Title

Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks

Document Type

Journal Article

Publisher

Elsevier BV, North-Holland

Faculty

Business and Law

School

Accounting, Finance and Economics

RAS ID

6259

Comments

This article was originally published as: Allen, D. E., Chan, F., McAleer, M., & Peiris, S. (2008). Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks. Journal of Econometrics, 147 (1), 163-185. Original article available here

Abstract

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.

DOI

10.1016/j.jeconom.2008.09.020

 

Link to publisher version (DOI)

10.1016/j.jeconom.2008.09.020