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Título : A general family of autoregressive conditional duration models applied to high-frequency financial data
Autor : Cunha, Danúbia R.
Vila Gabriel, Roberto
Saulo, Helton
Fernandez, Rodrigo N.
Assunto:: Distribuições Birnbaum-Saunders
Modelos autorregressivos
Bolsa de valores
Fecha de publicación : 2020
Editorial : MDPI
Citación : CUNHA, Danúbia R. et al. A general family of autoregressive conditional duration models applied to high-frequency financial data. Journal of Risk and Financial Management, v.13, n. 3, 45, 2020. DOI: https://doi.org/10.3390/jrfm13030045. Disponível em: https://www.mdpi.com/1911-8074/13/3/45?type=check_update&version=2. Acesso em: 17 maio 2021.
Resumen : 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.
Licença:: Copyright: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
DOI: https://doi.org/10.3390/jrfm13030045
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