On log-symmetric duration models applied to high frequency financial data
Helton Saulo () and
Jeremias LeÃ£o ()
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Helton Saulo: Department of Statistics, University of BrasÃlia, BrasÃlia, Brazil
Jeremias LeÃ£o: Department of Statistics, Federal University of Amazonas, Brazil
Economics Bulletin, 2017, vol. 37, issue 2, 1089-1097
This paper deals with a new generalization of autoregressive conditional duration (ACD) models. In special, we propose a new family of ACD models based on a class of log-symmetric distributions. In this new class, it is possible to model both median and skewness of the duration time distribution. We discuss maximum likelihood estimation of the model parameters. For illustrative purposes, we analyze a high frequency financial data set from the German DAX in 2016.
Keywords: Log-symmetric distributions; likelihood method; high frequency data; autoregressive conditional (search for similar items in EconPapers)
JEL-codes: C5 C4 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ebl:ecbull:eb-17-00030
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