EconPapers    
Economics at your fingertips  
 

On log-symmetric duration models applied to high frequency financial data

Helton Saulo () and Jeremias Leão ()
Additional contact information
Helton Saulo: Department of Statistics, University of Brasília, Brasília, Brazil
Jeremias Leão: Department of Statistics, Federal University of Amazonas, Brazil

Economics Bulletin, 2017, vol. 37, issue 2, 1089-1097

Abstract: 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)
Date: 2017-05-14
References: View references in EconPapers View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link)
http://www.accessecon.com/Pubs/EB/2017/Volume37/EB-17-V37-I2-P95.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ebl:ecbull:eb-17-00030

Access Statistics for this article

More articles in Economics Bulletin from AccessEcon
Series data maintained by John P. Conley ().

 
Page updated 2017-09-29
Handle: RePEc:ebl:ecbull:eb-17-00030