We investigate several families of univariate GARCH-type specifications in which both the unconditional dependence structure and the model coefficients evolve according to an unobserved Markov regime process. For these models we establish key probabilistic and inferential properties, and we develop a practical estimation strategy based on a suitably adapted EM-type procedure. A set of numerical experiments illustrates the accuracy and robustness of the resulting nonlinear inference.
Statistical Properties and Financial Applications of Selected Classes of Markov-Switching GARCH-Type Models / Cavicchioli, M., Cheng, J.. - (2026), pp. 519-525. (SIS-FENStatS 2026 Roma, Italy 22-25 June 2026) [10.1007/978-3-032-30877-1_84].
Statistical Properties and Financial Applications of Selected Classes of Markov-Switching GARCH-Type Models
Cavicchioli, Maddalena;Cheng, Jie
2026
Abstract
We investigate several families of univariate GARCH-type specifications in which both the unconditional dependence structure and the model coefficients evolve according to an unobserved Markov regime process. For these models we establish key probabilistic and inferential properties, and we develop a practical estimation strategy based on a suitably adapted EM-type procedure. A set of numerical experiments illustrates the accuracy and robustness of the resulting nonlinear inference.
Pubblicazioni consigliate
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris
