ESG Investing Portfolio Optimization based on Multiple Criteria Group Decision-Making

Abstract

Since its debut in a United Nations report in 2006, Environmental, Social, and Governance (ESG) performance has become a proxy for a company’s resilience and risk management capabilities; but it also demonstrates and enhances the long-term value of a business. Investments in firms corresponding to ESG has recently attracted significant attentions from both academic research and practical investing activities. In light of the observations that different investors and rating agencies could have different financial and non-financial evaluation results about the same firm, this study investigates the ESG investing portfolio optimization problem under the framework of multiple criteria group decision-making (MCGDM), in which both financial and ESG-related factors are simultaneously considered to evaluate the firm performance. In addition, both the financial and ESG-related data are prone to noise, this work employs the stochastic optimization and robust optimization techniques to address the endogenous uncertainty in ESG investing portfolio optimization. The application of proposed models is demonstrated using the empirical data collected from Hong Kong Stock Exchange (HKEX), Shenzhen Stock Exchange (SZSE) and Bloomberg.

Keywords: ESG investing; Portfolio optimization; Multi-criteria decision-making; Stochastic portfolio optimization; Robust portfolio optimization