Abstract
This chapter introduces the continuous GARCH models, namely COGARCH(p, q). These models are a generalization of the conditional heteroscedasticity GARCH time series models where the time is continuous and the innovation follows a Lévy process. Simulation and inference for this model are considered as well as the fit of COGARCH to real data. Full R code for completing the above analyses with yuima package is provided.
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Iacus, S.M., Yoshida, N. (2018). COGARCH Models. In: Simulation and Inference for Stochastic Processes with YUIMA. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-55569-0_7
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DOI: https://doi.org/10.1007/978-3-319-55569-0_7
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Publisher Name: Springer, Cham
Print ISBN: 978-3-319-55567-6
Online ISBN: 978-3-319-55569-0
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