In this paper we examine the forecasting performance of five nonlinear GARCH(1,1) models. Four of these have recently been proposed in literature, while the fifth model is a new one. All five models allow for switching persistence of shocks, depending on the value and/or sign of recent returns. We consider the models for weekly data on 5 major stock markets. Our results indicate that all models improve upon the linear GARCH(1,1) model and that our new model sometimes yields favorable forecasting results.
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Paper provided by Erasmus University of Rotterdam - Econometric Institute in its series Papers with number
9819/a.
Find related papers by JEL classification: C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
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