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Redes neuronales artificiales en las ciencias económicas

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  • Viviana María Oquendo Patiño

    ()

Abstract

Este documento proporciona un acercamiento teórico a los Sistemas de Redes Neuronales Artificiales, así como a los software en los que se pueden realizar estás implementaciones y mostrar la manera en que esta metodología puede constituirse como una método para predecir series de tiempo económicas. Con el fin de contrastar los resultados obtenidos, se ajusta un modelo ARIMA, que corresponde a una de las metodologías convencionalmente utilizadas en la ciencia económica. La aplicación de estos procesos es realizada sobre la Tasa Representativa del Mercado (TRM) con el apoyo del software R-Project resaltando una aproximación a los resultados que se pueden obtener con esta forma de inteligencia artificial.

Suggested Citation

  • Viviana María Oquendo Patiño, 2012. "Redes neuronales artificiales en las ciencias económicas," ECONOGRAFOS - ESCUELA DE ECONOMÍA 009938, UN - RCE - CID.
  • Handle: RePEc:col:000176:009938
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    File URL: http://www.fce.unal.edu.co/publicaciones/index.php?option=com_content&view=article&id=168:20-redes-neuronales-artificiales-en-las-ciencias-economicas&catid=44:econografos-escuela-de-economia
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    More about this item

    Keywords

    Artificial Neural Network Systems; ARIMA; TRM.;

    JEL classification:

    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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