• Medientyp: E-Artikel
  • Titel: A general family of autoregressive conditional duration models applied to high-frequency financial data
  • Beteiligte: Cunha, Danúbia R. [VerfasserIn]; Vila, Roberto [VerfasserIn]; Saulo, Helton [VerfasserIn]; Fernandez, Rodrigo Nobre [VerfasserIn]
  • Erschienen: Basel: MDPI, 2020
  • Sprache: Englisch
  • DOI: https://doi.org/10.3390/jrfm13030045
  • ISSN: 1911-8074
  • Schlagwörter: Box-Cox transformation ; ACD models ; generalized Birnbaum-Saunders distributions ; high-frequency financial data ; goodness-of-fit ; C53 ; C52 ; C51
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  • Beschreibung: 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 lambda 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.
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Namensnennung (CC BY)