Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/239135 
Year of Publication: 
2020
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 13 [Issue:] 3 [Publisher:] MDPI [Place:] Basel [Year:] 2020 [Pages:] 1-20
Publisher: 
MDPI, Basel
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 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.
Subjects: 
ACD models
Box-Cox transformation
generalized Birnbaum-Saunders distributions
goodness-of-fit
high-frequency financial data
JEL: 
C51
C52
C53
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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