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Rough Sets Approach to Economic Modeling: Unlocking Knowledge in Financial Data

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Book cover Economic Modeling Using Artificial Intelligence Methods

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

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Abstract

Building models to accurately forecast financial markets has drawn the attention of economists, bankers, mathematicians and scientists alike. The financial markets are the foundation of every economy and there are many aspects that affect the direction, volume, price, and flow of traded stocks. The markets’ weakness to external and non-financial features as well as the ensuing volatility makes the development of a robust and accurate financial market forecasting model an interesting problem. In this chapter a rough set theory based forecasting model is applied to the financial markets to identify a set of reducts and possibly a set of trading rules based on trading data.

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Authors and Affiliations

  1. Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

    Tshilidzi Marwala

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Marwala, T. (2013). Rough Sets Approach to Economic Modeling: Unlocking Knowledge in Financial Data. In: Economic Modeling Using Artificial Intelligence Methods. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-4471-5010-7_6

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  • DOI: https://doi.org/10.1007/978-1-4471-5010-7_6

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  • Online ISBN: 978-1-4471-5010-7

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