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Logistic Regression Model for Cognitive Biases in Financial Analysts Recommendations

Wang Lina, Zhu Weidong

Abstract


Basing on event study method, this paper explores whether analysts are prone to cognitive bias or not using a sample of 1857 recommendations for listed companies during 2011-2013 made by financial analysts from Shenyin and Wanguo Securities Research in China. Logistic regression results show that financial analysts are likely to award optimistic recommendations to stocks with better prior price performance and lower book-to-market. Moreover, good optimistic recommendations are characterized by better prior price performance, lower book-to-market and smaller firms size. The finding confirms the existence of cognitive biases in analysts recommendation behaviour.

Keywords


Logistic regression, cognitive bias, stock recommendation, financial analyst.

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