Multiple Criteria Decision Making and Applications in Portfolio Selection Problems

Multiple criteria decision making (MCDM) is a growing field that helps tackle complexproblems under multiple and often conflicting criteria. The portfolio selectiondecision is a fundamental problem in financial investment where the future performanceof assets is usually uncertain, but can be related to different attributesand factors. Thus, MCDM has a large potential to contribute in portfolio selectiondecisions. This thesis studies the applications of MCDM in portfolio selection problemsof insurance linked securities (ILS) and common stocks. An approach utilisingMCDM methods is developed and applied to real data: portfolio selection of ILS,and of the ASX200 stocks. The proposed model includes two main steps, screeningbased on MCDM methods to rank available assets in the investment universeaccording to a predefined criteria set, then standard portfolio optimisation techniquesare utilised to construct optimal portfolios from the top 20 highest rankedassets. Two popular MCDM techniques are: Analytic Hierarchy Process (AHP) andELECTRE III. Both of these techniques are considered in the screening step. Linearoptimisation with constraints is used for ILS portfolio selection, while standardmean-variance optimisation is used for stock portfolio selection in the optimisationstep. Results obtained from applying the model with AHP and ELECTRE areanalysed and compared against each other, and also against market portfolios. Theanalysis shows that optimal portfolios based on the proposed model dominate themarket portfolios. This demonstrates the relevance and usefulness of MCDM in aportfolio selection context. The final part of the thesis examines the link betweenAHP and another well established MCDM method: Multiple Attribute Utility Theory(MAUT). Different techniques to link AHP rating priority scales with the utilityfunctions in MAUT are suggested. They are based on piecewise linear functions andcurve fitting of parametric utility functions. The study indicates that AHP (directrating mode) could be viewed as a simplified version of MAUT in additive form.Results from applying the two methods to ILS portfolio selection are very similar.This highlights the similarity and efficiency of AHP compared to MAUT when usingthe proposed model to incorporate MCDM into portfolio selection