Metaheuristic Approach to Solve Portfolio Selection Problem
This work addresses portfolio selection for financial traders, but it is incremental as it builds on existing metaheuristic approaches.
The paper tackles the NP-hard portfolio optimization problem with cardinality and quantity constraints by proposing a heuristic method combining Tabu Search and TokenRing Search, achieving performance demonstrated on public benchmarks.
In this paper, a heuristic method based on TabuSearch and TokenRing Search is being used in order to solve the Portfolio Optimization Problem. The seminal mean-variance model of Markowitz is being considered with the addition of cardinality and quantity constraints to better capture the dynamics of the trading procedure, the model becomes an NP-hard problem that can not be solved using an exact method. The combination of three different neighborhood relations is being explored with Tabu Search. In addition, a new constructive method for the initial solution is proposed. Finally, I show how the proposed techniques perform on public benchmarks