title: Real-world datasets for portfolio selection and solutions of some stochastic dominance portfolio models.
abstract: A large number of portfolio selection models have appeared in the literature since the pioneering work of Markowitz. However, even when computational and empirical results are described, they are often hard to replicate and compare due to the unavailability of the datasets used in the experiments. We provide here several datasets for portfolio selection generated using real-world price values from several major stock markets. The datasets contain weekly return values, adjusted for dividends and for stock splits, which are cleaned from errors as much as possible. The datasets are available in different formats, and can be used as benchmarks for testing the performances of portfolio selection models and for comparing the efficiency of the algorithms used to solve them. We also provide, for these datasets, the portfolios obtained by several selection strategies based on Stochastic Dominance models (see "On Exact and Approximate Stochastic Dominance Strategies for Portfolio Selection" (Bruni et al. [2])). We believe that testing portfolio models on publicly available datasets greatly simplifies the comparison of the different portfolio selection strategies.
authors: Dip. Di Ingegneria Informatica, Automatica e Gestionale, Sapienza Università Di Roma, Rome, Italy.
authors: Renato
authors: R
authors: Bruni
authors: Dip. di Studi Aziendali, Università di Roma Tre, Rome, Italy.
authors: Francesco
authors: F
authors: Cesarone
authors: Facoltà di Economia, Università degli Studi Niccolò Cusano, Rome, Italy.
authors: Andrea
authors: A
authors: Scozzari
authors: Dip. Metodi e Modelli per l׳Economia, il Territorio e la Finanza, Sapienza Università di Roma, Rome, Italy.
authors: Fabio
authors: F
authors: Tardella