An Alternative Nonparametric Specification Test in Autoregressive Conditional Duration Models

41 Pages Posted: 16 Aug 2012

See all articles by Patrick Saart

Patrick Saart

University of Canterbury

Jiti Gao

Monash University - Department of Econometrics & Business Statistics

Date Written: August 16, 2012

Abstract

This paper introduces an alternative testing procedure to test the distribution of the error term in the Autoregressive Conditional Duration (ACD) class of models. In these models, the error term is normally interpreted as the standardized duration by which its probability distribution may have an important impact on the shape of the conditional intensity process of the financial duration in question.This paper illustrates that the testing procedure developed is applicable to various ACD types of models in the literature. Furthermore, when applied to parametric models, such as the Exponential ACD (EACD) and the weibull ACD (WACD), the test can be used as a diagnostic test of the accuracy of the required distributional assumption. Moreover, the hypothetical structure of the test is useful to the specification testing of a number of financial market microstructure hypotheses, especially those related to the information asymmetry in finance. Finally, the testing procedure introduced in this paper differs in many ways from those discussed in existing literatures. This paper shows theoretically and experimentally the statistical validity of the testing procedure, while demonstrating its usefulness and practicality using datasets from New York and Australia Stock Exchange.

Keywords: autoregressive conditional duration model, dependent point process, financial time series, hazard rate, high frequency data, semiparametric regression

JEL Classification: C14, C41, F31

Suggested Citation

Saart, Patrick and Gao, Jiti, An Alternative Nonparametric Specification Test in Autoregressive Conditional Duration Models (August 16, 2012). Available at SSRN: https://ssrn.com/abstract=2130454 or http://dx.doi.org/10.2139/ssrn.2130454

Patrick Saart (Contact Author)

University of Canterbury ( email )

Ilam Road
Christchurch 8140
New Zealand

Jiti Gao

Monash University - Department of Econometrics & Business Statistics ( email )

900 Dandenong Road
Caulfield East, Victoria 3145
Australia
61399031675 (Phone)
61399032007 (Fax)

HOME PAGE: http://www.jitigao.com

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