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作 者:胡聪慧 杜君 刘玉珍[3] HU Conghui;DU Jun;LIU Yuzhen(Beijing Normal University,Beijing,China;University of Toronto,Toronto,Canada;Peking University,Beijing,China)
机构地区:[1]北京师范大学经济与工商管理学院,100875 [2]多伦多大学罗特曼商学院 [3]北京大学光华管理学院,100871
出 处:《经济学动态》2024年第12期92-110,共19页Economic Perspectives
基 金:国家自然科学基金面上项目“智能投顾的价值创造机理研究”(72372011);中央高校基本科研业务费专项资金(1233200014)。
摘 要:行为偏误是个人投资者亏损的重要原因。干预和纠正行为偏误不仅是投资者教育的重要方向,也是增强投资者资本市场获得感的重要举措。本文旨在探讨如何测度和比较不同行为偏误对投资者的影响,并进一步确定合理的行为偏误干预顺序。本文首先梳理了股票投资中常见的七种行为偏误,然后提出了行为偏误损失严重性和顽固性的概念和测度方法,并指出应重点干预纠正损失大、顽固性强的行为偏误。基于脱敏账户数据的测算结果显示,中国股票市场投资者行为偏误的干预应优先关注外推偏差和有限注意等选股偏误,也应对频繁交易和分散不足加以积极引导。广为关注的处置效应并未给投资者带来显著的亏损。最后,本文还考察了行为偏误及其损失严重性和顽固性随投资者个人特征的变化情况,为开展差异化的行为偏误干预提供了方法和经验指导。总之,本文的研究不仅为理解行为偏误提供了新的框架,而且提出了行为偏误干预的顺序和基本原则。Behavioral finance highlights significant deviations between individual investors'actual behavior in financial markets and the rational optimal choices predicted by traditional financial theories.These deviations,referred to as behavioral biases,are among the primary causes of individual investors'losses.While previous literature has extensively studied specific biases,there is no consensus on how to systematically measure and compare the effects of different biases on investors.Additionally,due to substantial heterogeneity in behavioral biases among investors,studies focusing on single biases often fail to comprehensively capture their actual impact.This study aims to address these gaps by exploring methods to measure and compare the effects of various biases and determining an optimal sequence for behavioral interventions based on these measurements.This paper first reviews seven common behavioral biases in stock investment:excessive trading,disposition effect,under-diversification,limited attention,extrapolation bias,anchoring,and gambling preference.It then introduces the innovative concepts of severity and persistence of behavioral biases,along with corresponding measurement methods.Severity refers to the magnitude of losses caused by a particular bias,while persistence captures the likelihood that the bias diminishes as investors gain trading experience.This paper suggests prioritizing interventions for biases that cause significant losses and are challenging for investors to overcome independently,optimizing the cost-benefit of such interventions.Using anonymized account-level data from a major Chinese brokerage,the paper empirically quantifies the severity and persistence of the above-mentioned seven biases and examines how these biases vary with individual investor characteristics.The findings reveal that the most severe biases,in terms of potential losses to investors,are extrapolation bias,excessive trading,limited attention,under-diversification,gambling preference,and anchoring,in that order.Extrapol
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