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- W4301461172 abstract "HYGARCH model is basically used to model long-range dependence in volatility. We propose Markov switch smooth-transition HYGARCH model, where the volatility in each state is a time-dependent convex combination of GARCH and FIGARCH. This model provides a flexible structure to capture different levels of volatilities and also short and long memory effects. The necessary and sufficient condition for the asymptotic stability is derived. Forecast of conditional variance is studied by using all past information through a parsimonious way. Bayesian estimations based on Gibbs sampling are provided. A simulation study has been given to evaluate the estimations and model stability. The competitive performance of the proposed model is shown by comparing it with the HYGARCH and smooth-transition HYGARCH models for some period of the textit{S}&textit{P}500 indices based on volatility and value-at-risk forecasts." @default.
- W4301461172 created "2022-10-05" @default.
- W4301461172 creator A5049317976 @default.
- W4301461172 creator A5071815179 @default.
- W4301461172 date "2018-03-02" @default.
- W4301461172 modified "2023-09-27" @default.
- W4301461172 title "Markov Switch Smooth Transition HYGARCH Model: Stability and Estimation" @default.
- W4301461172 doi "https://doi.org/10.48550/arxiv.1803.00739" @default.
- W4301461172 hasPublicationYear "2018" @default.
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