The research which forms the basis of this thesis introduces a conceptual model for supporting a case-based reasoning (CBR) selection among decision support systems for strategic asset allocation. Strategic asset allocation is part of an investment policy and is used when choosing an investment portfolio. Strategic asset allocation decision support systems commonly follow a rule-based approach to decision making. The purpose of the conceptual model, introduced by this research, is to support the adoption of a CAR approach, as CAR can be used to produce learning abilities and flexibility. The conceptual model is supported by an intelligent agent framework. Experiments are used to demonstrate the operability of the conceptual model using different decision models. The conceptual model uses case-based learning and flexibility to learn the decision-making processes of different organisations. From evaluations of the conceptual model evidence was found that indicated that intelligent agents and CAR could introduce learning and flexibility into decision support systems used for strategic asset allocation. The conceptual model developed and validated by this research constitutes the research contribution to knowledge.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:556185 |
| Date | January 2008 |
| Creators | Falconer, E. |
| Publisher | University of the West of Scotland |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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