The stochastic conditional duration model: a latent factor model for the analysis of financial durations
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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|Date of creation:||2004|
|Date of revision:|
|Publication status:||Published in: Journal of econometrics (2004) v.119 n° 2,p.381-412|
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