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Support for Resistance: Technical Analysis and Intraday Exchange Rates • Among the technical trading signals supplied to customers by foreign exchange trading firms are “support” and “resistance” levels. These levels indicate points at which an exchange rate trend is likely to be interrupted or reversed. • A rigorous test of the levels specified by six trading firms during the 1996-98 period reveals that these signals were quite successful in predicting intraday trend interruptions. • Although all six firms were able to identify turning points in exchange rate trends, some firms performed markedly better than others. As a group, the firms predicted turning points in the dollar-yen and dollar-pound exchange rates more accurately than turning points in the dollar-mark exchange rate. • In addition, the predictive power of the support and resistance levels appeared to last at least five business days after they were first communicated to customers. Carol Osler is a senior economist at the Federal Reserve Bank of New York. E arly in the morning of each business day, the major foreign exchange trading firms send their customers lists of technical trading signals for that day. Timely technical signals are also supplied by major real-time information providers. These signals, which are based primarily on prior price and volume movements, are widely used by active foreign exchange market participants for speculation and for timing their nonspeculative currency transactions. In fact, 25 to 30 percent of foreign exchange traders base most of their trades on technical trading signals (Cheung and Chinn 1999; Cheung and Wong 1999). More broadly, technical analysis is used as either a primary or secondary source of trading information by more than 90 percent of foreign exchange market participants in London (Allen and Taylor 1992) and Hong Kong (Lui and Mole 1998).
Technical Analysis in the Foreign Exchange Market Christopher J. Neely and Paul A. Weller Working Paper 2011-001B http://research.stlouisfed.org/wp/2011/2011-001.pdf January 2011 Revised July 2011 FEDERAL RESERVE BANK OF ST. LOUIS Research Division P.O. Box 442 St. Louis, MO 63166 ______________________________________________________________________________________ The views expressed are those of the individual authors and do not necessarily reflect official positions of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors. Federal Reserve Bank of St. Louis Working Papers are preliminary materials circulated to stimulate discussion and critical comment. References in publications to Federal Reserve Bank of St. Louis Working Papers (other than an acknowledgment that the writer has had access to unpublished material) should be cleared with the author or authors. Prepared for Wiley’s Handbook of Exchange Rates Technical Analysis in the Foreign Exchange Market Christopher J. Neely* Paul A. Weller July 24, 2011 Abstract: This article introduces the subject of technical analysis in the foreign exchange market, with emphasis on its importance for questions of market efficiency. “Technicians” view their craft, the study of price patterns, as exploiting traders’ psychological regularities. The literature on technical analysis has established that simple technical trading rules on dollar exchange rates provided 15 years of positive, risk-adjusted returns during the 1970s and 80s before those returns were extinguished. More recently, more complex and less studied rules have produced more modest returns for a similar length of time. Conventional explanations that rely on risk adjustment and/or central bank intervention do not plausibly justify the observed excess returns from following simple technical trading rules. Psychological biases, however, could contribute to the profitability of these rules. We view the observed pattern of excess returns to technical trading rules as being consistent with an adaptive markets view of the world. Keywords: exchange rate, technical analysis, technical trading, intervention, efficient markets hypothesis, adaptive markets hypothesis
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 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 we apply this method to a large number of U.S. stocks from 1962 to 1996 to evaluate 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. ONE OF THE GREATEST GULFS between academic finance and industry practice is the separation that exists between technical analysts and their academic critics. In contrast to fundamental analysis, which was quick to be adopted by the scholars of modern quantitative finance, technical analysis has been an orphan from the very start. It has been argued that the difference between fundamental analysis and technical analysis is not unlike the difference between astronomy and astrology. Among some circles, technical analysis is known as “voodoo finance.” And in his inf luential book A Random Walk down Wall Street, Burton Malkiel ~1996! concludes that “@u#nder scientific scrutiny, chart-reading must share a pedestal with alchemy.” However, several academic studies suggest that despite its jargon and methods, technical analysis may well be an effective means for extracting useful information from market prices. For example, in rejecting the Random Walk * MIT Sloan School of Management and Yale School of Management. Corresponding author: Andrew W. Lo ~firstname.lastname@example.org!. This research was partially supported by the MIT Laboratory for Financial Engineering, Merrill Lynch, and the National Science Foundation ~Grant SBR– 9709976!. We thank Ralph Acampora, Franklin Allen, Susan Berger, Mike Epstein, Narasimhan Jegadeesh, Ed Kao, Doug Sanzone, Jeff Simonoff, Tom Stoker, and seminar participants at the Federal Reserve Bank of New York, NYU, and conference participants at the ColumbiaJAFEE conference, the 1999 Joint Statistical Meetings, RISK 99, the 1999 Annual Meeting of the Society for Computational Economics, and the 2000 Annual Meeting of the American Finance Association for valuable comments and discussion.
Charts always have a story to tell. However, from time to time those charts may be speaking a language you do not understand and you may need some help from an interpreter. Technical indicators are the interpreters of the Forex market. They look at price information and translate it into simple, easy-to-read signals that can help you determine when to buy and when to sell a currency pair. Technical indicators are based on mathematical equations that produce a value that is then plotted on your chart. For example, a moving average calculates the average price of a currency pair in the past and plots a point on your chart. As your currency chart moves forward, the moving average plots new points based on the updated price information it has. Ultimately, the moving average gives you a smooth indication of which direction the currency pair is moving.Each technical indicator provides unique information. You will find you will naturally gravitate toward specific technical indicators based on your trading personality, but it is important to become familiar with all of the technical indicators at your disposal.