An Evolutionary Optimization Approach to Risk Parity Portfolio Selection

Abstract

In this paper we present an evolutionary optimization approach to solve the risk parity portfolio selection problem. While there exist convex optimization approaches to solve this problem when long-only portfolios are considered, the optimization problem becomes nontrivial in the long-short case. To solve this problem, we propose a genetic algorithm as well as a local search heuristic. This algorithmic framework is able to compute solutions successfully. Numerical results using real-world data substantiate the practicability of the approach presented in this paper.

Assessing the Volume of Changes to Banking Assets and Liabilities Using Genetic Algorithms in Additional Funds Needed Model

“…Forecasting (FC) was intensively studied by [35,5,36,37,38,39,40,27,41,42,43,44,45,46,47,48,49,2,50,51,52,53,54]. Portfolio optimization (PSP) is another extensive researched topic by, [55,56,57,58,59,60,61,30,62].…”

Equity portfolio management with cardinality constraints and risk parity control using multi-objective particle swarm optimization

“…In all the proposed cases, portfolios with cost function value equal to zero achieve risk parity. Due to the non-smoothness and non-convexity of f RP 1 , f RP 2 and f RP 3 , approximation and heuristic approaches are used to solve the corresponding minimization problems (see, for instance, Hochreiter, 2015 andPalomar, 2015 ).…”

“…However, the existence and uniqueness of a solution to the risk parity portfolio selection problem can be guaranteed only in some special cases, for which ad hoc methods have been proposed in literature ( Bai et al, 2016;Griveau-Billion et al, 2013;Maillard et al, 2010;Spinu, 2013 ). The only effective tool for the general case is represented by the use of a heuristic algorithm that is able to find approximate solutions ( Hochreiter, 2015;Vijayalakshmi Pai and Michel, 2012 ).…”