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A Smooth Transition Autoregressive Conditional Duration Model

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  • Chiang Min-Hsien

    (National Cheng Kung University)

Abstract

This study presents a novel model for analyzing duration data, called the smooth transition autoregressive conditional duration model of price and duration, which considers past price changes and durations. The model enables the process of the conditional expected duration to switch in a smooth transition way, broadening the autoregressive conditional duration (ACD) model in Engle and Russell (1998). The model is applied to empirical data, and estimation results indicate that the process of the expected duration is nonlinear. The expected trade duration behavior on the market opening is affected by past trade durations, while the expected trade duration behavior during the trading hours is affected by past price changes and trade durations. Expected trade durations are much more persistent in the upward market compared to the downward market. Shocks to trade durations are more persistent on the market opening and gradually decrease in the downward market.

Suggested Citation

  • Chiang Min-Hsien, 2007. "A Smooth Transition Autoregressive Conditional Duration Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 11(1), pages 108-144, March.
    • Handle: RePEc:bpj:sndecm:v:11:y:2007:i:1:n:5
    DOI: 10.2202/1558-3708.1313
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    Cited by:

    1. Bhatti, Chad R., 2009. "On the interday homogeneity in the intraday rate of trading," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2250-2257.
    2. Bhatti, Chad R., 2009. "Intraday trade and quote dynamics: A Cox regression analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(7), pages 2240-2249.
    3. Helton Saulo & Jeremias Leão & Víctor Leiva & Robert G. Aykroyd, 2019. "Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial data," Statistical Papers, Springer, vol. 60(5), pages 1605-1629, October.
    4. Saulo, Helton & Balakrishnan, Narayanaswamy & Vila, Roberto, 2023. "On a quantile autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 425-448.
    5. Danúbia R. Cunha & Roberto Vila & Helton Saulo & Rodrigo N. Fernandez, 2020. "A General Family of Autoregressive Conditional Duration Models Applied to High-Frequency Financial Data," JRFM, MDPI, vol. 13(3), pages 1-20, March.

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