A Dynamic Semiparametric Proportional Hazard Model

U of Copenhagen Finance Working Paper No. 2006/05

34 Pages Posted: 16 Nov 2006

See all articles by Frank Gerhard

Frank Gerhard

Barclays Investment Bank

Nikolaus Hautsch

University of Vienna - Department of Statistics and Operations Research

Multiple version iconThere are 2 versions of this paper

Date Written: November 2006

Abstract

This paper proposes a dynamic proportional hazard (PH) model with non-specified baseline hazard for the modelling of autoregressive duration processes. A categorization of the durations allows us to reformulate the PH model as an ordered response model based on extreme value distributed errors. In order to capture persistent serial dependence in the duration process, we extend the model by an observation driven ARMA dynamic based on generalized errors. We illustrate the maximum likelihood estimation of both the model parameters and discrete points of the underlying unspecified baseline survivor function. The dynamic properties of the model as well as an assessment of the estimation quality is investigated in a Monte Carlo study. It is illustrated that the model is a useful approach to estimate conditional failure probabilities based on (persistent) serial dependent duration data which might be subject to censoring structures. In an empirical study based on financial transaction data we present an application of the model to estimate conditional asset price change probabilities. Evaluating the forecasting properties of the model, it is shown that the proposed approach is a promising competitor to well-established ACD type models.

Keywords: autoregressive duration models, dynamic ordered response models, generalized residuals, censoring

JEL Classification: C22, C25, C41, G14

Suggested Citation

Gerhard, Frank and Hautsch, Nikolaus, A Dynamic Semiparametric Proportional Hazard Model (November 2006). U of Copenhagen Finance Working Paper No. 2006/05, Available at SSRN: https://ssrn.com/abstract=945337 or http://dx.doi.org/10.2139/ssrn.945337

Frank Gerhard

Barclays Investment Bank ( email )

5 The North Colonnade
London, Canary Wharf E14 4BB
United Kingdom

Nikolaus Hautsch (Contact Author)

University of Vienna - Department of Statistics and Operations Research ( email )

Kolingasse 14
Vienna, A-1090
Austria

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