Hybrid optimization models of portfolio selection involving financial and ethical considerations
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In this paper, we propose a comprehensive three-stage multiple criteria decision making framework for portfolio selection based upon financial and ethical criteria simultaneously. It may be noted that the ethical investment movement that began from the USA in 1960s has gained tremendous momentum the world over recently. The growing instances of corporate scams and scandals have made it incumbent upon the investors to consider the quality of governance of corporations and ethicality of their conduct. Indeed, there has been a spate of reforms relating to corporate laws and capital markets all over the world. Also, the investors are becoming conscious of the desirability of ethical evaluation of the assets. The growing influence of institutional investors has reinforced this consciousness. Hence, the research in the area must take cognizance of these developments to construct models that accord due consideration to ethical criteria besides the financial criteria. We use multiple methodologies toward the purpose. Analytical hierarchy process technique is used to obtain the ethical performance score of each asset based upon investor-preferences. A fuzzy multiple criteria decision making method is used to obtain the financial quality score of each asset based upon investor-ratings on the financial criteria. Three hybrid portfolio optimization models are developed to obtain well diversified financially and ethically viable portfolios. These models have maximization of financial goal as main objective and differ in the way the ethical goal is pursued by the investor. Numerical illustrations are included to demonstrate the suitability of the models for obtaining diversified portfolios that meet the investor’s financial and ethical goals.
论文关键词:Portfolio optimization,Ethical investing,Multiple criteria decision making,Fuzzy set theory,AHP
论文评审过程:Received 3 April 2012, Revised 11 July 2012, Accepted 13 August 2012, Available online 24 August 2012.
论文官网地址:https://doi.org/10.1016/j.knosys.2012.08.014