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Technical analysis, also known as charting, is the study of the trading history (the price and volume over time) of any type of security (stocks, commodities, etc.) to attempt to predict future prices. In its purest form, technical analysis is concerned only with the actual price behavior of the instrument, based on the theory that all other factors affecting valuation will be reflected in the price before an investor can become aware of them through other channels.
General description
Technical analysis assumes that non-random price patterns and trends exist in markets, and that these patterns can be identified and exploited. While many different methods and tools are used, the study of charts of past price and trading action is primary. Technical analysts search for current price activity resembling archetypical patterns, such as the well-known head and shoulders reversal pattern, and also study the graphs of mathematical "indicators" derived from price and/or volume action, such as the popular moving average.
Technical analysis is not intended to be anywhere near 100% accurate in predicting price movements. Rather, the goal is to produce predictions of price direction and magnitude such that large gains from the relatively few correct predictions are more than enough to offset the many smaller losses from incorrect predictions, leading to a positive return in the long run through proper risk control and money management.
Technical analysis is frequently contrasted with fundamental analysis, the study of basic economic factors theorized to influence the price of an instrument in order to predict future price movement. Pure technical analysis holds that the effects of all such factors are already priced into the market long before the analyst can possibly become aware of them, and so one need only study the price action. Some traders use one or the other style exclusively, while many others use both types of analysis together to make trading decisions.
There are several schools of thought within technical analysis. Adherents of different schools (for example, candlestick charting, Dow Theory, and Elliott wave theory) often treat the other approaches with derision, though again, many traders successfully combine elements from more than one school.
Many practitioners view technical analysis as more art than science. Actual price patterns rarely conform exactly to a given price archetype, and a degree of judgement acquired through experience must be used to decide what pattern a particular instrument is in at a given time, and what the interpretation of that pattern should be. Technical analysts not infrequently disagree among themselves over the interpretation of a given chart.
Many academic studies conclude technical analysis has scant predictive power, but other studies suggest that it might produce excess returns. For example, measurable forms of technical analysis, such as non-linear prediction using neural networks, have been shown to occasionally produce statistically significant prediction results. As an example of the debate regarding the efficacy of technical analysis, Peter Lynch, a very well-known and successful fundamental analyst, once commented, "Charts are great for predicting the past." A Federal Reserve working paper has shown that the statistical properties of intraday foreign exchange prices change near "support and resistance" lines.
History
The premises of technical analysis were derived from observation of financial markets over hundreds of years. The oldest branch of technical analysis is the use of candlestick techniques by Japanese traders at least as early as the 18th century, and now one of the main charting techniques. Traditionally, "Honno, the God of the markets," a very successful rice trader in early Japan, is said to have invented technical analysis.
Dow Theory inspired the use and development of modern technical analysis from the end of the 19th century, a theory based on the collected writings of Dow Jones co-founder and editor Charles Dow. Modern technical analysis considers Dow Theory its cornerstone.
Many more technical tools and theories have been developed and enhanced in recent decades, with an increasing emphasis on computer-assisted techniques.
Beliefs
Technical analysis is not concerned with why a price is moving (e.g. poor earnings, difficult business environment, poor management, or other fundamentals) but rather whether it is moving in a particular direction or in a particular chart pattern. Technical analysts believe that profits can be made by "Trend following." In other words if a particular stock price is steadily rising (trending upward) then a technical analyst will look for opportunities to buy this stock.
Until the technical analyst is convinced this uptrend has reversed or ended, all else equal, he will continue to own this security. Additionally, technical analysts look for various price patterns to form on a price chart and will take positions in anticipation of the expected move following that pattern. The tools of technical analysis are believed to assist the technician in determining when trends have formed, ended, etc. and when particular patterns are unfolding.
For example, a popular technical analysis tool is a stock price's 200 day moving average. This is usually defined as the average closing price of a stock over the past 200 trading days (though there are many variations on the moving average used in technical analysis). A stock that has been trending higher will have a history of an increasing daily stock price and an increasing 200 day moving average. Though the daily stock price fluctuates (up 50 cents on day 1, down 20 cents on day 2, up 10 cents on day 3, etc.), the 200 day moving average changes much more slowly and traces a smooth curve that follows the current price on a chart.
When the 200 day moving average is violated by the daily stock price, a technical analyst uses this as strong evidence that a price trend has ended and that possibly a new one has begun to the opposite direction. Suppose IBM's 200 day moving average was 85 and the stock has been trending higher. If IBM closed at 84.50, then a technical analyst would consider selling his IBM holdings and perhaps selling short IBM because the perceived trend is ending.
The above example illustrates a few important characteristics and potential shortfalls of technical analysis. Much of technical analysis is art and open to some varying interpretation. One technical analyst might believe that IBM would need to trade below its moving average for two consecutive days before declaring its trend over. Another might say one day is adequate. To a technician a close below the 200 day moving average is always important, but two technicans might disagree on the best way to act. Still, it is safe to assume that both technicians expect to sell IBM.
The obvious problem in this example is: what if in the near term IBM climbs back above its 200 day moving average after the technician sells his stock? If the technical analyst follows his own rules then he might be buying stock back at a higher price than he just sold plus commissions. This is a substantial component of some of the criticisms of technical analysis (see below). Technical analysis says "false signals" or "whipsaws" are an unavoidable part of using technical analysis. To a technical analyst, the costs of these whipsaws are far outweighed by catching a stock at the beginning of a new long term trend. Some research disputes this assertion however.
Technical analysis may be at odds with fundamental analysis. Fundamental analysis maintains that markets may misprice a security and, through various methods of fundamental analysis, the "correct" price can be calculated. Profits can be made by trading the mispriced security and then waiting for the market to recognize its "mistake" and reprice the security. In contrast, a technical analyst is not interested in a security's "correct" price, only in price movement.
Two well known sayings among technical analysts are, "The trend is your friend," and "Forget the fundamentals and follow the money." An example of the different views of technical and fundamental analysis follows. Suppose a stock was trading at 124.25 pence, and that the consensus fundamental analysis view of the stock was that it was worth 120.00 pence. If the share price rose to 125.00 pence, then to 126.00 pence, and then to 127.00 pence, a technical analyst would likely be a buyer of this stock in order to profit from the perceived trend. In contrast, a fundamental analyst would possibly look to sell the stock as it is moving away from what the fundamental analyst believes is the "correct" price.
Market action discounts everything
The purpose of technical analysis is to interpret the signals generated from market price action. Technical analysts believe this method works because every possible bit of information will be reflected by means of market action.
Therefore it is redundant to explicitly do fundamental analysis, which may include a study of micro-factors like the instrument fundamentals and global-factors like economic, political issues. If that factor is going to affect the price of a financial instrument, the market will tell, vice versa. Only a study of the market is required. Murphy. Technical Analysis of the Financial Markets. pp. 24–31.
Prices move in trends
While it cannot be shown that prices must trend, technical analysis relies on empirical evidence to assert that prices do trend. To a technician, markets are trending up, trending down, or trending sideways (flat). This definition of a price trend is essentially the one put forward by Dow Theory. Murphy. Technical Analysis of the Financial Markets. pp. 24–31.
A person who does not believe that prices move in trends will find little use for technical analysis. The assumption that prices must trend is probably the most important concept in technical analysis.
An example of a security that is trending is AOL from November 2001 through August 2002. A technical analyst or trend follower recognizing this trend would look for opportunities to sell this security. AOL consistently moves downward in price. Each time the stock attempted to rise, sellers would enter the market and sell the stock; hence the "zig-zag" movement in the price. The series of "lower highs" and "lower lows" is a tell tale sign of a stock in a down trend. In other words, each time the stock edged lower, it went lower than its previous relative low price. Each time the stock moved higher, it could not reach the level of its previous relative high price.
Note that it is not until August that the sequence of lower lows and lower highs is broken. In August, the stock makes a low price that doesn't pierce the relative low set earlier in the month. Later in the same month, the stock makes a relative high equal to the most recent relative high. To a technical analyst, those are strong indications that the down trend is at least pausing and possibly ending. A technical analyst would likely stop actively selling the stock at this point.
History tends to repeat itself
Technical analysts believe that investors en masse repeat the behavior of the investors that preceded them. "Everyone wants in on the next Microsoft," "If this stock ever gets to $50 again, I will buy it," "This company's technology will revolutionize its industry, therefore this stock will skyrocket,"-- these are all examples of investors' attitudes repeating. To a technical analyst, the human characteristics of the market might be irrational, but they exist. Because investors' attitudes often repeat, investors' actions in the marketplace often repeat as well. I.e., patterns of price movement will develop on a chart that a technical analyst believes have predictive qualities.
Technical analysis is not limited to charting. Technical analysis is always primarily concerned with price trends. Anything that can influence the price trend is of interest to a technical analyst. As an example, many technical analysts monitor surveys of investor enthusiasm. These surveys attempt to gauge the general attitude of the investment community to determine whether investors are bearish or bullish. Technical analysts use these surveys to help determine whether a trend will reverse or whether a new trend will develop. A technical analyst would be alerted that a trend might change when these surveys report extreme investor reactions. When surveys are overly bullish, for example, a technical analyst will look for evidence that an uptrend will reverse. The logic being that if most investors are bullish, then they would have already bought the market (anticipating that the market will move higher). But because most investors are bulllish and have invested, it is safe to assume that there are few buyers remaining in the market. With most investors long, there are more potential sellers in the market than buyers despite the fact that the overall attitude of investors is bullish. This implies that the market is set to trend down and is an example of a technical analysis concept called contrarian trading.
Though former Federal Reserve Chairman Alan Greenspan has not described himself as a technical analyst, he has said that the history of investor behavior appears to repeat itself:
"…there is one important caveat to the notion that we live in a new economy, and that is human psychology. The same enthusiasms and fears that gripped our forebears, are, in every way, visible in the generations now actively participating in the American economy. Human actions are always rooted in a forecast of the consequences of those actions... To be sure, the degree of risk aversion differs from person to person, but judging the way prices behave in today's markets compared with those of a century or more ago, one is hard pressed to find significant differences. The way we evaluate assets, and the way changes in those values affect our economy, do not appear to be coming out of a set of rules that is different from the one that governed the actions of our forebears…. As in the past, our advanced economy is primarily driven by how human psychology molds the value system that drives a competitive market economy. And that process is inextricably linked to human nature, which appears essentially immutable and, thus, anchors the future to the past."
Also, the Boston branch of the Federal Reserve for years has published its monthly "Stock Market Report," which "incorporates technical and fundamental analysis commonly used by investment professionals to interpret the direction and valuation of equity markets." Each report begins with a discussion of "Technical Trends." It also includes the types of charts that technical analysts typically use, plus abundant notes and definitions regarding the technical indicators mentioned in each issue.
Criticism
Lack of evidence
Although chartists assert that their techniques empirically provide excess returns over time, many academics believe that technical analysis has no predictive power. Burton Malkiel in his book "A Random Walk Down Wall Street" (8th edition, 2003) and Eugene Fama in "Efficient Capital Markets: A Review of Theory and Empirical Work," May 1970 Journal of Finance summarize many early studies, conducted from the 1950s-70s, that show that after trading costs are considered, the returns generated by many technical strategies underperform a simple buy and hold strategy.
Cheol-Ho Park and Scott H. Irwin reviewed 93 modern studies on the profitability of technical analysis and considered 59 of them to indicate positive results, and 24 negative results. "Despite the positive evidence ... it appears that most empirical studies are subject to various problems in their testing procedures, e.g., data snooping, ex post selection of trading rules or search technologies, and difficulties in estimation of risk and transaction costs." See also .
Critics of technical analysis include well known fundamental analysts. Warren Buffett has said, "I realized technical analysis didn't work when I turned the charts upside down and didn't get a different answer" and "If past history was all there was to the game, the richest people would be librarians."
Inconsistencies with other market hypotheses
Efficient market hypothesis
The efficient market hypothesis (EMH) concludes that technical analysis cannot be effective. If all relevant information is reflected quickly in a security's price through the actions of traders who have that information, no method, including technical analysis, can "beat the market". News events and new fundamental developments which influence prices occur randomly and are unknowable in advance. EMH advocates have produced many studies that reject the efficacy of technical analysis.
Proponents of technical analysis counter that technical analysis does not completely contradict the efficient market hypothesis. Technicians agree with EMH in that they believe that all available information is reflected within a security's price; that is why technicians say a study of the price movement is necessary. Technicians argue that EMH ignores the realities of the market place, namely that many investors base their future expectations on past earnings, track records, etc. Because future stock prices can be strongly influenced by investor expectations, technicians claim it only follows that past prices can influence future prices.
Technicians point to the new field of behavioral finance. Behavioral finance essentially says that people are not the rational participants EMH makes them out to be. Market participants can and do act irrationally. Technicians have long held that irrational human behavior influences stock prices and claim to have ways of predicting probable outcomes based on this behavior.
EMH advocates reply that although individual market participants do not always act rationally (or have complete information), their aggregate decisions complement each other, resulting in a rational outcome, (i.e. irrational optimists, wishing to buy stock and bid the price higher, are counter-balanced by irrational pessimists trying to sell their stock, until the price reaches equilibrium). Likewise, complete information is reflected in the price because all market participants bring their own individual, but incomplete, knowledge together in the market.
Random walk hypothesis
The random walk hypothesis is also at odds with technical analysis and charting. Essentially, the hypothesis claims that stock price movements are a Brownian Motion with either independent or uncorrelated increments. In this model, movements in stock prices are not dependent on past stock prices, so trends cannot exist and technical analysis has no basis. Again, proponents of this theory have generated substantial research in support of the hypothesis. Random Walk advocates such as Burton Malkiel and John Allen Paulos believe that technical analysis and fundamental analysis are pseudo-sciences.
The random walk hypothesis may be derived from the weak-form efficient markets hypothesis, which is based on the assumption that market participants take full account of any information contained in past price movements (but not necessarily other public information).
Technical analysts maintain that trends are identifiable in the market and that it can be impractical to believe that market prices move in a random fashion. To a technician, over time prices will trend in a direction until supply equals demand. Therefore, there cannot be any pure random price movement. As stated earlier, one of the cornerstones of technical analysis is that prices trend. If one does not believe this concept, one will not agree with technical analysis.
Also, with regards to EMH and Random Walk Theory, technicians claim that both theories ignore the realities of the marketplace. To a technician, the market is neither composed of completely rational participants as EMH assumes (participants can be greedy, overly risky, etc. at any given time) nor is its stock price movement completely independent of its prior movement (technicians will point at charts like AOL above). Critics respond that one can find virtually any chart pattern after the fact, but that this does not mean the pattern has any predictive power. Technicians maintain that both theories would also invalidate numerous other trading strategies such as index arbitrage, statistical arbitrage and many other trading systems.
Industry
Globally, the industry is represented by The International Federation of Technical Analysts (IFTA). IFTA offers certification to professional technical analysts and researchers around the world as part of their Certified Financial Technician designation. In the United States, the industry is represented by two national level organizations: the American Association of Professional Technical Analysts (AAPTA) and the Market Technicians Association (MTA). The MTA awards the Chartered Market Technician certification to candidates who have passed a series of standardized exams. Numerous regional and local societies also exist in the U.S., such as the Technical Securities Analysts Association of San Francisco. In Canada the industry is represented by the Canadian Society of Technical Analysts.
Proponents of technical analysis
To many traders, trading in the direction of the trend is the most effective means to be profitable in financial or commodities markets. John W. Henry, Larry Hite, Ed Seykota, Richard Dennis, William Eckhardt, Victor Sperandeo, and Michael Marcus (some of the so-called Market Wizards in the popular book of the same name by Jack D. Schwager) have each amassed massive fortunes through the use of technical analysis and its concepts over the course of decades. George Lane, a technical analyst, coined one of the most popular phrases on Wall Street, "The trend is your friend!"
Many non-arbitrage algorithmic trading systems rely on the idea of trend-following, as do many hedge funds. A relatively recent trend, both in research and industrial practice, has been the development of increasingly sophisticated automated trading strategies. These often rely on underlying technical analysis principles (see algorithmic trading article for an overview).
Systematic trading and technical analysis
Neural networks
Since the early 90's when the first practically usable types emerged, artificial neural networks (ANNs) have rapidly grown in popularity. They are artificial intelligence adaptive software systems that have been inspired by how biological neural networks work. Their use comes in because they can learn to detect complex patterns in data. In mathematical terms, they are universal non-linear function approximators meaning that given the right data and configured correctly, they can capture and model any input-output relationships. This not only removes the need for human interpretation of charts or the series of rules for generating entry/exit signals but also provides a bridge to fundamental analysis as that type of data can be used as input.
In addition, as ANNs are essentially non-linear statistical models, their accuracy and prediction capabilities can be both mathematically and empirically tested. In various studies neural networks used for generating trading signals have significantly outperformed buy-hold strategies as well as traditional linear technical analysis methods.
While the advanced mathematical nature of such adaptive systems have kept neural networks for financial analysis mostly within academic research circles, in recent years more user friendly neural network software has made the technology more accessible to traders.
Rule-based trading
Rule-based trading is an approach to make one's trading plans by strict and clear-cut rules. Unlike some other technical methods or most fundamental analysis, it defines a set of rules that determines all trades, leaving minimal discretion.
For instance, a trader might make a set of rules stating that he will take a long position whenever the price of a particular instrument closes above its 50-day moving average, and shorting it whenever it drops below.
Charting terms and indicators
The five very common charting techniques used by everyday traders are:
- Balance days or "dojis"
- Double tops
- Channels
- Lines of resistance
- Pennants and/or flags
Other widely-known technical analysis concepts include:
- Accumulation/distribution index—based on the close within the day's range
- Average true range - averaged daily trading range
- Bollinger bands - a range of price volatility
- Breakout - when a price passes through and stays above an area of support or resistance
- Commodity Channel Index - identifies cyclical trends
- Elliott wave principle and the golden ratio to calculate successive price movements and retracements
- Hikkake Pattern - pattern for identifying reversals and continuations
- MACD - moving average convergence/divergence
- Momentum - the rate of price change
- Money Flow - the amount of stock traded on days the price went up
- Moving average - lags behind the price action
- On balance volume - the momentum of buying and selling stocks
- PAC charts - two-dimensional method for charting volume by price level
- Parabolic SAR - Wilder's trailing stop based on prices tending to stay within a parabolic curve during a strong trend
- Pivot point - derived by calculating the numerical average of a particular currency's or stock's high, low and closing prices
- Point and figure charts - charts based on price without time
- Relative Strength Index (RSI) - oscillator showing price strength
- Resistance - an area that brings on increased selling
- Stochastic oscillator, close position within recent trading range
- Support - an area that brings on increased buying
- Trend line - a sloping line of support or resistance
- Trix - an oscillator showing the slope of a triple-smoothed exponential moving average, developed in the 1980s by Jack Hutson
Books
- Ichimoku Charts, Nicole Elliott, Harriman House, 2007, ISBN 9781897597842
- Getting Started in Technical Analysis, Jack D. Schwager, Wiley, 1999, ISBN 0-471-29542-6
- New Concepts in Technical Trading Systems, J. Welles Wilder, Trend Research, 1978, ISBN 0-89459-027-8
- Reminiscences of a Stock Operator, Edwin Lefèvre, John Wiley & Sons Inc, 1994, ISBN 0-471-05970-6
- Street Smarts, Connors/Raschke, 1995, ISBN 0-9650461-0-9
- Technical Analysis of Futures Markets, John J. Murphy, New York Institute of Finance, 1986, ISBN 0-13-898008-X
- Technical Analysis of Stock Trends, 8th Edition (Hardcover), Robert D. Edwards, John Magee, W. H. C. Bassetti (Editor), American Management Association, 2001, ISBN 0-8144-0680-7
- Technical Analysis of the Financial Markets, John J. Murphy, New York Institute of Finance, 1999, ISBN 0-7352-0066-1
- The Profit Magic of Stock Transaction Timing, J.M. Hurst, Prentice-Hall, 1972, ISBN 0-13-726018-0
- The Free E-Book of Technical Analysis, Wallstreetcourier, www.wallstreetcourier.com/ebook/The_E-Book_of_Technical_Market_Indicators.pdf
Notes
- Murphy, John (1999). Technical Analysis of the Financial Markets. pp. 1–5.
- Skabar, Cloete, Networks, Financial Trading and the Efficient Markets Hypothesis
- Federal Reserve Bank of New York. Support for Resistance: Technical Analysis and Intraday Exchange Rates
- Nison, Steve (1991). Japanese Candlestick Charting Techniques. pp. 15–18.
- Hill, Arthur. "Dow Theory". Retrieved 2006-04-23.
- Murphy. Technical Analysis of the Financial Markets. pp. 24–31.
- Alan Greenspan, "Question: Is There a New Economy?", 4 September 1998.
- R. Lawrence. Using Neural Networks to Forecast Stock Market Prices
- B.Egeli et al. Stock Market Prediction Using Artificial Neural Networks
- M. Zekić. Neural Network Applications in Stock Market Predictions - A Methodology Analysis
See also
- Algorithmic trading
- Bollinger bands
- Box spread
- Business cycle
- Financial astrology
- Forex simulator
- Grand supercycle
- Market analysis
- Market timing
- Market trends
- Technical analysis software
- Trader (finance)
External links
- Society Of Technical Analysts Of New Zealand
- International Federation of Technical Analysts
- American Association of Professional Technical Analysts
- Market Technicians Association
- Technical Securities Analysts Association of San Francisco
- The Australian Society of Technical Analysts