The stochastic conditional duration model: a latent factor model for the analysis of financial durations

Bauwens, Luc;Veredas, David
(1999)

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  • Bauwens, Lucorcid-logoUCLouvain
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  • Veredas, David
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Abstract
A new model for the analysis of durations, the stochastic conditional duration (SCD) model, is introduced. This model is based of the assumption that the durations are generated by a latent stochastic factor that follows a first order autoregressive process. The latent factor is pertubed multiplicatively by an innovation distributed as aWeibull or gamma variable. The model can capture a wide range of shapes of hazard functions. The estimation of the parameters is performed by quasi-maximum likelihood, after transforming the original nonlinear model into a space state representation and using the Kalman filter. The model is applied to stock market price-durations, looking at the relation between price durations, volume, spread and trading intensity.
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Bauwens, L., & Veredas, D. (1999). The stochastic conditional duration model: a latent factor model for the analysis of financial durations (CORE Discussion Papers 1999/58). https://hdl.handle.net/2078.5/128159