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FAST: Fundamental Analysis Support for Financial Statements. Using semantics for trading recommendations

Author

Listed:
  • Alejandro Rodríguez-González

    (Universidad Carlos III de Madrid)

  • Ricardo Colomo-Palacios

    (Universidad Carlos III de Madrid)

  • Fernando Guldris-Iglesias

    (Universidad Carlos III de Madrid)

  • Juan Miguel Gómez-Berbís

    (Universidad Carlos III de Madrid)

  • Angel García-Crespo

    (Universidad Carlos III de Madrid)

Abstract

Trading systems are tools to aid financial analysts in the investment process in companies. This process is highly complex because a big number of variables take part in it. Furthermore, huge sets of data must be taken into account to perform a grounded investment, making the process even more complicated. In this paper we present a real trading system that has been developed using semantic technologies. These cutting-edge technologies are very useful in this context because they enable the definition of schemes that can be used for storing financial information, which, in turn, can be easily accessed and queried. Additionally, the inference capabilities of the existing reasoning engines enable the generation of a set of rules supporting this investment analysis process.

Suggested Citation

  • Alejandro Rodríguez-González & Ricardo Colomo-Palacios & Fernando Guldris-Iglesias & Juan Miguel Gómez-Berbís & Angel García-Crespo, 2012. "FAST: Fundamental Analysis Support for Financial Statements. Using semantics for trading recommendations," Information Systems Frontiers, Springer, vol. 14(5), pages 999-1017, December.
    • Handle: RePEc:spr:infosf:v:14:y:2012:i:5:d:10.1007_s10796-011-9321-1
    DOI: 10.1007/s10796-011-9321-1
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    References listed on IDEAS

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    1. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1770, August.
    2. Standfield, Ken, 2005. "Intangible Finance Standards," Elsevier Monographs, Elsevier, edition 1, number 9780126635539.
    3. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    4. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    5. Abarbanell, JS & Bushee, BJ, 1997. "Fundamental analysis, future earnings, and stock prices," Journal of Accounting Research, Wiley Blackwell, vol. 35(1), pages 1-24.
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    Cited by:

    1. R. Ramesh & H. Raghav Rao, 2012. "Information systems frontiers editorial December 2012," Information Systems Frontiers, Springer, vol. 14(5), pages 963-965, December.
    2. Tripathi Manas & Kumar Saurabh & Inani Sarveshwar Kumar, 2021. "Exchange Rate Forecasting Using Ensemble Modeling for Better Policy Implications," Journal of Time Series Econometrics, De Gruyter, vol. 13(1), pages 43-71, January.

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