Jump to content

Technical analysis: Difference between revisions

From Wikipedia, the free encyclopedia
Content deleted Content added
mNo edit summary
significance?
Line 7: Line 7:
Like any predictive method, it is not 100% accurate, but it attempts to give the "most likely" outcome.<ref>{{cite book | first = Martin | last = Pring | title = Technical Analysis Explained | year = 2002 | pages = 3}}</ref>
Like any predictive method, it is not 100% accurate, but it attempts to give the "most likely" outcome.<ref>{{cite book | first = Martin | last = Pring | title = Technical Analysis Explained | year = 2002 | pages = 3}}</ref>


Some forms of technical analysis, like charting, are viewed by many of its practitioners as more [[art]] than [[science]]. Many academic studies conclude that such methods have little, if any, [[predictive power]]. {{fact}} However, the practice has a dedicated following especially among active traders. Other, more robust and measurable forms of Technical Analysis have been shown to produce [[Statistical significance|statistically significant]] prediction results.
Some forms of technical analysis, like charting, are viewed by many of its practitioners as more [[art]] than [[science]]. Many academic studies conclude that such methods have little, if any, [[predictive power]].
<ref>Vinit Nagarajan; Ying Wu; Min Liu; Qing-Guo Wang (2005)
''Forecast studies for financial markets using technical analysis''
</ref> <ref>Resta, M. (2000)
''Towards an artificial technical analysis of financial markets''
</ref> <ref>Blakey, P. (2002)
''Pattern recognition techniques in stock prices and volumes''
</ref>


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." On the other hand, the U.S. [[Federal Reserve]] once published a study saying that certain elements of technical analysis were effective in price forecasting in the intraday [[foreign exchange market]].<ref>[[Federal Reserve Bank of New York]]. [http://www.ny.frb.org/research/epr/00v06n2/0007osle.html Support for Resistance: Technical Analysis and Intraday Exchange Rates]</ref>
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 <ref>[[Federal Reserve Bank of New York]]. [http://www.ny.frb.org/research/epr/00v06n2/0007osle.html Support for Resistance: Technical Analysis and Intraday Exchange Rates]</ref> has shown that the statistical properties of intraday [[foreign exchange]] prices change near "support and resistance" lines, without showing that this result could be used in a profitable trading strategy.


==History==
==History==

Revision as of 09:55, 11 July 2006

Technical analysis is the study of a security's price action for the purpose of forecasting probable price trends and movement. Price action is defined as movement in a security's price, volume, and open interest. [1]

Primarily, but not exclusively, technical analysis is conducted by studying charts of past price action. Many different methods and tools are used in technical analysis, but they all rely on the assumption that price patterns and trends exist in markets, and that they can be identified and exploited.[2]

Technical analysis does not try to analyze the financial data of a company such as cashflow, dividends and projection of future dividends. That type of analysis is called fundamental analysis. Nevertheless, some speculators try to combine elements from both technical and fundamental analysis.

Like any predictive method, it is not 100% accurate, but it attempts to give the "most likely" outcome.[3]

Some forms of technical analysis, like charting, are viewed by many of its practitioners as more art than science. Many academic studies conclude that such methods have little, if any, predictive power.

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 [4] has shown that the statistical properties of intraday foreign exchange prices change near "support and resistance" lines, without showing that this result could be used in a profitable trading strategy.

History

The premises of technical analysis were derived from observation of financial markets over hundreds of years. Perhaps the oldest branch of technical analysis is the use of candlestick techniques by Japanese traders at least as early as the 18th century, and still very popular today.[5]

Dow Theory, a theory based on the collected writings of Dow Jones co-founder and editor Charles Dow, inspired the use and development of technical analysis from the end of the 19th century. Modern technical analysis considers Dow Theory its cornerstone.[6]

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 defined as the average closing price of a stock over the past 200 trading days. (There are many variations of moving averages in technical analysis though.) 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 techncians 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.

Three Beliefs of Technical Analysis

Price action in the market discounts everything

Technical analysis holds that because every possible bit of information is immediately included in the price of a security, it is not necessary to explicitly analyze the fundamental, economic, political, etc. factors that might influence that price. Because all possible information is reflected in the price, only a study of the price movement is required. Murphy. Technical Analysis of the Financial Markets. pp. 24–31.

While it cannot be shown that prices must trend, technical analysis relies on empirical evidence and common sense 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.

File:AOLTIMEWARNERCHART2001.png
AOL TimeWarner price action.

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.[7]

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.

Criticism of Technical Analysis

Lack of evidence

Although chartists assert that their techniques provide excess returns over time, this assertion is controversial. 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 Financesummarize 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 [1] 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 [2].

Critics of technical analysis include well known fundamental analysts. Warren Buffett has exclaimed, "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." Still, even an investor like Buffett occasionally recognizes technical analysis. In a recent conference on investing in mining companies, Buffett commented, "In metals and oils, there's been a terrific [price] move. It's like most trends: at the beginning, it's driven by fundamentals, then speculation takes over...then the speculation becomes dominant." To a technician, Buffett basically paraphrased Dow Theory.

Inconsistencies with Other Market Hypotheses

The Efficient Market Hypothesis

The efficient market hypothesis (EMH) concludes that technical analysis cannot be effective. According to this hypothesis, all relevant information is quickly reflected in a security's price through the actions of traders who have that information. Thus, it is impossible to "beat the market," and technical analysis cannot work. News events and new fundamental developments which influence prices occur randomly and are unknowable in advance. Advocates of EMH 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.

The 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. [3]

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 is 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). 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 Henry, Larry Hite, Ed Seykota, Richard Dennis, Bruce Kovner, 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. 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).

Neural networks and Technical Analysis

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.[8] [9] [10]

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.


Charting terms and indicators

Many different techniques and indicators can be used to follow and predict trends in markets, and usually at least a few at a time are considered when making an investment decision. Some of the most widely known include:

Books

  • Technical Analysis of Futures Markets, John J. Murphy, New York Institute of Finance, 1986, ISBN 0-13-898008-X
  • The Profit Magic of Stock Transaction Timing, J.M. Hurst, Prentice-Hall, 1972, ISBN 0137260180
  • New Concepts in Technical Trading Systems, J. Welles Wilder, Trend Research, 1978, ISBN 0894590278
  • Street Smarts, Connors/Raschke, 1995, ISBN 0965046109
  • Reminiscences of a Stock Operator, Edwin Lefèvre, John Wiley & Sons Inc, 1994, ISBN 0471059706
  • Technical Analysis of the Financial Markets, John J. Murphy, New York Institute of Finance,1999,ISBN 0735200661
  • Technical Analysis of Stock Trends, 8th Edition (Hardcover), Robert D. Edwards, John Magee, W. H. C. Bassetti (Editor), American Management Association, 2001, ISBN 0814406807
  • Introduction to the Magee System of Technical Analysis, 2nd Edition (Hardcover), John Magee, W. H. C. Bassetti (Editor, Coauthor), American Management Association, 2003, ISBN 0814407293

Notes

  1. ^ Murphy, John (1999). Technical Analysis of the Financial Markets. pp. 1–2.
  2. ^ Murphy, John (1999). Technical Analysis of the Financial Markets. pp. 1–5.
  3. ^ Pring, Martin (2002). Technical Analysis Explained. p. 3.
  4. ^ Federal Reserve Bank of New York. Support for Resistance: Technical Analysis and Intraday Exchange Rates
  5. ^ Nilson, Steve (1991). Japanese Candlestick Charting Techniques. pp. 15–18.
  6. ^ Hill, Arthur. "Dow Theory". Retrieved 2006-04-23.
  7. ^ Murphy. Technical Analysis of the Financial Markets. pp. 24–31.
  8. ^ R. Lawrence. Using Neural Networks to Forecast Stock Market Prices
  9. ^ B.Egeli et al. Stock Market Prediction Using Artificial Neural Networks
  10. ^ M. Zekic. Neural Network Applications in Stock Market Predictions - A Methodology Analysis

See also