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biasedlearningcreatesoverconfidence
Ni Xuanming1; Wu Chen2; Zhao Huimin3
2018-01-01
Source Publicationjournalofsystemssciencecomplexity
ISSN1009-6124
Volume31Issue:6Pages:1603
AbstractThe 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.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/42189
Collection中国科学院数学与系统科学研究院
Affiliation1.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
Recommended Citation
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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