Abstract
The rough set theory is a useful tool for decision analysis. It allows a well structured procedure to organize quantitative and qualitative information. Most applications have been directed to problems characterized by “granularity” of the representation. Stock selection typically deals with large quantitative data sets. Finance theory describes assets in terms of their relative position within the stock market. Availability of long time series and computation technology have been powerful factors towards a full formalization of portfolio selection procedures. Recent empirical studies, meaningfully called “behavioural finance”, support an alternative description of the financial world. In this view, unexplainable anomalies for financial economics become effects of some psychological bias. Our rough set approach to stock selection is linked with the last mentioned researches. Our purpose is to show the practical relevance of organized information in this field. Results confirm the efficiency of rough set analysis as learning tool for the investor, although it cannot replace traditional methodology.
Partial financial support from Italian University and Scientific Research Ministry (M.U.R.S.T.) is acknowledged.
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© 1996 Physica-Verlag Heidelberg
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Greco, S., Lo Cascio, S., Matarazzo, B. (1996). Rough Set Approach to Stock Selection: an Application to the Italian Market. In: Bertocchi, M., Cavalli, E., Komlósi, S. (eds) Modelling Techniques for Financial Markets and Bank Management. Contributions to Management Science. Physica-Verlag HD. https://doi.org/10.1007/978-3-642-51730-3_12
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DOI: https://doi.org/10.1007/978-3-642-51730-3_12
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-0928-2
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