The performance of specific issues can differ widely, not only over the course of the total market bull move, but during its various stages as well. This concept was described in Chapter 22, which described the sector rotation process.
The first step is to decide whether the market is in a primary bull or bear trend using the principles outlined earlier. If it is fairly evident that a bull market began some time ago and there are few signs of a top or evidence of a bear market, intermediate lows are a good place to begin the analysis. I’ll have more to say on that one later, but for now, let’s assume that there is ample evidence that a new bull market is just beginning. Signs would include the observation that A/D line had been falling for a year or more. We would also probably see a confirmed new trend of declining interest rates and an oversold condition in the long-term momentum indicators, lots of media coverage on weakness in the stock market and the economy, layoffs at major brokerage firms, and so on.
If all of these conditions were present, it would be an odds-on probability that the market was either at or very close to a bear market low based on the principles outlined earlier in this chapter.
Selecting Stocks Close to a Bear Market Low
The next step would be an examination of the technical position of the various industry groups, especially the early-cycle leaders, to make sure that they are technically sound on both an absolute and relative basis. Finally, an examination of the stocks within the groups found to be the most sound should be undertaken.
In this respect, the obvious starting point would be an analysis of the relative positions of the various industry groups in terms of the sector rotation process described in Chapter 22. Some sectors do not fit conveniently into the chronological sequence that makes up a complete cycle, and not all that do respond in the way expected in every cycle. However, an analysis of the energy and financial sectors or the banks/aluminum ratio would be a good point to determine whether the environment was an inflationary or deflationary one. The next step would be to analyze the groups that were akin to the sector that looked more promising. We will do that later, but for now, let us assume that we have been lucky enough to identify a bear market low.
The 1990 bottom met these requirements. The S&P Composite actually fell for a relatively short period of time, yet the New York Stock Exchange (NYSE) daily A/D line had been falling for over a year by the time the market bottomed in late 1990. One of the good-looking groups falling into the early leader category at the end of 1990 was the brokerage industry. What made them especially appealing as a contrary play was the Businessweek cover story cited in Chapter 30 questioning the future of the industry.
Technically, Chart 32.9 shows that the index completed a base in early 1991.
CHART 32.9 S&P Brokerage Index, 1982–1993, and Three Indicators
The RS line was ahead of the game because it experienced an 8-year down trendline break a couple of months earlier right at the turn of the year. The index itself had simultaneously violated a smaller down trendline and crossed above its 24-month moving average (MA) as the RS line was breaking out. The RS line also crossed above its 24-month MA. Both long-term monthly Know Sure Things (KSTs) triggered bullish signals as well. Note how the RS line made a slightly lower low in 1990 than in 1987 but the RS KST did not. This positive divergence added icing to the bullish case, indicating the probability of an emerging bull market to be pretty high. The dotted vertical line on this chart indicates the approximate point where the initial trend breaks took place. They are replicated on Charts 32.10 through 32.15, which feature individual stocks.
CHART 32.10 Merrill Lynch, 1983–1993, and Three Indicators
CHART 32.11 Merrill Lynch, 1986–1991, Relative to the Brokerage Index
CHART 32.12 Legg Mason, 1986–1993, and Three Indicators
CHART 32.13 Legg Mason, 1986–1991, Relative to the Brokerage Index
CHART 32.14 Raymond James, 1985–1993, and Three Indicators
CHART 32.15 Raymond James, 1986–1993, Relative to the Brokerage Index
Merrill Lynch (symbol MER), formerly the largest broker and now no longer with us as a separate trading entity, is featured in Charts 32.10 and 32.11.
It violated a 2-year down trendline for the absolute price and an 8-year down trendline for the RS line against the S&P. Since both KSTs were turning bullish and the absolute one was actually completing a reverse head-and-shoulders pattern, MER would have qualified as a buy. Later on, the 8-year down trendline for the absolute price was penetrated on the upside, and that completed the bullish picture. Chart 32.11 shows the price together with an RS line against the Brokerage Index itself. A rising line means that the stock is outperforming the index and vice versa. It is fairly evident at the opening of 1991 that this stock has broken its downtrend and was, therefore, likely to outperform both the S&P and the Brokerage Index.
Legg Mason, featured in Chart 32.12, was also in a bullish position since both the absolute and relative prices had broken out from bases and their respective KSTs had gone bullish. Indeed, the relative KST was actually diverging positively from the RS line.
This sideways action was actually potentially more bullish than that of MER, which was reversing from a downtrend. However, Chart 32.13 shows us that RS line against the Brokerage Index was actually tracing out a top. Unfortunately, that was not known at the time of the breakout (i.e., at the dotted vertical line). There was little doubt by the early spring of 1991 that a switch to another broker would have made sense since the RS line completed the top and dropped below its 65-week estimated moving average (EMA).
Finally, Raymond James, featured in Chart 32.14, came away from the 1989–1990 bear market virtually unscathed. At the time of the broker breakout, both the absolute and relative lines were completing large bases.
Unfortunately, this was not a low-risk situation like Merrill because the long-term KST for the absolute price was reversing from a moderately overbought condition, which, on the one hand, made it less attractive. On the other hand, it often pays to go with the leader because strong stocks have a habit of getting stronger. This is because there are usually some good fundamentals that enabled them to be strong stocks in the first place. The arbiter in this case would have been the RS line against the Brokerage Index in Chart 32.15. Just after the breakout, it started to accelerate away from its 65-week EMA and up trendline and outperformed the Brokerage Index for the next year.
Using a Change in the Cycle to Select Stocks
Throughout the stock cycle, groups are continually changing leadership. One way of detecting this is to create a ratio of a leading and lagging group. Chart 32.16 shows such a series—aluminums against property casualty insurers.
CHART 32.16 S&P Aluminum/Property Casualty Ratio, 1984–2012, and Two Indicators
When the line is rising, it is bullish for aluminum producers relative to insurance stocks, and vice versa. We are looking for changes in the direction of the ratio, which offer a proxy for a change in leadership from early-cycle, liquidity-driven issues to late-cycle, earnings-driven sectors. It is fairly evident from looking at the chart that this is a pretty jagged relationship subject to numerous whipsaws. One way around this is to construct a smoothed long-term momentum indicator, such as a KST—the moving-average convergence divergence (MACD) or stochastic (24/15/10) can also be substituted. Note that the indicator in the bottom panel is similar in its trajectory since it is the long-term monthly KST for the inflation/deflation ratio discussed in Chapter 22. It’s a preferred measure and acts as a check, but for a “down and dirty” substitute, the more narrowly based aluminum/insurance ratio works fine. KST MA crossovers of the ratio are then used as a proxy for when a change in leadership might be taking place.
In most situations, the ratio bottoms out during the course of the cycle rather than at a bear market low. An exception developed during early 2009 because of the relative collapse of financials in the 2008–2009 crisis. For this exercise, we are interested in the point in the cyc
le when the ratios bottom, since that gives us a clue that the inflationary part of the cycle is underway. The arrows on the chart flag two such reversals in 1993 and the very end of 2005. The upside reversals indicated a switch to lagging or earnings-driven stocks. In these instances, both rallies lasted a couple of years. At the time it was not possible to note breakouts in resource-based stocks in 1993, as this was the early stage of the tech boom, but in Chart 32.17 the lagging technology sector appears to offer some potential.
CHART 32.17 S&P Computer Hardware, 1986–2012, and Three Indicators
In both cases a certain amount of stalking was necessary as the absolute and relative down trendlines were not violated for several months after the aluminum/insurance ratio signal was given. Eventually, the lines were violated and in the case of the 1993 signal, a worthwhile rally followed. There are lots of computer hardware stocks, but one well-known seasoned issue is IBM, featured in Chart 32.18. See how both KSTs bottomed and the absolute and relative trendlines violated on the upside in 1993 and 2005.
CHART 32.18 IBM, 1987–2010, and Three Indicators
Apple (Chart 32.19) is another industry giant, but while its KSTs bottomed in a sympathetic way to computer hardware action, neither the price itself nor its RS experienced an upside breakout.
CHART 32.19 Apple, 1987–2012, and Three Indicators
Short-Term Analysis
Short-term traders will need to adopt one more stage to the analysis, and that is to make sure that prior to a purchase, the stock in question is in a technically strong short-term position as well as being in a constructive mode from a long-term point of view.
Chart 32.20 shows McKesson with a short-term and long-term KST, both based on daily data.
CHART 32.20 McKesson, 1999–2001, and Two Indicators
In this case, the long-term KST uses the same time frames as the monthly formula, but multiplied by 21 to correspond to the approximate average trading day in a month. The vertical thick black line indicates the low point separating the bear market on the left from the primary bull trend on the right. The letters mark the short-term KST buy signals that developed close to or below zero. Other smoothed short-term oscillators, such as a stochastic, smoothed relative strength indicator (RSI); MACD; etc., could, of course, be substituted for the KST. Note that none of the signals labeled A to D had any form of upside magnitude, with the exception of C. Even here, the nice trendline break in the price was followed by a whipsaw breakout, simply because this was a bear market environment. This again emphasizes the point that the best signals go with the trend. This is not the same thing as saying that all short-term bear market buy signals result in whipsaws and all pro-trend moves will be successful. For example, the buy signal at H took place during the bull move but was essentially a false signal. Again, we could filter this one out because it was not possible to construct a meaningful trendline as it was at F, H, and I.
E, of course, was the most successful, but at the time, the long-term KST had not crossed above its MA. However, one of the principles of interpretation allows us to anticipate a reversal if the KST has flattened and if a trendline break in the price or short-term KSTs is sufficient to anticipate a reversal. In this case, an 8-month down trendline in the price had been violated, and the short-term KST had gone bullish and diverged positively with the price twice. Consequently, there would have been enough evidence to draw the conclusion that the odds favored a long-term KST buy signal being triggered.
Sometimes, when a computer scanning exercise returns a long-term smoothed momentum buy signal, the short-term situation is overbought. Chart 32.21 offers an example for IBM at arrow A. In such situations, it doesn’t matter too much for a long-term investor, but for a short-term trader, entering when the price is overbought can prove disastrous. Chart 32.21 shows that the first opportunity to buy once the long-term KST had crossed its MA came under the cloud of a short-term overbought situation.
CHART 32.21 IBM, 1993–1994, and Two Indicators
The next one came at B when the price broke above a small trendline and the short-term KST triggered a buy signal. Even this was not the greatest of signals, but at least the entry price was lower than that when the long-term series went bullish. The best signal of all developed at X when the price violated a down trendline and the short-term KST went bullish. Note also that the KST was barely below zero at the time, which was a tip-off for the sharp rally that followed. Since the long-term KST had reversed to the upside at this point, it would have been reasonable to use all this positive evidence to conclude that the probabilities strongly favored a long-term MA crossover.
I am not going to say that anticipating a long-term buy signal will work every time, but it is certainly true that on many occasions the first rally coming off a bear market low often turns out to be very worthwhile.
Summary
1. Most stocks go through ownership cycles, which normally take a long period to complete. It is important to identify whether a stock is in a secular uptrend or downtrend in order to better understand its position within its ownership cycle.
2. Substantial profit potential is available to the long-term investor who can identify stocks that are breaking out from extended bases when they are accompanied by expanding volume and an improving long-term trend in RS.
3. A bull market generally carries most stocks with it, but the performance of individual issues can vary enormously, both over the course of the primary upmove and within it.
4. Once a favorable market environment has been established, the process of selecting stocks should begin with the selection of industry groups with a positive long-term technical position.
5. Following the isolation of attractive sectors and subsequently groups, it is important to look for stocks that are also showing positive technicals.
33 TECHNICAL ANALYSIS OF INTERNATIONAL STOCK MARKETS
Equities are bought and sold throughout the world for essentially the same reasons, so the principles of technical analysis can be applied to any stock market. Unfortunately, the degree of sophistication in statistical reporting of many countries does not permit the kind of detailed analysis that is available in the United States, although things are improving rapidly. Even so, it is possible to obtain data on price, breadth, and volume for most countries. Information on industry groups and interest rates is also widely available.
In this chapter we will concentrate on longer-term trends for the purpose of gaining perspective, but the analysis can just as easily be used to identify intermediate-term and short-term trends.
Identifying Primary Global Trends
Chart 33.1a shows the Morgan Stanley Capital International (MSCI) World Stock Index, which is constructed from a selection of blue-chip stocks from many different countries weighted by capitalization.
CHART 33.1a MSCI World Stock Index, 1964–1992, Showing 4-Year Cycle Lows
This series has been adjusted to U.S. dollars and is widely published in the financial press. Other world indexes published by Dow Jones and the Financial Times can be adopted into the analysis, but the MSCI has been chosen because of its extensive history going back to the 1960s. In addition, MSCI indexes are available for direct investment in individual country and regional exchange-traded funds (ETFs), as is the World Index (symbol ACWI) itself. The World Index is a good starting point from which to analyze the cyclical trends of the various stock markets, just as the S&P Composite might be used as a starting point for the U.S. market. This is because the stock markets around the globe tend to move in the same direction, just as the majority of U.S. stocks reflect the primary trend of the S&P most of the time. Generally speaking, improvements in technology and communications have broken down geographical and trading patterns, and countries have become more interdependent, with the result that their stock markets and business cycles are now more closely related than they used to be. A giant leap in this direction appeared to take place after the 1987 crash, in which all markets participated on a synchronized basis. Thi
s was later reinforced almost 10 years later when the so-called “Asian meltdown” reverberated around the world. The introduction of international and specific country closed- and open-ended mutual funds in the 1980s and 1990s and their U.S.-based expansion in the opening decade of the current century is a striking example of this growing sense of international awareness. There are exceptions, though, because it is possible for different economies to be in a different state of expansion than others. An example might be the performance of neighbors Greece (ETF symbol GREC) and Turkey (TUR) in the 2011–2012 period in that the Greek economy was retrenching and the Turkish economy expanding. As a result of the variations in the long-term economic, financial, and political situations between countries, a good world bull market in equities may be brief or almost nonexistent for a country undergoing financial distortions, such as Hong Kong between 1986 and 1990. Country performance can also differ because of the makeup of specific markets. For example, the Swedish and Finish indexes performed superbly in the latter part of the 1990s because they were dominated by technology companies. Countries with substantial natural resources such as Canada (EWC) and Australia (EWA) tend to outperform when commodity prices are rising and so forth. An additional factor emanates from demographics. Regions and countries with a population pyramid skewed toward older people (Europe and Japan, for example) have a built-in disadvantage compared to countries such as Indonesia, India, Turkey, etc., whose population is skewed toward younger people, where growth characteristics such as family formation, consumer spending, and so forth are far more dominant.
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