Can People Learn about 'Black Swans'? Experimental Evidence

• 成果类型: Article
• 署名作者: Payzan-LeNestour, Elise
• 署名单位: University of New South Wales Sydney
• 刊物名称: REVIEW OF FINANCIAL STUDIES
• ISSN/ISSBN: 0893-9454
• DOI: 10.1093/rfs/hhy040
• 发表日期: 2018
• 页码: 4815
• 关键词: stock return predictability; model selection; JUDGMENT; DECISION; expectations; uncertainty; complexity; RISK; LAW

摘要

How do people cope with tail risk? In a lab experiment that removed informational and incentive confounds, subjects overwhelmingly behaved like Bayesian learners. The results of simulations further revealed that if one is to survive under tail risk, one needs to follow the Bayesian approach, as all boundedly rational alternatives fail. These findings support the Bayesian assumption commonly made in prior studies on tail risk and model uncertainty, and they also demonstrate the importance of optimal learning under tail risk.