is bearish. The strongest link exists between the CRB Index and Treasury bonds. The link to stocks had alsobeen ob-vious up to January of this year, when bonds and stocks were moving in lock-step with each other. The peak in the CPB Index in February (Figure 2) coincided with the recent trough in the U.S. dollar. The G-6 accord in Paris, which stablized the dollar, effectively prevented a bslllish breakout in the CPP Index over 215 (something some Federal Reserve Board members were quite concerned about).

'IHECPPINDEXANDS'IOCKGRCUPS

The impact of the CPP Index on traditional commodity markets carries important implications for commodity-related stock groups. Figures 5 and 6 show that the bottom in the CFB index in July, 1986 helped launch the strong rallies in gold and petroleum prices. Figures7and 8 show how thosecommodity rallies impacted on gold and domestic oil stocks. Figures 9 and 10 carry that story a bit further. The summer bottom in the CPP led turns in copper and copper shares. However, copper shares bottomed about a monthbefore

28

l¶lmJama#m?1987

copper futures. Currently, a strong rally in copper shares appears tobe signalling an impending bullish breakout in copper futures.

CRB DIRJ3ZI'IONHOLDS IMpoRTANl'CLUES 'IOFINANCIALMARRETS

Since 1980, falling commodity prices have been a major contributing factor to bull markets in bonds and stocks. In April, 1986, however, an upward spike in commodities (caused by the Chernobyl scare) began the leveling off process in that sector. That commodity trough marked the exact top in bond prices and the corresponding bottom in long-term yields (see Figure 4). The g-month 1986 consolidation in stock prices also began from that period. Since last April, the downtrend in commodity prices has been arrested. Whether or not a bottom is being formed will have important implicatio= in the financial arena. Commodity traders are watching the CRB Index closely. Financial traders should be doing the same.

*CHANGESINTHECFU3INDEX

The CRB Futures Prices Index is an unweighted geometric average of 26 non- financial commodity futures markets and includes all futures contracts 12 months into the future. The index has been changed periodically to reflect changing market conditions. The Commodity Research Bureau recently an- nounced some changes in the way the CRB Index is to be calculated. The changes take place in tm stages and are as follows:

1.

2.

3.

4.

Potato futures were dropped from the Index on March 2, 1987. Thatre- duced the number of commodity markets in the index from 27 to 26. The New York Mercantile Exchange recently decided to end trading in the potato contract.

Beginning on July 20, pending CFTC approval, prices for Minneapolis wheat will be dropped from the futures contract along with the four Win- nipeg markets: barley, flaxseed, rapeseed and rye.

Also on July 20, only 9 months of futures data will be used in the calculation instead of 12 months.

Contract months in which open interest is less than 25 contracts will not be included in the index calculation.

29

BIOGRAPHYFORJOHNMURPHY

John J. Murphy is a 20-year market veteran, spent mostly in futures. During 10 years with Merrill Lynch, he was Director of Commodity Technical Research and managed account trading advisor. In 1981, John started his own consult- ing/advisory firm, JJM TECHNICAL ADVISORS. He teaches technical analysis at the New York Institute of Finance and has authored the highly-acclaimed Technical Analysis of the Futures Markets. John is a regular speaker at CompuTrac conferences and does a weekly FNN broadcast. He has served on the Board of Directors of the MTA. Afte; 6 years as technical editor of the Commodity Research Bureau, John is now consultant to the New York Futures Exchange on the CRB Index futures contract.

30

F'IGURE 1: A weekly chart of the CRB Index

070284 1119&4 040885 082615 011386 060216 102086 030987 2DC CRBT 2883 250

I 1 I I I I 195,0t

I I I 0402

I I I I I 0430 0529 0626 0725 0822 0922 1020 1117 1216 0115 0212 0313

FIGUiE2: AdailychartoftheCRBIndexgoingbackayear. Comrrodity prices have been mving sideways since April, 1986. The recent rally failure was caused by the bottm in the dollar. 'Iheupperweeklychart spans 3years and showsthebreakingof a 2-year down trendline.

31

03/13/87 DC OR CRET LflST= 207,98 PCLS= 205,30 TRDS=

KNIGHT-RIDDER TRMCENTER 173 SW

OR YF3OY 300

LIST= 7051 PCLS= 7851 TRDS= 0 SPtJ= 300 I

9100

8080

8860

8,40

8,20

8800 ,

7080 .

7,6pi

7840 ,

7n20 ,

7,510 ,

222 #ai

1 220,0E

218 0d *

I

I I I I I I I I I 0130 0228

I 0402 0430

I 0529 0626 0725

I II I 0822

I 0922 1020 1117 1216 0115 0212 0313

FIGURE 4: The close correlation between the CRB Index and bond yields is clearly visible over the past year.

33

03/13/87 KNIGHT-RIDDER TRflDECENTER 1DC OR CUC 63865 250

1 OR SCOPE 75,93 250

I- 50a00

FUTURES

45,00 “l,,,, :‘*-- ‘* ,,,,, *. 40800

‘* * ‘YW U,lll ‘;*,* 6’

35800 3 5600,. FIG~E 9

I I I I I I 0401 0429 05X

I I I I 0625 0725

I 0822 0922 1020 1117 1216 0116 0213 0313

2DC OR CRET 207087 250 OR XOF’R 75,93 250

-- --

I I I I I I I I I I

.SYIYC I I I

0402 0430 0529 I

0626 0725 I

0822 0922 1020 1117 1216 0115 0212 0313 I

The upper chart shows copper futures and camm stocks bottoming last smmr, with copper shares hittjng bottom first. The recut strcmg action in the copper group bodes well for the outlook for copper prices. Thelowerchart shows the CRB Index leading the bottom in copper stocks last smmer.

KAJOUBW&NlJ87 35

0343187 KNIGHT-RIDDER TRRDECENTER bWC CRBT 208 820 150 1

280 ,BE 270,0E 260,0! 250 106 240,0t 230,0Q 220#0! 210,0e 200 ,ae 190,0!

I I I I I II I I I 070284 111984 040885 082685

l--y 011386 060286 102086 030987

195 m0t I I I I I I I I I I I I I

0402 0430 0529 0626 0725 0822 9922 1020 1117 1216 0115 0212 0313 Command ? _

36 KL7-i JUBWWhM 1987

03113187 KNIGHT-RIDDER TRRDECENTER DC OR CRBT L/XT= 208 009 PCLS= 208,30 TRDS= 164 SPN= 750

OR USC LIST= 100,10 PCLS= 100,10 TRDS= 0 SPN= 750 OR YXC LFIST= 167,05 PCLS= 167,05 TRDS= 0 SPN= 750

I , .: :r ’

100,00

95100

90800

85,00

80,00

75800

70100

u 4

19580

I I I I I I I I I I I I 1 I 0601 0813 1023 0104 0318 0530 0809 1021 0102 0314 0529 0808 1020 1231 0313

Command ? _

37

03/13/87 KNIGHT-RIDDER TRADECENTER DC OR CRBT LFIST= 207 198 PCLS= 208,30 TRDS= 173 SPN= 300

OR YP30Y LFIST= 7851 PCLS= 7,51 TRDS= 0 SPN= 300 I

7n60

t 7140

1 2148%

‘,.* ’

7120 ‘.‘ ; ’ I ’ . ’ ‘I II

7000 196,0t

I I I I I I I I I I I I I I I I 0130 0228 0402 0430 0529 0626 0725 0822 0922 1020 1117 1216 0115 0212 0313

Command ? _

38

03113187 KNIGHT-RIDDER TRRDECENTER

[lDC OR CRBT 207195 250 #3DC OR CRBT 207,95 250 1 OR CCC 41409 250 OR CLC 17893 250

V-IV IV 'f' " :a

w

,

320,0 L

I I I 1 0525 0808 1020 1231 0313 0529 0808 1020 1231 0313

2DC OR '&OLD 151,70 250 4DC OR XOILID 516869 250 OR CCC 414#9 250 OR CLC 17193 250

44000

t 42080

I I I 1 I I I I 1 I

0529 0808 1020 1231 0313 0529 0808 1020 1231 0313 Command ? _

03113187 KNIGHT-RIDDER TRRDECENTER

1DC OR CUC 63,65 250 OR ?COPR 75,93 250

I I I I I I I I I I I I I I

0401 0429 0528 0625 0725 0822 0922 1020 1117 1216 0116 0213 0313

2DC OR CRBT 207887 250 OR KOPR 75893 250 I

20510

200 ,a(

I I I I 195 ,BJ

I I I I I I I I I

0402 0430 0529 0626 0725 0822 8922 1020 1117 1216 0115 0212 0313 Command ? _

by Jack Schwager

Rarely a week goes by that program trading -- the purchase or sale of stock index futures against an equivalent opposite positicn in stocks -- is not blamed for some perceived ill of the stock market. Is the stock market volatile? Then program trading must be to blame. Is the market down sharply? Once again program trading is likely to be cited as the culprit.

The excesses and evils of program trading are widely believed to reach a crescendo with the approach of the “triple witching hour" - the quarterly simultaneous expiration of stock index futures, stock index options, and stock options. The triple witching hour now appears to have given way to the witch-hunt, with criticisms against program trading reaching near hyste- rical proportions. Newspapers and magazines, radio and television, congres- sman an3 the man on the street, all seem to be jumping on the bandwagen of pro-gram trading bashing.

Before more carefully examining the accusations against program trading, let us first divert to a brief description of this activity. The S&P 500 stock index futures contract, traded cn the Chicago Mercantile Exchange, precisely represents the basket of stocks for which it is named. At the quarterly expiration of this contract, all remaining open positions are set- tled at the price of the S&P 500 index on that day. In other words, by definition, stock index futures and to stock index itself must converge at the expiration of the futures contract.

Prior to expiration, futures normally trade at a premium to the cash stock index. Theoretically, this premium should reflect the difference b tween short-term interest rates and the annualized dividend yield on the stocks in the index. Why? Because by purchasing stock index futures instead of the underlying stocks, the vastportionof an investor's funds are left free for investment in short-term interest rate instruments (e.g., T-bills), while the dividends that would be realized in holding the actual stock position are forfeited. Since short-term rates are invariably higher than dividend yields, futures usually trade at a premium to the cash stock index. Generally speaking, the greater the time duration until the expiration of the futures contract, the greater its premium to the cash index.

The key point is that, at any given time, it is possible to calculati a theoretical fair value for futures relative to the cash index (based on prevailing levels for the cash index, short-term rates, and dividend yields). When futures trade significantly below their theoretical premium level, let alone discounts as can occasionally occur, there is an economic incentive for arbitrageurs to buy futures and sell stocks. Conversely, when the premium of futures is substantially greater than the theoretical level implied by prevailing short-term rates and dividend yield levels, arbitrageurs have

*Adaption, reprinted by permission from Futures Magazine.

41

an economic incentive tobuy the underlying stocks ard sell futures. The name "program trading" derives from the fact that computer programs are used to monitor the spread between futures and cash and flag when it is significantly out of line with theoretically expected levels.

In practice, to simplify the actual transactiohl and reduce execution costs, many program traders use a subset of the entire index (selected for its high correlation with the total index) as a proxy far the index itself. However, this is a fine point, which does r& meaningfully affect the ques- ticn of whether program trading acts as a disruptive market factor.

Let us now turn to the accusations. Perhaps the primary criticism leveled against program trading is that it is responsible for excessive market volatility. At surface glance, this claim may appear plausible. After all, isn't this the first time in history that daily fluctuations in the Dow Jones Index in excess of 30 points have become almost commonplace? Yes, of course, pointswingsintheDow and all other indexes have become much larger. However, one need rot dredge w program trading to find an ex- planation. The truth is much less exotic. The simple fact is that point swings are wider because the index levels themselves are much higher; A 40 point move when the Dow is at 2000 is precisely equivalent to a 20 point move when the Dow is at 1000, or a 10 point move when the Dow is at 500.

The relevant question is not whether point swings are wider, but whether percentage price changes are greater now than they were prior to the initiation of stock index futures trading in 1982. The answer should not be a matter of emotion or prejudice, but rather statistics. Figure lillu- &rates the average daily percent prior change in the cash S&P index since 1970. Note that when measured in percentage terms, there is mt a shred of evidence indicating any increase in volatility. In fact, the average daily percentage price change since the start of 1983 (the first full year to witness stock index futures trading) was equal to 0.60%, or slightly below the 0.66% average during the 1970-1982 period.

Case closed? Not yet. When offered the statistical evidence in the preceding chart most critics of program trading are likely tocounter as follows: "The problem with an annual average is that it dilutes the impact of program trading. No cne is saying that program trading consistently in- creases volatility, but rather thatitdoes so in dramatic fashion on occasional days (e.g., those approaching the infamous triple witching hour). Your annual average merely dilutes these events to the point of invisi- bility."

Fair enough. Enter into evidence Figure 2. This graph illustrates the maximum daily price change in the S&P cash index since 1970. If program trading were indeed creating intermittent havoc in the stock market, then certainly this should be evidenced by the maximum percent price change being greater in recent years than in the period prior to 1983. Once again, the statistics belie the accusation. Figure 2 demonstrates that 3 of the 4 years since 1983 actually witnessed a smaller maximum daily price change than 10 of the 13 years in the preceding 1970-1982 period. Only in 1986 was

42

the maximum daily price change relatively high. Even in this instance, the 1986 maximum was second to the maximum witnessed in 1970, ard only slightly larger than the corresponding figures for 1974 and 1982.

Let's give the critics one last chance. They might now respond: "Whereas the annual average was too broad, the use of a single day in the year to measure volatility is too narrow a measure. If you wish to see the impact of program trading, you must focus cn the weeks immediately preceding the triple witching hour." Table 1 compares average daily price changes during two week, one week, and cne day periods prior to futures expirations to the average level for the year asa whole. Finally, an element of sub- stance emerges: the S&P 500 index does indeed witness higher than average volatility on expiration daysin futures. However, note that this effect does not extend beyond the confines of these isolated days, as the average volatility levels in the one and two week periods prior to expiration are very close to the annual averages.

Thus, the entire volatility argument seems to be based on 4 days per year, or about11/2% of all trading days. Moreover, in three out of four years futures have traded, the highest volatility on an expiration day was less than half as large as the highest volatility for the year as whole (see Table 2). Thus, the extreme high volatility days that draw all the media attention are probably not even related to program trading.

To summarize, it seems to make little difference whether one focuses on price change in terms of annual averages, annual maximums, or averages during the weeks prior to the expiration of futures. In all cases, there appears to be no connection between market volatility and futures trading. To those who decry the increase in volatility due to program trading, the key question is: What increase in volatility?

Although futures trading does rot appear to be related to market volatility, there is one factor that explains a major portion of year to year changes in volatility: the existence or absence of major market trends. In years in which there are major market trends (up or down), daily price changes tend to be greater. Conversely, years characterized by trading range markets tend to witness low daily price changes. The range between the annual high and low, measured as a percent of the annual average, can be used as a proxy for the extent of trend in the market. As Figure 3 illustrates, higher daily price changes tend ti be associated with wider annual ranges. Note that 1986 -- the year in which program trading criticism reached new heights - fit tie general pattern perfectly.

Is the foregoing argument meant to imply that program trading never ex- acerbates market volatility? Of course rot. Certainly there are days when program trading may increase price swings. But, equally true, there are days when program trading modifies price swings. After all, program trading is simply another manifestation of arbitrage, a market forae which generally keeps related markets in line and provides stability. Eyebrows should not be raised because a decline in stock index futures is quickly followed by a decline in the underlying stock market. This is merely evidence of an ef-

43

ficient marketplace. In fact, the event which would reflect distortion, if not possible manipulation, would be tie failure of a price move in cne market (stocks or stock index futures) to be followed by a near equivalent move in the other.

Another major accusation against program trading is that by triggering occasional sell-offs it exerts a net negative influence on stock prices. This is such a preposterous claim, that it is hard tobelieve that anyone can take it seriously. Tobegin, the existence of stock index futures actually coincides with one of the greatest bull stock markets in history. The reverse argument would be for more plausible -- i.e., the proposition that stock index futures trading is responsible for rising stock prices. At least in this case, one could demonstrate a correlation between stock prices and the existence of stock index futures trading (albeit, this is likely a nonsense correlation - a coincident pattern lacking in any cause ard effect relationship).

A second reason why it is nonsensical to claim that program trading provides a net bearish market influence is that the mechanics of the marketplace make it far easier to buy stocks and sell futures than the reverse operation. Trading rules only permit short sales of stocks on upticks. Trying to implement an arbitrage trade, which depends upon speed and oar- tainty of entry, under such conditions is obviously very difficult. For this reason, in most program trading the initial transaction is a purchase of stocks and a sale of futures, with the opposite transaction occurring only when this initial position is liquidated. Of course, there will be some program trading in which short stocks/long futures represents the initial position, but this is hardly the norm. Consequently, it would be far easier to argue that program trading provides a price supportive influence to the stock market.

Finally, I doubt that there are many experienced traders, or market students, who believe that technical factors, such as program trading, can actually cause a sustained price move that would mt have occurred other- wise. Even on a day which witnesses a large price decline and program traders are known to be buying futures and selling stocks, it is difficult to argue that selling pressure would not simply have manifested itself directly in the stock market if there were ro futures market.

Stock index futures merely provide portfolio managers and investors with a quick means of reducing market commitment. If a portfolio manager wants to move from a 100% equity positicn to 80% pity and 20% cash, it is usually much simpler to sell an equivalent amount of stock index futures rather than actually liquidate specific stock holdings. Tba use of futures in such a case will reduce transaction costs and provide greater flexibility in adjusting the overall net equity commitment both up and dawn. (Naturally this assumes that the given portfolio is highly correlated with the S&P index.) If an economic development makes portfolio managers nervous about their stock holdings, the resulting selling would all occur in the stock market directly if there were no futures market. While it may be true that price swings develop more quickly in futures due tD that market's uniformity

44

KIR JWRNA#M 1987

and liquidity, there is 133 reason to believe that the resulting price moves are any different than would have occurred in the absence of a futures market.

The current wave of criticism against program trading is but one more example in the long history of futures trading being used as a scapegoat for true fundamental market forces. For example, in 1973, when supply short- ages, combined with strong meat demand, pushed retail meat prices up sufficiently sto spark consumer boycotts, futures speculators were often blamed for the price rise. Ironically, in recent years when a relentless downshift in meat demand resulted in steadily declining meat prices (as measured in real dollar terms) farmers blamed those same speculators for lower prices. It's simply human nature to seek a tangible villain -- e.g., those nasty speculators in Chicago -- rather than attribute one's predicament to an amorphous factor such as excess supply or demand.

As another example, in recent years, the steady decline of grain prices has led to increasing criticism that speculators selling futures are responsible for this decline. Never mind, that U.S. and world grain inven- tories are at record levels. Never mind that for decades the U.S.government has largely promulgated programs whi& have encouraged farmers to produce for government storage instead of the marketplace. Of course, these are the true factors responsible for lower grain prices. But, onoa again, it is easier to blame speculators in Chicago. It is interesting that there were no tractor parades protesting futures trading in the 1970s when grain prices were moving sharply higher. In both instances, futures were merely a reflection of the marketplace, not the cause of price movement. A falling barometer does rsot cause the storm.

In the current congressional session we will likely see increased political pressures for action against program trading. This is a cause of concern for all of those who believe in free economic markets. Stock index futures provide a useful economic function by facilitating the hedging of stock positions. This market's value and viability have been amply demonstrated by the steady expansion in the use of futures as a hedging vehicle by portfolio managers. Program traders merely provide an economic link between the stock market and stock index futures, assuring that these markets do rot move widely out of line. Any government action to impede the smooth operation of these economic forces could only be expected to create ineffi- ciencies.

One is reminded of the current vogue among politicians to blame various economic woes on free trade. However, if the protectionists succeed in im- peding free market forces -- in this case free trade -- history leaves little doubt that such a victory would exacerbate economic difficulties both in the U.S. and the world. The basic principle is the same, except in instances where clear harm to others can be demonstrated (e.g., pollution), government actions interfering with'free market forces are likely to have a net negative impact. (Although there are those that will claim that program trading does indeed harm others, much like pollution, as demonstrated earlier, the evidence is lacking.) The controversy over whether the govern-

45

ment should enact legislation restricting program trading is merely part of the larger question of government intervention in the marketplace. Tb pit it simply, those who believe in free markets, should oppose such intervention.

In the words of Sir William Osler, "The greater the ignorance the greater the dogmatism." It is time for those who criticize program trading (and perhaps to a larger extent stock index futures trading) to provide mrne facts rather than prejudice to support their position.

46

Average Daily Price Change in S&P (%)

Period Prior to Ebtures Expiration

Tbtal Last

Year Year 2 Weeks 1Week Day

1983 .64 .50 .50 .45

1984 .60 .63 .72 .92

1985 .50 .57 .52 .87

1986 .68 .83 .47 1.01

1983-86 Average .60 .64 .55 .81

47

m!AiiOma#W I987

-2

48

Year

1983 2.71 1.14

1984 2.77 1.18

1985 2.28 1.54

1986 4.81 1.43

Maximum Volatility Days (%)

Maximum

Volatility Day

During Year

Maxixrum

Volatility

on Futures

Expiration Day

Figure 1

1.1 AVERAGE DAILY PRICE CHANGE OF S6P5OOM

1 1.r

0.F

0.8’

O./

0.6’

0.5’

0.0’

0.3’

0.Z’

0.1”

0.0 70 16 1 2 6

Figure 2

MAXIMUM DAILY PRICE CHANGE OF S&P500 IN GIVEN YEAR(X) c EY J.J

I 5.0-

4.5--

4.0"

3.5"

3.r

2.5-'

2.0"

1.5-'

1.r

0.5"

0.0'- 70 '3 '6 1 72


X

X X

X xc1986

x x

X X

X

Figure 3

AVERAGE DAILY PRICE CHANGE OF SSPSOO VS. ANNUAL PRICE RANGE(X) I.11

X 1.0 --

0.9 --

X

0.5-- X X

x x

0.4 1 Y 1 I . I I I I 1 10 20 30 40 50

Annual Price Range (X)

Frederic H. Dickson

Sumnary

The most difficult problem for today's professional investor is information synthesis. On a given day, a portfolio manager will receive from five to one hundred written pieces of fundamental and technical research, have access to several electronic research delivery systems arxi whatever propri- etary information review services or systems which he or she manages themselves. In this cOntext, I have found a series of two market indicators and six technical tools for individual stocks to be invaluable for rapidly screening the massive number of fundamentally derived research ideas under consideration at any given time. Derived automatically from a very flexible computer software package, these tools allow me to synthesize ideas for investigation from a valuation and fundamental point of view. This paper presents the technical tools in a case review format.

Market Background--P/E Ratio Analysis and Manentum Analysis

As a technically-oriented portfolio manager, I always have a background par- spective about the stock market and the fixed income markets. I use two technical indicators on a daily basis to fix my equity market perspective. These indicators are the trend in Price/Earnings Ratios for the Dow Jones Industrials and Dow Jones Transports ard the 26 week ratz of change for the S&P 500 (a momentum indicator).

R P/E Ratio Analysis. My definition of a bull market is me where prices and price/earnings ratios are expanding. In this period virtually all stocks move up and it is relatively easy to make money. The price/earnings ratio is one of the few pure expectational measures of investor sentiment. If prices are stable or rising in a period of declining earnings, it signals strong investor confidence for an earnings recovery. If prices are stable or begin to fall during a period of rapidly rising earnings, it signals very poor investor expectations about the future.

Figure One presents charts of the DowJones Industrials and theDowJones Transports prices and Price/Earnings Ratios plotted over the last ten years. I find it interesting that the Price/Earnings ratios peaked ahead of the major averages in each of the last three market cycles. Investors begin to discount future earnings expectations at a point in a bull market prior to the peak in earnings momentum and slow down their buying enthusiasm. The peak in the Price/Earnings Ratio generally comes three to six months prior to the cyclical price peak.

I use the Dow Jones Industrials and Transports to confirm each other. The

51

underlying earnings cycles for these indices are slightly out of phase and when both are moving q or down together, I strongly believe that the rest of the economy ard all segments of the equity market are behaving in a similar fashion.

As of March 20, 1987 the price trend and Price/Earnings Patio trend for both indices were positive. This signals to me that the current bull market is still in tact.

B. Market Momentum Index. The second market benchmark indicator which I monitor daily is the 26 week rate of change for the S&P 500. This indicator is shown in Figure 2 for the period 1978 to 1987. The scale for the momentum index is set so that a zero 26 week rate of change is shown as 100, a 10% negative 26 week rate of change is shown as 90 and a 20% positive 26 week rate of change is shown as 120.

As seen in the chart, market momentum as measured by this indicator reaches a peak level in the 25% to 30% (120-130) range. Thus, when I observe a 26 week rate of change above 25% (125) I surmise that the market has passed through its most rapid rate of acceleration. I realize that the market will probably continue to advance for a while beyond this point, however I begin to become more cautious and plan defensive action for corrections as this occurs. On the chart, I have indicated trigger points for changing my market opinion from bullish to bearish. The signal point is a retracement in 26 week price momentum from the peak reading above 120 (20% rate of change) down through the 120 level (20% rate of change). The vertical spikes drawn on the chart show that in the last 9 years this sell rule provided goad timing of specific market tops.

I have found this momentum index to be less helpful gauging market bottoms as at market bottoms the rate of change is usually at 01: near its cyclical peak negative value. However, I am aware that when the 26 week rate of change is below 100 (negative) a bottom could rapidly form. This was the case in early 1979, March 1980, September 1981through August1982, June 1984 and September 1986. The indicator seems to error on the early side when used to time market buy decisions during extended bear markets. Iook- ing at the data for 1974, the indicator was negative throughout the year and the market declined from 900 to 575 with this indicator in negative terri- tory (below 100).

Technical Tools-Individual Stocks

Using Market Analyst Software (Anidata, IUC Active Investor Series), I have setup an automatic routine whereby I can very quickly scan the technical parameters of a particular issue using sixdifferent indicators. In this section I will present these tools using Telecredit (TCRU) as a case example.

52

Listed below are the six perspectives:

1. Price Momentum (26 week rate of change)

2. Price versus Accelerated Moving Average (52 week basis)

3. Trend Strength Analysis (Weekly AdvanceDecline Line)

4. Relative Strength Divergence (Price versus S&P 500)

5. Trend Persistence Index (Weekly Close versus Iow)

6. Rate of Change-Positive Volume Index

A. Price Momentum. As an portfolio manager, I am very concerned about whether a stock which is a candidate for purchase is overbought or oversold at the time it is identified on the basis of value or fundamental reasons. The 26 week rate of change indicator provides a helpful framework to gauge the intensity of price movement during recent periods of time. Looking at Telecredit in Figure 3, we observe that 26 week rates of change above 75% (175 on the scale) signal peak price acceleration. Conversely, negative rates of change in excess of 10% (90 on the scale) are observed at or near cyclical bottoms. From this chart, Telecredit is definitely extended in terms of price momentum, and a cautious attitude toward purchase would be warranted.

B. Accelerated Moving Average. Moving averages are used by Technical Analysts to smooth out cyclical price fluctuations and identify the underlying longer term trend. Due to their basis of calculation, moving averages lag the underlying price trends. They peak or trough ard reverse direction after the price series reverses direction. One way of eliminating or reducing the lag caused by the statistical method of calculation is to use an accelerated moving average. The statistician calls this statistical procedure double smoothing.

Prmedurally, one calculates a long-term moving average (50 week is used in this case study) for the weekly price series. Then the analyst takes a moving average of the first moving average. When plotted, the second moving average is even more lagged than the first versus the underlying price data. Next the difference between the first and second moving averages is determined for each and added back to the first (basis 50 week) moving average. Using optimizing routines from technical mftware such as RTR's Technifilter program, one can determine the appropriate period for the second moving average and a multiplier factor for the difference between the moving averages which produce the best historical fit.

In the case of Telecredit, a 50 week moving average was plotted, a 25 week moving average was calculated of the first 50 week moving average, ard the difference between the firstand second moving averages were determined. Then, 150% of the difference was added back to the basic moving average to

53

determine the accelerated moving average. The accelerated moving average is clearly identified U-I Figure 4.

Examining Figure 4, one can clearly see that the accelerated moving average is more responsive to prior turns than the basic 50 week moving average and that it produced fewer whipsaw signals. The ane problem using accelerated moving averages occurs witha sharpbut short duration correction coming after an extended rally. The accelerated moving average will signal a sell, however the subsequent buy signalwillbe late and at a higher price than the sell signal. The long-term moving average will tend mt to give either the sell or buy signal for a 10% correction which last 2 or 3 months in duration after a 6 month 200% rally. This weakness is shown during the mid- 1986 with Telecredit.

c. Trend Strength Analysis. Most technical analysts use the daily or weekly advance/decline line to gauge broad market breadth. I have found that applying the same concept to individual stocks gives me a very good perspective of the underlying trerd component of a stock's price activity. With many stocks, spike C)L: short duration intense price movements caused by a singlebuyer or seller distort the price action ona typical chart. For example, a stock could advance 10 points (25%) over a period of six weeks with all of the advanoa coming during 2 or 3 trading days. The day-to-day underlying support or resistance is hidden by the spike trades.

Figure 5 presents for Telecredit's Trend Strength Chart (Weekly Advance w cline Line). The index is simply calculated by adding the value of one to the previous indexpointeach week if the market close is above its prior weekly close and subtracting one from the index if the weekly close is below the previous weekly close.

With elimination of price spikes, the Trend Strength Chart seems to be significantly less volatile and more useful for classical technical analysis than the underlying price series itself. In the case of Telecredit, the correctim experienced during September 1986 was not particularly noticeable from the Trend Strength perspective. At present, both the price trend and trerd strength remain positive.

D. Relative Strength Divergence Analysis. Many analysts use relative strength to confirm absolute price trends. I use relative strength as a divergence indicator to spot problems ar opportunities with specific stocks. A stock which has outperformed the market during a major portim of a bull market which then reverses as the bull market progresses is very problema- tical to me. Historical studies show that this type of negative divergence is significant and that the stock will continue to underperform during tie remaining period of the bull market ard during the bear market phase of the cycle. A stock that has underperformed the market during a bear market which begins to show price stability or move up in price as the bear market continues presents a great opportunity. This positive divergence is statis- tically significant and the positive relative strength stock will continue to outperform the market when the market reverses upward.

54

In the case of Telecredit, as shown in Figure 6, one observes a period of negative relative strength divergence during mid-1983 arid a positive divergence during mid-1986. The stock followed the statistical tendencies subsequent to these periods by correcting sharply downward in 1983-1984 and upward in late 1986.

E Trend Persistence Index. This indicator is calculated by comparing tie weekly closing price of the stock to its weekly low price. A cumulative line of these differences is determined and a 20 week rate of change is calculated of this cumulative index line.

The logic behind the derivation of the index is very simple. During rising market periods stock prices tend to close successively nearer to their weekly highs and during extended down market periods, stocks tend to close successively nearer ti their weekly low prices. As shown in Figure 7, the Trend Persistence Index is a very stable index and does a reasonable job signalling long-term price turning points. It appears that this index is very useful for application of trendlines as it is less volatile than the underlying price series.

In the case of Telecredit, a major top was signalled in March 1983, approxi- mately 6 months ard within a few percentage points of the actual top. Like wise, a major buy signal was identified during June 1985 very close to its cyclical bottom observed during May 1985.

F. Pate of Change-Positive Volume Index. Many analysts use volume confirmation as part of their decision-making sequence. I have not been very successful applying volume indicators in a real-time decision making environment. However, I use one volume indicator, the 13 week rate of change of the Positive Volume Index as a short term timing tool. It has demonstrated reasonable accuracy when tested with the PTP Technifilter Software program.

The positive volume index is constructed by adding the weekly price change to a cumulative index when the weekly volume exceeds the volume of the preceding week. The 13 week rate of change is calculated for this index and plotted over time.

Figure 8 presents the 13 week rate of change in PositiveVolume Index for Telecredit. On the top portion of the chart I have clearly indicated the periods when the Rate of Change is negative. I have observed that the stock price seldom moves up sharply during these periods and most of the time during tfiese periods the stock is under sharp selling pressure. I like to use this tool in a defensive manner. It has helped me to avoid new purchase commitments during a period when the stock price might be cry vulnerable to further correction.

55

In Summary, as a portfolio manager I have come to rely on several Technical tools to provide an effective real-time quality control function for stock selection and portfolio revisions. Technical software which is commercially available allows the portfolio manager/analyst to review and quickly screen hundreds of ideas in a very efficient manner without losing precision or sacrificing the intuitive background which Technical Analysis provides to the knowledgeable user.

56

mn JUBUW&W 1987

KIR v 1987 57

FIGURE TWO

M?KET HOHENTU?l ANALYSIS mar 13 87 250 VERY SHORT TERM I3M05> C)K

THEN WATCH OUT I!!!

200

150

100

. . . C-26 wee< rate 0 C-26 wee< rate 0

130- 130-

58

35 25

15

10

TELECREDIT tTCRD1

59

FIGURE FOUR

TELECREDIT CTCRDB mar 13 87 ->

N#TE THE FASTER SGNALS-FEWER WHIPSAWS N#TE THE FASTER 5IGNAL5-FEWER WHIPSAWS

60

TELECREDIT tTCRD1 Mar 13 87 35- 25-

TREND STRENGTH ANRLV5IS 1 WEEK ADY-DECLINE LINE 40 WK MA OF RID LIME

61

FIGURE 51X

35

25

15

10

5

~RELRTIYE STRE)IGTH IV5 s&P 5001

128- ‘PERIOD5 CrF DIYERGEHCE ARE VERY t51GKXFICAKT.

62

TELECREDIT CTCRDI

TREND PERSISTENCE INDEX

CWH .DIFFERENCE BETWEEN WEEKLY

20: CLOS2HG PRICE AND WEEKLY LOW

63

TELECREDXT tTCRDIb Mar 13 87 -2 35

25

15

I@

5

;’ r

I:

/ P ‘6

I I

i I

POSITIY~- YI)LUME INDEX

64

SUtM~R’f OF STOCK SELEGTIOH STRhTEGIES MILLBURN[5HAREINYEST~

YALUATII)N FUNDAMENTAL TECHNICAL ANALYSK ANALY515 dNALY515

35

25 20 15

10

TELECREDIT CTCRDl

I

LICWIDITY MOMENTUM INDEX

10 8

CUM DIFFERENCE BETWEEN WEEKLY CLCb5ING PRICE AND WEEKLY LOW A-J

6

4

66

feb 27 87 -/; I II 1.1 I 1'1 '1.8 I """ i'i CCIFWARATIVE PERFORHANCE l 242fl

170. EQUITY PORTIOH-GRH TYCHE US 160- S&P 508

/ I a

150- CAM

140- TYCHE

13 12 11 10

9 8 7 6

0- 0- 0-

HEDGED 1115184 TO #/2/84

67

2.2 VERSUS THE S&P 500 2.1 2.0 1 l 9. I m %- lm?- 1 m 64 S&P 1.5-

COHPCLRATIUE PERFORHfiNCE 2 l 31 LOHG TER!l BONDS <30YR TRECISlJRIES3

BOND YIELDS CINYERTEDB

NOTE THE CLOSE CCbRRELATII)N DURING

I5 NOW EVIDENT-WANT R BOND RALLY -

68

Market Volatility: An Updated Study

bY Laszlo Birinyi, Jr. H. Nicholas Hanson, Ph.D.

Summary and Conclusions

We continue to believe that the trend of volatility in the stock market is not, in a historical context, worrisome or unusual.

l The fear of increased volatility in the stock market is cyclical. Articles have surfaced at regular intervals from as far back as 1972 on the concern about increased volatility.

l In addition to updating the data on the three quarters since we published Market Volatiliry: Perception and Reality, we have analyzed daily price changes since the beginning of the DJIA in 1915. Even more price instability occurred in decades prior to the 1980s - such as the 1920s and 1930s - but given the economic upheavals of those times, this is not surprising.

0 While derivatives (futures and options) are said to increase volatility, the British market (as measured by the FISE IOO), which does not have an active futures and options market, has been more volatile than the NYSE (as measured by the DJIA).

0 Investors’ concentration on the trading activity masks, we believe, the fact that the market is apparently in an invesmenr cycle. The best- performing DJIA issue over the past 18 months has been FW Woolworth, which should only be slightly affected by trading in derivatives.

69

Table of Contents Paee ~-

Summary and Conclusions 1

Volatility: Approaches and Background 3

1. This is Not a New Concern 3

2. Day-to-Day Price Changes Less Acute 4

3. Intraday Changes Not Increasing 6

4. Statistical Test of the S&P 500 Also Shows Decreasing Volatility 7

5. Futures and Options Expiration Days Are Not Necessarily Acute 8

6. Although the British Market Has No Equity Derivatives, It is More Volatile 10

7. Character of Market Cycles Not Changing 11

8. The Current Market Is an Investment, Not Trading, Environment 12

9. FW Woolworth - A Last Word 13

10. Group Rotation Has Not Increased 14

Figure 1. DJiA - Distribution of Daily Percentage Changes, 2 Jan 15 30 Jun 86 4

Figure 2. DJiA - Price Distribution, 2 Jan 15-30 May 88 5

Figure 3. DJIA - Average Absolute 16-Minute Change, 1 Jan 82-30 Jun 86 Figure 4. SIP 500 - Volatility, 1981-88 : Figure 5. SIP 500 - Volatility, First Quarter 1970~Second Ouarler 1986 7

Figure 6. S&P 500 - Closing Prices, First Ouarter 1970~Second Quarter 1986 Figure 7. DJIA - Average Absolute 15Minute Change, Monthly Average

versus Expiration Day, Jun 84-Jun 86 Figure 8. Expiration Day Change versus Mean for Month, Jun 84-Jun 86 Figure 9. DJIA - Daily Percentage Change, 1% Price Mows and Expiration

Days, 2 Jan 80-20 Jun 86 Figure 10. DJIA versus FTSE 100 - Daily Price Change Distribution, 7 May 84-

22 Apr 86

Figure 11. DJIA Rallies - Duration and Percentage Moves, 1914-88 Figure 12. DJIA - Largest Gainers, 30 Dee 84-30 Jun 86 Figure 13. FW Woolworth - 31 Dee 84-30 Jun 86 Figure 14. Performance of XMI Issues, 5 Jun 86 Figure 16. Industry Group Movement - Average Weekly Parcantage Gains of

Five Largest Rallies, 2 Jan 79-2 May 88 Figure 16. Aerospace Group - Largest and Current Rally, 20 Dee 74-18 Apr 86

7

8 8

9

10

11 12 12 13

14 14

70

Volatility: Approaches and Background

1. This is Not a New Concern

The theme that the market’s short-term movements are increasing is a recurrent one:

Liquidity: Is it Becoming a Problem Again?

. . . More important, the concerns aroused by the sudden price slides in so man)’ stocks this summer can do nothing but fuel the controversy over the power of institutions in the marketplace.

tnstitutional Investor, September 1972.

The causes (and cures?) of market volatility:

. . .following factors are significant:

1. The Land of the Giants: $ Millions Against $ Billions. 2. All Sellers and No Buyers, or All Buyers and No Sellers. 3. Efficient Markets Foster Faster Moves. 4. It S Hard to Keep a Secret. 5. Why it’s Hardfor Institutions to be Different.

The Journal of Portfolio Management, Winter 1976.

Is the equity market becoming more volatile?

The conclusions one might draw from this analysis would depend, to a large exfent, on the lime frame chosen and irs importance in the investment strategy and process.

The Journal of Portfolio Management, Spring 198 I.

Stock Prices Become More Volatile as Role of Institutions Grows . . . Computers Step Up Pace . . . Many Small Investors Upset

Volatility has been increasing in most U.S$nancial markets. Since October 1979, when the Federal Reserve System decided to let interest rates swing more freely, the once-staid bond markets have come IO resemble a high- stakes poker game. Now, the wild price action is overtaking exchange-listed stocks . . . To explain the sharply increased volatility, investment experts cite a number of structural changes that have helped fuel the recent gyrations and that they think will keep the market on a roller coaster well into the future . . .

The Wall Street Journal, November 30, 1982.

71

2. Day-to-Day Price Changes Less Acute

Figure 1 shows every change in the DJIA since 1915 by decade. The starting point of our data is the actual beginning of the average. Although the DJIA is available earlier, those dates (pre 1915) are for a reconstructed index.

We have separated the amounts in Figure 1 into eight distribution charts, one for each of the decades since the DJIA’s inception.

Figure 1. DJtA - Distribution of Daily Percentage Changes, 2 Jan 15-30 Jun 86

Y0V.S 1910s 1920s 193os 194OS 199OS 19901 1970s 199OS

Greater than 5% 01% 01% 1.5% 00% 0.0% 0.0% 0.0% 0 0%

4%~5% 01 01 0.9 0.1 0.0 01 01 3%-4% E 04 1.9 0.1 00 0.1 04 i.; 2%-3% 1.2 47 02 02 2.3 l%-2% 131 10.3 11.8

2 4.7 4.4

2 105

0%-l% 359 430 297 46.5 50.2 463 373 372

0%~( 1 )% 337% 324% 275% 40.7% 394% 42.8% 389% 385% (~%-(2)% 98 95 117 iA 4.6 56 10.3 99 (2)%-(3)% 19 07 03 09 (3)%-(4)%

:z 06

E 0.3 00 01

2

(4)%-(5)% 05 02 13 02 00 00 00.1, Greater than (5)% 01 03 11 01 00 00 00

72

Figure 2. DJIA - Price Distribution, 2 Jan 15-30 May 86

2 Jan 15-31 Dee 19

2 Jan 30-30 Dee 39

2 Jan 50-31 Dee 59

2 Jan 70-31 Dee 79

2 Jan 20-31 Dee 29

M!m ~tImm#W 1987

2 Jan 40-31 Dee 49

4 Jan 60-31 Dee 69

:=-as -9% -u -1)1 -2s -‘, es r** .n .* .a .s8 zsa

2 Jan 80-30 Mav 86

3. Intraday Changes Not Increasing

In the past three quarters, the 15-minute changes in the market have remained within parameters of those of the past four years. The computerized Block Monitor System - maintained by our Equity Market Department - provides a reading of the DJIA four times per hour. (The blank spaces below - February-March 1983 and January 1984 - are gaps in our data base.)

In addition to the general lack of short-term volatility, changes in market direction, especially in the last hour, are not a phenomenon of the derivative environment. For example, in the past, technical analysts have closely tracked the closing hour for a last-hour, technical indicator.3

Figure 3. DJIA - Average Absolute 15Minute Change, 1 Jan 62-30 Jun 86

w (%I 0.20 0.20

0.18 0.18

0.16 0.16

0.14 0.14

0.12 0.12

0.10 0.10

0.08 0.08

0.06 or 02 03 04 01 02 03 04 01 02 43 04 01 02 QJ 44 01 02

0.06

1962 1983 1984 1985

Fiaure 4. S&P 500 - Volatility, 1961.66a

1981 1982 1983 1984 1985 19868

Arerr9c Delly Stendrrd Treding Rengc Derietion

203% 041% 230 062 203 039 099 049 0 79 035 112 049

aThroughJune30

74

3 See “Hot New Indicator.” Eerron’s. June 15. 1981. pp. 9.

m V 1987

4. Statistical Test of the S&P 500 Also Shows Decreasing Volatility

The annualized standard deviation of the daily percentage price change by quarter is shown in Figure 5. The data of the past three quarters are clearly well within the range of this series over the past I5 years. The greatest volatility seems to occur near major market bottoms.

Figure 5. S&P 500 - Volatility, First Quarter 1970~Second Charter 1986

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

1970 71 72 73 74 75 76 77 76 79 80 61 02 03 05

Figure 6. SIP 500 - Closing Prices, First Ouarter 1970~Second Charter 1986

3oc

25C

300

250

75

5. Futures and Options Expiration Days Are Not Necessarily Acute

We segregated those Fridays on which near futures contracts and the options on Indexes expire. In the past three quarters, there has been a slight increase in the intraday fluctuations relative to the month. The critical point is that unlike in June 1985 and September 1984, there was no widely disparate move from the change during the rest of the month.

The change on those days may well be a function of expiration. We do not suggest that derivative instruments completely lack impact; rather, it is an extreme exaggeration to assume that every short-term fluctuation totally reflects the movements of these equities.

Figure 7. DJIA - Average Absolute 15-Minute Change, Monthly Average versus Expiration Day, Jun 84-Jun 88

(%I 0.20

0.15

0.10

0.05

0.00 n Jun Jun 3cp ucc MOT dun

1985 1986

(%) 0.20

0.15

0.10

0.05

0.00

Average Absolute 15-Minute

3JIA Chonge: Monthly Averoge

Averoge Absolute 1 S-Minute

DJIA Change: Expiration Day

The days of futures and options expirations do not endorse the concept of market instability or unusual price fluctuation. In Figure 9, we plot every instance of a ICC move in the market (denoted by periods) as well as the expiration day percentage moves (denoted by asterisks). In our view, these latter moves are not extraordinary.

Figure 8. Expiration Day Change versus Mean for Month, Jun 84-Jun 88

1984

Mean of Absolute Deily

Price Chenge Standard Devietlon

Jun 0 74% 0 55% -0 97% Sep 067 052 -1 22 Dee 0 59 061 -036

Mar Jun SeP Dee

051% 043% -101% 051 042 1 88 053 033 -066 062 0.52 -006

1988

Mar 0 19% 0 74?/, -1 980/c Jun 065 0 57 1 28

76 KB 3UBW&MY 1987

Figure 9. DJIA - Daily Percentage Change, lo/o Price Moves and Expiration Days, 2 Jan 80-20 Jun 96

(% e

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1 D6C 106' 1962 1063 1064 1685 tO66

77

6. A hhough the Britbh Market Has No Equity Derivatives, It is More Volatile

The British equivalent of the DJIA is the FISE 100. Although this Index is relatively new (it commenced on May 7, 1984), it is the most popular and widely followed gauge of the market in London. Given the fact that there is some overlap in trading hours, many of the factors that affect the British market should also affect the U.S. markets.

Although there are some futures on the Index, they are not apparently a factor, as little is ever discussed even in the Financiul Times. Despite this, the trading on the British market is even more volatile than that on the NYSE: 21.1% of its trading sessions over the May 7, 1984-April 22, 1986 period, had moves of 1% or greater. Concurrently, the DJIA only had 15.7% such sessions.

Figure 10. DJIA versus FUSE 100 - Dally Price Change Dirtributlon, 7Mav84-22 Am66

Ponitfve Mover3

0.23

2.093

8.5M

I I I I I

DJIA

> 3% I Negative Mover

1% - 2x .8X

c 1%

F

2.8%

t I I I I 1 50 40 30 20 10 0 0 10 20 Xl 40 50

Podtive Mover Negative Mover

44.7 34.2%

I I I I I I

50 40 30 20 10 0 0 ,b

78 KIR w 1987

7. Character of Market Cycles Not Changing

We have found filtered moves to be a useful tool for market analysis. In Marker Volatilirj;: Perception and Realit.v, we presented a table that listed every 107~ move m the post-World War II period and stated that by most measures, 1974 - not the current rally - was the most volatile or explosive. The December 6, 1974-July 15, 1975, gain was a 530~ climb in 150 sessions during which the average advancing day was 2.56%. At the 1800 level, that would be a 46-point gain per day.

We recently updated and published the same study from the inception of the DJIA. Below we depict the 85 rallies that have taken place in the market since 1915.4 The blue asterisk is the current move, which shows a 74.2yc rise that is 490 days (ended June 30, 1986) in duration. There is no visual suggestion that this is abnormal. In fact, the two largest moves - 96% in March-July 1933 and 93% in July-September 1932 - were accomplished in 90 and 51 trading days, respectively. We appreciate the marked differences in underlying economics and market structure, but our study also covered the 1950s 1960s and 1970s and we contend that the structure of this rally is not one of short, abrupt, trading-related moves.

Figure 11. DJIA Rallies - Duration and Percentage Moves, 1914.86’

1

loo - -100 .

.

I

(W .

OO- - 00

. .

B l c .

K 00 -

.

. - 00

ii

.

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.

.

.

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.

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20: ,* . l . \ - 20 *g, *,.’

4’ ‘# .

2.‘. 1 I 1

0 2oc 400 600

m

B n’ f W -. r

Duration o! Rally

a Through June 30

4 See Ra//y on Wa// Sfreef Augus! 1984 and Ra/lres and Declfnes 1946-84. Lsszlo Bmnyi. Jr., Salomon

Brothers Inc. December 1964. and Slack Marker Rallies. 14 Dee 14-15 Feb 34, Stock Market Declrnes, 30

Apr 15-19 May 34. Stock Market Ral/les. 19 May 34-16 May 86, Stock Market Dechnes. 18 Jun 34-24 Jut 84. Laszlo Blrmy,. Jr., Salomon Brothers Inc. June 1966

PEA JWFN&hW 1987 79

8. The Current Market Is an Investment, Not Trading, Environment

If an increase in short-term fluctuations and abruptness occurred, the premier investment strategy would be one of trading, turnover and short- term gains. This, however, is contrary to actual results of the past 18 months. Since the beginning of 1985, FW Woolworth has gained the most in the DJIA; Merck has been the second-strongest stock.

We recently wrote that the market is probably characterized by what we term the “Woolworth Syndrome”: Investors look for new ideas, group rotation and change in leadership;5 but the stocks like that retailer continue to gain, much to everyone’s chagrin. This might also be considered the market’s version of the “tortoise and the hare.” Since the beginning of last year, three of the top five gainers have been such stocks. We doubt that Westinghouse Electric and Owens-Illinois, like FW Woolworth, are perceived as “movers.”

80

Fiaurc 12. DJIA - Lerpest Gainers, 30 Dee 84-30 Jun 88

(30 DE& PllCr

(30 Jun 66) Puoentage

Change

FW Woolworth $10% $40 159 45% Merck 47 104% 122.34 Westmghouse Electrrc 26% 53% 10526 Owens-lllinofs 20% 30 % 09.44 McDonald s* 51% 73% 41 64

* McDonald’s was added to the DJIA on October 30,1985

Given the perception of volatility, commentators have overlooked the reality: This is a market in which investment has been a superior course. As Figure 13 shows, trying to time purchases and sales of FW Woolworth stock (even with perfect hindsight) would probably not have been nearly as profitable as buying and holding this and the other issues mentioned.

FiQure 13. FW Woolworth - 31 Dee 84-30 Jun 86

- 25

- 20

- CLOSING PRICE

SSee Stock Week, Laszlo Blrmyi. Jr. and J&e M Morrison. Solomon Brothers Inc. June 6. 1966

KIR JaJRM#M 1987

9. FW Woolworth - A Last Word

FW Woolworth illustrates another important facet of the current environment: Unexplained market movements are ascribed to derivative instruments. For example, on June 5, 1986, the stock rose by $2% in a 16- point rally that was “pure buy programs,“6 while the New York Times headlined “Late Program Buying Helps Dow Gain.” 7

Again, this movement overlooks the reality. This stock is not an ingredient in the XMI or OEX Indexes. The only program trading that should affect the stock is that of a purchase of the S&P Index where it is the 205th stock (as of March 3 1, 1986). A $iOO-million buy program would result in buying 2,100 shares of stock, which would be 2% of the average day’s volume, hardly the type of gain that was evidenced that day.8

To further illustrate our contention that derivatives are not the factor that they are widely thought to be, we examined the S&P issues of that day. Of the 20 largest stocks, only six outperformed the market, while four actually declined on the day. In addition, detailing the results of the XMI issues shows a conspicuous lack of strength in these names and this index - up 0.64yc - underperformed the DJIA’s 0.8776, which is hardly what one would expect if derivatives had been the major influence that day.

Fiaure 14. Performance of XMI Issues. 5 Jun 86

Lndlng Pwcenlogc P&C Chongc

Amerlcar Express

Al&T

Chevror Coca-Cola

DOV, Cbemjca'

$61 %; $61% 0.20%

24 1, 25 204

40; 4OYE -031 113YF 113 -011

56% 56‘;~ 022

El dLiPor: 86.< 867; 0 00

EastmanKodac 61 L 61 % 061

Exxor 59% 60 063

General Elecir,c 8 1 ;; 81 3, 062

General ~010~s 76 78 000

IBV lnternat~o7a' Pa;er

Johnsor &Johnsor

Me0

Minnesota Vng B Nlg

MobI: Carp

Phrllp Norr s

Procter 8 Gam,e Sears Roe3dk US Stee'

150 150ir 058

63 II 63 -040

69x 239 ;;; 97% 1.16

105% 107% 1.90

30% 31 0.40

682 68'/( -018

76'/; 77% 098

477; 48% 184 21 4c 21 3. ose

6 See"Abreas1 of the Market.' The W8llSfr8efJourn8l. June6.1986

'See New York Tlmes.Juned 1986

6 A Vs/ue h8 program would also cnclude the stock. but 10 an even lesser mtent

UA JWRNA#W I.987 81

IO. Group Rotation Has Not Increased

The earlier publication examined all of the moves in the airline stocks. We contended that this group was not having quicker, shorter or more abrupt moves. Since we maintain a history of every 10% rally and decline for all major market groups from 1974 to the present, we expanded this analysis to cover more groups.

Specifically, in this update the first five groups - listed alphabetically and not including airlines - were separated. Since the market is trading higher, we looked at the rallies in the various groups. We divided the absolute gain by the length of the rally (in weeks), which provided an average gain per week.

We ranked each group’s five largest average gains per week. The current rally was in no case among the top five for any of the five groups. For example, the largest gain per week in the aerospace group was 3.6%. From late October 1979 through February 1, 1980 (14 weeks), the group rose by 64%.

In Figure 15, we had intended to shade the current rally. Again, none of the groups is enjoying current rallies that would rank in its individual top five of the past 12 years.

Figure 15. Industry Group Movement - Average Weekly Percentage Gains of Five Largest Rallies, 2 Jan 79-2 May 88

Figure 18. Aerorpace Group - Largest and Current Rally, 20 Dee 74-18 Apr 88

BegInning En;;? Numbor Q8ln Date of woekr v?El:

80.46% 20Dec74 6451 26Oct79 5471 llJun82 31 50 31 Oct80 21 02 19Mar82 31.80 11 Oct85

27Jun75 27 225% 1 Feb80 :: 3.67 5Nov82 217 2Jan81 9 3.23 7 May82 7 2.80

18 Apr 88 27 1.05

m!?i .IGmN&M I987 82

Technical Analysis: Institutional Trading and Money Flows The Lessons of Stock Week

by Laszlo Birinyi, Jr. Susan 1. Field

Introduction

On J8nurry 4,1980, we begrn publishing 8 weakly-compendium of mrrkct commcntrry md strtistical highlights: Stock Week. The purpose of Stock Week h8s rlwtys been the following:

l To make institutions aware of what happened lo the stock market during the week, by presenting an unbiased account.

l To make portfolio managers and analysts more effective by directing them to those market sectors where sentiment was changing.

l To present institutional attitudes in a factual way. In a market that is more and more dominated by the behemoths, tracking these institutional giants is not only important - but vital.

l To give traders a tool for tracking current trends, rather than telling them where a group or a stock might be in the “intermediate term” or ‘long term.”

The experience of Stock Week hrs trught us thrt there 8re some rignifiunt technic81 implicrtions thrt cm lnord the institution81 investor mrny opportunities in money mrking rnd, perhrps even more importmtly, money swing. These implicrtions hrve come rbout Muse of the following:

l An important structural change in the market. Specifically, the increased institutionalization of the market. Our firsiissue of Stock Week showed that large block trades were 27.70%# of all stock market activity, with the SO-day trend for that week being 26.72%. The week ended April 16, 1982, showed blocks up to 43.55% of all volume, with the 50-day average being 42.37%.

l Improved monitoring capabilities, including the measurement of actual money flows for the market and subsectors of the market (including individual stocks). These new capabilities are detailed in this report.

In presenting the technical or foreasting use of both the old 8nd the new tools, we believe the best 8pprO8Ch is to look rt three 81~1s.

1. Block trades in individual stocks.

II. Block trades in industry groups.

III. Money fiows in the market, industry groups, and individual stocks.

KITA JOUHW@W I387 83

I. Block Trades in Individual Stocks

The idea of looking at block trades of 10,000 shares or more, and, more importantly, the associated tick, is not an original idea. Most technical efforts make some attempt to incorporate block trades, but these statistics are not easily obtainable. For those who suggest that the mere difference of an eighth or a quarter on a 540 stock is not important, we would point to the SEC’s Institutional Investor Study that monitored more than 8,000 blocks in an 18-month period and concluded:

“From the analysis of all minus- tick blocks, a new, lower level of prices appears to be established after the block trade. On the average, prices come back slightly (about 0.25%) within 10 trading days after the block, but are still below the original level of prices by more than IS%. Conversely, plus- tick blocks tend to establish a new, higher level of stock prices. . .

Furthermore,. . . (stocks traded in blocks) seem to set a persistent, higher or lower level of prices, depending on whether the block was purchased or sold. Thus, the results seem to indicate that the price changu arise from changes in the underlying values of the stock.”

These are not necessarily immediate trading situations, as there is often significant lead time before the event. In the October 17, 1980, issue of Stock Week, we pointed to the activity in a major oil stock.

“One of the internationals, however, which does appear is Texaco. Last week, of the 39 blocks in the stock (compared with a IO-week average of 28 blocks). 21 were effected on upticks and only 3 were done on downticks.”

Flgun 1. Prteo Yovomontr: Texaco and Cult Oil (1980)

84

While this development was late in the energy cycle (a similar situation for Gulf Oil was noted in the February 22, 1980, edition of Stock Week), it did show the interest in Texaco. That week. the stock was up 1% points to 538%. A week later, Texaco rose another point; but 5 weeks later, it closed at SSOM. Thus, adequate warning had been given by the market, and a large position could have been accumulated in advance of the sharp move upwards.

Thus, we would continue to recommend that investors follow block trends in individual stocks. However, we would especially focus on stocks which have the following characteristics.

1) Stocks that experience blocks indicating institutional purchase with resultant price appreciation, which is a result of a known piece of information (e.g., a corporate announcement, analysts’ increased expectations, etc.). This price move will usu8lly be retr8ced.

2) Stocks that show a divergence in their block trrdes. Divergent blocks 8re those where institution81 sentiment is contnry to the prttern exhibited by price l d often volume. One of the more dramatic examples of this was the trading in Americrn Cyrnrmid on December 10, 1979.

Fkun 2. Block lrrdw In Amwlcrn Cvrnrmld (10 December 1979 i

n.v.5.1. ILOCK 1110~5 ~11ON1701 DAlL or RUM - lzllIr7r. lUf5OAY __-__-.-_.____._--______________________--------- DAIE OF lIADt5 - 12~1B~79. nDNDAY

--~~~~~~-~~~~~~~

111 Yf CYSIP I55UU 10111 VOL. CLD5E Clllltt llllf “---------;O~LOCK 12ADE5

PIICE CWAIIOL L/S

UY bl 615J211. HUICA~ CYAMMID CO vta.u@ JI.03 2.125 ::::

t:::

tt::

::::

::::

i:::

1:::

::f:

::::

I:::

i::: 1Alb

::::

t:::

::::

t::: 150

25.500 .a0

::.t:: .ee*

JO:251

On December 10, 1979, rumors swept the New York Stock Exchange regarding the potential acquisition of American Cyanamid by any of several corporations. On that day, the stock was up 2l/s points, with volume of 920,800 shares. Figure 2 lists all of the block trades in the stock on that date, including time of day, size, price, and change from the price of the previous sale. The first block was at IO:04 am, when 12.700 shares traded at 529!4, unchanged from the price of the last sale. The next block was 14,200. 81 g30I/c - again, unchanged from the last sale. By dayend, there had been 32 blocks, but not 8 single block took plrce on l uptick.

UA JaJRM&W I.987 85

in effect, institutions were selling the stock to the public. The institutional money managers were saying that there was no basis for this rumor; thus, institutions sold at these higher prices. Whether or not they were right - subsequent events, in fact, proved they were - was not important. Also, the market’s straightforward conclusion was much more important than any that might have been made by any Wall Street chemical analyst.

However, institutional accumulation that results in a stock’s price rise is not necessarily a positive trend (unless, of course, someone has made a takeover bid, or the stock is up $20, or there has been a massive oil discovery). For example, in the May 15, 1981, issue of Stock Week, the buying in Lockheed was highlighted (18 blocks, but none effected on downticks). The stock rose S6 as investors reacted to positive research opinions on the stock which had been voiced during the week. Lockheed closed at $39 that week, then traded up to $42 in the next week or two, but shortly thereafter began a slide and was at $33 within a month of its $42 high.

It is for this reason that we resist making an index of the names that have appeared in the institutional buy/ sell lists in Stock Week. In many cases, while a stock meets the criteria of unusual block activity and imbalance of blocks to either the buy or sell side, the pattern is not necessarily indicative of a positive or negative trend. The purpose of those lists is to make readers aware of what is transpiring - not whether we agree or disagree with what is happening with individual stocks.

86

II. Block Trades in Industry Groups

If individual stocks must show unusual patterns to be included in our statistics, groups need not. We have found that the ten-week average of block trades, as outlined in the section of Stock Week entitled Industry Group Data, is an especially helpful technical tool. What these statistics do is to signal changes in sentiment usually far in advance of fundamental changes. The drugs have provided evidence of this.

The ten-week average of blocks in the drug group turned positive in the week ended November 13, 1981. This pattern should have suggested to the analyst, strategist, or portfolio manager that sentiment toward this group was changing and attention should have been directed toward it. Although the group has, since then, only undergone slight price appreciation (5%). it should be noted that the largest stock in the group - Merck (which is 17$& of the group) - is actually down $2 during this period. Thus, o:*erall, from November 13, 1981, to April 16.1982, IO of the 1 I other S&P drug stocks advanced, with Eli Lilly climbing from $5 I to $62, and Pfizer rising from $48 to s57.

Flguro 3. lnrtltutlonrl Gontimont: Drugs

10

-151 1 I I 1 I 1 1 I Fob Mar Apr May Jun Jul Aug Sop Ott Nov Dee Jan Fob Mar Apr

1981 1982

Another group which exhibited the same reversal in market sentiment long in advance of fundamental changes was the autos, which saw their blocks turn to the plus side in early December 198 1.

(clwra 4. lnrtltutlonrl Sontlmont: Automobllor

Fob Mar Apr May Jun Jut Aug Sop Ott Nov Dee Jan Fob Mar Apr 1981 1982

IfA JOURW&M I987 87

88

This type of analysis - which we refer to as zeropoint’ - cannot only signal changes; it can suggest that there have been no changes. For example, the international oils have been undergoing distribution for many months. While the group, from time to time, has afforded trading opportunities from 1981 onwards, the basic pattern has been institutional selling, long term, near term, and present. Any decisions to accumulate these stocks would have been the market equivalent of swimming upstream - i.e., fighting the tape. Furthermore, being aware of institutional sentiment should be a time-saving device as it suggests that fundamental reports regarding OPEC, spot prices, or whatever, are not that important as long as the tape shows on-going selling.

fkun s. lnauMlorul oentlnwnt Intofn8tlon8l Ollr

-181 1 I I , I I 1 I I I 1 I t h8oE Feb Mar Apr May Jun Jul Aug Sep Ott Nov Dee Jan Feb Mar Apr

1981 1982

While there is a high degree of correlation between block sentiment and prices for most market groups2, we have found that in some cases there is a considerable lag between the change in block attitude and the change in prices - especially in a group that becomes severely extended, on either side. However, we have found that by measuring the change in sentiment or momentum, a much greater degree of accuracy develops.

By merely looking at the points where blocks turn either positive or negative, the investor could be whipsawed. However, by measuring the slope of the line3 (the percentage-point difference between upticks and downticks over 50 days) this problem can be avoided. The technique is straightforward. If blocks are - 10 in week one, -8 in week two, -6 in week three, and -4 in week four, then:

l Week one’s slope would be [34-10)/(2-l)] =+2/l

l Week two’s slope would be [-H-10)/(3-1)] =+4/2, and so on.

l The longer periods - weeks three and four - seem to yield the best results.

1 Zoropolnt rmflocta I 8conrrlo whoraby the ton-wash l rago 01 block tndoa cr~#~s thm arotin0 in dthor direction (Lo.. tuwu poritivo or nogativr).

2 Among thr mrrkot groups whrro thir l ttort io of little help era the tobaccas (when them an only throw

otockr, ot which ona is e major brewer). and office rguipment (whrro the group ia too divot, I8 it

inclrdoa mainfnmr manut~cturars. office copirn. prriphoral dovicr. etc.).

J h4athomrtlully: (m’(y~y~Y(x~rl)l

(I) = dope. ylyl = chmnga in aontimont.

x2-11 = number of weeks.

MIX JCXMWhU 1987

Figure 6. showing both zeropoint and slope analysis for the conglomerates. tells of the extra dimension that the second technique could add. The slope approach turned positi\re on March 26. while the absolute number of blocks for the ten-week period has yet to do so.

Ftgure 6. Instltutlond Sentiment: Conglomenter - Zwopolnt versus Slope Analysts

* ;y- -_..,.. -..:-:. 4 ,...

. ...’

,... .:. . . . . . .

+ BO

. . . : '. . . . 10 .t

Q -‘- . .

‘.... ,:. . . . . . . .:. --1

s-2- ‘.....‘._....,,, ,:’ . . . . . . . . . . . . ..’

. . . . . . ,: -3 1 I I 1 1;

Jun Jul Aug ,&w Ott Nov Dee Jan FeblQOYar Apr

Flgure 7. Conplomenter - Yomontum Analyrlr

Yomwtum - Up

Slope over 3 penods

Slope over 4 periods

UP I of Slo&I W kll Conglomonlo~ Up In Orwp

25 Sep 81 31 Dee 81 729 010

2 ocr 81 31 Dee 81 7.40 410

Zeropomt analyss 27 Nov 81 5 Feb 82 -4.66 110

KX’A JCWlWS&M 1987

Flguro 0. Conglomorrlrr - Cumnt Stock Yomontum (Up)

Gulf 6 Western

28 Yer (2 1rApa2 CL $15 s15n .83%

IClnds 29% 30 127

Ill 25 25% 3.00

Littonlnds 45% 49% 9.92

Northwest lnds 61 66% 9.43

Teledyne 116 122 517

Tenneco 27% 28% .90

Texlron 22% 23% 7.91

S6P400 124.14 129.77 4.54

S&P500 111.94 116.61 4.35

Certain caveats in these techniques, however, do exist.

1) The momentum technique does not appear to add any value to groups where the zeropoint correlation is relatively strong. Automobiles, for example, as discussed earlier, did not show appreciable improvement using this second technique.

2) While the momentum measure may seem to encourage trading, we feel it should be monitored for an environmental setting, just as investment decisions are currently made first in an economic setting, then by sector, and so on.

90

III. Money Flows in the Market, Industry Groups, and Individual Stocks

Despite the recent growth of institutional activity and the importance of block trades, there are some omissions - specialists on the NYSE, member firms, traders, and the public. (Also, the nonblock activity of institutions, although we doubt that this differs in direction from that done in blocks.) To close this window, we have begun to track money flows.

Money is the major mover of stock prices; hence, the inordinate interest in cash positions, cash flows, and the like. In tracking money flows, we followed the same general rules as for tracking block trades: upticks are inflows; downticks are outflows. Thus, by this measure, if 1,000 shares trade up a quarter and 200 shares trade down a quarter, we would show a net inflow of 800 shares (times the price of the stock).

Inasmuch as this detailed information has only been available since mid- June 198 1, a thorough review will have to wait, as there is not sufficient data to calculate a ten-week average and monitor its rate of change over a meaningful time frame. A statistical relationship, however, does exist between net money (the difference between inflows and outflows) and the market. Such flows correlate with changes in the NYSE index at .7685, as Figure 9 indicates.

Flgure 0. Strtlrtlcal Rdrtlonrhlp: Money Flowr vw8ua NYSE (June 15.1961 -Awit 16.1962)

$40 15400 Independent Vanable Net Money Dependent Variable. NYSE Index ’ . 300

l . . 200 . m

l . .

-100

. -400 t-400

-3 -2 -1 0 1 2 NYSE (Daily Change)

The method we have used for tracking daily money flows is to keep a cumulative running total of the net money numbers. The key item to watch is the slope of the line. From our vantage point, the most important consideration is that money is coming out of the market. Rallies not sustained by money should falter. For example, the market rally of late September 1981, when the market rose 50 points, was not accompanied by an upturn in the money line. Instead, there was selling into the rally - and the rally faltered.

KIR JoLEWWkM 1987 91

FlgurolO.Cumulatlv~ NdYonoy vwxu8 NYSE (Junel5,1981-April16,1982)

02-

6obI 1 I 1 1 1 1 I ’ -12,ooo Jul Au9 SOP act Nov Dee Jen Fob Mar Apr

1981 1982

This concept can also be used for industry groups. The cumulative net money line for the electric power companies, presented below, illustrates precisely just how predictive discrepancies between price and money flows can be.

Figure 11. Money Flow.: Eloctrle Poworlndox (June 19,1982-April 16, 1982)

S6P 500: Electric Power Index

In July 1981, there was a large inflow of funds, even though the Electric Power Index was falling, indicating strength. During September and October, the same circumstances prevailed (i.e., falling prices, monetary inflows), and again a rally was forthcoming. The early part of 1982 also saw the money line rise in the face of declining prices, setting the stage for the utilities rally that we are currently experiencing. The ability of the money line to remain upward sloping when paired with a declining price level is dramatic, because it signifies that there are buyers who are truly buying on weakness.

92 mn iIamW3W 1987

This type of analysis can also be used for individual stocks. Again, WC measure the monetary value of each trade to determine whether money is coming in or going out of the stock. The key points regarding this type of analysis are as follows.

1) Divergence of money and prices creates the most interesting opportunities: such divergence shows either true “buying on weakness” or “selling on strength.”

2) Where there is no divergence, this can inform the investor that the stock’s rise is truly a function of buying, or that the decline is a matter of real selling - not because of a weak specialist, buyers pulling back, rumors, or “air pockets” in the stock.

3) The is no indicator telling whtn I; trtnd will terminate. Thus, if a stock is going up because of buyers, the buying will stop when money no longer continues to flow in. When that might be, and under what circumstances it will be, must be left to others to decide.

A. Rallies Not Con$irmed by Money Ffows

Flguto12. Monry Flowa: Exxon(January4,1962-April16,1962)

1. ..I....I....1....1...1....1....1..-.'....'....I....'...'-.- 8 15 22 29 5 12 18 26 5 12 1s 26 2 8

Jxn Fob Mar Av

As shown in Figure 12, the monetary flows in Exxon have been negative since the beginning of 1982. Market rallies in Exxon (as in late January, when the stock went from S29 to 5301%) were not preceded by an upturn in the cumulative net money line, but saw, instead, a steady outflow of money. There was selling into this strength because the market’s underlying attitude toward the stock had not changed. For the analyst whose opinion is positive on the stock, the picture above should suggest that reexamination may be necessary. Traders should view these happenings as a signal to be passive on buy orders and to truly “work the order.” Sellers might be advised to aggressively take advantage of any strength which might occur.

M!rA v 1987 93

B. Declines Not Confirmed by Money Flows

Fipun 13.Yoney Plowr:~omrrl Yotora Uanuary4.1982-ADril16.1962)

42-

Jan Fob

20 l9 26 2 8

Mar APT

General Motors presents an interesting example and illustrates an overworked market phase: buying on weakness. From the beginning of the year through February 23, the stock went from S38H to S34tA. Yet, during this time there was an actual inflow of money of just under S3 million. The absolute amount of money is not important, but rather that there was buying in a stock that was falling by more than 4 points.

Eastman Kodak is another example of the divergence that tells its own tale. Until February 26, 1982, money and price were roughly coincidental. However, after closing at S69% on that day, Eastman Kodak dropped two points in the next ten trading sessions. Now the portfolio manager, analyst, or trader was faced with the dilemma of what course of action to take. Clearly, the monetary flows suggest the stock’s strength as does the actual data. March 8, when the stock fell two points, should be especially noted, as $3.9 million net new money was committed to Eastman Kodak.

Flaun 14. Eastman Kodak - Not Yonov

Yueh 1n2 ““yzlr l rka clung.

1 s4.314 Sl

2 7,362 'k

3 (1866) VW

4 (rsle, (W

5 7.966 w

6 3.660 (2)

9 12ea 2%

10 2.630 (tic)

Figure 15. Money Flowa: Edman Kodak (January 4. 1982-March 12. 1982)

$76’ $40

74-

721

84...1. .-I I . ..I 15 22 29 5 12 19 26

..* 20 5

Jm Fob Mar

Figure 16 depicts the outcome of this before and after story, as Eastman

Kodak’s price rose 10.7% to S74% between March 12 and April 16.

Flours 16. Yonov Flowr: Eaaimrn Kodak (Januaw 4. 1982-ADrill6. 1982)

74-

-20 r -. 66- E

‘. ..( ..’ ...I .‘.... ‘--.I---.’ ,._..I __1.)-1 ._I 20 8 15 22 29 5 12 19 26 5 12 19 26 2 6

Jan Fob Mar AVr

95

THE STOCK MARKET AND ITS LONG TERM SECULAR UPTREND ORlGlNAllNG 1982

DOW JONES INDUSTRIAL AVERAGE 1887-1988 STANDARD 6 POOR’S YEARLY OBSERVATIONS INDUSTRIAL INDEX 1872-l 986

%

G s

OCM1*10I4 NDNENTUN SECURITIES 5.15. 3

GRAPHICS

tson MOST RECEW

OEC 31. tax

mn CLS- rau 35

TRENDI !m 1779.543

TURN:

llh2.620 PRICE *I,:

205+3

UPTRENO SECUWITy ONIGINATION

0 4’hYm

,sw ,907 ,s,, a?7 ,831 ,wr tew low wr7

Secular uptmnds have been designated I, 2 and 3.

TNE STOCK MARKET AND ITS NEW LONU TERM SECULAR UPTREND ORtGtNATtNQ 19S3

~pr~4to4~~~r~~cydsbegsnAugu~i982andisnaw52monlhsold.Thecycleorlginstsdanewaecular~rend(orbadsadstadcswhtchIslike)ylopenist

lhMugh lnl0 the 1999%.

Through the 29th century the stock markets’ secukxr uptrends that deue@sd hem “wIdowa of lnwvdon” pushfed for 10 you8 (1919 to 1929) and 27 years (1941 lo

1999). The current secular uptrend o+ated in 1992 and is already 4% years okt. (Refer lo Uaw 100 Year chart abnve.) *np the trvo past secular uptrend lima frames to the 19fJ2 bottom woukt 9tve tha currenl secular uptrend a life span throu@ lo 1992 or 2909. Avera9e duration tor these two past secular uptrends would ptaca the secular

lop at the yeer 2909. Consideralkm ot the Trend and Cycte disciptine In respact lo lha ton9 term trend smoothing line and the price momentum data oI tb 100 year chart

suggests that the secutar uptrend may persist lor at least annlher 12 obsewa~bns - that is. 12 years betore a secular top phase takas ptace in the 19952999 period. We have one to three 4 to 4r/, year cycles remaining in the le span ot the currenl secular uptrend. The 1992-7 4 lo 4% year market cycle occurs al a transiltcnal time between two eras-lhedamisedlhe4lhtory etxmomic -Kcndra~iett-wave and the bklh of the 5th kng ecenomic -Kondratielt-wave.

MtSToRlcAL PERspEcTlvE TO THE 1992-7 4 TO 4’A YEAR CYCLE

Shamprlcesh~~ncedsohrandfast~hcydethatmosto(ushaMloslhk~l pmpdtve. To keep lhin@x in pWpXHWWMlOtthefONOWlng:

l Trend PersIstermy. Market Tachnktans use the tottowIng meesurlng approach - trend duratkm nat internrpled by a 1996 or mcra price ml mcement. There have been onty

two occa&na this century when the stock market has advam~rd Ior 24 months or longer without a 1996 decline.

September 1953 lo September 1955 - 24 months October 1962 to May 1995 - 31 mcnlhs (1953-7 - 4 to 4% yew cych) (19924 - 4 IO 4% yeu cych)

~~ar~uplrendo(~l920’sdoesna(hweacydelhatquallfies-theclosestoneisIheadvancobeglnnlngOcloberl928adlhsl~Int~~byacanscl~ot more than 10% in Cclcber 1927.

Falhlr~~~~rrhlch~hJu)r’~hr~(ar~~24mon(hrrl(hou(al0n~ --mr*lngiIIhOWd --crnhyl

l ChnIemd Advmdng Ye8m. Sinca 1997 the Ucrw posted gains for tive cunsecutlve yean as fobws: 1924 lo 1929 and 1982 to I-. The Standard 6 Pocr’s haa never

before adwwd for five cuwcullve yew - 1992 lo 1986 was the Hrst such occasion.

STOCK MARKET SCHEMATIC 1940 - 1991

ILLUSTRATING THE 4 TO 4% YEAR CYCLE AND UNDERLYING SECULAR GROWTH PATTERNS WITH MARKET AND ECONOMIC THEMES

l FROM 1941 THROUGH 1992 ELEVEN CYCLIC LOWS ARE INDKXTEO ON iHE SHARE PRKX TRACK THEY DESIGNATE THE LAST TEN 4 TO 455 YEAR CYCLES THAT OCCURRED FOR THAT 41 YEAR PERlOCI

l A CYCLIC LOW THROUGH 2ND OUARTER 1987 WOULD COMPLETE THE ELEVENTH 4’4 YEAR CYCLE AND SET UP THE CONDITION FOR A NEW 4’A YEAR CYCLE.

l THE NEW CYCLE STARTING 2NDt3RD OTR 1967 WOULD BE THE SECOND 4% YR. CYCLE FOR THE CURRENT SECULAR UPTRENO ORlGINATI$5 \N 1992.

’ Next Qdii Bona likely 2Ix30 1987.

-Thmtoa new 4 IO 455 Yr.

cycle 1907-91.

SHARE PRICES

1

THE KONDRATIEFF LONG WAVE

ECONOMIC LONG WAVE

The economk long wsve, or Kondmtbff cycle, is a 49 to 99 yew fhetuatlan in capital ~rodudm, t-1 hmowlon and pmdwMty. Starting with the Industrial Ftevotutiin we have experienced four m economic waves of major expansion (inflation) and contraction (deflation). The approximate dating for the long economic waves and the dominant forces thereof are set out in the accompanying table.

Communkatlon

NOtlOMl France and Econombs Britain

Britain Germany United States OrientJapan- United States

ThOlongWOVOhwCWSSdthSf#fOOtCfOpdOM ot~lb30’s,lb90’sandthe1930’s.A~a~ ottl-mJ-* lndushblpbntd~~brebulIt around a new technob9kal mlx ot Industrbs at about 59-year Intervab. Such a tmnsltlon b bqjlnnlng at the present time. Todays succedul lnnovatlons will deflne ths character of the next fang wave.

TRANSITION TIMi BETWEEN ERAS. “The Soft Landlng Cmcapt”

TbIlOWWOVOdTWhdOgbS b not msourcdntenslve. The other detbtkmry oontmctfon per&da of the long wave were always dominated by declining commodity prices based on resourceintenslva technology. Furthermore. it is likely that the rapidly spreading effects of the information age will shorten the time required for techno-economic revival and thereby, give us a fragmanted shortened “soft kmdtn#’ defWonq coneoWn. The kng wava depmssii is much less severe whan there is significant entrepreneurial activity in the economy. Thk was the case in the U.S. and Gennany in the 1870’s and 1880’s and it is true in the U.S. today.

TlMlNG THE LONG WAVE - ECONOMlC LOW - 19977

Using the kmg wave turning points prepared on the economy by Van Duijn,’ hiiodcally ecomnniclawsinthelongwavehavebeenspaced41.49and53yearsapart.This places the last economic K-wave low at year 1939, and implies that the next few would be 1977.1995 or 1999. The next low may also be estimated from the past intervals between a hiih and the next low. These have been 32 years, 22 years and 19 years. That would position the low in 1999, 1997. and 1974. Excluding the 1974 year that has already passed, the average of the three estimates placed the NEXT ECONOMIC LOW POINT IN 1997.

Thekmgwave economic few is due to bottom out through the 1997-1990 period. Forrester” points out that the burden of debt on governments. companies and indtkfiduals is not being liquidated and that widespread defaults and business failures are likely to occur at and following the economic low. Ltqukfation of debt may be very rough on some individuals. industrfes and natfons. (Debt repudiation is likely in tha case of nations.) Overall the effect d tha afommentkmed is likely to be “cushii” by tha strong entrepreneurial environmant already operattng In the U.S. The innovation leading to the 5th long wave is already oparating and should take off through tha 1999’s - note that only some indiiuals. companies and nations will take advantage of the 5th long wave.

KONDRAllEff LONG WAVE INFLUENCE ON -ES

canhsabndthe4thbn9 eccnomkwavebflng3tomecommodammal)ly~elsa ~ytaoerrMch~~h1915.The~bMcdyK,pada~Mome~~

1990%.opooelnothbtfWlldbthl3WW5mbng~ Incluence*hlch~ninIheea~l1900’s.ThbbnpwcMtaoo~Imrkmouatbn.~~lndushy

whkhIntum~ahobntwmmWlorutHbingfaW tMtOfbbudensgytloWEOS.T~ ree+xmetomealommsntloneddiwNsekngtenn eamcmk In(luences b

cummttyloundlnthe pmckwmmd sector. Here platinum b buoyant. numved by new technokgkal unee. white the bebnw of matab are rebth&y dormant and subject to

theconmctingtorcesofthe4thbngeconomkrvsvs.

~M~lTlES - LONG TERM TREND FORECAST - 1975 COMMOOITIES - LONG TERM TREND FORECAST (JULY-1999)

..7”‘.7

SECULAR UPTREND I ORIGINATION I I

1930 1940 1950 1960 1970 lee0 1990 moo 2010 YEARS

MlANcEoFws’THRouwws-TwD9cENAmo!3-DEFl.ATlDNoR lmNFLATKlN-RERITKm-TK)Is

Theobjec(dour1975~(char(exhiMtabove)muto~ ~probaMecwnetok,Wtsndwlngthedblnlla(bnary~~phsseol~4rnbngearomlcwavs.

Adjacent chart (mvbsd July. 1996) Is mae sensitive to qrtk wave mythms and at the same thne attem~s to detlneate Iwo posslbb SOMMO~ for the bdance ot the 80’s through

Into the 1990%.

-- casMmbnlsadmgtoDEFLATwN

-MWdU-ISUAIlgtO -TloN-REFlATloN~ATloN

These amcspts am lnmqorated in the adjncant commodity market achematk.

caNcLu9loN

l A nulgnitude failure by me cunlmt amlmodlty cycle rnmugh 1987 enhancss the

~~lorme4mlone

economk wave contractkn to contlnub into the aarty

CoMMoMTlES MARKET SCHEMATIC 1932 TO 2909 Showing Secular and Cytlk trod Infhmnceo

Hkely to me from 1999 throqh 2ooo

Likely cuurs(I hJlkwing tar Base. Disinllatim - wbhn Fibres and Energy

prke level

19324 SECULAR UPlflEND OAlGlNATtON

THE STOCK MARKET AND THE NEW LONG TERM SECULAR UPTREND ORIGINATING 1982

mw mw cvatc PosuenmEs w8cw3rt TOZOlBO7THATFAUwrrrmSTHELOWERlERMSECUURUPTREM)

LoNGTmYTRENo

MOWNLY CHART oow JONES lNmJ!aTmAL AYERAGE loo moN7M!3 SM. 39,117a TlmomM OEC. 31. lrn

For perkdkily of prior cye@s 1950-m refer to ChEctOllpage8

----I ---- ur(aU’hAyucydkJunctur@ Possible startup Wne for new c@ wilhin secular upmd. Secular uptrend Is likely to ptmist through inlo mk% or lel*19Ws.

Mar. 1979

SECUIAR UPTREND ORtGINATION Augus11982

CYCLE - 19@7-01- A NOW TM!S. THEN THAT STRATEGY

EXPECTATIONAL - SUPERIOR PERFORMANCE - SECTORS, GROUPS 6 STOCKS

LOW TERM CYCUC FOBSIBtUTIES WWNIN TME CURRENT SECWAR UPTREND BIAS

Cyclk tap Nov W-Jan 87

SEEN ON AN INTERMEMATE TREND BASIS &HA 2200-2300 I MabrSeaff3haw1cY2a87

pqsEgw

\ Low SECtlIAR UPTREND July 64 EL4 ORIGINATION tmmAUQUN1962

LONWk*COUW: Summer 19W cycb mild bear phase la 1-7 tsm

UPTREND SECULARITY INFLUENCE ON THE FOUR TO FOUR AND ONE HALF YEAR CVCLE

THE EFFECrS OF UPTREND SECULARITY Incre~dnguphendsecubrltyladstochangetheprlcemoNa,olacye(e,haa~kinto~Mkwlngmalf~ price models: exponential. linear. and combination (quadratk and llnenr aunblned).

n /l/rsl wAoR4llc EXKJNENTIM LINEAR fxMEuNATioN

Cyclesaremessured~~totmugh.The~nmwnrtb~l)edacyclswan, campomnt. The elfecl 01 dominant secularity is to change the duralbn of bull and bear phases (skews) Win the cycle wave axnpnnen~. Secularicy alters tfw duration for the bull and bear skews (phases) but W does not after the duratbn of lhe four IO four and one hall year cycle.

NORMAL CVCLE BEucuRvEMooEL uNllERsEculARu~ INFLUENCE

Intermediate

Trend Waves are numbered

Ourdra(k~banidealked~kmclrk~cydemodd.Ibsymmehlcalanddbpl~the~durcltbntor both bu(( and bear skews wilh 3 intennediaIe uplegs and 3 intermediate trend downlags (on centre picture).

i -.---4b4’~yem --

UpWldWCthdtyOtlnluncesIhe-d~ bullsk~to aflcmpm4Io5hllamediatetmnd waves.ThebearskewlsIherlrfJdumd1oone or two lnlermedlate trend downlegs

OJIA (39 lNOUSlRIALS) MONTHLV HI-LO. Wkmtmttng 4 to 4lh Vesr Cycle. Avsmgs owsllom Last 9 cycles 1949 IO lH2 Is 49.8 months. AwJmga

Tapphme19W38lobn~bmknnssahr.

Bull Phmo Skew la 35.4 m Avemge Bear Phmsu Skew la 14.4 montha. I I

,sm ‘Bs, ‘ma lam In4 ISM tm, ‘SW lw8 ls5s 1* I”, ,u 1sN la4 ‘me INS w.7 1w WSD lwo 1.71 r*n tm w74 1

ANALYZING SECULAR TREND DOMINANCE FOR THE 1992-7,1997-91 - 4 TO 435 YEAR CYCLES

CYatc PNA$Es WmuN SEaJlAR UPTRENO - caup-stock~atkn ledng to shal axmdklallng bear phases are caammmk lortllesacubrpNlod.Longtermbear

phases am llkdy to baams mom ampressad in duraIion falling wdl bekw that d 10 month% (Avwage Bear phase b 14.4 months - sw model oppoalte page - “Under

Secular Uptrend Inttuence”.)

Tol9B4,BankdMonheatlsanexampleddomlnmt cyell rwponw. moving to secular up4mnd domlnatkn. Forthecurmntcyclkbearpheseapriceconsdktation hasapemtadtorHmlast12months.

WALMART STORES

A t@cal linear secular uptrenri showing minhnal cydii responseb

MORE ON SECULAR UPTBENB BOMtNATtON

CawafExponahtBucularUptmnd.

CasadtmndmaaxbdmbrOugM~bytha lnMncedthadamhanl mcuhr u@mnd.

MSlNRAllON - REFLATION COMES EARLV TO CANADA

%

5

During 1986 me Canadian market hecame fragmented. DefbMrlary bardkiarbs recoded cyclic top phases while inflationary bewfkbdaa approached or formad new cycfk bottom phases. We classify Ihls situatii as a Iwo tier marketplace.

THE TWO TIER CANADIAN MARKETPLACE FOR 1987-9

~Tkr:TheRn(tierbpasltbnedInabngtermcyclkl~phase.ThisactionkwelldisplayedbythebroadmarketTSECompodlol~xad~~24o(the~graups and subgrwps of the TSE. Tha New York markel breadth (ADL.22 - cfwwl shown below) refkwts a similar brig &arm cycfii position as do most U.S. groups and stocks. Many international markets show a similar fang term cyclic lop phase reading.

Sacond Tfw Tha Canadian second lbr is expressed in the breadth chart (TADL.22) on the “T” databank (charl b&w). Hera lfm lrand raadlngs shaw a reverse cyelk pklum lo that displayed by the Canadian first tier. A long term cyclic botlom phase is forming and is likefy lo regisler al E year bws. Tfw Canadian breadth is similar to the perfom’tanca of the energy rebtad saclw and - mining stocks. 3 groups and sufx~roups directly fit this picture with another 17 groups reffecling similar aclion IO lfte breadth picture of a baar phase for the last 18 months. We note that the Australian market has developed a similar two tbr feature with the deflationary twtaficiarbs topping and hearfsh and the nalural

resources and gdds enjoying counter trend hull phases. (Canadian groups and slacks pages l&14).

1ST TlER CYCLE TGPPfNG 2ND TfER Bo?-lOMlf4G OUT ANDEOR PURSUING A NEW BULL

Gmupaflllkqlhe~l~opS~aned024Gm~pa-34.22%mlgM:Managanent toe. 7.gl.plrMsMng6Rlnwng3.78.~6Faaa~2.89.~~2.47. FinencblMgt.2.2o.Foodslona1.91.~1.4o.Tnat.ssvings~Lmn1.34.prapertyMgl.1.34.~~1.38,lnswanc~ .n. Ckthing Stores ~32. Food Procasing 73. Rmadmhg .64. Auto .e& lrwasimanlcb9. .M. Packagkg hoducts .57. Cabb so. Dapt. !%res Sl. MeIal Fab. 39. c%amkak 36. whok@m 36. -34. Household Goods 25.

WategyzUqddmeatUmednxtfntemmcMa wandto~wpactadFabruay1987. v thm@l latand Gtr. 1w7.

r e s

105

DISINFLATION - REFLATION COMES EARLY TO CANADA (conU~

FITTING THE TWO TIER MARKEl SCENERK) TO THE BIG STOCK WEIGHTS IN THE MAJOR NORTH AMERICAN STOCK INDICES - DECEMBER 1986

,. 2. 3. 4 1. 6. 7. 6. 6.

to. 1,. 12. 15. 14. 15. IS 17. to. (9. 20 21. 22. 23. 24. 2s. 2s. 27. 2s

7em 420 4.0, 54s 201 223 2.23 2 4s 2 IO 205 2w 1m 1.W 1.w (3s 134 122 1.w t.1. t.1. 10s 10s 1.W 087 OlWJ OS4 OW 0.73

3 3 3 2

i 3

: . 2 3 3 2 3 3 3 2 . 3 9 3 3 3

1. 2. 3. 4. 6. 0.

:: 0.

10. 9,. 12. 13. 1.. (5 1s (7 1s. w. w. 21. R 23. 24 2s 2s 27. 2s.

4.4646 2.04 2 1s 16s 1.4, 1.w 122 10s l.Of 066 0.83 OS2 091 0.66 007 0.W 08 0.76 0.m 076 076

i.z 074 0.73 0.73 0.R 0.7,

3 2 2 2 2 3 3 3 2 2 3 2 2 2 2 3 3 3 3 2 3 3 3 2 3 2 3 3 - ~.___~___

TOTAL--- --____- ssnb ----___ ---.-. -. - .-

ols-OFBMWUGNTEO STOCKS IN FlfR3T ANU SECONU TIERS

Hemlhedlffemnm~IheU.S.andCenedianmarkegisobvbus

FhtTbr soamdllw

~-(28-l 10 ww 18 (64%) U.S. (29 Stocks) 21(75%) 7 (2w

andTierOnefmdTierTwodMbulbnbygrarpwui#tkqvvfthinIhe

Canadian TSE 300 CompmHe Index.

llu one 29.9596 Tier Two 70.05%

~Iwotbrmerkslplace~ms(Ihelhemeta1987endIhe~~cydewMbe llwNFLATloN-RmAI1cm-~.

BKiSTOCKYARKR~WEWlTS

(from Wle above using T.P.L. quadranl placemenl)

TPL LONG TERM cvalc OIJADRANT msTmmJnoN DEcEMsER cLo!x 19w

CANADA UNITE0 STATES

Cyclically it is very different from Canada witft most of its stocks conforming to our Tkrr One classification - excepttons are energy, gotds, metals, airlines, steels, and big capital tech nology issues. From February 1987 U.S. equitii are likely to succumb to a sharp intermediate corrective downwave. A significant market tow is likely to form in t& April - May 1987 period (see nominal cycle chart). This bottom is likely to set the stage for the dewtopment of the next 4 - 455 year cycle (1987-91) and thereby the continuatton of the dominant very long term secular uptrend. The secular uptrend began at the August 1982 bottom and is now 4lh years ofd. The current secular uptrend is tha third very lorq term uptrend experience for this century, the first persisted for 10 years (1919 to 1929) and the second 27 years (from 1941 to 1969).

TtER II - f3AMFLES FROM 28 EUG WEIGHTS - Starting new cyclic bull phases or well advanced in bear phases.

Leadfn~.Newcyclefs4monthsold within linear secular uptrend advance.

1,.,--d ,,MM

Bull phase originated September 1988 folkwtnc~ an 18 month cyclii bear phase consoliiation.

,I n

Next intermediate trend bottom (expected AprtWay period) is likely to usher in a new bull phase.

TIERI-EXAMPLESFROM28BlGWl3GNTS - Currentfy long term cyclic top phases are underway. Next purchase opportunity occurs at intamwdiate trend bottoms expected Aprif-May and August-September 1987. Note distance from current price to secular uptrend trendline.

PAST,PRESENTANDPROBABLECYCI..ICJUNCI'IJRES l)-piul Cycles with Financial Serier SboAq Tbeir IJ~BI Sequeatial Relation&pm

I I I I I I I I I I

COMMODITIES

COMMODlTIES AND COLD

PAS-r AND PRESENT CYCLIC JuNcKlREs

Viewed w&b lsrpial Cyckr OfFiiseriea

KCA JCUMN&M 1987

COMMODITIES - REFLECT VERY LONG TERM DEFLATIONARY BIAS

1997 - A BULL PHASE FOR MOST COMMODITIES OnIMspaOs~bng~~~o(IhecaModltylndeXcmdgoldrvhlch~h~~cydeschematic mlhaPaQaoPlmana.~bngtanncycRc~amndd on ammad of tha 100 month charts and match those cydk bctums recorded on the bend juncture achematk. ifbwhg the xbtnatk. n mid appar that m cammodlies and lntennt Rates mova l-her In trend hamony for a fair proportion of the cycle.

C.R.B. CDMMDDITlES A lmnuf mafkat cunmodny indax. C.R.B. GRAINS INDEX

m MIra -,m... U.. I.1 - m. .x Y m -w. R. a,. ,m, 8.. - nm .I ”

RY

COPPER ENERGY

SECUtAR - DOWNTREND-

DISINFUTIONARY

FORCES

IS uKELv OOCD MnwoH lm7. PLATINUM

MSlNFlATlONARY r Mm 00

srJrupmdps*l FORCES I

A BOND MARKEI’ SCHEMATIC

ILLUSTRATING VEFIY LONG TERM SECULAR AND CYCLIC TREND DEVELOPMENTS

First published 1982 (Revised Dec. 84, July 86 and Dec. 86)

SELL OF A GENERATION

I

SELL OF A GENERA 77ON

I

An unfolding period of dominant DEMllON for the 1987-1991

4 to 4th year cycle would likely cause BONDS to adopt this steeper uptrend.

Cyclic top forming 3Q1986lstQ1987

BUY OF A GENERAnON 4th quarter 1981-2nd quarter 1982

and the origin for the new secular uptrend GENERAnON within the advancing very long term

An unfofdlng period of DISINFLATION-REfIAflON COMBlNAltON would likely cause BONDS to maintain their cyclic movement within

the existing secular uptrend channel.

DlSlNFlATlONARYPERlOD PENIDDDF For 1982-7 4 to 4th year cycle M!3lNFlATlON/REFlATtDN COMBlNAlWN - 199749

DmAnDN - 1989-91 For 1987-1991 4 to 4’h YEAR CYCLE

INTEREST-SENSMVES - FOR 1982-7 4 to 4% YEAR CYCLE

We haw drawn In on the bng term 100 month charts of feveral interestsnaithfes the secular upIre channel iWatraled in the s&anatk V.MJabngt-mcrclk juncture dates hew also been designated to clarify the relationship with the Bond Market Schematic. Nob Ihe Irend leadership establiihad by then U.S. ebchic utilities ahead d lhe bond market.

D.J.

CANADIAN BONDS m ‘.umIC. - . ” *.*I I.. - w z* Y

CYCLIC TOP PHASE 3RD OTR. 86 -

THROUGH 1 ST OTR. 87

- PHASE 3RD OTR. 86 - THROUGH 1ST OTFL 87

BELL CANADA h?-rvdgMin- markel(7.m9b) ~o:SinceMay1985Bd(hmbsenpertormlngInabsarphase-~ngtrend to U.S. lnlerest senslllves hence 2nd Tbr t9asMcation.

“1 nm,c. .Y LI .R 1L I.. - . 7

THE 4 TO 4’,$ YEAR CYCLE - INTERNATIONAL MARKETS AND THEIR RELATED CURRENCIES

1.

f : 4.

i: 7.

20 INTERNATKBNAL MARKETS - PERFORMANCE (NOMINAL)

Renked lay magnitude - metxwred from Mfiy 1994 kw to 1999 peak.

MrJxltx - up 974% 9. Austmlia - . . . . . . . . . . . . . . . . . . . Up . . . . . . . . . . . . . . . . . . . . . 125% 15. naly - up . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341% 9. B0Qium - Up . . . . . . . . . . . . . . . . . . . . . 106% 16. sp&l - up . . . . . . . . . . . . . . . . . . . . . . . . . 244g 10. Holland - Up ._.............._....... 96% 17.

~2%$%3; U”.::::::::::::::::: 172% 11. Sweden - up . . . . . . . . . . . . . . . . . . . . . . . 93% 15. 12.

- up _...................... 142% 13. Japan - Up . . . . . .._.........._........ 91% 19. Bnlnin - Up . . . . . . . . . . . . . . . . . . . . . . . . . . 79% 20.

Germany - up . . . . . . . . . . . . . . . . . . . . 130% 14. Switzeriand - up . . . . . . . . . . . . . . . . . . 74%

U.S.A. - up.. ........................ 71% Nor&ry-&Jp ... p’. ................ 51%

................. 49% Canede - Up Y.. ..................... 43% Dl?KlX?Kl--“g6;;;;;.~~~~~ ::::: :::::, c

The Wodd tnrk~x WLD.22 turned in a psrtannence of 107% (or lhe same pedod, placing iI around 10th poailii. We note lhat lhe U.S. &J ranked 15th and Canada is 19th.

8ULL PHASE EXl’E~sKw( - France, Japan. Britain and Ihe U.S. have experienced suffk&nt sectorgrwpstock ml rc4ation to lead to new cycle highs thrwgh 1st quarter 1997.

zN$WRCm - Hong Korg and Singepore. These are the markets which. thrwgh 19tE. responded lo bearish r~unlercydlccll action. or are prea~n% engaged In

suPE~PEaFof?MANcE-suoedor~ Is~dymbccurin1987~orAuslre)iswdCeMde.Hero(hodankranlMhKal~ end 8aaoc&ted lndustrkcs

are devekping new bull phMas.

B

Woddstqcklndexdbplays~cyclktopphawwlthina Linear secular uplmnd from late 1940’s. J-pan and

narrow secular uplrend. Note that this index is ranked Britain should be used a5 bellweathews indicating any

10th in the above pwfonnfmce table. chen9e lo secular Irend.

CYCLICALITY - Now bull phnoa out ol sync wtIh mool lntm mukotm.

HONG KONG SINGAPORE cr, CPI.w-5 lna*ecI*I. 1oolvnle *n ” m -II-? vm.11\ r,nr 1Io” toa mnnc =a.? 2, $3

Uneer secular uptmnd from 1974. Cydk top phase is

Iww underwey.

LOllding. New secular uplmnd b underway.

New bull pfume is just 8 months old. Sir$$wore’s per-

lormence in the comparall~ Iable above rqtistemd negathdy owing to countercycllcsf performance dur- Im tha mPr.,wmn~~t nrrhl

A maturing cyclic bear phase. New bull phase is ex-

pected fmm March 1997.

E

INTERNATIONAL MARKETS - CURRENCIES

CURRENCIES - Through 1987 stress and strain in the monay economy k llkety to impact directly on currency markets. Crfses will add more vokea calling for a change from a (loeting to a Rxerf exchange rate. No sustainable advance is seen for Ihe U.S. dollar until American interest rales effect a rising trend,

U.S. DOLLAR JAPANESE YEN

Linear secular uptrend odglnated 197% terminated

1995 and by Sept. ‘86 a long term cyclic bear phase registered. An extended cyclk bottom phase is unlold-

ing through 1st~2nd quarter ‘87.

The yen is the only major currency that had maintain-

ed a cyclic pattern against the U.S. Dollar through the 1980’s. Current long term bull phase signalled a lop

phase October ‘86. Cyclic lop phase extension Is likely until a rising U.S. inlerest rate environment is

forthcoming.

I I

From 1980. a linear secular downlrend operated

lhrough to March ‘85. The ensuing bull phase Icwed oul Augusl ‘85. well ahead ol other currencfes. The current bear phase is already 9 months old. A new bull

phase is likely to occur 3rd quarter ‘87.

AUSTRAUAN MARKET - SUPERKM PERFORMANCE - Australia has dev&ged into a two tfer marketplace with the dominant minfng. energy and w sectors just beginning or already performing In a powerful, youthful bull phase. The deflationary beneficiaries had already made Ifwir cyclic lop phases lhrough 3rd4th quarters ‘86.

SYDNEY SYDNEY - IN RELATIVE TERMS AUSTRALIAN DOLLAR

0% DIl.. ..nDIa.aum I”F0n.e <*,I I, ,a,,,,,, . ,a,, ,.,, ,., .< .., ,..,,., ,A Irn., Y U*“I”.ml.. Irn”.“l ..L>, II , *.,\

,t

Dominant natural resource bfg wefghts in early bull phases - CRA. Westem Minfng and CSR - are likely lo

take thk tndex to above the 22QO area.

Here we are vfewfng a relative strength plot expressed

in terms of U.S. dollar9 of the Australian market versus Ihe World Index. It sftows that a new “bull phase” is

pending in relative performance terms for the Australians.

The Australian dollar b still in a kxtg term secular

downtrend. Cyckicalty Ihe currant bear phase is likely lo persist through into 3rd quarter ‘87 and IO relest the

ofd lows.

CANAMAN MARKET - Sknilar to the Australian market. A two tfer marketplace - Sea analysis for Ihe Canadian market peges 1014.

TORONTO TORONTO - IN RELATIVE TERMS 1. ..ne. ‘-,-I- I-- ..,I * . . , , ,., ,. I

Through 1987 Iha big weIghted second tier groups. natural resource. gokh, banks and Mephones. sftoukf put the Canadian market up to tha TSE 4200-4500

-V.

Herewearevbwlngarelatlm9tmngthpkftexpru9aed

In U.S. dollars of the Canadian market IO the World Index. It shows a similar picture to lfte Australian

market. A new “bull phase” of powerful rdalfve

performance Is underway.

I . . . . . .

: :.:+!!

, , . . ; t

..,a

Ths hear secular downtrend odgfnalfng and ofnsratfng horn 1977 k Ilkely to be reversed earty 1987. New

hktodc fows against the U.S. doflar were seen 1st quarter ‘96. The cununt cycik bull phase was relnslalcd

2ndqumtef’ef3andf9tfkelytocenttnueInto2ndquartet

‘87, mchlng up to llu n-so cent rmga.

Ian Notley is a Research Director with Dominion Securities in Canada. He is

a vice president of the Canadian Society of Technicians and Chairman of Mem-

bership of Im as well as a member of the Ml'A.

114

m2dlnicalAnalysisofthe Fixed-Inooremrkets

By Steven Blitz, Vice President, Futures and Options Analyst Saloman Brothers Inc.

Introduction

The purpose of this paper is to offer a shortprimeron the application of technical analysis to the fixed-income markets. The application of technical analysis to the fixed-income markets is relatively new - especially in comparison to the historically extensive use of this analysis in the stock, commodity and foreign exchange markets. While there have been individuals involved with technical analysis of the cash bond market, the explosion in the use of this analysis effectively coincides with the advent of the futures market.

The reasons why are straightforward: Exact open, high, low, and closing prices; a single "non-maturing" instrument on which liquidity is focused; and volume and open interest data. The problems with applying technical analysis to futures antracts involve factors such as movements in the basis over time, a trading day that is only a portion of the cash trading day (this probelm has grown with increased ovrnight activity in Tokyo and Iondon), and the interaction between locals and technical trading systems in the futures pit. This paper will concentrate on the Treasury bond futures contract, because of its high degree of liquidity, and the strong expectational aspect of trading in the long-erd of the cash market.

What makes technical analysis of the fixed-income market different from analyzing other markets are the distinct limits as to how far expectations alone can push the market. Indeed, since an interest rate is, in the end, the market-clearing price for the supply and demand of funds in the economy, the fundamentals will, over the long-term, dictate the general level of rates. Price objectives from chart patterns must also be tempered at time - there are limits as to how low interest rates can fall, and tohowhigh they can rise. A huge head-and-shoulders in the Treasury bill futures price chart, for example, has a price objective of over 100. Since nominal interest rates didn't even turn negative during the Depression, they are unlikely to d-3 so in the near future.

Technical analysis can, however, be successfully applied to tie fixed-income markets. The question is how. Simply, technical analysis can be used in two ways: 1) To create an "automated" trading system, such as cne involving moving average cross*vers; or 2) Using a variety of technical indicators to discern turning points in the market, short- and long-term trends, and daily supprt/resistance levels.

The major difference between these two uses is that the second is often used by individuals charged with attempting t6 identify turning points, short- and long-term, preferably just before they occur. The periodic losses often incurred with a technical system may not be acceptable to those individuals, nor may these individuals be in a position to use such a system even if they wanted to use one. Market-makers are an excellent example of such indivi-

115

duals. For these participants in the bond market, it is of primary importance to know when to stop adding to a position and get ready for a reversal, when tobegin closing out positions and get set for the reversal, and when to go and put cn positions that profit fran the reversal.

Inqortmce of Charts

Charting is the most important of the various technical tools. Its importance lies in the picture that it gives of the ebb and flow of buyers and sellers in the bard market, and of where, ultimately, the market is finding value. All the moving averages and oscillators work only in conjunction with what the chart is showing. There is no reason to go through the variety of chart patterns in this article, especially with the number of excellent texts around. It is, however, worth noting that the bond market tends to bottan with a double bottom an3 top with a spike.

As for support and resistance levels derived from charts, whether they are trendlines or breadkout levels for a chart pattern, too much emphasis on breaks can be dangerous. The futures pit may, at time, appear to be pushing into these support or resistance levels in an attempt to push out stop orders. This can occur when these are price levels that are well-known to the market, obvious to even the novice chartist. In addition, these prices are just as likely to be extremely important levels for the market -- a 13 wek low or yesterday's settlement price, for example. For the technical trader, the resulting difficulty lies in identifying a legitimate breakout. The anly answer is to watch whether the break holds. If it doesn't, ignore the penetration with one exception -- the new level reached on the break will become the next important support or resistance point.

Moving Averages and Oscillators

There are, in the technician's bag of tricks, a variety of mathematical for- mulations derived with the intent of identifying trend, momentum, ard overbought/oversold conditions. Because they are all based upon price data, they have a tendency to look alikeafter awhile -- especially in the bond market, where mly one instrument is being investigated. For this reason, it is important to suppress the desire to look at every mathematical calis- thenic. It is also worthwhile to mix up some volume and open interest data with prices.

Of the technical series included in my personal inventory, almost each series is viewed in a variety of ways. I have designated three levels of technical signals. Get Ready, GetSet,and Go. Within each category, the signals should confirm each other as well as the market. In other words, do not rely on cnly one indicator to point out a change in market trend. Iook instead for several indicators to be emitting the same signal. When that takes place, then you knew that you are on the right track.

Getting Ready

These signals are meant to keepone from entering the market in the trend

116

direction at the extremes of a market move and, at the same time, gets me sensitized to the idea that a trend reversal is imminent. Because bonds can still run another point or two after these signals appear, a key virtue of these signals is patience. Staying out of the market during this period, as reversal indicators are growing, it not easy. When followed faithfully, these "get-ready" signals prevent one from getting long at the highs and short at the lows.

A sampling of these signals are:

1.

2.

Call/Put Volume Patio (Figure 1). This ratio of the moving average of the volume of call and put trading in the option on Treasury bond futures is an excellent early warning system. The idea is to identify periods when market sentiment is overdone to an extreme that suggests an imminent reactionary price swing. Because these have been a time trend to this ratio (market participants have increasingly found uses for put options), do r-rot look for a strict oscillator movement - such as would be founj with a relative strength index or a stochastic.

It has been my experience that once the ratio reached 1.25 or higher, begin looking for confirming signals to sell the bond futures contract. On the buy side, begin looking to go long once the ratio drops through 1.00. There are occasions when the ratio will overshoot these levels, as occurred last August. Such instances underscore the reason why the ratio is in the early warning category.

Up/Down Volume (Figure 1). This is a moving average of the ratio of trading volume in the bond contract on days when the contract closes higher to days when the contract closes lower. The rationale behind this incidator is that such measured volume activity will move to extremes that cannot be sustained. Peaks often occur just prior toa trend change in prices. A stronger signal from this indicator that a market turn is near takes place when prices are trending in cne direction, while this indicator is moving in the opposite direction. fI%ese divergences more often occur at tops than at bottoms.

As the chartin Figure 1 illustrates , a classic divergence period occurred in the beginning of March. Bond prices continued to rise while this volume ratio declined steadily. Indeed, since that period, the ratio has root supported any of the up moves in price that could be clas- sified as a trend. Typically, an extreme for this ratio occurs when it is above or below 1. Below 1, and the indication is to look for a buy -- above 1, look to sell.

3. Relative Strength Index (9 day) (Figure 3). This is ane indicator that is used in each signal category. In the "get-ready" area, the key is to look for extreme levels. Not just tie traditional 30-70 range, but extremes relative to recent highs ard lows in the index.

4. Net Change Oscillator (Figure 3). This moving average of the daily change in the contract's closing price has become a very useful barometer of future price direction. At tiis "get-ready" level, look for an extreme level -- such as plus are minus 0.5.

117

Getting Set

The purpose of this level of technical signals is to identify when the price action points to, at best, the beginning of a trend reversal or, at worst, the beginning of a period of price consolidation. Chances of the market running a few more points are, at this stage, relatively small. What typically follows these signals is very choppy price action. For this reason, closing out the previous tend position is more than warranted. Taking a position that profits if these reversal signals are correct is possible, but still somewhat ris)cy given that the chopw price actian may close out such positions that carry tight stops. In addition, the expected reversal may not even take place as only a period of consolidation may ensue. In sum, these are weak signals of a reversal, designed more as a signal to close out previous trend positions than to aggressively look far a trend reversal.

The initial chart signals for a turn in the marketaredifferentfor tops and bottoms. A top in the bond market is usually a spike: A day in which the market trades to a new high but closes in the lower end of the day's trading range. Often, the spread between the high and low of that day is wide, and volume, relative to the previous day or two, is typically large as well. A spike top typically occurs after a relative long and steepening bar-d market rally. In the chart in Figure, there is an excellent example of a spiked top in early March.

Market bottoms are somewhat more complex in that cne day never signals the erd of a selloff. Instead, the market tends to make retest the lows before a reversal occurs. The first bounce off the low generally starts with a spike bottom and is followed by aggressive short-covering. This is rarely a good environment to enter into on the long side -- except perhaps for a day trade. As illustrated in Figure 1, there is evidence of a double bottom re- versing the bard market as recently as mid February.

Spike tops an3 double bottoms require confirming acticn from other technical indicators before a reversal or consolidation can reasonably be assumed to be in progress. Su& confirming indicators include turns in various oscillators and moving average cross--avers.

Some of the indicators to look for in the early stages of market reversal are:

1. Stochastic -- 9-day (Figure 4). At this stage in the bond's price behavior, examine not the cross-over point of the fast ard slow lines, but the difference between these lines. As the chart in Figure 4 illustrates, this difference oscillates with a fair degree of regularity. When the difference is at an extreme, it is a "get ready" signal. The "get set" occurs when a definite turn has taken place. Do not necessarily expect a turn at only the extreme plus aa minus 20 level. Turns can quite often occur at levels where previous turns have taken place. The top in late December and in early January, and the bottoms in early and mid December, are two recent examples.

118

2. Relative Strength Index -- g-day (Figure 3). With this index, the first reversal signal is given when the index reverses direction. It may take a day or two, however, before the reversal in the RSI is evident. One way toidentifya turn in the RSI would be to look for a brteak of RSI support or resistance line, or of a moving average of the index. The best indicator of a turn in the market at this stage is a divergence bf~ tween the price action and the action of theRS1. As rated, a classic bond market bottom is a double bottom in prioe action. A double bottom in the RSI typically occurs at the same time, with the exception that the second FL% bottom is above its previous low - thereby creating the price/I61 divergence.

3. Wet Change Oscillator (Figure 3). Analysis of this indicator is similar to that used for the RSI: When a price reversal of trend is beginning look for turns in the direction of the NCO. As with the RSI, moreover, the validity of these turns, especially at bottoms, is made stronger when a divergence with price action is taking place.

4. Eight-day Moving Average of Closing Price (Figure 2). Moving-average cross-over indicators are a staple of any trading system, in almost any market. The use of the eight-day average for the bond is one of the better short-term indicators of market trend, and subsequent reversals. The methal for using the indicator is rather straight forward -- look for a close above, or below the average, and then set the position ac- cordingly.

The average will also be a fairly good support/resistance point during the day's trading. It is, in addition, worthwhile to know before the day begins what closing price will push the contract through the average at the day's end. This fairly simple calculation is especially useful in that it allows entrance into tie market during tie course of the day, and eliminates the wait to enter the market at tk close or at the next day's open. In a sharply trending market, this opportunity mitigates the situaticn of entering a position that often must endure a market re- action before the trend resumes.

These "go" signals identify when a position reversal is warranted -- without a high probability of having to endure the chopw price action attendant with the first signs of a market reversal. For the most part, these "go" indicators are somewhat more conservative. As a consequence, during a sideways market with a relatively arrow price range, such as the one the bond market endured through much of the first quarter of this year, these signals will be tD0 late in getting one into and out of the market.

Some of these "go" indicators include:

1. 'Iwo vs Five-Day Moving Average of Closing Price (Figure 2). My studies have shown that going long when the two is above the five day average, and short when the two is below the five day, has been, for the bond market, one of the better trading tools.

119

2. Stochastic -- 9 day (Figure 4). The cross-over of the fast and slow lines have been excellent indicators of a trend reversal. During relative flat market periods, moving to a five-day stochastic has helped. Through all markets, however, the nine-day has remained the staltwart performer.

3. Net Change Oscillator (Figure 3). The final use of this indicator occurs as it crosses the zero line - going long when it is positive, and short when it is negative. While the NC0 is mt as strong of an indicator as the other two in this category, it is an excellent means of confirming the validity of the signals given by the moving average cross- over an3 the stochastic.

AWord OnLong-TermTrends

Time &es rot permit me to go through tie litany of longer-term indicators that are valuable in viewing the bond market. These indicators become especially valuable when the market is spending a protracted period within a relatively narrow price range. With a long-term view,one can use these long consolidation periods to build a position to profit from the eventual breakout.

Some of the indicators to look at in garnering a long-term perspective, aside from a weekly bar chart, are: the 20 versus the 200 day moving average of Friday closing prices, g-week Stochastic, g-week Relative Strength Index, ati new issuanoa of fixed-coupon long-term corporate bonds. In addition, look at many of these same technicals in related markets, namely: CRR Index of Wity Futures, foreign exchange, gold, ard oil.

There are no magic formulas for trading thebond market. Toomanydirect fundamental factors can destroy even the most conservative technical trading system. A surprise entrance into the market by the Federal Reserve, an un- expected demand for gold for a Japanese coin program, or surprises in foreign exchange intervention by the world's central banks, are all recent examples of these fundamental factors. remember, also, that the bond market is ultimately driven by fundamental factors that keep prices within ranges that technicals may sometimes suggest as being too limited. In the proba- bilities of a successful trade. When all the various iridicators are used in conjunctimwitheachother, theymaykeepyou ina trending market ati they may prevent you from buying at highs, and selling at lows - but they won't yield "Rosetta Stone" with the magic formula for always trading the bond market for profit.

120

~_----__----_----~~~~~~~-~ Salomon Brothers Inc

102 FIGURE 1. - r 102

Treasury Band Futures - Jun 87. DaiLy High, - a ) Low, and Chse 100

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96 - ;- 1 96

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90 Apr

1986 1987

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1.50

1.25

G 5 1.00

E

0.75 1 *. a I* 1 * .I. ‘1 ” 1’ 1’ ’ n n *I. ” ” * * ” ’ * ’ *‘a .I Au!l Sep act Nov Dee Jan Feb Mar

0.75 Apr

1986 1987

r cc &?/Art VoLtme Ratao (Options m T-Bond Futures). 5-Day Avg A

J’J _._....._....... . . . . . . . . . . _. _. ..__.. .., . . . . . .._..... . . . . .._....._................. . . . . . . . . . . . . . . 2.00

1.75

1.50

1.25

1.00

2.0 1.5

1.0

0.5

0.0

-0.5

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-Bond Futures Trading Volume Ratio of Up Days to Down Days. IO-Day Avg

r-

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1986 1987

--_----------------------- Solomon Brothers Inc ---~--~~--~~~_-~~_-~~~~~~~

102 ’

100 Treasury Bond Futures - Jun 87. Daily IIigh.

*+l TlJ+ 98 . $T tT 1

96 . II T ?+t 1 94 ‘tT 1 II.

FIGURE 2. ’ 102

Low. and Close . 100

. 98

- 96

. 94

. 92 I

901 * " ' * * +. *'* ' ' - " * " ' - * -'* ' ' * " * * ' ' ' ' ,'* J Au9 Sep act Nov Dee Jon Feb Mar

90

1986 Apr 1987

Close minus 8-Da9 Yov Avg

-3’ - * * ’ I.. . . , . ..,. . , .I., *. L., , , . . . .I. ._ &I Sep Ott Nov Dee Jan Feb Mat-

-3

1986 APf- 1987

.

. . . . . . . . . . . . . . . -3 . . . . . . . . . . . . . . . .

-------------_--_----i---- Solomon Brothers Inc _____---------------------

FIGURE 4. 102 102

100 100

98 98

96 96

94 94

92 92

9o1 . . . , . , t. I .I * . . . , . . . , . . . *I. . 1 * I . . . 1 . . . *I.

Aug Sep act Nov Oec Jan Feb Mar .lgo Apr

1986 1987

100

- a0

. 60

. 40

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

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1 A A . . . . . . . . . . . . h 1 15

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Jan Feb Mot- ' -20

Av 1987

Steven Blitz is a Vice President in the Bond Market Research Department of Salomon Brothers, and reports to Dr. Henry Kaufman. Mr. Blitz is responsible for the firm's technical analysis of the financial futures and options markets, developing market strategies involving these markets, and maintain- ing a general research effort that covers this sector of the financial market. Mr. Blitz is the author of a daily technical canmentary on the bond

r and other: fixedtincome markets and, in addition, publish& the Monthly Re- view of Futures 'and Options. Mr; Blitz also publishes separate market strategy pieces, the most recent examining of interest ratekaps for real estate developers.

M.r. 'Blitz holds a M.A. in economics from Columbia University and an A.B. in economics from New York University. Prior to joining Salomon Brothers in 1982, he was a financial economist and econometrician working in the National Forecasting Group of Data Resources Inc. for Dr. Allen Sinai. Mr. Blitz has also worked in the economics departments of Manufacturers Hanover Trust and the Chase Manhattan Bank.

125

m .7Cmm#w 1987

journal of technical analysis (jota). issue 27 (1987, may)

Economy & Finance

new jersey robert

tabell delafield

tabell new york stock

new york richard orr

pine street new yok

tabell princeton

financial technical

technical trends