Bivariate autoregressive conditional models: A new method for jointly modeling duration and number of transactions of irregularly spaced financial data

Autor:	Saulo, Helton, Pal, Suvra, Vila, Roberto
Rok vydání:	2023
Předmět:	Statistics - Applications 62F99 62M99 G.0 G.3
Druh dokumentu:	Working Paper
Popis:	In this paper, a new approach to bivariate modeling of autoregressive conditional duration (ACD) models is proposed. Specifically, we consider the joint modeling of durations and the number of transactions made during the spell. The proposed bivariate ACD model is based on log-symmetric distributions, which are useful for modeling strictly positive, asymmetric and light- and heavy-tailed data, such as transaction-level high-frequency financial data. A Monte Carlo simulation is performed for the assessment of the estimation method and the evaluation of a form of residuals. A real financial transactions data set is analyzed in order to illustrate the proposed method. Comment: 21 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2306.13764 Zobrazit plný text záznamu View this record from Arxiv