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Reducción del ruido y predicción de series temporales de alta frecuencia mediante sistemas dinámicos no lineales y técnicas neurales

Author

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  • Diego G. Fernández

    (Banco Central del Uruguay)

Abstract

The analysis of economic phenomena from direct observation can lead to incorrect conclusions because the data surveyed as an expression of the magnitude studied is often contaminated by multiple factors that introduce noise and prevent clearly perception of the underlying evolutionary patterns that seeks to analyze. It is essential to decompose the magnitude observed in terms of variations not directly observable. To do this methods in nonlinear dynamical systems are studied to remove noise that contaminates high frequency time series with eventual chaotic behavior

Suggested Citation

  • Diego G. Fernández, 2014. "Reducción del ruido y predicción de series temporales de alta frecuencia mediante sistemas dinámicos no lineales y técnicas neurales," Documentos de trabajo 2014001, Banco Central del Uruguay.
    • Handle: RePEc:bku:doctra:2014001
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    File URL: https://www.bcu.gub.uy/Estadisticas-e-Indicadores/Documentos%20de%20Trabajo/1.2014.pdf
    File Function: First version, 2014
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    More about this item

    Keywords

    noise reduction; prediction; dynamic systems; nonlinear; high frequency;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C65 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Miscellaneous Mathematical Tools

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