.png){kind=icon}
返回
Predictability in financial analyst forecast errors: Learning or irrationality?
.png){kind=icon}
PRE
AI
DOI：10.1111/j.1475-679X.2006.00215.x.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this paper, we propose a rational learning-based explanation for the predictability in financial analysts' earnings forecast errors documented in prior literature. In particular, we argue that the serial correlation pattern in analysts' quarterly earnings forecast errors is consistent with an environment in which analysts face parameter uncertainty and learn rationally about the parameters over time. Using simulations and real data, we show that the predictability evidence is more consistent with rational learning than with irrationality (fixation on a seasonal random walk model or some other dogmatic belief).
Keyword:
EARNINGS FORECASTS
SECURITY ANALYSTS
PREDICTIVE-ABILITY
PRICE CHANGES
INFORMATION
EXPECTATIONS
TESTS
MODEL
UNDERREACTION
OVERREACTION
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.3
论文数:
1.7K
被引数:
1.3W
机构
暂无机构信息
引用论文
Self-organized perturbations enhance class IV behavior and 1/f power spectrum in elementary cellular automata.png)
Biosystems
BiosystemsIF0
PREAI
分享收藏
查看更多内容