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The Birnbaum–Saunders autoregressive conditional duration model

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  • Bhatti, Chad R.

Abstract

In this paper we introduce the Birnbaum–Saunders autoregressive conditional duration (BS-ACD) model as an alternative to the existing ACD models which allow a unimodal hazard function. The BS-ACD model is the first ACD model to integrate the concept of conditional quantile estimation into an ACD model by specifying the time-varying model dynamics in terms of the conditional median duration, instead of the conditional mean duration. In the first half of this paper we illustrate how the BS-ACD model relates to the traditional ACD model, and in the second half we discuss the assessment of goodness-of-fit for ACD models in general. In order to facilitate both of these points, we explicitly illustrate the similarities and differences between the BS-ACD model and the Generalized Gamma ACD (GG-ACD) model by comparing and contrasting their formulation, estimation, and results from fitting both models to samples for six NYSE securities.

Suggested Citation

  • Bhatti, Chad R., 2010. "The Birnbaum–Saunders autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2062-2078.
  • Handle: RePEc:eee:matcom:v:80:y:2010:i:10:p:2062-2078
    DOI: 10.1016/j.matcom.2010.01.011
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    References listed on IDEAS

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    Cited by:

    1. Lemonte, Artur J. & Ferrari, Silvia L.P., 2011. "Testing hypotheses in the Birnbaum-Saunders distribution under type-II censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(7), pages 2388-2399, July.
    2. Pooi AH-HIN & Ng KOK-HAUR & Soo HUEI-CHING, 2016. "Modelling and Forecasting with Financial Duration Data Using Non-linear Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 79-92.
    3. Rafael Farias & Artur Lemonte, 2011. "Bayesian inference for the Birnbaum–Saunders nonlinear regression model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 423-438, November.
    4. Marchant, Carolina & Bertin, Karine & Leiva, Víctor & Saulo, Helton, 2013. "Generalized Birnbaum–Saunders kernel density estimators and an analysis of financial data," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 1-15.
    5. repec:eee:csdana:v:56:y:2012:i:12:p:3887-3897 is not listed on IDEAS

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