Technical analysis is the study of price charts and various indicators derived from them, with the aim of predicting price movements. It is based on three principles that we will now examine.
The Three Fundamental Principles of Technical Analysis
Prices Reflect All Available Information
This assertion is the essential foundation of technical analysis, which claims that “anything that can possibly affect the price—fundamentally, politically, psychologically, or otherwise—is actually reflected in the price of that market”, without worrying about why prices rise or fall.
To begin with, these assertions show a certain simplification of how markets work and reduce the study of markets to the study of charts, which only formally reflect what has happened.
Moreover, prices may certainly incorporate all available market information, but can purely private information, particularly when it can be exploited before being made public (insider trading), really be regarded as available information? As we stated earlier, markets are not perfectly efficient; consequently, prices do not perfectly reflect all market information.
Finally, as we will see in more detail below, the market does not always incorporate all available information immediately because of the under- and overreaction of investors to information.
An interesting study on the under- and overreaction of financial analysts in post-crash periods highlights the following aspects. “The analysis of reactions to news mainly reveals a sharp decline in underreaction to the extremely negative news.
Overreaction to extremely positive news, more hesitant before the crash, also abates.” Therefore, this analysis indicates the existence of underreaction to extremely negative news and overreaction to extremely positive news in the pre-crash period.
Investors may also react to a lack of information, be tempted to react to rumors, or simply tell themselves stories to invent reasons to act. Evidently, the assertion that prices immediately reflect all available information is not always corroborated by the reality of the financial markets.
Prices Move in Trends
According to the second concept, prices move in trends and “a trend is more likely to continue than reverse or a trend in motion will continue in the same direction until it reverses”. Therefore, it is advisable to surf the trend for as long as possible before its reversal.
Price movements are certainly a succession of increases and decreases, but do prices follow a random path or can their movements be predicted? We will try to answer this question in the next section, but let's stay for a moment with this idea of trends, as in our view it is an important concept.
A series of higher highs (closing prices for example) coupled with higher lows indicates a bullish movement. The market reaches new heights and the lower levels are gradually rising. Conversely, a series of lower lows and lower highs indicate a bearish movement. When movement is lateral or without any defined direction, it is referred to as “sideways”.
Analysts usually define a long-term trend over a period of more than a year, an intermediate trend over a one to three-month period, and a short-term trend over a period of less than one month.
Alternations between bullish and bearish trends are called market cycles and are generally classified according to their duration. Long-term or primary cycles last for two years or more.
The seasonal cycle lasts one year. The intermediate or secondary cycle lasts for nine to 26 weeks. Finally, the four-week trading cycle is separated into two shorter cycles, alpha, and beta, which last an average of two weeks each.
The Kondratieff cycle lasts about 54 years, during which the economy undergoes phases of growth and correction. There are four periods (seasons): spring, summer, autumn and winter and, according to some analysts, the winter that should have started sometime around the year 2000 may have begun after the last peak in 2007. This winter cycle will last about fifty years.
Generally speaking, the primary and seasonal cycles determine the major trend of a market. Following the three most significant high points and the three most significant low points, it is possible to draw the upper and lower lines of a channel, which can be used to identify trend reversals. However, once a trend reversal is noticed, this means that we have already entered the new trend.
Other tools which help determine trends or trend reversals include chart patterns, such as the “head and shoulders”, “cup and handle”, “double or triple tops and bottoms” or “triangles”, as well as several indicators such as the MACD, Bollinger bands, RSI or the stochastic oscillator.
A former trader who taught technical analysis for more than 10 years and became a major expert on Elliott waves said one day that, in his opinion, all these indicators should be forgotten in order to focus on what he believed was the essential aspect: trends. This concept, which we also see as essential, will be covered in more detail in the following sections.
As for Elliott waves, he said he would sometimes wake in the middle of the night, panicking, not knowing if we were in the 2nd or 3rd wave. The fact his wife thought he was going crazy combined with the difficulty of applying this theory finally led him to abandon the approach. However, at this stage, it will be interesting to spend a moment looking into this theory.
THE NATURE OF TECHNICAL ANALYSIS
Technical analysts try to gauge investor sentiment by studying stock prices, trading volume, and various measures of investor sentiment.
Technicians do not look at dividends or profits, either for individual companies or for the market as a whole. If they are studying an individual company, they don’t even need to know the company’s name. It might bias their reading of the charts.
A technical analyst can be compared to a person who watches a computer program draw lines on a monitor and tries to discover a pattern that will predict the next line to be drawn. The lines themselves are all that matters and it would be distracting to think about whether the computer program was written in Java or C++.
In the same way, the mood of the stock market can be gauged by watching stock prices; additional news about the economy or specific companies would be distracting.
John Magee, who co-authored the so-called bible of technical analysis, boarded up the windows of his office so that his readings of the hopes and fears of the market would not be influenced by the sight of birds singing or snow falling.
A technician’s most important tool is a chart of stock prices. The most popular are vertical-line charts, traditionally using daily price data. Each vertical line spans the high and low prices, with horizontal slashes showing the opening and closing prices.
Conclusion on Technical Analysis
All three basic concepts of technical analysis are truly debatable. This technique is essentially used by traders or speculators with a short-term view and a goal of speculation rather than an investment objective.
Many academic or empirical studies have shown that this approach, net of transaction costs, does no better than a “buy and hold strategy”, i.e., holding assets over the long term with little portfolio rotation.
The strategy of simply holding an index fund generates more money. Various tests have been done with different technical indicators, and it has also been shown that these are of no use for investors.
Again, as Malkiel notes, human nature likes order and the idea of chance is hard to accept. Taleb also adds that “our minds are wonderful explanation machines, capable of making sense out of almost anything, capable of mounting explanations for all manner of phenomena, and generally incapable of accepting the idea of unpredictability”.
So, people seek models and patterns in random movements. By developing models, they seek to predict and perhaps invent, a kind of future, but the reality is sometimes not the one that was expected.
The Chinese, known for being more gamblers than investors, may have the right idea in considering the stock market as a giant casino and luck as a decisive factor for the return on their investment.
Since information on companies appears randomly, prices must follow a random movement. This aspect will be looked at in more depth in the following books. Finally, we will reiterate that charts only provide information on the past and, as noted by Warren Buffett, “if history revealed the path to riches, librarians would be rich”.
Nonetheless, supports and resistances can indicate important levels, and breakouts from these thresholds can indeed provide valuable clues about future price movements.
When a stock price moves within an interval without it being possible to meaningfully predict the next movement, investors should wait for more clarity. It is better to make a moderate but sure profit than to speculate on a profit that may indeed be higher but is hypothetical.
In our view, the fact that a certain number of market participants use technical analysis to make their investment decisions should be taken into account.
Accordingly, technical analysis can be useful for determining trends and support and resistance levels.
It should not, however, be used as the sole decision-making tool for investment. It is also useful for setting limit orders, which usually should not be placed on levels of support or resistance, but around these values. Supports are previous low levels and resistances are previous peaks. Depending on price movements, these thresholds may be reversed.
Investors should not spend too much time valuing financial assets but should focus instead on the opportunity to invest in one or several asset classes according to their attractiveness and outlook.
Stock Market Patterns
Millions of investors have spent billions of hours trying to discover a formula for beating the stock market. It is not surprising that some have stumbled on rules that explain the past remarkably well but are unsuccessful in predicting the future. Many such systems would be laughable, except for the fact that people believe in them.
Analysts have monitored sunspots, the water level of the Great Lakes, and sales of aspirin and yellow paint.
Burton Crane, a longtime New York Times financial columnist, reported that a man “ran a fairly successful investment advisory service based in his ‘readings’ of the comic strips in The New York Sun.”
Money magazine once reported that a Minneapolis stockbroker selected stocks by spreading the Wall Street Journal on the floor and buying the stock touched by the first nail on the right paw of his golden retriever. The fact that he thought this would attract investors says something about him—and his customers.
Here’s their recipe for investment riches:
At the beginning of the year, calculate the dividend yield for each of the thirty stocks in the Dow Jones Industrial Average.
Of the thirty Dow stocks, identify the ten stocks with the highest dividend yields.
Of these ten stocks, choose the five stocks with the lowest price per share.
Of these five stocks, cross out the stock with the lowest price.
Invest 40 percent of your wealth in the stock with the next lowest price.
Invest 20 percent of your wealth in each of the other three stocks.
No, I’m not making this up.
Any guesses why this strategy is so complicated, verging on baffling? Data mining perhaps?
Steps 1 and 2 are plausible. There is a long-established investment strategy called the Dogs of the Dow that favors buying the Dow stocks with the highest dividend yields, and this sensible strategy has been reasonably successful.
The strategy is pure data mining. Step 3 has no logical foundation since a stock’s price depends on how many shares the company has outstanding. If a firm were to double the number of shares, each share would be worth half as much.
There is no reason why a Dow stock with more shares outstanding (and a lower price per share) should be a better investment than a Dow stock with fewer shares outstanding (and a higher price per share).
Berkshire Hathaway (which is not in the Dow) has very few shares outstanding and consequently sells for a mind-boggling price of nearly $200,000 per share. Yet it has been a great investment.
Computerized trading systems
Computerized trading systems remove all human judgment. The computers are programmed to track stock prices, other economic and noneconomic data, and news stories, looking for patterns that precede stock price movements.
For example, the computers might notice that after the number of stocks going down in price during the preceding 140 seconds exceeds the number going up by more than 8 percentage points, the S&P 500 usually rises.
The computer files this indicator away and waits. When this signal appears again, the computer moves fast, buying thousands of shares in a few seconds and then selling these shares seconds later.
Done over and over, day after day, a profit of a few pennies (or even a fraction of a penny) in a few seconds on thousands of shares can add up to real money. The technology magazine Wired gushed that these automated systems are “more efficient, faster, and smarter than any human.”
True, these programs process data faster than any human, but they are no smarter than the humans who write the code that guides the computers. If a human tells a computer to look for potentially profitable patterns—no matter whether the discovered pattern makes sense—and to buy or sell when the pattern reappears, the computer will do so—whether it makes sense or not.
Indeed, some of the human brains behind the computers boast that they don’t understand why their computers decide to trade. After all, their computers are smarter than them, right? Instead of bragging, they should be praying.
On May 6, 2010, the U.S. stock market was hit by what has come to be known as a “flash crash.” Investors that day were nervous about the Greek debt crisis, and an anxious mutual fund manager tried to hedge his portfolio by selling $4.1 billion in S&P 500 futures contracts.
The idea was that if the market dropped, the losses on this fund’s stock portfolio would be offset by profits on its futures contracts. This seemingly prudent transaction somehow triggered the computers.
The computers bought many of the futures contracts the fund was selling, then sold them seconds later. Futures prices started falling and the computers were provoked into a trading frenzy as they bought and sold futures contracts among themselves, like a hot potato being tossed from hand to hand.
Nobody knows exactly what unleashed the computers. Remember, even the people behind the computers don’t understand why their computers to trade. In one fifteen-second interval, the computer traded 27,000 contracts among themselves, half the total trading volume, and ended up with a net purchase of only 200 contracts at the end of this fifteen-second madness.
The trading frenzy spread to the regular stock market, and the flood of sell orders overwhelmed potential buyers. The Dow Jones Industrial Average fell nearly 600 points (more than 5 percent) in five minutes.
Market prices went haywire, yet the computers kept trading. Procter & Gamble (P&G), a rock-solid blue-chip company, dropped 37 percent in less than four minutes.
Some computers paid more than $100,000 a share for Apple, Hewlett-Packard, and Sotheby’s. Others sold Accenture and other major stocks for less than a penny a share. The computers had no common sense. They blindly bought and sold because that’s what their algorithms told them to do.
The madness ended when a built-in safeguard in the futures market suspended all trading for five seconds. Incredibly, this five- second time-out was enough to persuade the computers to stop their frenzied trading. Fifteen minutes later, markets were back to normal and the temporary 600-point drop in the Dow was just a nightmarish memory.
There have been other flash crashes since and there will most likely be more in the future. Oddly enough, Procter & Gamble was hit again on August 30, 2013, on the New York Stock Exchange (NYSE) with a mini flash crash, so called because nothing special happened to other stocks on the NYSE and nothing special happened to P&G stock on other exchanges.
Inexplicably, nearly 200 trades on the NYSE, involving a total of about 250,000 shares of P&G stock, occurred within a one- second interval, triggering a 5 percent drop in price, from $77.50 to $73.61, and then a recovery less than a minute later.
One lucky person happened to be in the right place at the right time and bought 65,000 shares for a quick $155,000 profit. Why did it happen? No one knows. Remember, humans, aren’t as smart as computers.
Fortunately, value investors are inoculated from the perils of technical analysis, since value investors do not try to predict stock prices. Value investors buy a stock because it is an inexpensive money machine, generating bountiful cash, it is hoped, over many, many years.