Abstract
We propose a structural model for durations between events and (a vector of) associated marks, using a multivariate Brownian motion. Successive passage times of one latent Brownian component relative to random boundaries define durations. The other, correlated, Brownian components generate the marks. Our model embeds the class of stochastic conditional (SCD) and autoregressive conditional (ACD) duration models, which impose testable restrictions on the relation between the conditional expectation and conditional volatility of durations. We strongly reject the SCD and ACD specifications for both a very liquid and less liquid NYSE-traded stock, and characterize causality relations between volatilities and durations.
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.
