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A Multi-Objective Evolutionary Algorithm for Portfolio Optimisation
Year Of Publication: 2009
Month Of Publication: March
Pages: 6
Download Count: 3
View Count: 1386
Comment Num: 0
Language: English
Source: working paper
Who Can Read: Free
Date: 4-24-2011
Publisher: Administrator
Summary
The use of heuristic evolutionary algorithms to address the problem of portfolio optimisation has been well documented. In order to decide which assets to invest in and how much to invest, one needs to assess the potential risk and return of different portfolios. This problem is ideal for solving using a Multi-Objective Evolutionary Algorithm (MOEA) that maximises return and minimises risk. We are working on a new MOEA loosely based on Zitzler’s Strength Pareto Evolutionary Algorithm (SPEA2) [20] using Value at Risk (VaR) as the risk constraint. This algorithm currently uses a dynamic population in order to overcome the problem of loosing solutions. We are also investigating a dynamic diversity and density operator.
Author(s)
Bradshaw, Nöel-Ann Sign in to follow this author
Walshaw, C_hris Sign in to follow this author
Parrott, Kevin Sign in to follow this author
Ierotheou, Cos Sign in to follow this author
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