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Usefulness of Artificial Neural Networks for Predicting Financial and Economic Crisis

Author

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  • Mioara CHIRITA

    (Faculty of Economics and Business Administration, Dunarea de Jos University of Galati, Romania)

Abstract

The objective of the present study is to explore the issue of the forecasting of economic crisis using the neural network. The subject is of great importance in the economy, more so as that most countries affected by crisis, declared at the end of 2010, the economic growth but the crisis paralyzed the financial world over the past three years. Neural network techniques have been frequently applied in order to predict problems like economic forecasting. The results show that creating a model using the neural networks might be a powerful tool and could be applied to prevent economic crises

Suggested Citation

  • Mioara CHIRITA, 2012. "Usefulness of Artificial Neural Networks for Predicting Financial and Economic Crisis," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 61-66.
    • Handle: RePEc:ddj:fseeai:y:2012:i:2:p:61-66
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    File URL: http://www.ann.ugal.ro/eco/Doc2012.2/Mioara_Chirita.pdf
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    References listed on IDEAS

    as
    1. Hill, Tim & Marquez, Leorey & O'Connor, Marcus & Remus, William, 1994. "Artificial neural network models for forecasting and decision making," International Journal of Forecasting, Elsevier, vol. 10(1), pages 5-15, June.
    2. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
    3. Fioramanti, Marco, 2008. "Predicting sovereign debt crises using artificial neural networks: A comparative approach," Journal of Financial Stability, Elsevier, vol. 4(2), pages 149-164, June.
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    Cited by:

    1. Seyma Caliskan Cavdar & Alev Dilek Aydin, 2015. "An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures," JRFM, MDPI, vol. 8(3), pages 1-18, August.

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    More about this item

    Keywords

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    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G01 - Financial Economics - - General - - - Financial Crises
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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