信息错觉:不同数量的信息和股票价格估计

IF 3.4 3区 经济学 Q1 ECONOMICS
Andreas Oehler, Matthias Horn, Stefan Wendt
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引用次数: 0

摘要

我们发起了一项基于问卷的股票价格预测竞赛,以分析参与者对不同信息量的感知以及对股票价格估计的影响。结果表明,提供更多的信息会增加相关信息的感知量,但不会改变参与者对股票价格的估计及其准确性。个体参与者的特征,如性别、金融知识或过度自信,不会影响这些发现。这意味着添加的信息起到了安慰剂信息的作用,导致了信息错觉。然而,增加的信息会影响个人对股价预测竞争本身的预期,并导致不太自信的投资者降低他们对回报和获奖机会的预期。我们的发现对从业者和研究人员都有启示。监管机构和政策制定者都应该考虑到,安慰剂信息会显著影响投资者的认知,因此,对提供给散户投资者的信息的监管应侧重于相关信息,避免不相关信息。研究人员应该意识到,安慰剂信息不对称地影响了实验中表现出不同程度过度自信的参与者的期望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information Illusion: Different Amounts of Information and Stock Price Estimates

We initiate a questionnaire-based stock price forecast competition to analyze participants' perception of different amounts of information and the impact on stock price estimates. The results show that providing more information increases the perceived amount of relevant information but does not alter participants' stock price estimates and their accuracy. Individual participants' characteristics, such as gender, financial knowledge, or overconfidence, do not affect these findings. This means that the added information acts as placebic information and leads to information illusion. However, the added information has an impact on individual expectations about the stock price forecast competition itself and leads less overconfident investors to decrease their expectations regarding payoff and chances to win a prize. Our findings provide implications for practitioners and researchers alike. Both regulators and policy makers should consider that placebic information can significantly impact investors' perception, and, therefore, regulation on information that is provided to retail investors should focus on relevant and avoid irrelevant information. Researchers should be aware that placebic information asymmetrically influences expectations of participants in experiments who show different levels of overconfidence.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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