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Abstract
This thesis is the result of a project aimed at the study of a crucial topic in finance: default risk, whose measurement and modelling have achieved increasing relevance in recent years. We investigate the main issues related to the default phenomenon, under both a methodological and empirical perspective. The topics of default predictability and correlation are treated with a constant attention to the modelling solutions and reviewing critically the literature. From the methodological point of view, our analysis results in the proposal of a new class of models, called Poisson
Autoregression with Exogenous Covariates (PARX). The PARX models, including both autoregressive end exogenous components, are able to capture the dynamics of default count time series, characterized by persistence of shocks and slowly decaying autocorrelation.
Application of different PARX models to the monthly default counts of US industrial firms in the period 1982-2011 allows an empirical insight of the defaults dynamics and supports the identification of the main default predictors at an aggregate level.
Abstract
This thesis is the result of a project aimed at the study of a crucial topic in finance: default risk, whose measurement and modelling have achieved increasing relevance in recent years. We investigate the main issues related to the default phenomenon, under both a methodological and empirical perspective. The topics of default predictability and correlation are treated with a constant attention to the modelling solutions and reviewing critically the literature. From the methodological point of view, our analysis results in the proposal of a new class of models, called Poisson
Autoregression with Exogenous Covariates (PARX). The PARX models, including both autoregressive end exogenous components, are able to capture the dynamics of default count time series, characterized by persistence of shocks and slowly decaying autocorrelation.
Application of different PARX models to the monthly default counts of US industrial firms in the period 1982-2011 allows an empirical insight of the defaults dynamics and supports the identification of the main default predictors at an aggregate level.
Tipologia del documento
Tesi di dottorato
Autore
Agosto, Arianna
Supervisore
Co-supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze economiche e statistiche
Ciclo
26
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Credit risk; Count time series; Poisson autoregression
URN:NBN
DOI
10.6092/unibo/amsdottorato/6188
Data di discussione
21 Gennaio 2014
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Agosto, Arianna
Supervisore
Co-supervisore
Dottorato di ricerca
Scuola di dottorato
Scienze economiche e statistiche
Ciclo
26
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Credit risk; Count time series; Poisson autoregression
URN:NBN
DOI
10.6092/unibo/amsdottorato/6188
Data di discussione
21 Gennaio 2014
URI
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