Abstract
Continuous-time GARCH (COGARCH) processes are one of the influential and successful models in financial data analysis. In contrast to such stationary process, in this paper we study a class of COGARCH processes driven by semi-Lévy process (SL-COGARCH) that has periodically correlated (PC) increments. Under sufficient conditions the strictly periodically stationarity of the state and volatility processes are shown. We verify that the increments with constant length of the SL-COGARCH process constitute a discrete-time PC process. To justify this property, we use simulations of the SL-COGARCH(1,3) process and evaluate its increments. Then we provide the sample spectral coherence test to show the PC behavior of this discrete-time process. We apply the SL-COGARCH(2,2) process to the Dow Jones Industrial Average indices and show that this model provides better prediction of the squared log returns in compare to the retrieved Lévy driven COGARCH method.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Physica A: Statistical Mechanics and its Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
