Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks
This paper concerns the properties of the Quasi Maximum Likelihood Estimator (QMLE) of the Logarithmic Autoregressive Conditional Duration (Log-ACD) model. Proofs of consistency and asymptotic normality of QMLE for the Log-ACD model with log-normal density are presented. This is an important issue as the Log-ACD is used widely for testing various market microstructure models and effects. Knowledge of the distribution of the QMLE is crucial for purposes of valid inference and diagnostic checking. The theoretical results developed in the paper are evaluated using Monte Carlo experiments. The experimental results also provide insights into the finite sample properties of the Log-ACD model under different distributional assumptions. Finally, this paper presents two extensions to the Log-ACD model to accommodate asymmetric effects. The usefulness of these novel models will be evaluated empirically using data from Australian stocks.
Year of publication: |
2008
|
---|---|
Authors: | Allen, David ; Chan, Felix ; McAleer, Michael ; Peiris, Shelton |
Published in: |
Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 147.2008, 1, p. 163-185
|
Publisher: |
Elsevier |
Keywords: | Conditional duration Asymmetry ACD Log-ACD Monte Carlo simulation |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Finite sample properties of the QMLE for the Log-ACD model : application to Australian stocks
Allen, David E., (2008)
-
Finite sample properties of the QMLE for the log-ACD model : application to Australian stocks
Allen, David E., (2006)
-
Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks
Allen, David, (2008)
- More ...