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Long-term effects of the asymmetry and persistence of the prediction of volatility: Evidence for the equity markets of Latin America

Author

Listed:
  • Raúl de Jesús Gutiérrez

    (Universidad Autónoma del Estado de México, México)

  • Edgar Ortiz

    (Universidad Nacional Autónoma de México, México)

  • Oswaldo García Salgado

    (Universidad Autónoma del Estado de México, México)

Abstract

This article proposes an extension to the CGARCH model in order to capture the characteristics of short-run and long-run asymmetry and persistence, and examine their effects in modeling and forecasting the conditional volatility of the stock markets from the region of Latin America during the period from 2 January 1992 to 31 December 2014. In the sample analysis, the estimation results of the CGARCH-class model family reveal the presence of short-run and long-run significant asymmetric effects and long-run persistency in the structure of stock price return volatility. The empirical results also show that the use of symmetric and asymmetric loss functions and the statistical test of Hansen (2005) are sound alternatives for evaluating the predictive ability of the asymmetric CGARCH models. In addition, the inclusion of long-run asymmetry and long-run persistency in the variance equation improves significantly the out of sample volatility forecasts for emerging stock markets of Argentina and Mexico.

Suggested Citation

  • Raúl de Jesús Gutiérrez & Edgar Ortiz & Oswaldo García Salgado, 2017. "Long-term effects of the asymmetry and persistence of the prediction of volatility: Evidence for the equity markets of Latin America," Contaduría y Administración, Accounting and Management, vol. 62(4), pages 1081-1099, Octubre-D.
    • Handle: RePEc:nax:conyad:v:62:y:2017:i:4:p:1081-1099
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Asymmetric volatility; Emerging stock markets; Symmetric and asymmetric loss functions; Superior predictive ability test;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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