Measuring costly behavioral bias factors in portfolio management: a review

IF 1.5 Q3 BUSINESS, FINANCE Financial Markets and Portfolio Management Pub Date : 2024-02-19 DOI:10.1007/s11408-024-00444-7
David Gorzon, Marc Bormann, Ruediger von Nitzsch
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Abstract

Various factor models extended by Jensen’s (J Financ 23:389–416, 1968) alpha have been used to measure the retail investors’ portfolio (under-) performance compared to the market portfolio. The previous studies tried to explain this anomaly in behavioral finance by examining retail investors’ cognitive biases that induce irrational trading behavior. While operationalizing these cognitive biases in trading is not trivial, researchers still have found measures to proxy for biases and prove their statistical and economic significance. However, these studies only focused on linking one or a subset of behavioral biases and their effect on portfolio performance. In addition, different measures of biases across studies complicate the comparability of results. Therefore, this paper provides a structured overview of the current state of the literature regarding behavioral biases and their measurements to design a behavioral factor model that should help to explain the performance alpha from a behavioral finance perspective. The paper presents an overview of 11 behavioral bias factors and 29 corresponding measurements to consider inputting in such a model. With an application-oriented focus, it is recommended to include the most researched bias factors in a factor model, which are also the most detrimental to portfolio performance, as well as to include the most frequently used and least complex measures, which results in the primary inclusion of the following eight behavioral bias factors: disposition effect, under-diversification, home bias, local bias, lottery stock preference, trend chasing, overtrading, and trade clustering.

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衡量投资组合管理中代价高昂的行为偏差因素:综述
由詹森(J Financ 23:389-416,1968 年)的阿尔法扩展而来的各种因子模型被用来衡量散户投资者的投资组合(低于)市场投资组合的表现。以往的研究试图通过研究散户投资者的认知偏差来解释行为金融学中的这一反常现象,这些认知偏差会诱发非理性交易行为。虽然将交易中的这些认知偏差可操作化并非易事,但研究人员仍找到了替代偏差的措施,并证明了其统计和经济意义。不过,这些研究只侧重于将一种或部分行为偏差与它们对投资组合表现的影响联系起来。此外,不同研究对偏差的衡量标准不同,也使结果的可比性变得复杂。因此,本文对有关行为偏差及其测量方法的文献现状进行了结构化概述,以设计一个行为因素模型,帮助从行为金融学的角度解释阿尔法表现。本文概述了 11 种行为偏差因子和 29 种相应的测量方法,以考虑将其输入该模型。本文以应用为导向,建议在因子模型中纳入研究最多的偏差因子,这些因子也是最不利于投资组合表现的因子,同时纳入最常用、最不复杂的测量方法,因此主要纳入了以下八个行为偏差因子:处置效应、分散不足、主场偏差、本地偏差、彩票股偏好、趋势追逐、过度交易和交易集群。
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来源期刊
CiteScore
3.20
自引率
0.00%
发文量
21
期刊介绍: The journal Financial Markets and Portfolio Management invites submissions of original research articles in all areas of finance, especially in – but not limited to – financial markets, portfolio choice and wealth management, asset pricing, risk management, and regulation. Its principal objective is to publish high-quality articles of innovative research and practical application. The readers of Financial Markets and Portfolio Management are academics and professionals in finance and economics, especially in the areas of asset management. FMPM publishes academic and applied research articles, shorter ''Perspectives'' and survey articles on current topics of interest to the financial community, as well as book reviews. All article submissions are subject to a double-blind peer review. http://www.fmpm.org Officially cited as: Financ Mark Portf Manag
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