Abstract
Level shifts confound the estimation of persistence. This paper shows analytically, in simulations, and using high-frequency stock price data that models for financial volatility that feature a separate source of randomness in the volatility equation are less susceptible to this effect. Such models include recently proposed time series models for realized volatility, as opposed to GARCH models for daily observations, which are highly sensitive to unknown shifts, as has been shown before.
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 callDisclaimer: 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.
