A stock market forecasting support system based on fuzzy logic

Interviews with portfolio managers suggests that a stock market forecasting support system should have a general model, which the users can refine to match their personal needs and beliefs The model should offer interactive problem solving and justification of its conclusion, and be able to process expert knowledge which is typically uncertain and vague. Fuzzy logic is capable of storing uncertain and vague knowledge and providing a declarative, interactive and explanatory prediction. Potential benefits of a fuzzy logic forecast support are: better decision making due to the model-based approach, knowledge management, and knowledge accumulation. The paper presents a general approach to stock market prediction and introduces an architecture of a fuzzy logic forecasting support system. The system architecture supports easy modification of the knowledge base, facilities to trace problem solving, and simulation. Evaluation of the implementation demonstrates the system's functionality.<
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