Prospect Theory and Stock Market Anomalies

• 成果类型: Article
• 署名作者: Barberis, Nicholas; Jin, Lawrence J.; Wang, Baolian
• 署名单位: Yale University; California Institute of Technology; State University System of Florida; University of Florida
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/jofi.13061
• 发表日期: 2021
• 页码: 2639-2687
• 关键词: PORTFOLIO OPTIMIZATION; loss aversion; RISK; preferences; DECISION; returns; options

摘要

We present a new model of asset prices in which investors evaluate risk according to prospect theory and examine its ability to explain 23 prominent stock market anomalies. The model incorporates all of the elements of prospect theory, accounts for investors' prior gains and losses, and makes quantitative predictions about an asset's average return based on empirical estimates of the asset's return volatility, return skewness, and past capital gain. We find that the model can help explain a majority of the 23 anomalies.