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More aboutMSGARCH available athttp://keblu.github.io/MSGARCH/.

By usingMSGARCH you agree to the following rules:

1. You must citeArdia et al. (2019) in working papers and published papers that useMSGARCH.
2. You must place the following URL in a footnote to help others findMSGARCH:https://CRAN.R-project.org/package=MSGARCH.
3. You assume all risk for the use ofMSGARCH.

Ardia, D., Bluteau, K., Boudt, K., Catania, L., Trottier, D.-A. (2019).
Markov-switching GARCH models in R: The MSGARCH package.
Journal of Statistical Software, 91(4), 1-38.
https://doi.org/10.18637/jss.v091.i04

Ardia, D., Bluteau, K., Boudt, K., Catania, L. (2018).
Forecasting risk with Markov-switching GARCH models: A large-scale performance study
International Journal of Forecasting, 34(4), 733-747.
https://doi.org/10.1016/j.ijforecast.2018.05.004

Ardia, D., Bluteau, K., Ruede, M. (2019).
Regime changes in Bitcoin GARCH volatility dynamics.
Finance Research Letters, 29, 266-271.
https://doi.org/10.1016/j.frl.2018.08.009