Behavioral Aspects in Portfolio Selection Diana Barro, Marco Corazza, and Martina Nardon Abstract We introduce elements of Cumulative Prospect Theory into the portfo- lio selection problem and then compare stock portfolios selected under the behav- ioral approach with those selected according to classical approaches, such as Mean Variance and Mean Absolute Deviation ones. The mathematical programming prob- lem associated to the behavioral portfolio selection is highly non-linear and non- differentiable; for these reasons it is solved using a Particle Swarm Optimization approach. An application to the STOXX Europe 600 equity market is performed. Keywords Behavioral finance · Cumulative prospect theory · Portfolio selection · Particle Swarm Optimization 1 Introduction The literature on portfolio selection models is wide and since the founding work of Markowitz [4] has grown rapidly and has been extended along many different directions. Among them, modeling risk measures and performance evaluation are certainly crucial themes. Our aim is to suggest a selection model able to provide optimal decisions tailored to individual attitudes to risk and loss aversion, allowing for a larger flexibility in the description of the portfolio problem. In particular, Prospect Theory (PT) [2] provides a framework to effectively represent a wide range of risk attitudes. Within this framework, [5] propose a behavioral portfolio model. D. Barro · M. Corazza · M. Nardon (B ) Department of Economics, Ca’ Foscari University of Venice, Sestiere Cannaregio 873, 30121 Venezia, Italy e-mail: mnardon@unive.it D. Barro e-mail: d.barro@unive.it M. Corazza e-mail: corazza@unive.it © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 M. Corazza et al. (eds.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, https://doi.org/10.1007/978-3-030-78965-7_14 87