TY - JOUR
T1 - Price trends and patterns in technical analysis
T2 - A theoretical and empirical examination
AU - Friesen, Geoffrey C.
AU - Weller, Paul A.
AU - Dunham, Lee M.
N1 - Copyright:
Copyright 2009 Elsevier B.V., All rights reserved.
PY - 2009/6
Y1 - 2009/6
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=62749102119&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=62749102119&partnerID=8YFLogxK
U2 - 10.1016/j.jbankfin.2008.12.010
DO - 10.1016/j.jbankfin.2008.12.010
M3 - Article
AN - SCOPUS:62749102119
VL - 33
SP - 1089
EP - 1100
JO - Journal of Banking and Finance
JF - Journal of Banking and Finance
SN - 0378-4266
IS - 6
ER -