The stochastic conditional duration model: a latent factor model for the analysis of financial durations
AbstractA 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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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 1999058.
Date of creation: 01 Nov 1999
Date of revision:
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Duration; High frequency data; Market microstucture; Factor model.;
Other versions of this item:
- Luc Bauwens & David Veredas, 2004. "The stochastic conditional duration model: a latent factor model for the analysis of financial durations," ULB Institutional Repository 2013/136234, ULB -- Universite Libre de Bruxelles.
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
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