Do Security Analysts Herd on Stock Recommendations and Does It Affect Returns?

Tsai-hui Lin, Woan-yuh Jang, Seng-su Tsang


This study explores the herding behavior of security analysts, the firm characteristics in attracting herding, and the consequences of the herding recommendations on returns in China’s stock market. By applying the LSV method, the stock recommendations of analysts are partitioned into buy- and sell-recommendations. The results show that the herding level of sell-recommendation is greater than that of buy-recommendation, which is particularly evident in the bear market. Moreover, investors selling the holdings that analysts herd to recommend “sell” might help avoid losses in the bear market. Notably, when in the bull market, if analysts herd to make sell-recommendations, investors might gain more by acting conversely. These performance variations according to market sentiments appear to be partially explained by a firm’s characteristics based on additional regression analyses and are partially attributed to analysts’ individual attitudes toward market sentiments.

Full Text:



International Journal of Economics and Finance  ISSN  1916-971X (Print) ISSN  1916-9728 (Online)

Copyright © Canadian Center of Science and Education

To make sure that you can receive messages from us, please add the '' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.