MIDAS volatility forecast performance under market stress: Evidence from emerging stock markets
AbstractThis paper evaluates weekly out-of-sample volatility forecast performance of univariate Mixed Data Sampling (MIDAS) model compared to the benchmark model of GARCH(1,1) for ten emerging stock markets. The results show that the MIDAS model offers a statistically better forecasting precision during the recent financially turbulent era, based on the test suggested by West (2006). For the tranquil period, however, the MIDAS model cannot produce a statistically better weekly volatility forecast.
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Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 117 (2012)
Issue (Month): 2 ()
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Web page: http://www.elsevier.com/locate/ecolet
Mixed Data Sampling regression model; Conditional volatility forecasting; Emerging markets;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
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