This repository contributes to reproducible research in portfolio selection using R. In particular, we evaluate several portfolio rules used in the literature by utilizing different publicly available data sets. The primary analysis builds on a recent empirical design by Kan, Wang, and Zhou (2022) (henceforth KWZ), which represents one of the standard frameworks pursued in the literature. Our empirical investigation reproduces 198 performance metrics reported by the original research, covering six public data sets, eleven portfolio rules, and three performance metrics. Additionally, the experiment can be generalized to accommodate additional data sets and portfolio rules. This generalization, however, presumes that the user is willing to put extra effort to (1) add new data sets to the main data_list object using the same format and (2) follow the logic behind the primary decision rule function (DR_function) to incorporate other portfolio rules with the same vector structure.
Kan, R., Wang, X., & Zhou, G. (2022). Optimal portfolio choice with estimation risk: No risk-free asset case. Management Science, 68(3), 2047-2068.