An ELECTRE III Based CBR Approach to Combinatorial Portfolio Selection

Abstract

Investors generally learn from historical data and use it to improve future investment decisions. However, existing portfolio selection research rarely considers such a concept. This paper proposes a novel approach to the combinatorial portfolio selection problem. Our solution employs the Case-Based Reasoning (CBR) approach with ELECTRE III, based on the Industry Classification Benchmark standards. The target stocks are ranked based on their similarities to a reference case, allowing specified selection criteria. Similarities are calculated based on selected ELECTRE III metrics. Experimental results with the Stock Exchange of Thailand data show that our CBR approach with ELECTRE III outperforms the traditional method.techniques for solving the portfolio selection problem with a single security have been developed. Recent studies have presented encouraging results on portfolio selection using reinforcement learning (Moody et al.

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