A Knowledge-based Framework for Incorporating Investor's Preference into Portfolio Decision-making

摘要: This paper describes a framework for the integration of rule-based system capable identifying an investor's risk preference into quantitative portfolio model based on and expected return. By inferring rules consisting objective subjective preferences, integrated methodology provides assets suitable preferences. Through investment in composed assets, investor is able to obtain following benefits: reduction costs time spent determine target alleviation anxiety from ‘out-of-favor’ assets. The applied development knowledge-based constructing preference-oriented portfolio. In procedure finding optimal portfolio, uses artificial intelligence method case-based reasoning thresholds when past records are available. Experimental results show that contributes significantly construction better perspective benefit/cost ratio than produced by existing models. Copyright © 2004 John Wiley & Sons, Ltd.