Markov Switching Component ARCH Model: Stability and Forecasting

Autor:	Alemohammad, N., Rezakhah, S., Alizadeh, S. H.
Rok vydání:	2013
Předmět:	Statistics - Methodology 60J10 62M10 62F15
Druh dokumentu:	Working Paper
Popis:	This paper introduces an extension of the Markov switching GARCH model where the volatility in each state is a convex combination of two different GARCH components with time varying weights. This model has the dynamic behavior to capture the variants of shocks. The asymptotic behavior of the second moment is investigated and an appropriate upper bound for it is evaluated. The estimation of the parameters by using the Bayesian method via Gibbs sampling algorithm is studied. Finally we illustrate the efficiency of the model by simulation and empirical analysis. We show that this model provides a much better forecast of the volatility than the Markov switching GARCH model. Comment: 17 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1303.5525 Zobrazit plný text záznamu View this record from Arxiv