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A range-based GARCH model for forecasting financial volatility

Author

Listed:
  • Dennis S. Mapa

    () (University of the Philippines School of Statistics, University of the Philippines Diliman, Quezon City)

Abstract

A new variant of the ARCH class of models for forecasting the conditional variance, to be called the Generalized AutoRegressive Conditional Heteroskedasticity Parkinson Range (GARCH-PARK-R) model, is proposed. The GARCH-PARK-R model, utilizing the extreme values, is a good alternative to the “realized volatility” model which requires a large amount of intra-daily data that remain relatively costly and are not readily available. The estimates of the GARCH-PARK-R model are derived using the Quasi-Maximum Likelihood Estimation (QMLE). The results suggest that the GARCHPARK- R model is a good middle ground between intra-daily models, such as the realized volatility, and inter-daily models, such as the ARCH class. The forecasting performance of the models is evaluated using the daily Philippine Peso-U.S. Dollar exchange rate from January 1997 to December 2003.

Suggested Citation

  • Dennis S. Mapa, 2003. "A range-based GARCH model for forecasting financial volatility," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 40(2), pages 73-90, December.
  • Handle: RePEc:phs:prejrn:v:40:y:2003:i:2:p:73-90
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    File URL: http://pre.econ.upd.edu.ph/index.php/pre/article/view/22/567
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    Cited by:

    1. Nikkin L. Beronilla & Dennis S. Mapa, 2008. "Range-based models in estimating value-at-risk (VaR)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 45(2), pages 87-99, December.
    2. Tomasz Skoczylas, 2013. "Modelowanie i prognozowanie zmienności przy użyciu modeli opartych o zakres wahań," Ekonomia journal, Faculty of Economic Sciences, University of Warsaw, vol. 35.

    More about this item

    Keywords

    Volatility; GARCH-PARK-R; QMLE;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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