Price trends and patterns in technical analysis: A theoretical and empirical examination |
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Authors: | Geoffrey C. Friesen Paul A. Weller Lee M. Dunham |
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Affiliation: | 1. Department of Finance, College of Business, University of Nebraska – Lincoln, Lincoln, NE 68508, USA;2. Department of Finance, Henry B. Tippie College of Business, University of Iowa, Iowa City, IA 52242, USA;3. Department of Finance, College of Business, Creighton University, Omaha, NE 68178, USA |
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Abstract: | While many technical trading rules are based upon patterns in asset prices, we lack convincing explanations of how and why these patterns arise, and why trading rules based on technical analysis are profitable. This paper provides a model that explains the success of certain trading rules that are based on patterns in past prices. We point to the importance of confirmation bias, which has been shown to play a key role in other types of decision making. Traders who acquire information and trade on the basis of that information tend to bias their interpretation of subsequent information in the direction of their original view. This produces autocorrelations and patterns of price movement that can predict future prices, such as the “head-and-shoulders” and “double-top” patterns. The model also predicts that sequential price jumps for a particular stock will be positively autocorrelated. We test this prediction and find that jumps exhibit statistically and economically significant positive autocorrelations. |
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Keywords: | G11 G12 G14 |
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