Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)

Arianna Agosto; Giuseppe Cavaliere; Dennis Kristensen; Anders Rahbek

doi:10.1016/j.jempfin.2016.02.007

Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)

Arianna Agosto, Giuseppe Cavaliere, Dennis Kristensen, Anders Rahbek

23 Citations (Scopus)

Abstract

We develop a class of Poisson autoregressive models with exogenous covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used in the analysis of the asymptotic properties of the maximum-likelihood estimators of the models. The PARX class of models is used to analyze the time series properties of monthly corporate defaults in the US in the period 1982–2011 using financial and economic variables as exogenous covariates. Results show that our model is able to capture the time series dynamics of corporate defaults well, including the well-known default counts clustering found in data. Moreover, we find that while in general current defaults do indeed affect the probability of other firms defaulting in the future, in recent years economic and financial factors at the macro level are capable to explain a large portion of the correlation of US firm defaults over time.

Original language	English
Journal	Journal of Empirical Finance
Volume	38
Issue number	Part B
Pages (from-to)	640–663
ISSN	0927-5398
DOIs	https://doi.org/10.1016/j.jempfin.2016.02.007
Publication status	Published - 1 Sept 2016

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title = "Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)",

abstract = "We develop a class of Poisson autoregressive models with exogenous covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used in the analysis of the asymptotic properties of the maximum-likelihood estimators of the models. The PARX class of models is used to analyze the time series properties of monthly corporate defaults in the US in the period 1982–2011 using financial and economic variables as exogenous covariates. Results show that our model is able to capture the time series dynamics of corporate defaults well, including the well-known default counts clustering found in data. Moreover, we find that while in general current defaults do indeed affect the probability of other firms defaulting in the future, in recent years economic and financial factors at the macro level are capable to explain a large portion of the correlation of US firm defaults over time.",

author = "Arianna Agosto and Giuseppe Cavaliere and Dennis Kristensen and Anders Rahbek",

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TY - JOUR

T1 - Modeling corporate defaults

T2 - Poisson autoregressions with exogenous covariates (PARX)

AU - Agosto, Arianna

AU - Cavaliere, Giuseppe

AU - Kristensen, Dennis

AU - Rahbek, Anders

N1 - JEL classification: C13; C22; C25; G33

PY - 2016/9/1

Y1 - 2016/9/1

N2 - We develop a class of Poisson autoregressive models with exogenous covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used in the analysis of the asymptotic properties of the maximum-likelihood estimators of the models. The PARX class of models is used to analyze the time series properties of monthly corporate defaults in the US in the period 1982–2011 using financial and economic variables as exogenous covariates. Results show that our model is able to capture the time series dynamics of corporate defaults well, including the well-known default counts clustering found in data. Moreover, we find that while in general current defaults do indeed affect the probability of other firms defaulting in the future, in recent years economic and financial factors at the macro level are capable to explain a large portion of the correlation of US firm defaults over time.

AB - We develop a class of Poisson autoregressive models with exogenous covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used in the analysis of the asymptotic properties of the maximum-likelihood estimators of the models. The PARX class of models is used to analyze the time series properties of monthly corporate defaults in the US in the period 1982–2011 using financial and economic variables as exogenous covariates. Results show that our model is able to capture the time series dynamics of corporate defaults well, including the well-known default counts clustering found in data. Moreover, we find that while in general current defaults do indeed affect the probability of other firms defaulting in the future, in recent years economic and financial factors at the macro level are capable to explain a large portion of the correlation of US firm defaults over time.

U2 - 10.1016/j.jempfin.2016.02.007

DO - 10.1016/j.jempfin.2016.02.007

M3 - Journal article

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SP - 640

EP - 663

JO - Journal of Empirical Finance

JF - Journal of Empirical Finance

IS - Part B

ER -

Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)

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