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Rough sets: technical computer intelligence applied to financial market

Author

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  • Paulo Henrique Kaupa
  • Renato José Sassi

Abstract

Investments in stock markets has called the attention of new investors by providing larger financial returns when compared to traditional investments, such as fixed income. However, this is a type of investment with a high degree of risk to which the investor must select a portfolio of stocks that combine maximised profit with minimised risk. Thus, correctly identifying the trends in stock prices with the help of a technique is critical for this investor. Computer intelligence techniques can be applied in this identification such as the rough sets theory. The rough sets theory was proposed as a mathematical model for knowledge representation and treatment of uncertainty, and it has been used subsequently in the development of techniques for classification in machine learning. The objective of this work was to apply rough sets in the selection of stocks for investment in the São Paulo Stock Exchange. The experiments were carried out with historical data extracted from the São Paulo Stock Exchange and the portfolio returns were compared with the Ibovespa Index, used as a benchmark. The results obtained positively point out to the application of rough sets in selecting stock portfolios for investment in the stock exchange.

Suggested Citation

  • Paulo Henrique Kaupa & Renato José Sassi, 2017. "Rough sets: technical computer intelligence applied to financial market," International Journal of Business Innovation and Research, Inderscience Enterprises Ltd, vol. 13(1), pages 130-145.
    • Handle: RePEc:ids:ijbire:v:13:y:2017:i:1:p:130-145
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    Cited by:

    1. Haibei Chen & Xianglian Zhao, 2023. "Use intention of green financial security intelligence service based on UTAUT," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(10), pages 10709-10742, October.
    2. Pamucar, Dragan & Macura, Dragana & Tavana, Madjid & Božanić, Darko & Knežević, Nikola, 2022. "An integrated rough group multicriteria decision-making model for the ex-ante prioritization of infrastructure projects: The Serbian Railways case," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).

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