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Why investors use technical analysis? Information discovery versus herding behavior

Why investors use technical analysis? Information discovery versus herding behavior Purpose – The purpose of this paper is to establish two competitive models to explain why investors use technical analysis (TA). Design/methodology/approach – Information Discovery Model suggests that technical traders are able to infer non-public information; Herding Behavior Model argues that TA is a kind of irrational herding behavior that can make profit when other noise traders exist. Findings – The empirical results from Chinese stock market show that some technical trading rules generate significant excess returns. Research limitations/implications – The empirical results from Chinese stock market show that some technical trading rules generate significant excess returns. Stocks with stronger information asymmetry and lower liquidity experiences higher excess return, which support the Information Discovery Model that TA is a method of information discovery for rational investors when the market is not fully efficient. Originality/value – Stocks with stronger information asymmetry and lower liquidity experiences higher excess return, which support the Information Discovery Model that TA is a method of information discovery for rational investors when the market is not fully efficient. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png China Finance Review International Emerald Publishing

Why investors use technical analysis? Information discovery versus herding behavior

Wang, Tiandu; Sun, Qian
China Finance Review International , Volume 5 (1): 16 – Feb 16, 2015
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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2044-1398
DOI
10.1108/CFRI-08-2014-0033
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to establish two competitive models to explain why investors use technical analysis (TA). Design/methodology/approach – Information Discovery Model suggests that technical traders are able to infer non-public information; Herding Behavior Model argues that TA is a kind of irrational herding behavior that can make profit when other noise traders exist. Findings – The empirical results from Chinese stock market show that some technical trading rules generate significant excess returns. Research limitations/implications – The empirical results from Chinese stock market show that some technical trading rules generate significant excess returns. Stocks with stronger information asymmetry and lower liquidity experiences higher excess return, which support the Information Discovery Model that TA is a method of information discovery for rational investors when the market is not fully efficient. Originality/value – Stocks with stronger information asymmetry and lower liquidity experiences higher excess return, which support the Information Discovery Model that TA is a method of information discovery for rational investors when the market is not fully efficient.

Journal

China Finance Review International – Emerald Publishing

Published: Feb 16, 2015

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