Intelligent hybrid systems for financial decision making

Abstract

An intelligent hybrid systems approach for financial decision making which combines genetic algorithms and fuzzy logic is outlined. The genetic algorithm is used to induce fuzzy decision rules operating on data with 'linguistic' categories such as low, medium and high. The genetic algorithm is based on Packard's genetic algorithm for complex data analysis. The combination of genetic algorithms and fuzzy logic produces extremely easy to understand 'transparent' decision models which can be appreciated by technical personnel and high level strategic decision-makers alike. Further, the induced decision models naturally lend themselves to judgmental revisions by decision makers.