Metaheuristic Algorithms For Portfolio Selection Problem: An Overview Including Crypto-Assets

Due to the NP-hard nature of the portfolio optimization problem, a plethora of techniques, such as metaheuristic algorithms have been reported and used in the literature. Their capacity to produce top-quality solutions in reduced computing times makes them a seductive tool for decision-makers (investors, portfolio managers, policymakers...) by supplying real-time solutions. This paper provides an overview of the literature on the use of metaheuristics for solving NP-hard versions of portfolio selection optimization and focuses on their readiness to provide high-quality solutions. In addition, the existing literature including crypto-assets is highlighted. A major finding of this paper is that studies conducted in this specific framework are scarce.