Technical Analysis: Key Papers

"We have argued that because information is costly, prices cannot perfectly reflect the information which is available, since if it did, those who spent resources to obtain it would receive no compensation."
GROSSMAN, S.J., et al., 1980. On the Impossibility of Informationally Efficient Markets. The American Economic Review. [Cited by 848] 33.25

"Technical analysis, or the use of past prices to infer private information, has value in a model in which prices are not fully revealing and traders have rational conjectures about the relation between prices and signals."
BROWN, D.P. and R.H. JENNINGS, 1989. On Technical Analysis. Review of Financial Studies. [Cited by 102] 6.18

"The rising importance of chartists"
FRANKEL, J.A., K.A. FROOT and M.P. PAGE, 1990. Chartists, Fundamentalists, and Trading in the Foreign Exchange Market. The American Economic Review. [Cited by 123] 7.93

"This article attempts a formal study of technical analysis, which is a class of informal prediction rules, often preferred to Wiener-Kolmogorov prediction theory by participants of financial markets. Yet Wiener-Kolmogorov prediction theory provides optimal linear forecasts. This article investigates two issues that may explain this contradiction. First, the article attempts to devise formal algorithms to represent various forms of technical analysis in order to see if these rules are well defined. Second, the article discusses under which conditions (if any) technical analysis might capture those properties of stock prices left unexploited by linear models of Wiener-Kolmogorov theory."
NEFTCI, S.N., 1991. Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis.". The Journal of Business. [Cited by 68] 4.69

In a comprehensive and influential study, Brock, Lakonishok, and LeBaron [BrLL92], analyzed 26 technical trading rules using 90 years of daily stock prices from the Dow Jones Industrial Average up to 1987 and found that they all outperformed the market.
BROCK, W., J. LAKONISHOK and B. LEBARON, 1992. Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance. [Cited by 332] (24.49/year)

Technica, or chartist, analysis of financial markets involves providing forecasts or trading advice on the basis of largely visual inspection of past prices, without regard to any underlying economic or ‘fundamental’ analysis. This paper reports the results of a questionnaire survey, conducted on behalf of the Bank of England, among chief foreign exchange dealers based in London in November 1988. Amongst other findings, it is revealed that at least 90 per cent of respondents place some weight on this form of non-fundamental analysis when forming views at one or more time horizons. There is also a skew towards reliance on technical, as opposed to fundamentalist, analysis at shorter horizons, which becomes steadily reversed as the length of horizon considered is increased. A very high proportion of chief dealers view technical and fundamental analysis as complementary forms of analysis and a substantial proportion suggest that technical advice may be self-fulfilling. TAYLOR, M.P. and H. ALLEN, 1992. The use of technical analysis in the foreign exchange market. Journal of International Money and Finance. [Cited by 212] 15.70

"The authors investigate the informational role of volume and its applicability for technical analysis. They develop a new equilibrium model in which aggregate supply is fixed and traders receive signals with differing quality. The authors show that volume provides information on information quality that cannot be deduced from the price statistic. They show how volume, information precision, and price movements relate, and demonstrate how sequences of volume and prices can be informative. The authors also show that traders who use information contained in market statistics do better than traders who do not. Technical analysis, thus, arises as a natural component of the agents' learning process."
BLUME, L., D. EASLEY and M. O'HARA , 1994. Market Statistics and Technical Analysis: The Role of Volume. The Journal of Finance. [Cited by 198] 17.22

"There is reliable evidence that simple rules used by traders have some predictive value over the future movement of foreign exchange prices. This paper will review some of this evidence and discuss the economic magnitude of this predictability. The profitability of these trading rules will then be analyzed in connection with central bank activity using intervention data from the Federal Reserve. The objective is to find to what extent foreign exchange predictability can be confined to periods of either high or low central bank activity. The results indicate that after removing periods in which the Federal Reserve is active, exchange rate predictability is dramatically reduced." LEBARON, B.D. and M.P. PAGE, 1994. Technical trading rule profitability and foreign exchange intervention. [Cited by 98] 8.52

"Using genetic programming techniques to find technical trading rules, we find strong evidence of economically significant out-of-sample excess returns to those rules for each of six exchange rates, over the period 1981-1995. Further, when the dollar/deutschemark rules are allowed to determine trades in the other markets, there is a significant improvement in performance in all cases, except for the deutschemark/yen. Betas calculated for the returns according to various benchmark portfolios provide no evidence that the returns to these rules are compensation for bearing systematic risk. Bootstrapping results on the dollar/deutschemark indicate that the trading rules are detecting patterns in the data that are not captured by standard statistical models."
NEELY, C.J., P. WELLER and R. DITTMAR, 1996. Is technical analysis in the foreign exchange market profitable?: a genetic programming approach. [Cited by 126] 13.26

"Christopher J. Neely briefly explains the fundamentals of technical analysis and the efficient markets hypothesis as applied to the foreign exchange market, evaluates the profitability of simple trading rules, and reviews recent ideas that might justify extrapolative technical analysis."
NEELY, C., 1997. Technical Analysis in the Foreign Exchange Market: A Layman's Guide. Federal Reserve Bank of St. Louis Review. [Cited by 37] 4.35

"This article reports the results of a questionnaire survey conducted in February 1995 on the use by foreign exchange dealers in Hong Kong of fundamental and technical analyses to form their forecasts of exchange rate movements. Our findings reveal that>85% of respondents rely on both fundamental and technical analyses for predicting future rate movements at different time horizons. At shorter horizons, there exists a skew towards reliance on technical analysis as opposed to fundamental analysis, but the skew becomes steadily reversed as the length of horizon considered is extended. Technical analysis is considered slightly more useful in forecasting trends than fundamental analysis, but significantly more useful in predicting turning points. Interest rate-related news is found to be a relatively important fundamental factor in exchange rate forecasting, while moving average and/or other trend-following systems are the most useful technical technique."
LUI, Y.H. and D. MOLE, 1998. The use of fundamental and technical analyses by foreign exchange dealers: Hong Kong evidence. Journal of International Money and Finance. [Cited by 53] 7.07

"This article reconciles an apparent contradiction found by recent research on U.S. intervention in foreign exchange markets. LeBaron (1996) and Szakmary and Mathur (1997) show that extrapolative technical trading rules trade against U.S. foreign exchange intervention and produce excess returns during intervention periods. Leahy (1995) shows that U.S. intervention itself is profitable over long periods of time. In other words, technical trades make excess returns when they take positions contrary to U.S. intervention - U.S. intervention itself is profitable, however. This article will first present recent research on these subjects. Then it will discuss how differing investment horizons and varying returns and position sizes may reconcile these facts."
NEELY, C.J., 1998. Technical Analysis and the Profitability of US Foreign Exchange Intervention. Federal Reserve Bank of St. Louis Review. [Cited by 35] 4.67

In this paper we investigate the profitability of a simple technical trading rule based on Artificial Neural Networks (ANNs). Our results, based on applying this investment strategy to the General Index of the Madrid Stock Market, suggest that, in absence of trading costs, the technical trading rule is always superior to a buy-and-hold strategy for both "bear" market and "stable" market episodes. On the other hand, we find that the buy-and-hold strategy generates higher returns than the trading rule based on ANN only for a "bull" market subperiod. FERNANDEZ-RODRIGUEZ, F., C. GONZALEZ-MARTEL and S. , 2000. On the profitability of technical trading rules based on artificial neural networks: Evidence from …. Economics Letters. [Cited by 23] 4.18

"This study shows that past trading volume provides an important link between “momentum” and “value” strategies. Specifically, we find that firms with high (low) past turnover ratios exhibit many glamour (value) characteristics, earn lower (higher) future returns, and have consistently more negative (positive) earnings surprises over the next eight quarters. Past trading volume also predicts both the magnitude and persistence of price momentum. Specifically, price momentum effects reverse over the next five years, and high (low) volume winners (losers) experience faster reversals. Collectively, our findings show that past volume helps to reconcile intermediate-horizon “underreaction” and long-horizon “overreaction” effects."
LEE, C.M.C. and B. SWAMINATHAN, 2000. Price Momentum and Trading Volume. THE JOURNAL OF FINANCE. [Cited by 200] 36.35

"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."
LO, A.W., et al., 2000. Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical …. The Journal of Finance. [Cited by 89] 16.18

"This paper extends genetic programming techniques to show that US foreign exchange intervention information improves technical trading rules’ profitability for two of four exchange rates over part of the out-of-sample period. Rules trade contrary to intervention and are unusually profitable on days prior to intervention, indicating that intervention is intended to halt predictable trends. Intervention seems to be more successful in checking such trends in the out-of-sample (1981-98) period than in the in-sample (1975-80) period. Any improvement in performance results from more precise estimation of the relationship between current and past exchange rates, rather than from information about contemporaneous intervention."
NEELY, C.J. and P. WELLER, 2001. Technical analysis and central bank intervention. Journal of International Money and Finance. [Cited by 25] 5.55

The apparent conflict between the level of resources dedicated to technical analysis by practitioners and academic theories of market efficiency is a long-standing puzzle. We explore a previously unexamined feature of technical analysis — namely its relation to liquidity provision. We demonstrate that support and resistance levels coincide with peaks in depth on the limit order book and moving average forecasts reveal information about the relative position of depth on the book. Furthermore, we show that these relationships stem from technical rules locating depth already in place on the limit order book.
KAVAJECZ, K.A., E.R. ODDERS-WHITE and O. JOURNALS, 2003. Technical Analysis and Liquidity Provision. Review of Financial Studies. [Cited by 14] 5.60

"This paper makes an extensive simulation comparison of popular dynamic strategies of asset allocation. For each strategy, alternative measures have been calculated for risk, return and risk-adjusted performance (Sharpe ratio, Sortino ratio, return at risk). Moreover, the strategies are compared in different market situations (bull, bear, no-trend markets) and with different market volatility, taking into account transaction costs and discrete rebalancing of portfolios. The simulations show a dominant role of constant proportion strategies in bear and no-trend markets and a preference for benchmarking strategies in bull markets. These results are independent of the volatility level and the risk-adjusted measure adopted."
CESARI, R. and D. CREMONINI, 2003. Benchmarking, portfolio insurance and technical analysis: a Monte Carlo comparison of dynamic …. Journal of Economic Dynamics and Control. [Cited by 11] 4.40

PARK, C.H. and S.H. IRWIN, 2004. The Profitability of Technical Analysis: A Review.. AgMAS Project Research Report No. [Cited by 2] 1.33