Technical analysis

About: Technical analysis is a research topic. Over the lifetime, 2705 publications have been published within this topic receiving 72361 citations.

Efficient capital markets: a review of theory and empirical work*

Abstract: Efficient Capital Markets: A Review of Theory and Empirical Work Author(s): Eugene F. Fama Source: The Journal of Finance, Vol. 25, No. 2, Papers and Proceedings of the Twenty-Eighth Annual Meeting of the American Finance Association New York, N.Y. December, 28-30, 1969 (May, 1970), pp. 383-417 Published by: Blackwell Publishing for the American Finance Association Stable URL: http://www.jstor.org/stable/2325486 Accessed: 30/03/2010 21:28

Simple Technical Trading Rules and the Stochastic Properties of Stock Returns

Abstract: This paper tests two of the simplest and most popular trading rules—moving average and trading range break—by utilizing the Dow Jones Index from 1897 to 1986. Standard statistical analysis is extended through the use of bootstrap techniques. Overall, our results provide strong support for the technical strategies. The returns obtained from these strategies are not consistent with four popular null models: the random walk, the AR(1), the GARCH-M, and the Exponential GARCH. Buy signals consistently generate higher returns than sell signals, and further, the returns following buy signals are less volatile than returns following sell signals, and further, the returns following buy signals are less volatile than returns following sell signals. Moreover, returns following sell signals are negative, which is not easily explained by any of the currently existing equilibrium models.

The Efficient Market Hypothesis and Its Critics

Abstract: Ageneration ago, the efe cient market hypothesis was widely accepted by academic e nancial economists; for example, see Eugene Fama’ s (1970) ine uential survey article, “ Efe cient Capital Markets.” It was generally believed that securities markets were extremely efe cient in ree ecting information about individual stocks and about the stock market as a whole. The accepted view was that when information arises, the news spreads very quickly and is incorporated into the prices of securities without delay. Thus, neither technical analysis, which is the study of past stock prices in an attempt to predict future prices, nor even fundamental analysis, which is the analysis of e nancial information such as company earnings and asset values to help investors select “ undervalued” stocks, would enable an investor to achieve returns greater than those that could be obtained by holding a randomly selected portfolio of individual stocks, at least not with comparable risk. The efe cient market hypothesis is associated with the idea of a “ random walk,” which is a term loosely used in the e nance literature to characterize a price series where all subsequent price changes represent random departures from previous prices. The logic of the random walk idea is that if the e ow of information is unimpeded and information is immediately ree ected in stock prices, then tomorrow’ s price change will ree ect only tomorrow’ s news and will be independent of the price changes today. But news is by dee nition unpredictable, and, thus, resulting price changes must be unpredictable and random. As a result, prices fully ree ect all known information, and even uninformed investors buying a diversie ed portfolio at the tableau of prices given by the market will obtain a rate of return as generous as that achieved by the experts.

Market Statistics and Technical Analysis: The Role of Volume

Abstract: We investigate the informational role of volume and its applicability for technical analysis We develop a new equilibrium model in which aggregate supply is fixed and traders receive signals with differing quality We show that volume provides information on information quality that cannot be deduced from the price statistic We show how volume, information precision, and price movements relate, and demonstrate how sequences of volume and prices can be informative We 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 TECHNICAL ANALYSIS OF MARKET data has long been a pervasive activity in both security and futures markets Technical analysts believe that price and volume data provide indicators of future price movements, and that by examining these data, information may be extracted on the fundamentals driving returns1 If markets are efficient in the sense that the current price impounds all information, then such activity is clearly pointless But if the process by which prices adjust to information is not immediate, then market statistics may impound information that is not yet incorporated into the current market price In particular, volume may be informative about the process of security returns In this paper we investigate the informational role of volume That volume may play an important role in markets has long been a subject of empirical research (see, for example, Gallant, Rossi, and Tauchen (1992); Karpoff (1987) provides an excellent review of previous research) This research has documented a remarkably strong relation between volume and the absolute