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

Luc Bauwens and David Veredas

No 1999058, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

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.

Keywords: Duration; High frequency data; Market microstucture; Factor model. (search for similar items in EconPapers)
JEL-codes: C10 C41 G10 (search for similar items in EconPapers)
Date: 1999-11-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (28)

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Related works:
Working Paper: The stochastic conditional duration model: a latent factor model for the analysis of financial durations (2004)
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