A range-based GARCH model for forecasting financial volatility
AbstractA 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.
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Bibliographic InfoArticle provided by University of the Philippines School of Economics and Philippine Economic Society in its journal Philippine Review of Economics.
Volume (Year): 40 (2003)
Issue (Month): 2 (December)
Volatility; GARCH-PARK-R; QMLE;
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- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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- 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.
- Mapa, Dennis & Beronilla, Nikkin, 2008. "Range-Based Models in Estimating Value-at-Risk (VaR)," MPRA Paper 21223, University Library of Munich, Germany.
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