Essays in the econometrics of dynamic duration models with application to tick by tick financial data
(2009)
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- Authors
- Supervisors
- Bauwens, Luc
- Abstract
- (en) This thesis organizes three contributions on the econometrics of duration in the context of high frequency financial data. We provide existence conditions and analytical expressions of the moments of Log-ACD models. We focus on the dispersion index and the autocorrelation function and compare them with those of ACD and SCD models We apply the effcient importance sampling (EIS) method for computing the high-dimensional integral required to evaluate the likelihood function of the stochastic conditional duration (SCD) model. We compare EIS-based ML estimation with QML estimation based on the Kalman filter. We find that EIS- ML estimation is more precise statistically, at a cost of an acceptable loss of quickness of computations. We illustrate this with simulated and real data. We show also that the EIS-ML method is easy to apply to extensions of the SCD model. We carry out a nonparametric analysis of financial durations. We make use of an existing algorithm to describe nonparametrically the dynamics of the process in terms of its lagged realizations and of a latent variable, its conditional mean. The devices needed to effectively apply the algorithm to our dataset are presented. We show that: on simulated data, the nonparametric procedure yields better estimates than the ones delivered by an incorrectly specified parametric method, while on a real dataset, the nonparametric analysis can convey information on the nature of the data generating process that may not be captured by the parametric specification.
- Affiliations
Citations
Galli, F. (2009). Essays in the econometrics of dynamic duration models with application to tick by tick financial data. https://hdl.handle.net/2078.5/132576