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biasedlearningcreatesoverconfidence
Ni Xuanming1; Wu Chen2; Zhao Huimin3
2018
发表期刊journalofsystemssciencecomplexity
ISSN1009-6124
卷号31期号:6页码:1603
摘要The aim of this paper is to develop a multi-period economic model to interpret how the people become overconfident by a biased learning that people tend to attribute the success to their abilities and failures to other factors. the authors suppose that the informed trader does not know the distribution of the precision of his private signal and updates his belief on the distribution of the precision of his knowledge by bayer's rule. the informed trader can eventually recognize the value of the precision of his knowledge after an enough long time biased learning, but the value is overestimated which leads him to be overconfident. furthermore, based on the definition on the luckier trader who succeeds the same times but has the larger variance of the knowledge, the authors find that the luckier the informed trader is, the more overconfident he will be; the smaller the biased learning factor is, the more overconfident the informed trader is. the authors also obtain a linear equilibrium which can explain some anomalies in financial markets, such as the high observed trading volume and excess volatility.
语种英语
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/42189
专题中国科学院数学与系统科学研究院
作者单位1.北京大学
2.中国科学院数学与系统科学研究院
3.中山大学
推荐引用方式
GB/T 7714
Ni Xuanming,Wu Chen,Zhao Huimin. biasedlearningcreatesoverconfidence[J]. journalofsystemssciencecomplexity,2018,31(6):1603.
APA Ni Xuanming,Wu Chen,&Zhao Huimin.(2018).biasedlearningcreatesoverconfidence.journalofsystemssciencecomplexity,31(6),1603.
MLA Ni Xuanming,et al."biasedlearningcreatesoverconfidence".journalofsystemssciencecomplexity 31.6(2018):1603.
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