CEO Optimism and Analyst Forecast Bias: Empirical Evidence from the US

• Main Authors: Tsung-Hsien Lu, 呂宗弦
• Other Authors: Yen-Hsien Lee
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/13894254715852531027

碩士 === 中原大學 === 財務金融研究所 === 105 === This study examines the impact of optimistic CEOs’earnings predictions on analysts’ forecast bias in the United States from 1993 to 2015; the study also attempts to find the characteristics of firms exhibiting reductions in forecast bias. This study uses the definition of analyst forecast bias in Wong and Zang (2014) and that of optimistic CEO proxy variables in Jenner et al. (2016) and employs the I/B/E/S and Compustat databases to establish the main research objectives. Following Steve and Williams (2001), who revealed the presence of asymmetry sensitivity between analysts’ positive and negative forecast bias, we analyze the positive and negative forecast error sample. By using cash dividend changes, external financing, credit rating, and CEO gender as media for corporate release information, we examine whether these four variables can improve analysts’ ability to predict and reduce the analyst forecast bias caused by optimistic CEOs. The empirical findings show that more optimistic CEOs are more likely to release higher earnings forecasts, resulting in an increase in analyst forecast bias. Furthermore, this effect occurs more significantly in relation to analysts’ negative forecast bias. Analysts can reduce the forecast bias caused by optimistic CEOs by receiving corporate information from cash dividend changes, debt financing, credit ratings, and CEO gender. This effect is more significant in relation to the analysts’ negative forecast bias.