Summary: Technical analysis focuses on identifying market trends, which can be upward, downward, or sideways. Analysts use tools like trend lines and moving averages to predict price movements and recognize patterns. Understanding these trends is essential for making profitable trading decisions.
the answer is that technical analysis is the study of prices in freely traded markets with the intent of making profitable trading or investment decisions. (View Highlight)
Students new to any discipline often ask, “How can I use the knowledge of this discipline?†Students new
to technical analysis are no different. Technical analysis is used in two major ways: predictive and reactive. Those who use technical analysis for predictive purposes use the analysis to make predictions about future market moves. Generally, these individuals make money by selling their predictions to others. Market letter writers in print or on the Web and the technical market gurus who frequent the financial news fall into this category. The predictive technical analysts include the more well-known names in the industry; these individuals like publicity because it helps market their services. (View Highlight)
On the other hand, those who use technical analysis in a reactive mode are usually not well known. Traders
and investors use techniques of technical analysis to react to particular market conditions to make their decisions. (View Highlight)
Trends of different lengths tend to have the same characteristics. In other words, a trend in annual data will
behave the same as a trend in five-minute data. (View Highlight)
Several requirements are needed to convert pure technical analysis into money. The first and most
important, of course, is to determine when a trend is beginning or ending. The money is made by “jumping†on the trend as early as possible. Theoretically, this sounds simple, but profiting consistently is not so easy. (View Highlight)
In sum, the basic strategy to make money using technical methods includes • “The trend is your friendâ€â€”Play the trend. • Don’t lose—Control risk of capital loss. • Manage your money—Avoid ruin.
Technical analysis is used to determine the trend, when it is changing, when it has changed, when to enter a
position, when to exit a position, and when the analysis is wrong and the position must be closed. It’s as simple as that. (View Highlight)
The trend length of interest is determined solely by the investor’s or trader’s period of interest. This is not to say that different trend lengths should be ignored. Because shorter trends make up longer
trends, any analysis of a period of interest must include analysis of the longer and shorter trends around it. (View Highlight)
Those who could not failed. In sum, investment strategies change and evolve; innovation is the secret of survival; and survival is the goal rather than maximizing the utility of risk versus return. (View Highlight)
The focus of this chapter has been on the importance of understanding price trends to the practice of
technical analysis. We have introduced some of the basic assumptions and beliefs of technical analysts. As we go through the next few chapters, we address each of these assumptions in more detail. Some of the basic beliefs that technical analysis is built on and that we build upon throughout this book are as follows: • The interaction of supply and demand determine price. • Supply and demand are affected by investors’ emotions and biases, particularly fear and greed. • Price discounts everything. • Prices trend. • Recognizable patterns form within trends. • Patterns are fractal. (View Highlight)
Honma’s rules are recorded as the “Sakata constitution.†These rules include methods of analyzing one
day’s price record to predict the next day’s price, three days of rice prices to predict the fourth day’s price, and rate of change analysis (View Highlight)
Honma’s rules might also be considered “trading rules†rather than “technical rules†because they had much to do with how to limit loss and when to step away from markets. (View Highlight)
Technical analysis is a means for the uninformed to become informed. With recording of prices and the calculation of averages, analysts began to see that prices often traded with
certain repetitive patterns. (View Highlight)
market dynamics are complicated and influenced by people and their own way of looking at investments, their own periods of interest, their own information, and their own emotions. (View Highlight)
Although this book provides the groundwork for the development of fundamental analysis, a closer reading of it reveals that Graham and Dodd did not believe that fundamental analysis alone determined stock prices. (View Highlight)
Rather we should say that the market is a voting machine, where on countless individuals register choices which are the product partly of reason and partly of emotion. (View Highlight)
it has been discovered that there is an inverse correlation between high trader emotional control and market volatility as well as a positive relationship between trader emotion and experience, suggesting that emotional regulation is important to trader expertise (View Highlight)
Finally, the large ups and downs in the market from
49 (View Highlight)
2002 on discouraged fundamental research because those research advocates had no sense of market timing, and regardless of how attractive a stock might look under the fundamental scope, it invariably got clobbered in one of the large market declines. With its ability to minimize loss, technical analysis began to come back as a useful and viable method for reducing losses during these massive declines. (View Highlight)
The reason is that people trading and investing in an imperfect, emotionally charged world determine prices. (View Highlight)
reason is that people trading and investing in an imperfect, emotionally charged world determine prices. Because technical analysis deals only with price and some other incidental trading information, it has evolved into a study of more intangible information, concerned mostly with psychology and trading behavior. Modern computer technology has demonstrated that prices are not necessarily random, but they are not perfectly predictable either. (View Highlight)
Because knowledge of all possibilities is impossible, individuals must decide on the period of interest, methods, and instruments best suited to their personality, ability, knowledge, and time available. (View Highlight)
Maurice Olivier, in his 1926 dissertation, and Frederick C. Mills, in The Behavior of Prices (1927), provided further evidence of a “leptokurtic distribution†of price changes. The leptokurtic distribution is more “pointed†than the normal, Gaussian, distribution. The leptokurtic distribution has a thinner peak and fatter tails than the normal, Gaussian, distribution. These fat tails indicate that stock prices are more likely to deviate extraordinarily from the mean more often than the normal, Gaussian, distribution of returns suggests. (View Highlight)
Therefore, we can expect cycles of expansions and contractions in the future. However, each of these business cycles is unique; the cycles vary in length and intensity. Thus, acknowledgment of a recurring cycle cannot be equated with the ability to predict the timing of an expansion or the intensity of a recession. (View Highlight)
Market participant actions depend on how individuals process information and make decisions.
Information interpretation and decision making are subject to cognitive bias and limits. Behavioral finance and neurofinance study the irrational and often unconscious behavior of investors and how they interpret information. Some of the results have shown illogical behavior that would be undesirable in the marketplace, such as comfort in crowds called “herding†(Huberman and Regev, 2001), overconfidence based on little information (Fischoff and Slovic, 1980; Barber and Odean, 2001; Gervais and Odean, 2001), overreaction (De Bondt and Thaler, 1985), psychological accounting (Tversky and Kahneman, 1983), miscalibration of probabilities (Lictenstein et al., 1982), hyperbolic discounting (Laibson, 1997), and regret (Bell, 1982; Clarke et al., 1994). More and more of these kinds of studies are demonstrating that investors often act irrationally or unconsciously. Preference in markets (View Highlight)
Invariably, they chose, when presented with potential gains, a riskaversion strategy, and when presented with potential losses, a risk-seeking strategy. In the financial markets, this kind of decision making can be disastrous. It suggests that investors have a strong tendency to sell winning positions and to keep losing positions, quite contrary to the rationality assumption of the EMH. (View Highlight)
But technical analysis is the study of price, and people determine prices. People affect long-term prices as much as short-term prices. Analysis of price behavior over the long term is just as valuable to the investor as analysis over the short term is to the trader. Indeed, the professional managers who have been the most successful have been so because they used technical analysis for long-term decisions. (View Highlight)
Cheol-Ho Park and Scott Irwin conducted one of the most extensive reviews of these tests. In their 2003 report, they review 92 post-1986 academic studies that tested the profitability of technical analysis strategies.2 2. Many tests of technical trading strategies conducted before the mid-1980s focused on only one or two trading systems, did not test for statistical significance of trading profits, and did not correctly address issues of risk.
Of the 92 studies reviewed, 58 of the studies concluded that positive results could be gained from using
technical analysis; only 24 of the studies concluded that the use of technical strategies led to negative results. (View Highlight)
Conclusion Like any practical discipline, especially one working with an indefinite and fickle subject such as the
marketplace, technical analysis has problems. The Random Walk Hypothesis is not perfect; yet at many times, prices appear to behave randomly. The EMH has many holes that cannot be explained, yet prices seem to be very efficient and the possibility of profit often slim. Fundamental analysis also has its problems, most of which were exaggerated during the market decline in the early 2000s and more recently in 2007–2009, but there is little question that stock prices, commodity prices, and currency rates change over the long run due to the fundamental changes in the economy and structure of markets. Technical analysis is no different. It has many flaws, is difficult to learn, is subject to error and bias, and often falls on its face. Nevertheless, technical analysis can be extremely useful to investors wanting to profit from timing and trend riding while limiting risk. (View Highlight)
Let us begin by dividing markets into categories based on how organized or integrated the market is. Using this type of division results in four different types of markets: direct search markets, brokered markets, dealer markets, and auction markets. (View Highlight)
The next level of market organization, the brokered market, addresses the direct search market problem of
the buyer and seller finding each other. In markets in which the volume of trading in a particular good is sufficiently high, brokers can specialize in bringing buyers and sellers together. (View Highlight)
Note: Market Profile is useful here
Notice that the players have different sources of information, different interpretations of that information,
different reasons for trading IBP’s stock, different time horizons, and different expectations (View Highlight)
The net result is a transaction between opposing players at a specific price. That price reflects the sum of all the information and interpretation by all players at that instant in time. (View Highlight)
The players only see the price and the volume of shares traded. Thus, we have a series of transactions at different prices and different volumes reflecting the interpretation
of different information by the different players. (View Highlight)
What is important to the trader or investor is that the price moves in such a manner that its direction can be determined or confirmed from past experience. This is why technical analysts study price behavior. It discounts all known information and interpretation and considers only what the price action implies about future price action. (View Highlight)
In short, the marketplace is not a stable system headed in a straight line toward equilibrium. The interaction is dynamic and nonlinear. The system is complex. (View Highlight)
How Is the Market Measured? As more of the market players want to buy stocks and fewer want to sell their stock holdings, stock prices
will be driven up. Likewise, if many market players want to sell their stocks relative to the number of participants who want to buy stocks, stock prices will fall. Looking at the increase or decrease in the price of one stock will tell us how strong the market for that one particular stock is. If we want to measure the overall direction of the stock market, however, we need a way of measuring the movement of the broad market that is composed of the stocks of many companies. (View Highlight)
Building on Dow’s initial concept, other individuals have also developed averages, or indices, to measure
market movement. Today there are almost as many averages or indices as there are stocks. Although the concept of a market average or index might be simple, choosing a method to use to construct the index is complicated. There are three major types of index construction: price weighted, market capitalization (View Highlight)
Because of the weighting scheme used, stocks with a large number of shares outstanding and high prices
have a disproportionate influence on a market capitalization weighted index. In the Table 5.3 sample data, one stock increased in value by 10% while all the other stocks remained the same on Days 2, 3, and 4. Look at how much more sensitive the index was to changes when the stock had a relatively high price or number of shares outstanding. Just as the price-weighted index is not representative of the way most investors purchase stocks, neither is the market capitalization weighted index. An investor seldom invests in stocks in proportion to their market capitalization. (View Highlight)
Note: Concept of Basket, Market Leader
In this chapter, we have explored the basics of how markets work. Because our interest lies in the area of
using technical analysis, we have focused on markets in which substitutable, liquid, continuously traded assets are bought and sold. In these markets, we find informed, uninformed, and liquidity players buying and selling securities and, thus, affecting the price of these securities. As technical analysts, we are concerned with observing and predicting price movements as these various market players go about their trading. Market indices are used to measure the overall price movement in the marketplace. As we continue through Part II, “Markets and Market Indicators,†we build upon these basic ideas. The
focus of Chapter 6, “Dow Theory,†is Dow Theory and the basic fundamental relationships between markets and the economy. In Chapter 7, “Sentiment,†we focus on the market players; we examine the notion of sentiment: the way emotions and human biases impact the behavior of both the informed and uninformed market participants. Chapter 8, “Measuring Market Strength,†focuses on measuring the strength of the market. Going beyond the indices we use to measure historical market performance, we examine indicators that measure the market’s ability to maintain its performance into the future. Chapter 9, “Temporal Patterns and Cycles,†addresses temporal tendencies; historically, analysts have found seasonal and cyclical tendencies in the marketplace that impact price movements. Finally, in Chapter 10, “Flow of Funds,†we address the movement of money in the marketplace, known as the “flow of funds.†(View Highlight)
Charles H. Dow was the founder of the Dow-Jones financial news service in New York, and founder and first editor of the Wall Street Journal. He died in December, 1902, in his fifty-second year. He was an experienced newspaper reporter, with an early training under Samuel Bowles, the great editor of the Springfield [MA] Republican. Dow was a New Englander, intelligent, self-repressed, and ultra-conservative; and he knew his business. He was almost judicially cold in the consideration of any subject, whatever the fervor of discussion. It would be less than just to say that I never saw him angry; I never saw him excited. His perfect integrity and good sense commanded the confidence of every man in Wall Street, at a time when there were few efficient newspaper men covering the financial section, and of these still fewer with any deep knowledge of finance. (Hamilton, 1922) (View Highlight)
The term “Dow Theory†was first used by Dow’s friend, A. C. Nelson, who wrote in 1902 an analysis of Dow’s Wall Street Journal editorials called The A B C of Stock Speculation. (View Highlight)
Hamilton also described the basic elements of this theory in his book The Stock Market Barometer, in 1922. (View Highlight)
In other words, contrary to Cowles’s original study, Brown, Goetzmann, and Kumar conclude that Hamilton could time the market very well using Dow Theory. In addition, they found that when Hamilton’s decisions were replicated in a neural network model of out-of-sample data from September 1930 through December 1997, Hamilton’s methods still had validity. His methods worked especially well in sharp market declines and considerably reduced portfolio volatility. (View Highlight)
After Hamilton’s death, Robert Rhea further refined what had become known as Dow Theory. In 1932,
Rhea wrote a book called The Dow Theory: An Explanation of Its Development and an Attempt to Define Its Usefulness as an Aid to Speculation. (View Highlight)
The first of these hypotheses dealt with the notion of manipulation. Although Rhea believed that the
secondary and the minor, day-to-day motion of the stock market averages could possibly be manipulated, he claimed that the primary trend is inviolate. (View Highlight)
Dow Theory posited that there are three basic trends in price motion, each defined by time:
There are three movements of the averages, all of which may be in progress at one and the same time. The first, and most important, is the primary trend: the broad upward or downward movements known as bull or bear markets, which may be of several years duration. The second, and most deceptive movement, is the secondary reaction: an important decline in a primary bull market or a rally in a primary bear market. These reactions usually last from three weeks to as many months. The third, and usually unimportant, movement is the daily fluctuation. (Rhea, 1932) (View Highlight)
The Primary Trend
Correct determination of the primary movement (or trend) is the most important factor in successful speculation. There is no known method of forecasting the extent or duration of a primary movement. (Rhea, 1932) (View Highlight)
The Secondary Trend
…a secondary reaction is considered to be an important decline in a bull market or advance in a bear market, usually lasting from three weeks to as many months, during which intervals the price movement generally retraces from 33 percent to 66 percent of the primary price change since the termination of the last preceding secondary reaction. (Rhea, 1932) (View Highlight)
The Minor Trend
Inferences drawn from one day’s movement of the averages are almost certain to be misleading and are of but little value except when “lines†are being formed. The day to day movement must be recorded and studied, however, because a series of charted daily movements always eventually develops into a pattern easily recognized as having a forecasting value. (Rhea, 1932)
A line is two to three weeks of horizontal price movement in an average within a 5% range. It is usually a sign of accumulation or distribution, and a breakout above or below the range high or low respectively suggests a movement to continue in the same direction as the breakout. Movement from one average unconfirmed by the other average is generally not sustained. (Rhea, 1932)
The portion of the Dow Theory which pertains to “lines†has proved to be so dependable as almost to deserve the designation of axiom instead of theorem. (September 23, 1929, in Rhea, 1932; pg. 249)
The stock market is not logical in its movements from day to day. (1929, in Rhea, 1932; (View Highlight)
“Conclusions based upon the movement of one average, unconfirmed by the other, are almost certain to prove misleading†(Rhea, 1932). (View Highlight)
Confirmation in the Dow Theory comes when both the industrial and railroad averages reach new highs or
new lows together on a daily closing basis. These new levels do not necessarily have to be reached at exactly the same time, but for a primary reversal, it is necessary that each average reverses direction and reaches new levels before the primary reversal can be recognized (see Figure 6.3). Confirmation, therefore, is the necessary means for recognizing in what direction the primary trend is headed. Failure to reach new levels during a secondary reaction is a warning that the primary trend may be reversing. For example, when there is a primary bull market, the failure of the averages to reach new highs during a secondary advance alerts the analyst that the primary trend may be reversing to a bear market. These are called nonconfirmations. In addition, if lower levels are reached during the secondary bear trend, it is an indication that the primary trend has changed from an upward bull trend to a downward bear trend. Thus, more extreme levels occurring during a secondary retracement in the opposite direction of the primary trend are evidence that the primary trend has changed direction. When confirmed by the other average, the technical analyst then has proof that the primary trend has reversed and can act accordingly. (View Highlight)
Importance of Volume
Various meanings are ascribed to reductions in the volume of trading. One of the platitudes most constantly quoted in Wall Street is to the effect that one should never sell a dull market short. That advice is probably right oftener than it is wrong, but it is always wrong in an extended bear swing. In such a swing…the tendency is to become dull on rallies and active on declines. (Hamilton, May 21, 1909, as quoted in Rhea, 1932)
Although volume of transactions cannot signal a trend reversal, it is important as a secondary confirmation
of trend. Excessively high market prices that are accompanied by less volume on rallies and more activity on declines usually suggest an overbought market (see Figure 6.5). Conversely, extremely low prices with dull declines and increased volume on rallies suggest an oversold market. “Bull markets terminate in a period of excessive activity and begin with comparatively light transactions†(Rhea, 1932). (View Highlight)
The originators of Dow Theory were quick, however, not to overstate the importance of volume.
Although volume was considered, it was not a primary consideration. Price trend and confirmation overrode any consideration of volume.
The volume is much less significant than is generally supposed. It is purely relative, and what would be a large volume in one state of the market supply might well be negligible in a greatly active market. (Hamilton, 1922, p. 177) (View Highlight)
As a general rule, it is foolish to do just what other people are doing, because there are almost sure to be too many people doing the same thing. (William Stanley Jevons [1835– 1882], as quoted in Neill, 1997, p. 13) (View Highlight)
When emotion becomes excessive and prices thereby deviate substantially from the norm, a price reversal is usually due, a reversion at least to the mean and sometimes beyond. It is, thus, important for the technical analyst to know when prices are reflecting emotional extremes. (View Highlight)
Market Players and Sentiment
The appropriate corresponding timing strategy is to follow informed trader sentiment, act against positive feedback trader sentiment, and ignore liquidity trader sentiment. (Wang, 2000) (View Highlight)
It is not simply the profession or career standing of a market player that classifies an individual as an informed or uninformed player; it is the timing of the player’s optimistic buying and pessimistic selling relative to market highs and lows. (View Highlight)
The informed market players tend to act in a way that is contrary to the majority. That is, the informed
market participants tend to sell at the top, when the majority is optimistic, and buy at the bottom, when the majority is fearful and selling. Just as uninformed players need not be amateurs, informed players need not be professionals. They can be corporate insiders or day traders sitting in their dens in the Caribbean. (View Highlight)
By and large, the uninformed players have considerably more money than the informed players during a
market trend. While day to day the informed players stabilize the markets by spotting and acting upon small anomalies in prices and act as contrarian investors investing in undervalued assets, over longer periods, the uninformed tend to overwhelm the price action with their positive feedback, in many instances forcing the informed to ride with the trend of emotion. (View Highlight)
“Many pathological mood states (such as depression, mania, anxiety, and obsession), neurological conditions (such as Parkinson’s disease and Alzheimer’s disease), and impulsecontrol disorders (such as kleptomania, compulsive shopping, and pathological gambling) are known to affect financial decision making: depression is associated with risk aversion, mania with investing overconfidence, anxiety with “analysis paralysis,†and compulsions with overtrading. Interestingly, the financial symptoms of these illnesses can be reduced by medications.†(Peterson, p. 47) (View Highlight)
However, the field of behavioral finance has defined numerous ways in which investors act less than rational. These biases are common not just to the occasional investor or uninformed public but to professionals as well. Just look at how many professional securities analysts were caught in the late 1990s stock market euphoria. These were not stupid, irrational people, but their inherent biases, those common to all humans, overcame their ability to reason, and they became caught up in the optimism of the time to tragic effect. (View Highlight)
…our brains often drive us to do things that make no logical sense—but make perfect emotional sense. (View Highlight)
Understanding that investor emotion and bias affect investment decisions is important for two reasons.
First, understanding the links between emotions, investment behavior, and security prices can help the technical analyst profit by spotting market extremes. Second, technical analysts must remember that they are subject to the same human biases as other investors. This set of human biases is so strong that even those who recognize them still are affected by them and must constantly fight against them. Successful traders and investors often say that the worst enemy in investment is oneself. Technical analysts hope to profit from understanding how human bias can cause people to pay prices greater than the intrinsic value for a stock, but if they are not careful, their own biases may cause them to do the same. (View Highlight)
Crowd Behavior and the Concept of Contrary Opinion
The art of contrary thinking may be stated simply: thrust your thoughts out of a rut. In a word, be a nonconformist when using your mind.
Sameness of thinking is a natural attribute. So you must expect to practice a little to get into the habit of throwing your mind into directions that are opposite to the obvious. Obvious thinking—or thinking the same way in which everyone else is thinking— (View Highlight)
commonly leads to wrong judgments and wrong conclusions. Let me give you an easily remembered epigram to sum up this thought: When everyone thinks alike, everyone is likely to be wrong. (Neill, 1997, p. 1) (View Highlight)
A “crowd†thinks with its heart (that is, is influenced by emotions) while an individual thinks with his brain. (Neill, 1997, p. 3) (View Highlight)
Contrary opinion is a “way of thinking… It is more of an antidote to general forecasting than a system for
forecasting. In a few words, it is a thinking tool, not a crystal ball†(Neill, 1997, p. 9). To be a contrarian, an investor must sell (be pessimistic) when the overall market mood is grossly optimistic and buy (be optimistic) when most investors are pessimistic and in a panic. (View Highlight)
Remember that one of the basic tenets of Dow Theory is that prices trend. When prices are trending upward, we want to be in a long position, riding the trend. The goal of understanding sentiment is to discern when that trend is losing energy and will reverse. Therefore, the task of the contrarian player is to find a way in which to quantify which direction the majority of market players is headed and to question whether there is enough remaining energy to keep the market moving in that direction. Remember that so long as players still have money to invest in the market, their optimism will drive prices higher. It is only when players are fully invested that their optimism will not be accompanied by security purchases. At this point, the market is at an excess, and the trend often ends. To quantify these excesses, the technical analyst uses publicly available data to construct indicators of emotional excess. (View Highlight)
How Is Sentiment of Uninformed Players Measured? A top in the market is the point of maximum optimism, and a bottom in the market is the point of maximum pessimism. (Davis, 2003, p. 9) (View Highlight)
Sentiment Indicators Based on Options and Volatility To glean some information about what uninformed traders are doing, analysts often consider option
trading activity and volatility measures. Option trading can be a sign of market speculation, and volatility can be an indication of the anxiousness of market players. (View Highlight)
Because the purchase of a call represents one who believes the stock market will rise and a put reflects a
bearish opinion, a ratio of calls to puts or puts to calls represents the relative demand for options by speculators and, thus, is a hint as to their disposition toward the market. The more call buyers relative to put buyers, the more optimistic are the speculators. (View Highlight)
How We Test and Optimize Oscillators When an indicator oscillates about a horizontal line within specific bounds, the most common method of discovering buy and sell signals is to use two additional horizontal lines, one for buys (or long positions) and one for sells (or short positions). (In addition to using the sell signals for exiting a long position, they can be used to tell us the optimal profit on the downside if an investor uses them to enter into a short position.) As the indicator declines below the upper line, it gives a signal, and as it rises above the lower line, it gives another signal. If the oscillator is in sync with the market, namely that highs occur at market highs and lows at market lows, the lower band becomes a buy signal and the upper line a sell (or short) signal. In some cases, the relationship between the market and the indicator is inverse, that is when the indicator is high at market bottoms and vice-versa, in which case the upper line becomes the buy line and the lower the sell line. We added one more rule to the testing method that helps keep the number of signals down and avoids many premature signals. This rule states that when a buy signal occurs, the direction and price high of that bar is recorded, and only when a subsequent price trades above that high will the entry buy be executed. For sell signals, the opposite is true: The price must break below the recorded low for an execution to occur. (View Highlight)
The final, simplest, and most consistent method of calculating puts to calls is to calculate a ratio of the
total volume of puts traded in a day versus the total volume of calls (McMillan, 1996). (View Highlight)
While having some predictability in that form, it is shown to demonstrate how volatility is mean reverting, oscillating about its long-term mean but always returning to it. (View Highlight)
As in security returns, however, this is not an absolute. Just as there are fat tails in the distribution of price
returns, fat tails also occur in volatility distributions. Another common assumption is that volatility is independent of price return. In other words, adherents to this assumption claim that the ability to predict the volatility of a security will not aid in predicting the future price direction or return. Some evidence refutes this hypothesis. Volatility is often a measure of the anxiousness of the players in the security market, increasing as they become nervous and decreasing as they become complacent. Because the players act as a crowd and are often uninformed, volatility can be a predictive factor in markets. (View Highlight)
Implied volatility is a figure derived from the Black-Scholes option formula. The Black-Scholes
option-pricing model, the most common method of determining the value of an option, suggests that the price of an option is a function of the spread between the underlying security price and the strike price of the option, the time remaining in the option, the prevailing interest rate, and the volatility of the underlying security. (View Highlight)
VIX is the exchange symbol for a percentage indicator of implied volatility in Standard & Poor’s 500
options. Volatility in the Nasdaq Composite and the S&P 100 Index are represented by VXN and VXO, respectively. VIX, VXN, and VXO are traded on the CBOE as futures and options. Instead of measuring historical volatility, these indicators measure implied volatility. Historic volatility is past volatility and generally oscillates with past anxiousness. By looking at implied volatility, the analyst hopes to measure market participants’ anxiousness about the future. (View Highlight)
Most of the time (65%), the ratio remained between the two extremes. This is quite characteristic of the usefulness of sentiment as a market signaling method. Extremes in sentiment are the most meaningful and tend to be accurate contrary indicators, but most of the time, sentiment remains in the middle and is not useful. (View Highlight)
Another method suggested by Goepfert to use the VIX as a market-timing indicator is the VIX 3-month
spread. This is the difference between the price of VIX futures 1-month out and 3-months out and is shown in Figure 7.8. According to Goepfert, “the spread will be high if futures traders think volatility is going to spike in the near-term,†and will be low if VIX traders are complacent. Because high volatility is associated with market bottoms, a high in the spread should signal when to buy. We tested this concept with the moving band method and found that, indeed, the spread had a predictive capacity. (View Highlight)
Emotions play an important role in determining the actions of market participants. Market participants demonstrate periods of both extreme optimism, when bubbles occur, and periods of extreme pessimism, when crashes or panics occur. The uninformed market players tend to be most optimistic as the market reaches a peak. These same individuals tend to be most pessimistic when the market is at its lowest point in a downturn. In other words, most investors are fully invested just at the time they should liquidate their holdings and out of the market just at the point when they could be buying stocks at a low price. Sentiment indicators help the technical analyst pick these market extremes. By following a contrarian strategy, the technical analyst hopes to act opposite of the uninformed majority of market players. (View Highlight)
One important factor in
measuring market internals is the calculation of market breadth line (advance-decline line). Market breadth is a measure of how widely a market move is spread throughout the stock market. In other words, measuring breadth tells the analyst whether an increase in the market index is characterized by a large increase in the price of a few stocks or a smaller increase in the price of the majority of the market stocks. Is the typical stock moving the same way that the market index (which can be influenced by big moves in a few stocks) is moving? If so, the market direction is confirmed by the internals. If not, the internals and the index are diverging, indicating that internal strength is changing. (View Highlight)
Another way of looking at internal market strength is to look at up and down volume. Instead of looking
at the number of issues that advanced or declined on a particular day, look at up and down volume measures. Using this type of measure, each stock issue is not given equal weight. Instead, stocks with heavy trading volume are given more weight and play a more important role in gauging internal market strength. (View Highlight)
Although the statistical methods demonstrating some of the temporal patterns are flawed, several appear to
have some merit. Though not something to depend strictly upon, they are consistent enough to be considered when timing long-term investments. These are the long-term Kondratieff cycle, the alternating 17-year cycle of dormancy and intensity, the 4-year cycle, and the seasonal cycle. Each has been relatively reliable, statistically sound, with some generous and occasional adjustments, and if applied mechanically have produced substantial results. The other cycles and patterns may occasionally prove to have merit, but the technical analyst should approach their use with great caution. (View Highlight)
Flow of funds indicators are a good means of assessing the available funds for investment. We have looked
at some indicators of funds within the marketplace and from outside the marketplace, and we have looked at their interest rates. The most reliable signals seem to come from interest rates. Some technical analysts believe that the study of the flow of funds is best left to quantitative analysts or quants, who closely follow the historic relationships between equities and fixed income securities. (View Highlight)
A chart is like a cat’s whiskers. A cat’s whiskers tell the cat which way the mouse will turn and thus which way to pounce. The mouse doesn’t think about which way it will turn, but the cat must anticipate that direction. Likewise, the market doesn’t know which way it will turn, but the speculator must anticipate that turn regardless. He uses a chart as his whiskers. (Sieki Shimizu, 1986) (View Highlight)
The details may be different, and perhaps the methods of profiting depend on various trade-offs between risk and reward, but still the analyst must use the rules and decide on the entry and exit points. The difficulty of profiting from technical analysis is not with the rules themselves but with their application. (View Highlight)
Our discussion of trend, support and resistance, and pattern nuances will show where they can be in error or where interpretation can be particularly difficult. Rules have developed over the years that will help with interpretation. Nevertheless, the student, when he can, should test and experiment (View Highlight)
Do not, therefore, expect the following observations and rules to be an easy means to profit. Study, have patience, and study some more. (View Highlight)
There is no need to rush. The markets are always there. (View Highlight)
Remember that profit with minimum capital risk in the securities markets is the sole objective, and
technical analysis is an effective way to profit as well as to control risk. (View Highlight)
The key to profiting in the securities market is to follow these three steps: 1. Determine, with minimum risk of error, when a trend has begun, at its earliest time and price. 2. Select and enter a position in the trend that is appropriate to the existing trend, regardless of direction (that is, trade with the trend—long in upward trends and short or in cash in downward trends).
3. Close those positions when the trend is ending. (View Highlight)
The principal caveat, however, in technical analysis, as mentioned previously, is that although the trend
concept is easy to understand, its application is difficult largely because the determination of trend and trend reversal is, in many instances, a subjective decision that depends on one’s skill and experience in the securities markets and one’s ability to control one’s own emotions. Practice and mental anguish are the background of any successful technical analyst. (View Highlight)
All market participants make mistakes, but the regimented professionals correct theirs quickly. (View Highlight)