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

    137685_137685.pdf (343.5Kb)
    Access Status
    Open access
    Authors
    Allen, D.
    Chan, Felix
    McAleer, M.
    Peiris, S.
    Date
    2008
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Allen, David and Chan, Felix and McAleer, Michael and Peiris, Shelton. 2008. Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks. Journal of Econometrics. 147 (1): pp. 163-185.
    Source Title
    Journal of Econometrics
    DOI
    10.1016/j.jeconom.2008.09.020
    ISSN
    03044076
    Faculty
    Curtin Business School
    School of Economics and Finance
    Remarks

    The link to the journal’s home page is: http://www.elsevier.com/wps/find/journaldescription.cws_home/505575/description#description. Copyright © 2008 Elsevier B.V. All rights reserved

    URI
    http://hdl.handle.net/20.500.11937/34878
    Collection
    • Curtin Research Publications
    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.

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