Measuring costly behavioral bias factors in portfolio management: a review

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.