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A Semiparametric Conditional Duration Model

Author

Listed:
  • Aman Ullah

    (Department of Economics, University of California Riverside)

  • Mardi Dungey

    (University of Tasmania, Australia)

  • Xiangdong Long

    (Bank of Communications Schroder Fund Management Co. Ltd)

  • Yun Wang

    (University of International Business and Economics, China)

Abstract

We propose a new semiparametric autoregressive duration (SACD) model, which incorporates the parametric and nonparametric estimators of the conditional duration in a multiplicative way. Asymptotic properties for this combined estimator are presented. The empirical application to the transaction duration of the US 2-Year Treasury note shows the outperformance of our SACD models over parametric ACD models.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Aman Ullah & Mardi Dungey & Xiangdong Long & Yun Wang, 2014. "A Semiparametric Conditional Duration Model," Working Papers 201408, University of California at Riverside, Department of Economics.
  • Handle: RePEc:ucr:wpaper:201408
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    References listed on IDEAS

    as
    1. Bauwens, Luc & Giot, Pierre & Grammig, Joachim & Veredas, David, 2004. "A comparison of financial duration models via density forecasts," International Journal of Forecasting, Elsevier, vol. 20(4), pages 589-609.
    2. repec:bla:jecsur:v:22:y:2008:i:4:p:711-751 is not listed on IDEAS
    3. Luc Bauwens & Pierre Giot, 2000. "The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks," Annals of Economics and Statistics, GENES, issue 60, pages 117-149.
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    5. Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, vol. 3(1), pages 16-38.
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    7. Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
    8. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Modelling financial high frequency data using point processes," LIDAM Discussion Papers CORE 2006080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    More about this item

    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G0 - Financial Economics - - General

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