of thosecharts. Even fundamental tools like the price/earnings ratio havea technical side to them. Anytime you introduce price into theequation, you’re moving into the realm of technical analysis. Orwhen security analysts say the dividend yield of the stock marketis too low, aren’t they saying prices are too high? Isn’t that thesame thing as saying a market is overbought?
Finally, there are the academics who have reinventedtechnical analysis under the new name of Behavioral Finance. Foryears, the academics espoused the Efficient Market Hypothesis toprove that technical analysis simply didn’t work. No less anauthority than the Federal Reserve Board has thrown some doubton those ideas.
FEDERAL RESERVEFINALLY APPROVES
During August of 1995, the Federal Reserve Bank of New Yorkpublished a Staff Report under the title: “Head and Shoulders: NotJust a Flaky Pattern.” The report was intended to examine thevalidity of the head and shoulders pattern in foreign exchangetrading. (The first edition of this book was cited as one of the pri-mary sources on technical analysis.) The opening sentence in theintroduction reads:
Technical analysis, the prediction of price movementsbased on past price movements, has been shown to gen-erate statistically significant profits despite its incompat-ibility with most economists’ notions of “efficient mar-kets.” (Federal Reserve Bank of New York, C.L. Osler andP.H. Kevin Chang, Staff Report No. 4, August 1995.)
A more recent report, published in the fall of 1997 by theFederal Reserve Bank of St. Louis, also addresses the use of tech-460 Chapter 19
nical analysis and the relative merits of the Efficient MarketHypothesis. (Technical Analysis of the Futures Markets was againcited as a primary source of information on technical analysis.)Under the paragraph titled, “Rethinking the Efficient MarketsHypothesis,” the author writes:
The success of technical trading rules shown in the pre-vious section is typical of a number of later studies show-ing that the simple efficient market hypothesis fails inimportant ways to describe how the foreign exchangemarket actually functions. While these results did notsurprise market practitioners, they have helped persuadeeconomists to examine features of the market ... thatmight explain the profitability of technical analysis.(Neely)
CONCLUSION
If imitation is the sincerest form of flattery, then market techni-cians should feel very flattered. Technical analysis is practicedunder many different names, and often by those who may notrealize they’re using it. But it is being practiced. Technical analy-sis has also evolved. The introduction of intermarket analysis, forexample, has changed the focus away from “single market”analysis to a more interdependent view of the financial markets.The idea that all global markets are linked isn’t questioned muchanymore either. That’s why the universal language of technicalanalysis makes it especially useful in a world where the financialmarkets, here and abroad, have become so intertwined. In aworld where computer technology and lightning-fast communi-cations require quick responses, the ability to read the market'ssignals is more crucial than ever. And reading market signals iswhat technical analysis is all about. Charles Dow introducedtechnical analysis at the start of the twentieth century. As thetwentieth century draws to a close, Mr. Dow would be proud ofwhat he started.APPENDICESAppendix A: Advanced
Technical Indicators*rae eee
This appendix introduces several more advanced technical meth-ods that can be used by themselves or with other technical stud-ies. As with any technical approach, it is always recommendedthat investors do their own independent testing and researchbefore actually investing.
DEMAND INDEX (DI)
Most technicians will agree that volume analysis is an importantingredient in determining a market’s direction. The Demand Index(DI) is one of the early volume indicators that was developed inthe 1970s by James Sibbett. The formula is quite complex (see endof this appendix). The Demand Index is the ratio of buying pres-
*This Appendix was prepared by Thomas E. Aspray.
463464 Appendix A
sure to selling pressure. When the buying pressure is greater thanthe selling pressure, the DI is above the zero line, which is posi-tive. Greater selling pressure means the DI is below zero, whichimplies prices will move lower. Most traders also look for diver-gences between the DI and prices.
Figure A.1 is a weekly chart of T-Bond futures from early1994 until late 1997. From April to November 1994, the DI wasmostly below the zero line as bonds declined from 104 to the 96area. While prices made lower lows (line A), the DI formed high-er lows (line B). This is a classic positive, or bullish divergence,which suggested that bond prices were bottoming. The diver-gence was confirmed when the DI moved above the zero line atpoint 1. The DI reached its highest level for this rally in late May1995 at point 2, and then dropped for the next six weeks before
Bonds Weekly with Di indicatorbe/11193 — ~~ (US_1053P) US T.BondsG46/00
 
 
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Figure A.1_ The Demand Index (DI), which incorporates price and vol-ume, is shown here as a histogram. Values above zero are positive; belowzero they are negative. Notice the bullish divergence in late 1994 and thebearish divergence in late 1995. (Courtesy MetaStock Equis International.)Advanced Technical Indicators 465
crossing below the zero line at point 3. It stayed negative for fiveweeks before it again turned positive. On the next rally the DIformed a significantly lower high in late November at point 4.While the DI was lower (line D), the bond contract was almost sixpoints higher (line C). This negative or bearish divergence warnedof a price peak.
This indicator can also be used with stocks. The weeklychart of General Motors (Figure A.2) shows the DI plotted as aline rather than a histogram. This allows for trendlines to moreeasily be drawn on the indicator. I have personally found trend-line analysis of indicators to be quite valuable. Indicator trend-lines are often broken ahead of price trendlines. This was thecase in late 1995 as the downtrend in the DI (line A) was broken
 
amdimwe - General Motors 116/95 - 7/3187
 
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Figure A.2 The Demand Index (solid line) compared to a weekly chartof GM. Trendline breaks on the DI line often preceded trendline breaks onthe price chart. Notice the negative (bearish) divergence in April 1996.(Courtesy MetaStock, Equis International.)466 Appendix A
a week before the corresponding price downtrend (line B). Asthis chart indicates, buying just one week earlier could have sig-nificantly improved the entry price. The DI also warned of aprice high in mid-April 1996. While GM was making a new pricehigh (line C), the DI had formed lower highs (line D). This warn-ing signal came well ahead of the serious price decline in Juneand July.
HERRICK PAYOFF INDEX (HPI)
This indicator was developed by the late John Herrick as a way ofanalyzing commodity futures through changes in the open inter-est. As discussed in Chapter 7, changes in the open interest cangive traders important clues as to whether a market trend is wellsupported or not.
The Herrick Payoff Index uses price, volume, and open inter-est to determine money flow into or out of a given commodity.This helps the trader spot divergences between the price actionand the open interest. This is often quite important as buying orselling panics can often be identified through analysis of the openinterest by the Herrick Payoff Index.
The most basic interpretation of the HPI is whether it isabove or below the zero line. A positive value means that the HPIis projecting higher prices and that open interest is rising alongwith prices. Conversely, negative readings suggest that funds areflowing out of the commodity being analyzed.
One of the more volatile commodity markets is coffee, fea-tured in Figure A.3. During March and April of 1997, the HPI hadfour crossings of the zero line with the last positive signal in earlyApril (B) lasting until early June. The HPI dropped below zero inJune, and even though prices were well below the highs, coffeedropped another 70 cents. Once again the HPI turned positive inlate July very close to the lows. Over the next two months therewere two short term signals and then another longer term sell sig-nal. This is characteristic of the HPI when used on the daily dataas it will cross above and below the zero line several times beforea longer lasting buy or sell signal is given.Advanced Technical indicators 467
Coffee Dally with HPI indicator
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Figure A.3— The Herrick Payoff Index (HPI) shown as a histogram withcoffee prices. HPI uses price, volume, and open interest in its calculation andis used in futures markets. Crossings above zero are buys (B); crossings beloware sells (S).
The HPI, like the Demand Index, is most effective whenused on the weekly data, as fewer false signals are evident.Divergence analysis can also be used to warn the trader of achange from positive to negative money flow. There are severalgood examples on the weekly T-Bond futures charts (Figure A.4)that covers approximately six years of trading. The HPI stayedpositive from late 1992 until late 1993. The HPI peaked in early1993 and, when bonds were almost 10 points higher (line A),the HPI was forming a lower high (line B). This negative diver-gence warned bond traders of the decline in prices that tookplace in 1994. The HPI violated the zero line in late October of1993, but then turned slightly positive in early 1994 beforeplunging back below the zero line. The HPI reached its lowest468 Appendix A
T Bonds Weekly with HP! indicator
15/01 (US_1053P) US T.BondsG46/00IS T BondsG4e00-Weekly 01/208 C=110.280 2.780 O=121.310 He122.110 [#1 19.240 Va20s3333
 
 
 
 
 
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Figure A.4 A weekly version of Herrick Payoff Index with TreasuryBonds. Notice the bearish divergences in 1993 and 1995, and the bullishdivergence in 1994,
level in the first half of 1994 and bottomed well ahead of prices.As prices were making lower lows (line C), the HPI was forminghigher lows and therefore a positive divergence (line D). The HPImoved back into positive territory in December 1994 as bondswere very close to their lows. A negative divergence was formedin late 1995 (line F), after bonds had rallied over 25 points fromthe late 1994 lows. The zero line was crossed several times in1996 and early 1997 before the HPI moved firmly into positiveterritory. These two examples should illustrate why the HPI andits analysis of open interest can be helpful in analyzing a com-modity market’s direction.Advanced Technical Indicators 469
STARC BANDS ANDKELTNER CHANNELS
As discussed in Chapter 9, banding techniques have been used formany years. Two types that I prefer are based on the Average TrueRange. Despite this common factor, these two types of bands areused in very different ways. Average True Range is the average oftrue price ranges over x periods. True Range is the greatest distancefrom today’s high to low, yesterday’s close to today’s high, or yes-terday’s close to today’s low. See Welles Wilder’s New Concepts inTechnical Trading Systems.
Manning Stoller, a well known expert in the commoditybusiness, developed the Stoller Average Range Channels or starcbands. In his formula the 15 period Average True Range is doubledand added to or subtracted from a 6 period moving average (MA).The upper band is starc+; the lower is starc-. Movement outside ofthese bands is uncommon and indicates an extreme situation. Inthis manner they can be used as trading filters. When prices arenear or above the starc+ band, it is a high risk time to buy and a lowtisk time to sell. Conversely, if prices are at or below the starc— band,then it is a high risk selling zone and a more favorable point to buy.
' The weekly continuation chart of gold futures (Figure A.5) isplotted with both the starc+ and starc—- bands. In Feb. 1997 at point1, gold prices slightly overshot the starc- band. Though the priceaction was weak, the starc bands indicated that this was not a goodtime to sell. By waiting, a better selling opportunity was likely tooccur. Just three weeks later gold was $22 higher and at the starc+band (point 2). Point 2 was a low risk selling opportunity. In July(point 3), gold prices dropped well below the starc-band, butinstead of declining further, prices moved sideways for the next 12weeks. Gold prices then started to move lower from November toDecember 1997 and touched the starc- band three times (points 4).In all instances prices did stabilize or move higher for 1-2 weeks.These bands work well in all time frames even as short as 5 to 10minute bar charts. Starc bands can help the trader avoid chasing themarket, which almost always results in a poor entry price.470 Appendix A
Weekly goldprice withstarc bands
Upper line =starc+
Middle line = 6week average
Lower line =starc~
 
Figure A.5_—Starc bands plotted around a 6 week moving average of week-ly gold prices. Points 1 and 3 show prices bouncing after dipping below thelower band. Point 2 shows prices falling after rising above the upper band.
The Keltner channels were originally developed by ChesterKeltner in his 1960 book How to Make Money in Commodities.Linda Raschke, a very successful commodity trader, has reintro-duced them to technicians. In her modification, the bands arealso based on the average true range (ATR), but the ATR is caiculat-ed over 10 periods. This ATR value is then doubled and added toa 20 period exponential moving average for the plus band andsubtracted from it for the minus band.
The recommended use of the Keltner channels is much dif-ferent from the starc bands. When prices close above the plusband, a positive signal is given as it indicates a breakout inupward volatility. Conversely, when prices close below the lowerband, it is negative and indicates prices will move lower. In manyrespects, this is just a graphical representation of a four weekchannel breakout system discussed in Chapter 9.Advanced Technical Indicators 471
 
Figure A-6 is a daily chart of March 1998 copper futures.Prices closed below the minus band in late October 1997 at point1. This indicated that prices should begin a new downtrend andcopper prices dropped 16 cents in the next two months.
Daily copper prices with KeltnerChannels
Upper line = plus channel
Middle line = 20 dayexponential average
Lower line = minus channel
 
Figure A.6__ Keltner Channels plotted around a 20 day exponentiallysmoothed average of daily copper prices. With this indicator, moves belowthe lower channel (such as point 1) are interpreted as a sign of weakness.
There were many other closes below the minus band dur-ing this period. Until prices close above the plus band, the nega-tive signal will stay in effect. The second chart is March 1998 cof-fee prices (Figure A.7) and illustrates a positive signal at point 1.After two consecutive closes above the plus band, prices thendeclined to the 20 period EMA. In a rising market the 20 periodEMA should act as support. Several days after the EMA wastouched (point 2), coffee prices began a dramatic 30 cent rise injust a few weeks.472 Appendix A
 
Daily coffee chartwith Keltner Bands
 
Figure A.7 Keltner Channels with a daily coffee chart. Point 1 showsprices breaking the upper channel which is a sign of strength. Notice thatafter that buy signal, prices found support at the 20 day exponential movingaverage (middle line) at point 2.
Both of these techniques offer an alternative approach toeither percentage envelopes or standard deviation bands (likeBollinger Bands). Neither is presented as a stand-alone tradingsystem but should be considered as additional tools of thetrade.Advanced Technical Indicators 473
FORMULA FOR DEMAND INDEX
The Demand Index (DJ) calculates two values, Buying Pressure
(BP) and Selling Pressure (SP), and then takes a ratio of the two.
DI is BP/SP. There are some slight variations in the formula. Here’s
one version: .If prices rise:
BP = V or VolumeSP = V/P where P is the % change in price
If prices decline:
BP = V/P where P is the % change in priceSP = V or Volume
Because P is a decimal (less than 1), P is modified by mul-tiplying it by the constant K.
P = P(K)K=(xO©/VA
Where C is the closing price and VA (Volatility Average) is the 10day average of a two day price range (highest high - lowest low).
If BP > SP then DI = SP/BP
The Demand Index is included on the MetaStock chartingmenu.Appendix B:Market Profile*
 
INTRODUCTION
The purpose of this writing is to illustrate what Market Profile isand to define its underlying principles. Before the early 1980s,the only technical tools available were the bar chart and thepoint and figure chart. Since then Market Profile®! was intro-duced to expand the arsenal of technical tools. Market Profile isessentially a statistical approach to the analysis of price data.” Forthose without a statistics background, a familiar example may behelpful. Consider a group of students taking an exam. Typically,some score very high (say 90 or higher), some score very low (say
*This appendix was prepared by Dennis C. Hynes.
The Market Profile® is a registered trademark of the Chicago Board of Trade(CBOT), hereafter referred to as Market Profile or the profile. The concept was developed byJ. Peter Steidlmayer, formerly of the CBOT. For further information on the subject, contactthe CBOT or read Mr. Steidlmayer’s latest book: 141 WEST JACKSON—1996.
2Originally introduced for commodity futures prices, the format can be used forany price data series where continuous transaction activity is available.
475476 Appendix B
60 or lower), but most scores tend to be clustered around theaverage score (say 75). A histogram can be used to depict the fre-quency distribution of these test scores in a “statistical picture”(Figure B.1).
How Students Scores were Distributed
76543210
35 55 60 65 70 75 80 8 90 95 100Test Scores
 
Figure B.1
As can be seen, the most frequent score, or modal score,is 75 (6 students) while the range of scores is defined by the low-est and highest scores (55 and 95). Note how the scores distrib-ute evenly around the modal score. For a perfectly symmetricdistribution, the modal score will be equal to the mean, or aver-age score. Next observe that the distribution is “bell-shaped,”the telltale sign of a normal distribution. For a perfect normaldistribution, specific standard deviation intervals correlate tospecific numbers of observations. For example, if the test scoresare, in fact, perfectly normally distributed, then 68.3% of theseScores will fall within one (1) standard deviation of the mean.While actual data is unlikely to form a perfect normal distri-bution, it is often close enough that these relationships can beemployed.
Prices, like other physical measurements (e.g., school testgrades, population heights, etc.), distribute around a mean pricelevel as well. What is the Market Profile graphic? Visualize it assimply, a frequency distribution of prices displayed as a price his-togram turned on its side (see Figures B.2a and B.2b).Market Profile 477
Price HistogramVertical
Price Histogram
Horizontal
r‘5‘a2‘°
ar OePrion.
  
Figure B.2a Traditional. Figure B.2b Flipped on its side.
The centerpiece of the Market Profile graphic is the (bell-shaped) normal curve used to display the evolving price distribu-tion. Once the normal curve assumption is acknowledged, amodal or average price can be identified, a price dispersion (stan-dard derivation) can be computed and probability statements canbe made regarding the price distribution. For example, virtuallyall values fall within three (3) standard deviations of the averagewhile about 70% (68.3% to be exact) fall within one (1) standarddeviation of the average (see Figure B.3).
Market Profile provides a pictureof what’s happening here and now in themarketplace. In its pursuit of promotingtrade, the market is either in equilibriumor moving toward it. The profile’s natur-al tendency toward symmetry defines, ina simple way, the degree of balance(equilibrium) or imbalance (disequilibri-um) that exists between buyers and sell-ers. As the market is dynamic, the profilegraphic portrays equilibrium as periods ofFigure B.3— The pro- market balance—when price distribu-file graphic reveals that _ tions are symmetric, and represents dise-market activity is regular- quilibrium as periods of market imbal-ly normally distributed. —_ ance—when price distributions are not
symmetric or are skewed.
 478 Appendix B
Market Profile is not a trading system nor does it providetrade recommendations. The aim of the profile graphic is to allowthe user to witness a market's developing value on price reoccur-rence over time. As such, Market Profile is a decision support toolrequiring the user to exercise personal judgment in the tradingprocess.
MARKET PROFILE GRAPHIC
The Market Profile format organizes price and time into a visualrepresentation of what happens over the course of a single ses-sion. It provides a logical framework for observing market behav-ior in the present tense displaying price distributions over a periodof time. The price range evolves both vertically and horizontallythroughout the session. How is a profile graphic constructed?
Consider a 4 period bar chart (see Figure B.3a). This tradi-tional bar chart can be converted to a profile graphic as follows:(1) assign a letter for each price within each period’s price range,letter A for the 1° period, B for the 2"4, and so on (see Figure B.3b)and then (2) collapse each price range to the leftmost or first col-umn (see Figure B.3c). The completed profile graphic reflectsprices on the left and period frequency of price occurrence on theright, represented by the letters A through D.
  
Figure B.3bMarket Profile 479
 
Each letter repre-sents a Time Price Opportu-nity or TPO to identify aspecific price at which themarket traded during aspecific time period (e.g.,in B period prices tradedbetween 163 and 166).These TPOs are the basicunits of analysis for theday’s activity. In otherwords, each TPO is anopportunity created by themarket at a certain time Figure B.3cand certain price. MarketProfile distributions areconstructed of TPOs. The Chicago Board of Trade (CBOT) assignsa letter to each half-hour trading period on a 24 hour basis; upper-case letters A through X represent the half-hour periods frommidnight to noon while lowercase letters from a through x repre-sent the half-hour periods from noon to midnight.3
DBAAAAA
 
MARKET STRUCTURE
When you visit a commodities trading pit on a busy day, youobserve what is best described as “controlled chaos.” Beneath thescreaming and gesturing locals and other traders, there is adescribable process. Think of the market as a place where partici-pants with differing price needs and time constraints competewith each other to get business done. Emotions can run high asanxiety levels soar.
The Market Profile concept was introduced by Mr.Steidlmayer in an attempt to help describe this process. As a
3Letter assignments can vary between vendors. For example, CQG assigns upper-case letters A through Z from 8:00 am CST while lowercase letters from a through z from10:00 p.m. CST.480 Appendix B
CBOT floor trader (Jocal) and student of market behavior, heobserved recurring patterns of market activity, which ultimatelylay the foundation for his understanding of the market. Sincethe CBOT trading floor conducts trade in an auction-like man-ner, he defined Market Profile principles in auction terms. Forexample, an off-the-floor trader would describe an advancingmarket as one that is rallying or trading up, whereas Mr.Steidlmayer would instead say something like, “the market con-tinues to auction up, advertising for sellers to appear in order toShut off buying.”
To explain why a trading pit auction process works theway it does, he invented some new terms unfamiliar to off-the-floor traders. He began with a definition of a market’s purpose,which is to facilitate trade. Next, he defined some operationalprocedures, namely that the market operates in a dual auctionmode as prices rotate around a fair or mean price area (i.e., sim-ilar to the way school grades were distributed). Lastly, hedefined the behavior characteristics of market participants,namely that traders with a short term time frame seek a fairprice, while traders with a longer term time frame seek anadvantageous price.
MARKET PROFILEORGANIZING PRINCIPLES
Auction Setting: The purpose of the marketplace is to facilitateor promote trade. All market activity occurs within this auctionsetting. Initially, as price moves higher, more buying comes in, asprice moves lower, more selling comes in. The market moves upto shut off buying (i.e., auctioning up until the last buyer buys)and moves down to shut off selling (i.e., auctioning down untilthe last seller sells). The market actually operates through a dualauction process. When price moves up and more buying comesin, the up-move advertises for an opposite response (i.e., selling)to stop the directional move. The opposite is true when pricemoves down.Market Profile 481
 
Continuous Negotiation: When a mar-ket moves directionally it establishesprice parameters, an unfair high and anunfair low, and then trades between themto establish a fair value area. All tradetakes place through this negotiatingprocess and remains within these parame-ters until one side or the other side iseventually taken out (i.e., a new high ornew low is formed). (see Figure B.4.)
Market Balance and Imbalance:The market is either in equilibrium orworking toward equilibrium betweenbuyers and sellers. To facilitate trade, themarket moves from a state of balance(equilibrium) to one of imbalance (dise-quilibrium ) and back to balance again.% i This pattern of market behavior occursUntairLow Area |_:*if all times frames, from intraday ses-sion activity to single session activity toaggregated or consolidated sessionsFigure B.4 activity which form the longer term
auction.
Time Frames and Trader Behavior: The concept of differ-ent time frames was introduced to help explain the behavioralpatterns of market participants. Market activity is divided intotwo timeframe categories, short term and longer term. The shortterm activity is defined as day time frame activity where traders areforced to trade today (e.g., locals, day traders and options traderson expiration day fall into this category). With limited time toact, the short term trader is seeking a fair price. Short term buyersand sellers do trade with each other at the same time and at thesame price. Longer term activity is defined by all other timeframeactivity (e.g., commercials, swing traders, and all other positiontraders fall into this category). Not forced to trade today and withtime as an ally, these traders can seek a more advantageous price. Inpursuit of their interests, longer term buyers seek lower prices
Range Parameters
Unfair High Area
 482 Appendix B
while longer term sellers seek higher prices. As their price objec-tives differ, longer term buyers and sellers generally do not tradewith each other at the same price and at the same time. It is thebehavioral interaction between these two distinct timeframetypes of activity that causes the profile to develop as it does.
The Short Term Trader and Longer Term Trader PlayDifferent Roles: Short term and longer term traders play key,but different, roles in facilitating trade. A market's initial balance(i.e., a place where two-sided trade can occur) is usually estab-lished in the first hour of trade by short term buyers and sellers(day timeframe activity) in their pursuit of a fair price. Most ofthe day’s activity occurs in the fair price or value area. Pricesabove and below this developed fair value area offer opportuni-ty and are advantageous to longer term traders. With time ontheir side, longer term traders can either accept or reject pricesaway from fair value. By entering the market with large enoughvolume, longer term buyers and sellers can upset the initial bal-ance, thereby extending the price range higher or lower. Thelonger term trader is responsible for the way the day’s rangedevelops and for the duration of the longer term auction. Inother words, the role of the longer term trader is to move themarket directionally.
Price and Value: The distinction between price and valuedefines a market-generated opportunity. There are two kinds ofprices: 1) those that are accepted—defined as a price area wherethe market trades over time and 2) those that are rejected—defined as a price area where the market spends very little time.A rejected price is considered excessive in the market—defined asan unfair high or unfair low. Price and value are all but synony-mous for short term traders as they ordinarily trade in the fairvalue area. For longer term traders, however, the concept thatprice equals value is often inaccurate. Price is observable andobjective while value is perceived and subjective, depending uponthe particular needs of longer term traders. For example, a priceat the top of today