Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial data

Saulo, H, Leão, J, Leiva, V et al. (1 more author) (2019) Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial data. Statistical Papers, 60 (5). pp. 1605-1629. ISSN 0932-5026

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Copyright, Publisher and Additional Information: © Springer-Verlag Berlin Heidelberg 2017. This is a post-peer-review, pre-copyedit version of an article published in Statistical Papers. The final authenticated version is available online at: https://doi.org/10.1007/s00362-017-0888-6. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Big data; Birnbaum–Saunders distribution; Forecasting ability; Influence diagnostics; Likelihood-based methods; Monte Carlo simulation; R software
Dates:
  • Published: October 2019
  • Accepted: 8 February 2017
  • Published (online): 2 March 2017
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 10 Feb 2017 10:41
Last Modified: 16 Oct 2019 15:17
Status: Published
Publisher: Springer Verlag
Identification Number: https://doi.org/10.1007/s00362-017-0888-6

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