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64-608: The Dow theory on stock price movement is a form of technical analysis that includes some aspects of sector rotation . The theory was derived from 255 editorials in The Wall Street Journal written by Charles H. Dow (1851–1902), journalist, founder and first editor of The Wall Street Journal and co-founder of Dow Jones and Company . Following Dow's death, William Peter Hamilton , Robert Rhea and E. George Schaefer organized and collectively represented Dow theory, based on Dow's editorials. Dow himself never used

128-546: A body of knowledge that describes the field of Technical Analysis. A body of knowledge is central to the field as a way of defining how and why technical analysis may work. It can then be used by academia, as well as regulatory bodies, in developing proper research and standards for the field. The CMT Association has published a body of knowledge, which is the structure for the Chartered Market Technician (CMT) exam. Technical analysis software automates

192-626: A computer can perform. Several trading strategies rely on human interpretation, and are unsuitable for computer processing. Only technical indicators which are entirely algorithmic can be programmed for computerized automated backtesting. John Murphy states that the principal sources of information available to technicians are price, volume and open interest . Other data, such as indicators and sentiment analysis , are considered secondary. However, many technical analysts reach outside pure technical analysis, combining other market forecast methods with their technical work. One advocate for this approach

256-443: A concept later known as " Dow theory ". However, Dow himself never advocated using his ideas as a stock trading strategy. In the 1920s and 1930s, Richard W. Schabacker published several books which continued the work of Charles Dow and William Peter Hamilton in their books Stock Market Theory and Practice and Technical Market Analysis . In 1948, Robert D. Edwards and John Magee published Technical Analysis of Stock Trends which

320-421: A condensed format. The correct way to draw a point and figure chart is to plot every price change but practicality has rendered this difficult to do for a large quantity of stocks so many point and figure chartists use the summary prices at the end of each day. Some prefer to use the day’s closing price and some prefer to use the day’s high or low depending on the direction of the last column. The high/low method

384-489: A paper published in the Journal of Finance , Dr. Andrew W. Lo , director MIT Laboratory for Financial Engineering , working with Harry Mamaysky and Jiang Wang found that: Technical analysis, also known as "charting", has been a part of financial practice for many decades, but this discipline has not received the same level of academic scrutiny and acceptance as more traditional approaches such as fundamental analysis. One of

448-494: A possible explanation why fear makes prices fall sharply while greed pushes up prices gradually. This commonly observed behaviour of securities prices is sharply at odds with random walk. By gauging greed and fear in the market, investors can better formulate long and short portfolio stances. Caginalp and Balenovich in 1994 used their asset-flow differential equations model to show that the major patterns of technical analysis could be generated with some basic assumptions. Some of

512-427: A rational outcome (optimists who buy stock and bid the price higher are countered by pessimists who sell their stock, which keeps the price in 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 may be derived from the weak-form efficient markets hypothesis, which

576-404: A security that had an apparent trend 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 rose, 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"

640-467: A stock's price movement is random in nature or a result of a statistically significant trend. The random walk index attempts to determine when the market is in a strong uptrend or downtrend by measuring price ranges over N and how it differs from what would be expected by a random walk (randomly going up or down). The greater the range suggests a stronger trend. Applying Kahneman and Tversky's prospect theory to price movements, Paul V. Azzopardi provided

704-402: A strictly mechanical or systematic approach to pattern identification and interpretation. Contrasting with technical analysis is fundamental analysis : the study of economic and other underlying factors that influence the way investors price financial markets. This may include regular corporate metrics like a company's recent EBITDA figures, the estimated impact of recent staffing changes to

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768-463: A way that prevents it from happening in the future." Malkiel has stated that while momentum may explain some stock price movements, there is not enough momentum to make excess profits. Malkiel has compared technical analysis to " astrology ". In the late 1980s, professors Andrew Lo and Craig McKinlay published a paper which cast doubt on the random walk hypothesis. In a 1999 response to Malkiel, Lo and McKinlay collected empirical papers that questioned

832-622: Is John Bollinger , who coined the term rational analysis in the middle 1980s for the intersection of technical analysis and fundamental analysis. Another such approach, fusion analysis, overlays fundamental analysis with technical, in an attempt to improve portfolio manager performance. Technical analysis is also often combined with quantitative analysis and economics. For example, neural networks may be used to help identify intermarket relationships. Investor and newsletter polls, and magazine cover sentiment indicators, are also used by technical analysts. Whether technical analysis actually works

896-837: Is a federation of regional and national organizations. In the United States, the industry is represented by both the CMT Association and the American Association of Professional Technical Analysts (AAPTA). The United States is also represented by the Technical Security Analysts Association of San Francisco (TSAASF). In the United Kingdom, the industry is represented by the Society of Technical Analysts (STA). The STA

960-417: Is a matter of controversy. Methods vary greatly, and different technical analysts can sometimes make contradictory predictions from the same data. Many investors claim that they experience positive returns, but academic appraisals often find that it has little predictive power . Of 95 modern studies, 56 concluded that technical analysis had positive results, although data-snooping bias and other problems make

1024-407: Is a tell tale sign of a stock in a down trend. In other words, each time the stock moved lower, it fell below 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 the sequence of lower lows and lower highs did not begin until August. Then AOL makes a low price that does not pierce the relative low set earlier in

1088-502: Is an analysis methodology for analysing and forecasting the direction of prices through the study of past market data, primarily price and volume. As a type of active management , it stands in contradiction to much of modern portfolio theory . The efficacy of technical analysis is disputed by the efficient-market hypothesis , which states that stock market prices are essentially unpredictable, and research on whether technical analysis offers any benefit has produced mixed results. It

1152-452: 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). In his book A Random Walk Down Wall Street , Princeton economist Burton Malkiel said that technical forecasting tools such as pattern analysis must ultimately be self-defeating: "The problem is that once such a regularity is known to market participants, people will act in such

1216-516: Is distinguished from fundamental analysis , which considers a company's financial statements, health, and the overall state of the market and economy. The principles of technical analysis are derived from hundreds of years of financial market data. Some aspects of technical analysis began to appear in Amsterdam-based merchant Joseph de la Vega 's accounts of the Dutch financial markets in

1280-428: Is found, by estimating CAPMs , that technical trading shows no statistically significant risk-corrected out-of-sample forecasting power for almost all of the stock market indices." Transaction costs are particularly applicable to "momentum strategies"; a comprehensive 1996 review of the data and studies concluded that even small transaction costs would lead to an inability to capture any excess from such strategies. In

1344-476: Is less clear cut than the distinction with fundamental analysis. Some sources treat technical and quantitative analysis as more or less synonymous, while others draw a sharp distinction. For example, quantitative analysis expert Paul Wilmott suggests technical analysis is little more than 'charting' (making forecasts based on extrapolating graphical representations), and that technical analysis rarely has any predictive power. A core principle of technical analysis

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1408-536: Is most often performed for technical indicators combined with volatility but can be applied to most investment strategies (e.g. fundamental analysis). While traditional backtesting was done by hand, this was usually only performed on human-selected stocks, and was thus prone to prior knowledge in stock selection. With the advent of computers, backtesting can be performed on entire exchanges over decades of historic data in very short amounts of time. The use of computers does have its drawbacks, being limited to algorithms that

1472-639: Is often available as a web or a smartphone application, without the need to download and install a software package. Some of them even offer an integrated programming language and automatic backtesting tools. Since the early 1990s 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. They are used because they can learn to detect complex patterns in data. In mathematical terms, they are universal function approximators , meaning that given

1536-585: Is over 100 years old. "Hoyle" was the first to write about it and showed charts in his 1898 book, The Game in Wall Street. The first book/manual dedicated to Point and Figure was written by Victor Devilliers in 1933. Chartcraft Inc, in the USA, popularized the system in the 1940s. Cohen founded Chartcraft and wrote on point and figure charting in 1947. Chartcraft published further pioneering books on P&F charting, namely those by Burke, Aby and Zieg. Chartcraft Inc

1600-635: Is still running today, providing daily point and figure services for the US market under the name of Investors Intelligence. Veteran Mike Burke still works for Chartcraft, having started back in 1962 under the guidance of Cohen. Burke went on to train other point and figure gurus, such as Thomas Dorsey who would go on to write authoritative texts on the subject. A detailed history can be found in Jeremy du Plessis’ ‘The Definitive Guide to Point and Figure’ where many references and examples are cited. Du Plessis describes

1664-458: Is that a market's price reflects all relevant information impacting that market. A technical analyst therefore looks at the history of a security or commodity's trading pattern rather than external drivers such as economic, fundamental and news events. It is believed that price action tends to repeat itself due to the collective, patterned behavior of investors. Hence technical analysis focuses on identifiable price trends and conditions. Based on

1728-678: Is trending, and if it is, the probability of its direction and of continuation. Technicians also look for relationships between price/volume indices and market indicators. Examples include the moving average , relative strength index and MACD . Other avenues of study include correlations between changes in Options ( implied volatility ) and put/call ratios with price. Also important are sentiment indicators such as Put/Call ratios, bull/bear ratios, short interest, Implied Volatility , etc. There are many techniques in technical analysis. Adherents of different techniques (for example: Candlestick analysis,

1792-619: Is where Du Plessis suggests the name point and figure came from. Modern point and figure charts are drawn with Xs and Os where columns of Xs are rising prices and columns of Os are falling prices, although many traditionalists such as David Fuller and Louise Yamada still use the Xs only point method of plotting. Point and Figure charts are based primarily on price action, not time. If there are no significant price moves over time, P&F charts will show no new data. This difference can make P&F charts ideal for detecting directional patterns and trends in

1856-436: Is widely considered to be one of the seminal works of the discipline. It is exclusively concerned with trend analysis and chart patterns and remains in use to the present. Early technical analysis was almost exclusively the analysis of charts because the processing power of computers was not available for the modern degree of statistical analysis. Charles Dow reportedly originated a form of point and figure chart analysis. With

1920-555: The board of directors , geopolitical considerations, and even scientific factors like the estimated future effects of global warming . Pure forms of technical analysis can hold that prices already reflect all the underlying fundamental factors. Uncovering future trends is what technical indicators are designed to do, although neither technical nor fundamental indicators are perfect. Some traders use technical or fundamental analysis exclusively, while others use both types to make trading decisions. The contrast against quantitative analysis

1984-496: The 17th century. In Asia, technical analysis is said to be a method developed by Homma Munehisa during the early 18th century which evolved into the use of candlestick techniques , and is today a technical analysis charting tool. Journalist Charles Dow (1851-1902) compiled and closely analyzed American stock market data, and published some of his conclusions in editorials for The Wall Street Journal . He believed patterns and business cycles could possibly be found in this data,

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2048-501: The Dow theory from 1902 to 1929 produced excess risk-adjusted returns. Specifically, the study from Goetzman and Brown found the return of a buy-and-hold strategy was higher than that of a Dow theory portfolio by 2%, but the riskiness and volatility of the Dow theory portfolio was lower, so that the Dow theory portfolio produced higher risk-adjusted returns according to their study. Technical analysis In finance, technical analysis

2112-405: The Dow theory strategy produced annualized returns of 12%. After numerous studies supported Cowles over the following years, many academics stopped studying Dow theory believing Cowles's results were conclusive. In recent years Cowles' conclusions have been revisited. William Goetzmann, Stephen Brown, and Alok Kumar believe that Cowles' study was incomplete and that W.P. Hamilton's application of

2176-422: The advanced mathematical nature of such adaptive systems has 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. Systematic trading is most often employed after testing an investment strategy on historic data. This is known as backtesting (or hindcasting ). Backtesting

2240-415: The analysis difficult. Nonlinear prediction using neural networks occasionally produces statistically significant prediction results. A Federal Reserve working paper regarding support and resistance levels in short-term foreign exchange rates "offers strong evidence that the levels help to predict intraday trend interruptions", although the "predictive power" of those levels was "found to vary across

2304-474: The attitude of market participants, specifically whether they are bearish or bullish . Technicians use these surveys to help determine whether a trend will continue or if a reversal could develop; they are most likely to anticipate a change when the surveys report extreme investor sentiment. Surveys that show overwhelming bullishness, for example, are evidence that an uptrend may reverse; the premise being that if most investors are bullish they have already bought

2368-499: The charting, analysis and reporting functions that support technical analysts in their review and prediction of financial markets (e.g. the stock market ). In addition to installable desktop-based software packages in the traditional sense, the industry has seen an emergence of cloud-based applications and application programming interfaces (APIs) that deliver technical indicators (e.g., MACD, Bollinger Bands) via RESTful HTTP or intranet protocols. Modern technical analysis software

2432-541: The dynamics of group behavior, behavioral finance offers succinct explanations of excess market volatility as well as the excess returns earned by stale information strategies.... cognitive errors may also explain the existence of market inefficiencies that spawn the systematic price movements that allow objective TA [technical analysis] methods to work. EMH advocates reply that while individual market participants do not always act rationally (or have complete information), their aggregate decisions balance each other, resulting in

2496-674: The effectiveness of technical analysis. By comparing the unconditional empirical distribution of daily stock returns to the conditional distribution – conditioned on specific technical indicators such as head-and-shoulders or double-bottoms – we find that over the 31-year sample period, several technical indicators do provide incremental information and may have some practical value. In that same paper Dr. Lo wrote that "several academic studies suggest that ... technical analysis may well be an effective means for extracting useful information from market prices." Some techniques such as Drummond Geometry attempt to overcome

2560-490: The emergence of behavioral finance as a separate discipline in economics, Paul V. Azzopardi combined technical analysis with behavioral finance and coined the term "Behavioral Technical Analysis". Other pioneers of analysis techniques include Ralph Nelson Elliott , William Delbert Gann , and Richard Wyckoff who developed their respective techniques in the early 20th century. Fundamental analysts examine earnings, dividends, assets, quality, ratios, new products, research and

2624-504: The emotions in the market may be irrational, but they exist. Because investor behavior repeats itself so often, technicians believe that recognizable (and predictable) price patterns will develop on a chart. Recognition of these patterns can allow the technician to select trades that have a higher probability of success. Technical analysis is not limited to charting, but it always considers price trends. For example, many technicians monitor surveys of investor sentiment. These surveys gauge

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2688-622: The exchange rates and firms examined". Technical trading strategies were found to be effective in the Chinese marketplace by a recent study that states, "Finally, we find significant positive returns on buy trades generated by the contrarian version of the moving-average crossover rule, the channel breakout rule, and the Bollinger band trading rule, after accounting for transaction costs of 0.50%." An influential 1992 study by Brock et al. which appeared to find support for technical trading rules

2752-456: The field of behavioral finance , specifically that people are not the rational participants EMH makes them out to be. Technicians have long said that irrational human behavior influences stock prices, and that this behavior leads to predictable outcomes. Author David Aronson says that the theory of behavioral finance blends with the practice of technical analysis: By considering the impact of emotions, cognitive errors, irrational preferences, and

2816-498: The historical development of these charts from a price recording system to a charting method. Traders kept track of prices by writing them down in columns. They noticed patterns in their price record and started referring to them first as ‘fluctuation charts’ and then as ‘figure charts’. They started using Xs instead of numbers and these charts became known as ‘point charts’. Traders used both point charts and figure charts together and referred to them as their point and figure charts, which

2880-489: The hypothesis' applicability that suggested a non-random and possibly predictive component to stock price movement, though they were careful to point out that rejecting random walk does not necessarily invalidate EMH, which is an entirely separate concept from RWH. In a 2000 paper, Andrew Lo back-analyzed data from the U.S. from 1962 to 1996 and found that "several technical indicators do provide incremental information and may have some practical value". Burton Malkiel dismissed

2944-477: The irregularities mentioned by Lo and McKinlay as being too small to profit from. Technicians say that the EMH and random walk theories both ignore the realities of markets, in that participants are not completely rational and that current price moves are not independent of previous moves. Some signal processing researchers negate the random walk hypothesis that stock market prices resemble Wiener processes , because

3008-528: The length of the thrust off a high or low and projects the thrust to obtain a target. The horizontal method measures the width of a congestion pattern and uses that to obtain a target. In the US, Chartcraft used an IBM S/360 in the 1960s to produce point and figure charts. Point and figure charts were automated in the UK in the early 1980s by the Indexia company run by Jeremy Du Plessis. This automation increased

3072-888: The like. Technicians employ many methods, tools and techniques as well, one of which is the use of charts. Using charts, technical analysts seek to identify price patterns and market trends in financial markets and attempt to exploit those patterns. Technicians using charts search for archetypal price chart patterns, such as the well-known head and shoulders or double top/bottom reversal patterns, study technical indicators , moving averages and look for forms such as lines of support, resistance, channels and more obscure formations such as flags , pennants , balance days and cup and handle patterns. Technical analysts also widely use market indicators of many sorts, some of which are mathematical transformations of price, often including up and down volume, advance/decline data and other inputs. These indicators are used to help assess whether an asset

3136-408: The main obstacles is the highly subjective nature of technical analysis – the presence of geometric shapes in historical price charts is often in the eyes of the beholder. In this paper, we propose a systematic and automatic approach to technical pattern recognition using nonparametric kernel regression , and apply this method to a large number of U.S. stocks from 1962 to 1996 to evaluate

3200-481: The market (anticipating higher prices). And because most investors are bullish and invested, one assumes that few buyers remain. This leaves more potential sellers than buyers, despite the bullish sentiment. This suggests that prices will trend down, and is an example of contrarian trading . The industry is globally represented by the International Federation of Technical Analysts (IFTA), which

3264-407: The month. Later in the same month, the stock makes a relative high equal to the most recent relative high. In this a technician sees strong indications that the down trend is at least pausing and possibly ending, and would likely stop actively selling the stock at that point. Technical analysts believe that investors collectively repeat the behavior of the investors who preceded them. To a technician,

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3328-419: The oldest form of technical analysis developed by a Japanese grain trader; Harmonics ; Dow theory ; and Elliott wave theory ) may ignore the other approaches, yet many traders combine elements from more than one technique. Some technical analysts use subjective judgment to decide which pattern(s) a particular instrument reflects at a given time and what the interpretation of that pattern should be. Others employ

3392-440: The past data bias by projecting support and resistance levels from differing time frames into the near-term future and combining that with reversion to the mean techniques. The efficient-market hypothesis (EMH) contradicts the basic tenets of technical analysis by stating that past prices cannot be used to profitably predict future prices. Thus it holds that technical analysis cannot be effective. Economist Eugene Fama published

3456-442: The patterns such as a triangle continuation or reversal pattern can be generated with the assumption of two distinct groups of investors with different assessments of valuation. The major assumptions of the models are the finiteness of assets and the use of trend as well as valuation in decision making. Many of the patterns follow as mathematically logical consequences of these assumptions. Point and figure chart The technique

3520-820: The popularity and usage of point and figure charts because hundreds of charts could be viewed and altered quickly and easily. At the same time a method of log scaling point and figure charts was devised, where the value of the Xs and Os was set to a percentage rather than a price. This allowed the sensitivity of Point and Figure charts to remain constant no matter what the price level. Kaufman , in New Trading Systems and Methods , 2005, documents research he and Kermit Zeig performed over many years computerizing point and figure charting. LeBeau and Lucas also developed computerized point and figure charts in Technical Traders Guide to Computer Analysis of

3584-410: The premise that all relevant information is already reflected by prices, technical analysts believe it is important to understand what investors think of that information, known and perceived. Technical analysts believe that prices trend directionally, i.e., up, down, or sideways (flat) or some combination. The basic definition of a price trend was originally put forward by Dow theory . An example of

3648-805: 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 the variables used in fundamental analysis can be used as input. As ANNs are essentially non-linear statistical models, their accuracy and prediction capabilities can be both mathematically and empirically tested. In various studies, authors have claimed that neural networks used for generating trading signals given various technical and fundamental inputs have significantly outperformed buy-hold strategies as well as traditional linear technical analysis methods when combined with rule-based expert systems. While

3712-481: The seminal paper on the EMH in the Journal of Finance in 1970, and said "In short, the evidence in support of the efficient markets model is extensive, and (somewhat uniquely in economics) contradictory evidence is sparse." However, because future stock prices can be strongly influenced by investor expectations, technicians claim it only follows that past prices influence future prices. They also point to research in

3776-423: The statistical moments of such processes and real stock data vary significantly with respect to window size and similarity measure . They argue that feature transformations used for the description of audio and biosignals can also be used to predict stock market prices successfully which would contradict the random walk hypothesis. The random walk index (RWI) is a technical indicator that attempts to determine if

3840-537: The term Dow theory nor presented it as a trading system. The six basic tenets of Dow theory as summarized by Hamilton, Rhea, and Schaefer are described below. Alfred Cowles in a study in Econometrica in 1934 showed that trading based upon the editorial advice would have resulted in earning less than a buy-and-hold strategy using a well diversified portfolio . Cowles concluded that a buy-and-hold strategy produced 15.5% annualized returns from 1902 to 1929 while

3904-498: The value of a certain number of Xs or Os. Traditionally this was one and is called a 1 box reversal chart. More common is three, called a 3 box reversal chart. Because point and figure charts are plotted on squared paper, 45 degree lines may be used to define up trends and down trends from important highs and lows on the chart allowing objective analysis of trends. Also in common usage are two methods of obtaining price targets from point and figure charts. The vertical method measures

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3968-878: Was a founding member of IFTA, has recently celebrated its 50th anniversary and certifies analysts with the Diploma in Technical Analysis. In Canada the industry is represented by the Canadian Society of Technical Analysts. In Australia, the industry is represented by the Australian Technical Analysts Association (ATAA), (which is affiliated to IFTA) and the Australian Professional Technical Analysts (APTA) Inc. Professional technical analysis societies have worked on creating

4032-507: Was invented by A.W. Cohen in his 1947 book, 'How to Use the Three-Point Reversal Method of Point & Figure Stock Market Timing' and has a large following. The charts are constructed by deciding on the value represented by each X and O. Any price change below this value is ignored so point and figure acts as a sieve to filter out the smaller price changes. The charts change column when the price changes direction by

4096-539: Was tested for data snooping and other problems in 1999; the sample covered by Brock et al. was robust to data snooping. Subsequently, a comprehensive study of the question by Amsterdam economist Gerwin Griffioen concludes that: "for the U.S., Japanese and most Western European stock market indices the recursive out-of-sample forecasting procedure does not show to be profitable, after implementing little transaction costs. Moreover, for sufficiently high transaction costs it

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