(interest rates) is an exact number. Fair value istherefore always fuzzy. This doesn’t change the fact that it should rise and fall asinterest rates change. The degree of fuzziness of fair value determines the sizeand play feedback loops will have on prices. Feedback loops can occur only if anexact, agreed-on amount for fair value doesn’t exist because if it did, no onewould buy or sell at any price other than the true value.
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be paid 30 years from now. We saw the same thing earlier, when wewatched how the present value of a dollar to be paid in 10 years can undergo a sudden increase when interest rates change. This mathematicalreality is important since interest rates can and do change, sometimes by20% in a month. On the contrary, a recession is usually expected to modify only a few years’ worth of the future stream of dividends, with thefarther-away dividends less affected. Only when the dividends are perceived to be in trouble for a long time (such as during the Great Depression) does the long-term reduction in dividends usually matter morethan the reduction in interest rates.This explains why stock prices often hit bottom in the worst part ofthe recession, when the future for business looks the worst but interestrates are declining. Many investors think that stocks start rising in themiddle of a recession because farsighted investors anticipate the recovery and see expanding earnings and dividends. Yes, there is a little of thatactivity, but the important point is that stock prices rise because lower interest rates make the smaller dividends stack to a higher price today thanthey did the day before.The tremendous importance of interest rates to stock prices can beseen in Figure 3.8. About 50% of the long-term gains in stock pricessince 1982 (when the Dow Jones started its rise from just under 800), isdirectly attributable to the drop in interest rates from 15% to 5%. Therest of the gain is attributable to the expansion and increase in earningsand dividends.NOTEToday, there are many ways to pay dividends. Some companieshave started to repurchase their own stock, which acts like a dividend payment. I don’t intend to cover the alternative methods ofpaying dividends because any effect would be measured much thesame way we do using the theory of stacking the money. None of itchanges the basic conclusion of that theory.
Response Time to Interest Rate ChangesTheoretically, stock prices should respond to interest rate changes as immediately and directly as bond prices do. In practice, however, the difficulties involved in predicting dividends loosen the connection, and the
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FIGURE 3.8 As the stacking-the-money theory indicates, about half the gains ofthe 18-year bull market are the result of the long drop in interest rates from 15%to 5%.
relationship is not as direct as with bonds. It is not uncommon to seeboth interest rates and stock prices decline simultaneously. Such a chainof events runs counter to theory. If this continues for a time, peopleoften start saying that stock prices and interest rates have uncoupled. Although they are partially right—that is, stock prices and interest rates dooccasionally break off their dance—a closer inspection reveals what is really happening. For whatever reason during these periods, investors turntheir attention away from the denominator and focus entirely on the numerator. It usually happens after a severe economic event for which investors are trying to evaluate the economic ramifications.A shift like this happened during the market decline of 1998, whena miniature currency crisis rippled through the global economy. Duringthis crisis, American stocks experienced a 20% decline. Interest ratesalso declined as the crisis worsened. However, investors were so concerned about the economic repercussions on the fuzzy numbers thatthey didn’t notice—or didn’t care—that interest rates were plunging.
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What had happened was that the crisis triggered feedback loops, whichfor a while were much more powerful than what theory was saying at thetime. After the panic subsided, the theory of stacking the money tookhold and prices rocketed upward.Always pay strict attention to periods in which interest rates are either rising or falling and stock prices continue going their own way, ignoring theory. For example, in the spring of 2001, the Federal Reserveboard engineered a constant decline in interest rates, and for a time,stock prices continued to decline. Commentators started saying thatmaybe this time the decline in rates wasn’t going to stimulate the economy. When you hear that, bells should go off; they’re putting your attention on the wrong part of the fraction again. At such moments, oneshould study the other information, such as contrary opinion, to help youfigure out what is going on.Inflation and the Theory of Stacking the MoneyIt’s important to keep in mind that the D/I formula does not indicatewhether future dividend growth occurs because of inflation or because ofreal growth. For example, suppose that the amount of goods a companysells remains the same, but the company increases the price of its goodsby 10%. This means that the company’s earnings and dividends also riseby 10%. Such an increase does not represent real growth, however, because the 10% rise is due to inflation.By contrast, assume that inflation is zero but that sales and earnings(and eventually dividends) increase by 10%. The theory of stacking themoney treats this situation identically to the situation of 10% inflation.You might think that these two should not be treated the same becauseone represents real expansion in business and the other doesn’t, but theyare treated the same—and they should be.The difference between these two cases doesn’t occur in the dividend number; it occurs in the bottom number, interest rates. During periods of inflation, interest rates are higher, and thus the dividends stackto a lower sum. In other words, if too much of a company’s growth is inflation growth, a lower fair value is accorded because the interest rate(denominator) is bigger. When real growth occurs, you have the best ofboth worlds: high expected dividend growth and low interest rates. Thetheory allows for the highest possible fair value during these periods.
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Applying the Model to Companies That Don’t Pay DividendsWhat about companies that don’t pay dividends—how are their pricesestablished? Their prices are predicated on the idea that the companywill someday pay a dividend. The hope, of course, is that fantastic corporate growth will result in really big dividends in the future (Figure3.9). After all, there is a present value for a payment, even if that payment is 10 or 15 years away. If those dividends are expected to be largeenough, theory would justify a high stock price today. But if at any timeinvestors begin to think that the company’s dividends ultimately won’tmaterialize, its stock price would go through a major evaluation.To understand this principle, suppose that we have a time machineand go 50 years into the future. We go to a library, search the records,and discover that the small computer company named XYZ (which dealsin computers, chips, software, and the Internet) grew for a time into ahuge company that earned billions of dollars. After a while, however, the
FIGURE 3.9 Even if a company isn’t paying dividends now, large dividendsexpected in the future result in a big stock price today.
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company declined and eventually went bankrupt. Most importantly, suppose that over its entire life it never paid a dividend. If we then flew backto the present and could convince everyone that what we had learnedwas real and accurate, at that point the price of XYZ company stockshould go to zero. I don’t care if the company still had 15 years of earnings growth in the billions of dollars ahead of it. Based on our equationfor fair price, XYZ’s stock price should be zero.In practice, when dividends lie far in the future, analysts attempt toestimate them by looking at earnings. After all, dividends must eventually come out of earnings. Mature companies often pay out as much as50% of their earnings as dividends. Therefore, by keeping track of howearnings are growing, analysts can form some idea of what dividendsmight be in the future.Today, there are many companies paying few, if any, dividends, aswell as many companies doubling and tripling in price that have no earnings at all. If this continues for a long time, investors can start thinkingthat dividends don’t matter. After all, fortunes are being made withoutany consideration for dividends.This just shows how fuzzy the numbers can get. The same investorswill soon learn the realities of finance if they don’t remember that theseprice movements are 100% speculation. Sooner or later, the price of astock must have a real basis. Ultimately, the great growth cycle mustcomplete, and the piper must be paid.Current Dividend Yieldand Market Expectation
The fair value term D/I in our model describes the effect of dividendsand interest rates on stock prices and helps us understand some important things happening today. One is the current yield on stocks. The current dividend yield on stocks is very low (around 1.3% for the S&P 500).This number is calculated by dividing the current dividend by the current price. What does this low yield mean? To have a low ratio you needto have a high price. From our theory of stacking the money, we knowthat high prices result from the expectation of very large future dividends (Figure 3.10).The low dividend yields result because the present dividend is verysmall compared to the high stack (price) from all those huge expected future dividends. In other words, the current price of stocks is built on a
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FIGURE 3.10 The stacking-the-money theory says that a low dividend yieldimplies that Wall Street is expecting high dividend (and earnings) growth in thefuture. This expectation of future growth allows investors to accept today’s lowdividend yield. If confidence in the expected growth were ever shaken, a majorprice readjustment would occur.
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STACKING THE MONEY RESOLVES TWOOF THE INVESTING PARADOXESWe are now in a position to resolve two of the investing paradoxes introduced in Chapter 1.Resolving Paradox 1: I’m Happy When I’m Sad.Recall Paradox 1 from Chapter 1: I’m happy when I’m sad. An exampleof this paradox in action occurred in September 1997, when the government announced the good economic news that payroll levels were
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increasing. As a result, the stock market sold off 100 points. The presswas puzzled to explain it. The analysts said that good news often meansthat the Fed will raise rates, and this is not good. Carried to its extreme,however, the better the economy gets, the more the market should selloff. Is good news really bad and bad news really good?The analysts were correct, but they didn’t go into the matter inenough detail. In fact, this paradox involves the yin and yang of stockprices explained earlier. After reading this chapter, you now know thatinterest rates are just as important when calculating stock prices, as areearnings and dividends. Thus, the chain of events makes sense: Whenemployment goes up, investors fear that the government will raise interest rates in order to stem inflation, and higher rates call for lowerprices. The positive news indicating that the economy is strengthening isnot as important in D/I equations as higher interest rates.Resolving Paradox 2: How Can the Tail Wag the Dog?Now recall Paradox 2: How can the tail wag the dog? To understand thisparadox, you need to remember that the stock market is one of 12 leading economic indicators, probably the best of the 12. However, to predictthe stock market, people usually turn to interest rates. Here is the paradox: The U.S. government classifies interest rates as a lagging economicindicator. Although stocks are one of the first things to move in a business cycle, interest rates are one of the last. How can people use a laggingeconomic indicator to determine what a leading indicator is about to do?How can the tail wag the dog?The paradox is resolved when you learn that the word cycle comesfrom the same root as the word circle. A rotating point on a circle tracesout a normal cycle, or sine wave. Can you find the leading and lagging
FIGURE 3.11 The word cycle comes from the same root as the word circle.Where is the leading point on a circle, and where is the lagging point?
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points on the circle in Figure 3.11? It’s true that interest rates usuallycome down at the end of a normal business cycle, but remember that theend of one cycle is the beginning of a new cycle. We should ask why stockprices move up early in the next business cycle. Is it because investors areso good at seeing the higher D (dividends) from an expected new business recovery, or is it because interest rates are lower, making for highertheoretical stock prices? I believe it is because lower rates calculate tohigher stock prices.The theory for fair value indicates that the actual pattern is this: Interest rates come down, signaling the end of the previous business cycle.Lower interest rates allow stock prices, even in the face of deterioratingbusiness, to have a higher fair value, and investors respond. Higher stockprices then seem to indicate the start of the new cycle.At one time, conventional wisdom held that the stock market was agood leading indicator because investors were farsighted enough to seethe new recovery even in the midst of a recession. Early in my career, Icouldn’t see the end of recessions; I wondered why everyone else hadsuch foresight and I was the one sitting out in the cold. In truth, theyweren’t clairvoyant; they were just acting according to a theory I had notyet learned: the theory of stacking the money.
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rying to make money during a trading range market is very difficult. Not only do you have the almost impossible task of locatingthe start of such a period (which means, in effect, predicting theend of a long bull market), you also need to find the beginning and endof the major swings that will form the trading range.A long-term bull market, like the one we’ve been in since 1982,spoils investors. When prices decline, investors become conditioned tothe idea that if they wait, prices will come back and go higher. They become sloppy because investing becomes too easy—just put your moneyin and watch as almost everything moves higher. It’s the best of allworlds. A warning against lazy investing is found in a wise old sayingfrom market lore: “Never mistake brains for a bull market.”When a long bull market ends and a new period begins, the importance of accurate and disciplined trading again comes to the fore. Stocksno longer show the characteristic long-term upward advance. Manystocks decline and never come back. A significant number decline so severely that they wipe out all the gains of the previous long bull market.At these times, you must have greater trading disciplines and tight guidelines that will get you out quickly when your ideas are proved wrong.Consider Figure 4.1. The dots at the end of the solid line are my projection of the upcoming trend in stock prices. To invest through a periodlike this successfully, it is necessary to bring every reliable tool to bear in74
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FIGURE 4.1 The coming trading range period. The bottom straight lineindicates the stock market’s long-term trendline since 1928. Notice how the bullmarket of the last 10 years has pushed prices far away from this trendline. Itwould be normal for the market to digest these tremendous gains over time byworking slowly back and forth until prices end up closer to the line.
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the effort. As I explain in Chapter 6, the Elliott wave pattern is the basicblueprint for forecasting the broad outline of what to expect from prices.However, the trader must always keep every forecast fluid; it is never tobe written in concrete. The Elliott wave pattern, with the innumerable andcomplex variations that the theory allows, by itself is incomplete; you mustincorporate other information to help limit the number of possible Elliottwave patterns. One important tool in this effort is technical analysis.
TECHNICAL ANALYSIS VERSUS FUNDAMENTAL ANALYSISTwo broad studies of the stock market exist: technical analysis and fundamental analysis. In fundamental analysis, investors compile and consider economic data in an effort to predict stock prices. They look atsales, earnings, dividends, interest rates, and so forth. In technical analysis, investors consider only the information generated on the floor of the
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exchanges: volume, price history, short interest, put and call ratios, andso on. In fact, you can classify these two disciplines solely by specifyingthe physical location where the information is generated. If the information originates in the business world, it is fundamental data; if the information originates on the floor of the exchanges, it’s technical data.For years, these two schools have been battling over which one is thecorrect discipline to predict and explain stock market movements. Theargument is quite silly because it is a battle over what really amounts toseparate turf. I have mentioned that a clear definition of the time intention of the trade helps determine what type of data you should study. Ifyou are investing for price movements of more than nine months, youshould study primarily fundamental data. If you’re interested in predicting price movements of less than six months, you should study technicaldata.You should understand that technical analysis is the discipline thatstudies and measures the three feedback-loop terms in the model andthat fundamental analysis studies the fair-value term. Because feedbackloops can’t last more than 3 months maximum in a decline and 6 monthsin an advance, and major bull and bear markets can last for years, I wantto clarify the difference between these two disciplines using a timegraph. The clarification takes place as we return to the time intention ofthe trade.At the bottom of the graph in Figure 4.2, the X-axis is the time intention of the trade, which is the period of the investment or the periodover which you are trying to predict stock prices. It starts with trades lasting a few hours (far left), going into days, weeks, and then months as youmove to the right. At the far right are investments that are intended tolast a few years. Along the vertical axis, the Y-axis, is a scale that measures
Fundamental analysis is the process of compiling and consideringeconomic data such as sales, earnings, and dividends in an effort topredict stock prices.Technical analysis is the process of compiling and considering information gathered on the stock exchange floor, such as volume,current stock prices, and short interest, in an effort to predict stockprocess.
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FIGURE 4.2 The relative importance of technical analysis and fundamentalanalysis in predicting market movement. The time intention of the tradedetermines which discipline should be used.
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the usefulness of any information to predict, with zero being useless and100% being vital.Let’s attempt to plot where technical and fundamental analysis fit onthis chart. At the far left, where the time intention of the trade is a fewdays, the importance of technical analysis should be close to 100% andfundamental analysis close to zero. Only technical analysis has anychance of predicting movements lasting a few days. Moving to the right,the situation gradually changes. At the far right, the importance of fundamental analysis is 100% and the importance of technical analysis iszero. Where is the crossover? It’s difficult to locate, but I place it somewhere between six and nine months.
CLARIFYING THE TIME LIMITATIONSON TECHNICAL ANALYSISLet’s go back to the model of the stock market introduced in Chapter 1.The model holds that stock prices are equal to a fair value stretched andmodified by three somewhat independent feedback loops. Now I’m
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going to make a statement that may surprise, and maybe even upset,some technical analysts. I believe that technical analysis is primarily useful in predicting only the price movements caused by the action of thethree feedback loops, short-term, intermediate-term, and long-termfeedback loops. Because of this, I think that analysts who use only technical analysis to predict major bull and bear markets are applying the discipline incorrectly. In my opinion, any effort to use technical analysisbeyond its applicable time range pushes the subject beyond what it is capable of accomplishing. (The only exception to this, I believe, is whenhigh readings in investor sentiment exist simultaneously with extremelevels of public speculation in stocks.)Many technicians would say that I am wrong, pointing to the deteriorating technical situation that existed before many bear markets asproof that technical signals can anticipate them. I do not deny this. Nevertheless, it is my contention that these technical indicators were incapable of distinguishing whether the market was just unstable and readyfor a three-to-six-month correction or whether a major bull or bear market was imminent. In the cases they cite, I believe that the indicatorswere measuring an instability that eventually transformed itself, for economic reasons, into a lengthy bull or bear market. If a decline is to lastmore than nine months and turn into a major bear market, there must bean economic reason—a foundation for a decline of this magnitude andtime duration.
BASICS OF TECHNICAL ANALYSISThe Market Technicians Association (MTA) web site (www.MTAUSA.org) lists more than 100 technical indicators of all types. Some 10 or20 indicators are different types of volume measurement, 20 or 30 measure different periods of the advance-decline line, and so on. You mightassume that indicators are measuring many different types of ideas, butthere are really only four or five basic ideas in technical analysis. All thevarious indicators are just different ways to measure these four or fivebasic concepts.I can’t cover the entire subject of technical analysis in this book, but Iwill highlight a few of the ideas that are fundamental to the subject. As youread along, keep in mind that there is one additional, and quite important,part of technical analysis not covered in this chapter: the theory of contraryopinion. The theory of contrary opinion is so significant that it has its own
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chapter (Chapter 5). As you read this chapter, remember that there is aninvaluable addition to the technical picture not being described.Highlighting DivergenceAlmost all technical analysis is associated with divergence in one form oranother. Divergence occurs when two things that were acting together ina certain way start acting separately, or differently, than they did earlier.In technical analysis, unless there is some form of divergence, there is nosignal. Almost all the technical tools used, except for the theory of contrary opinion, are based on some type of divergence.The original Dow theory of the late 1900s was essentially a divergencetheory. A hundred years ago, Charles Dow postulated that it is a negative indication when the Dow industrials average goes to new highs but thetransportation average fails to follow. This divergence in activity is the basisof the Dow theory. The divergence idea is found throughout technicalanalysis. If I were to check, I believe I’d find that more than 80% of the indicators at the MTA web site measure some type of divergence.For example, one of the most basic technical principles, referencedmore than any other (except contrary opinion), is when the advancedecline line diverges from the large capitalized indexes. The advancedecline line is the ongoing sum of the number of stocks advancingevery day minus the number declining. Usually, this line moves up, alongwith the various price indexes. At times, however, after a long advance,it makes a top and never again exceeds that point, although the price indexes do. This is the point of divergence. If this divergence continues fora few months, it is a sign of a weak, unstable market.Many excellent books on technical analysis explain the various indicators and the ideas they are based on. One vital point is seldom covered,however: How do you determine if the technical indicator is signalingstrength or weakness over the short, intermediate, or long term? For
Divergence is the observation in technical analysis that two indicators or market averages that usually move up and down together arenow moving in opposite directions or doing opposite things. One isnot confirming the other.
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example, how do you determine if the divergence of the advance-declineline is indicating a short-term decline or a long-term one?An Important Principle: Time Invariance
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In 1973, I formulated a principle that has served me well over the years.I call it the principle of time invariance. I have never proved it, I don’tknow if others have established the same idea or if modern technicalworks address it, and I have never seen it stated in the books I’ve read.It is a principle very similar to the concept behind fractals (covered inChapter 6). The principle is this: In technical analysis, what is true forthe long term is true for the short term.
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In technical analysis, what is true for the long term is true for theshort term. What this means is that if some technical principle is discovered that applies to intermediate-term movements, the sameprinciple will be found to apply to short-term moves—only the timescale changes.
What this principle means is that, in technical analysis, if there is acertain sequence of events that usually occurs at a major market top orbottom, you’ll find the same sequence, albeit smaller in size, before ashort-term market top or bottom. For example, in a bull market, totalmarket volume usually peaks before stock prices reach their peak, generally about four months before. You will find volume also peaks beforeprice in a move that lasts only four weeks. In this case, however, it peaksmaybe five or six days before the price peaks. Everything is scaled backin terms of time, but the sequence is the same.The model we have put forth is that stock prices equal a fair valuemodified and stretched by three feedback loops. Each feedback loopcan cause exaggerated price movements in its time realm. If you are attempting to predict prices over the very short term, you use the sametechnical tools scaled to the time scale. In other words, you don’t needdifferent technical tools to predict different-size moves—you just scaleback the time frame of the tool.
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For example, when measuring volume, a very short-term tradermight go to a moving average of hourly volumes to compare. Anintermediate-term trader might use a moving average of daily volume,and a longer-term investor might use weekly volume. What this principlesays is that, no matter the time scale, each would look for the same pattern or divergence over that time scale.In my opinion, not knowing or misunderstanding this principle isthe cause of some of the misstatements made by market technicians.They get confused about the time frame referenced by the technical indicator they are looking at. This is also true when comparing the different characteristics between market tops and market bottoms. Thetechnical differences one finds between long-term tops and long-termbottoms are the same differences that distinguish short-term tops andbottoms.The Two Categories of Technical IndicatorsWe can classify technical indicators into two types. I call the first type atransition indicator and the second, a confirming indicator. The first indicator tries to locate exact market tops and bottoms—transition pointswhere the market is changing trend. The other indicator type doesn’tlook for market tops or bottoms but defines when a market trend hasbeen established, confirming when a new trend is in play. Confirmingindicators give signals after a top or bottom has been made. The ideabehind it is to let the market make top or bottom, then get in afterwardand ride the trend.You can appropriately classify indicators as one or the other: Does itmark a transition point (a top or bottom) or does it respond after a top orbottom, confirming a market that has established a trend? Rememberthat these two approaches always conflict. A transition indicator such ascontrary opinion always looks best at the worst point in the trend of themarket. Keep them separate in your mind; their goals and targets arecompletely different.Understanding the Difference betweenMarket Tops and BottomsFrom a technical perspective, market tops and bottoms behave differently, and you use different technical tools for each. Tops are usually long,large, rounded affairs (think of an open fan), often to the point where it
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becomes difficult to find the exact top. The top seems to be spread out,and it appears to be more of a process than an event. Bottoms are different. Bottoms are usually short, they end quickly, and they are rather easyto locate. They are more of an event than a process (Figure 4.3).It’s important to realize that these are just the usual forms of topsand bottoms; otherwise, you may not recognize something because afixed idea prevents you from considering it. This happened to many analysts in 1982. The 1982 bear-market bottom was not a normal event bottom. The bottom didn’t occur suddenly on a single day but stretchedover six months as a rolling, compression bottom. In Figure 4.4, you cansee the compression process in the contracting number of stocks thatmade new lows as the market worked lower. I started to see the evidencefor what was happening in the late spring of 1982, about three monthsbefore the final bottom. When I spotted what was happening, watchingthe market finish the process and make bottom was like watching a threeact play: The bottom occurred in the final act. Holding to the idea thatdeclines end only in climaxes prevented many technicians from seeingthat this was a process bottom and not an event bottom, even though theevidence was there.
FIGURE 4.3 Market bottoms are usually abrupt and end quickly. Market topsusually form over an extended period.
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FIGURE 4.4 The unusual 1982 “process bottom.” The top line plots thenumber of stocks making new lows. While the New York composite index wentlower, the decreasing number of stocks hitting new lows pointed to thecompression process in progress. Careful study of individual stocks shows thathundreds of them went through powerful “saucer bottoms” as the processcontinued. (Source: © DecisionPoint.com.)
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In technical analysis, the underlying idea is that in any bull market ormajor price