Template-Type: ReDIF-Paper 1.0
Author-Name:  Adriana Bruscato Bortoluzzo
Author-Name-First: Adriana Bruscato
Author-Name-Last: Bortoluzzo
Author-Name:  Pedro A. Morettin
Author-Name-First: Pedro A.
Author-Name-Last: Morettin
Author-Name: Clelia M. C. Toloi
Author-Name-First: Clelia M. C.
Author-Name-Last: Toloi
Title: Time-Varying Autoregressive Conditional Duration Model
Abstract:  The main goal of this work is to generalize the autoregressive conditional duration (ACD) model applied to times between trades to the case of time-varying parameters. The use of wavelets allows that parameters vary through time and makes possible the modeling of non-stationary processes without preliminary data transformations.
The time-varying ACD model estimation was done by maximum likelihood with standard exponential distributed errors. The properties of the estimators were assessed via bootstrap.
We present a simulation exercise for a non-stationary process and an empirical application to a real series, namely the TELEMAR stock. Diagnostic and goodness of fit analysis suggest that time-varying ACD model simultaneously modelled the dependence between durations, intra-day seasonality and volatility.
Length:  22 pages
Creation-Date:  2009
Order-URL: https://repositorio.insper.edu.br/handle/11224/5758
File-URL: https://repositorio.insper.edu.br/handle/11224/5758
File-Format: text/html
File-Function: Full text
Number: 059
Handle: RePEc:aap:wpaper:059