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Forecasting the variance and return of Mexican financial series with symmetric GARCH models

Author

Listed:
  • Fátima Irina VILLALBA PADILLA

    (Escuela Superior de Economia IPN, Mexico)

  • Miguel FLORES-ORTEGA

    (Escuela Superior de Economia IPN, Mexico)

Abstract

The present research shows the application of the generalized autoregresive conditional heteroskedasticity models (GARCH) in order to forecast the variance and return of the IPC, the EMBI, the weighted-average government funding rate, the fix exchange rate and the Mexican oil reference, as important tools for investment decisions. Forecasts in-sample and out-of-sample are performed. The covered period involves from 2005 to 2011.

Suggested Citation

  • Fátima Irina VILLALBA PADILLA & Miguel FLORES-ORTEGA, 2013. "Forecasting the variance and return of Mexican financial series with symmetric GARCH models," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(580)), pages 61-82, March.
    • Handle: RePEc:agr:journl:v:xx:y:2013:i:3(580):p:61-82
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    Citations

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    Cited by:

    1. Raúl De Jesús Gutiérrez & Reyna Vergara González & Miguel A. Díaz Carreño, 2015. "Predicción de la volatilidad en el mercado del petróleo mexicano ante la presencia de efectos asimétricos," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, March.
    2. Caporale, Guglielmo Maria & Carcel, Hector & Gil-Alana, Luis, 2018. "The EMBI in Latin America: Fractional integration, non-linearities and breaks," Finance Research Letters, Elsevier, vol. 24(C), pages 34-41.
    3. Tristan Nguyen & Thi Thanh Mai Bui, 2018. "Modeling the Volatility and Forecasting the Stock Price of the German Stock Index (DAX30)," International Journal of Economics and Financial Research, Academic Research Publishing Group, vol. 4(4), pages 72-92, 04-2018.

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