Abstract
In this paper we use an autoregressive conditional intensity approach to estimate local high-frequency volatility, and examine to what extent a large universe of market microstructure variables affects local volatility. Our findings support a sequential information arrival hypothesis on the high-frequency level since we show that contemporaneous trading volume is negatively, and lagged trading volume is positively related to local volatility. The use of a penalized likelihood method allows us to obtain a ranking in terms of the relative importance of all market microstructure variables considered. We find that, in a descending order, contemporaneous volume, bid-ask spread, absolute order imbalance, absolute order flow and absolute quote difference carry the most important information for local volatility modelling.
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 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.
