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A Fuzzy Cognitive Map-Based Bi-Directional Inference Mechanism: An Application to Stock Investment Analysis
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1997
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EngineeringDecision AnalyticsFuzzy Multi-criteria Decision-makingAsset PricingFuzzy OptimizationQuantitative ManagementFinancial ModelingHierarchical Knowledge BaseKnowledge RepresentationFuzzy LogicFuzzy ComputingCausal Knowledge BaseAccountingQuantitative FinanceStock Investment AnalysisInvestment StrategyFinanceKnowledge BaseReal InvestmentFuzzy Expert SystemBusinessStock Market PredictionFinancial Engineering
The objective of this paper is to apply fuzzy cognitive map (FCM)-related techniques to (1) extract causal knowledge from a specific problem-domain, (2) construct a hierarchical knowledge base, and (3) perform a bi-directional inference. The causal knowledge base built by FCM can be described as a matrix form, guaranteeing mathematically compact operation compared with a production (if–then) knowledge base. Based on the causal knowledge base, we can break down a given decision problem into a multi-leveled one. Then bi-directional (downward or upward) inference can be applied to the multi-leveled problem to find a more robust solution. We applied our method to a stock investment analysis problem which is typical of highly unstructured problems in OR/MS fields. © 1997 by John Wiley & Sons, Ltd.