A re-examination of firm's attributes and share returns: Evidence from the Chinese A-shares market

Li, B, Boo, Y, Ee, M and Chen, C 2013, 'A re-examination of firm's attributes and share returns: Evidence from the Chinese A-shares market', International Review of Financial Analysis, vol. 28, pp. 174-181.


Document type: Journal Article
Collection: Journal Articles

Title A re-examination of firm's attributes and share returns: Evidence from the Chinese A-shares market
Author(s) Li, B
Boo, Y
Ee, M
Chen, C
Year 2013
Journal name International Review of Financial Analysis
Volume number 28
Start page 174
End page 181
Total pages 8
Publisher Elsevier
Abstract It is widely accepted that some firms' attributes or characteristics, such as a firm's size or book-to-market ratio, attract premiums in terms of average returns, which is a pervasive phenomenon not restricted to just a few individual markets. However, the way to derive these premiums by sorting firms based on their characteristics that are known to be associated with share returns, is not without controversy. This study takes a totally different approach by adopting a novel Self-Organizing Maps approach to cluster share returns first and identify the attributable factors afterwards. It finds eminent presence of the value effect in the Chinese A-shares market. It also finds that two other firm attributes, ROA and cash-flow-to-price, also have explanatory power over share returns. Liquidity and the ratio of tradable to total shares, which are often used to proxy corporate governance, show little evidence of explaining share return dispersion. Surprisingly, a "reversed" size effect is reported in this study.
Subject Finance
Pattern Recognition and Data Mining
Keyword(s) Chinese A-shares
Share attributes
Sorting
Cluster
Asset pricing
DOI - identifier 10.1016/j.irfa.2013.02.007
Copyright notice © 2013 Elsevier Inc. All rights reserved.
ISSN 1057-5219
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Citation counts: TR Web of Science Citation Count  Cited 2 times in Thomson Reuters Web of Science Article | Citations
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