Abstract
This paper presents an intelligent decision support system for financial portfolio management. An adaptive business intelligence approach combines optimization, forecasting and adaptation with application specific financial information processing and quantitative investment paradigms.
The methodology involves constructing a ranking of stocks by strength of a buy or sell recommendation which is inferred using an adapting forecasting model that considers a range of factors. These include company balance sheet information, market price and trading volume as well as the wider economy. The system adjusts its prediction model dynamically as market conditions change. An evolving fuzzy rule base mechanism encodes a model of relationships between model factors and a recommendation to buy, sell or hold securities.
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Ghandar, A., Michalewicz, Z., Zurbruegg, R. (2009). Intelligent Decision Support: A Fuzzy Stock Ranking System. In: Marciniak, M., Mykowiecka, A. (eds) Aspects of Natural Language Processing. Lecture Notes in Computer Science, vol 5070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04735-0_16
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DOI: https://doi.org/10.1007/978-3-642-04735-0_16
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