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Modelos de memoria larga para series económicas y financieras

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Abstract

This paper provides a review of time series models with long memory in the mean and conditional variance, with special attention to Fractionally Integrated ARMA processes (ARFIMA) and fractionally integrated GARCH and SV processes. Their more important properties are reviewed and its application to model economic and .nancial time series is discussed. The main estimation methods and tests proposed in the literature for the long memory property are also reviewed. Finally, this paper reviews the main results on prediction of future values of long memory time series.

Suggested Citation

  • Ana Pérez & Esther Ruiz, 2002. "Modelos de memoria larga para series económicas y financieras," Investigaciones Economicas, Fundación SEPI, vol. 26(3), pages 395-445, September.
    • Handle: RePEc:iec:inveco:v:26:y:2002:i:3:p:395-445
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    Cited by:

    1. Sylvain Prado, 2011. "Free lunch in the oil market: a note on Long Memory," EconomiX Working Papers 2011-23, University of Paris Nanterre, EconomiX.
    2. Ochoa García, Libardo, 2001. "Alianza para la Exportación entre Pequeños Agricultores Pobres en Colombia," IDB Publications (Working Papers) 1164, Inter-American Development Bank.
    3. Libardo Ochoa García, 2001. "Alianza para la Exportación entre Pequeños Agricultores Pobres en Colombia," IDB Publications (Working Papers) 9638, Inter-American Development Bank.
    4. Fernando Zarzosa Valdivia, 2020. "Inflation Dynamics in the ABC (Argentina, Brazil and Chile) countries," Ensayos de Política Económica, Departamento de Investigación Francisco Valsecchi, Facultad de Ciencias Económicas, Pontificia Universidad Católica Argentina., vol. 3(2), pages 77-99, Octubre.

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    Keywords

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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