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A General Family of Autoregressive Conditional Duration Models Applied to High-Frequency Financial Data

Author

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  • Danúbia R. Cunha

    (Department of Economics, Catholic University of Brasilia, 71966-700 Brasilia, Brazil)

  • Roberto Vila

    (Department of Statistics, University of Brasilia, 70910-900 Brasilia, Brazil)

  • Helton Saulo

    (Department of Statistics, University of Brasilia, 70910-900 Brasilia, Brazil)

  • Rodrigo N. Fernandez

    (Department of Economics, Federal University of Pelotas, 96010-610 Pelotas, Brazil)

Abstract

In this paper, we propose a general family of Birnbaum–Saunders autoregressive conditional duration (BS-ACD) models based on generalized Birnbaum–Saunders (GBS) distributions, denoted by GBS-ACD. We further generalize these GBS-ACD models by using a Box-Cox transformation with a shape parameter λ to the conditional median dynamics and an asymmetric response to shocks; this is denoted by GBS-AACD. We then carry out a Monte Carlo simulation study to evaluate the performance of the GBS-ACD models. Finally, an illustration of the proposed models is made by using New York stock exchange (NYSE) transaction data.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jjrfmx:v:13:y:2020:i:3:p:45-:d:327540
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    References listed on IDEAS

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