Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614643
Title: Modelling corporate default risks in the UK and measuring the risk-spillover connectedness of the European banking system
Author: Chi , Hongzhu
Awarding Body: University of Leeds
Current Institution: University of Leeds
Date of Award: 2013
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Abstract:
This thesis aims to explore the determinants of corporate default in the UK industrial companies and propose the best performing probability of default measurement. we re-examine some of the most popular probability of default models in the literature (Altman's Z-Score and Olson's O-Score) and define a hybrid model (H-Score), estimated from a dynamic legit model using accounting and market variables. Our Z-Score and O-Score results update many of the original covariate values proposed by above authors. Various performance test analysis show that H-Score provides the most information about the probability of default for our UK dataset. These various probability of default measurements arc then applied as the proxy of distress risk to examine the empirical analysis of distress risk premium in the UK context, mainly documented as a negative risk premium in US studies. We follow the latest development in this literature (Campbell et al (2008) and Chen et al. (2010) and carry out portfolio analysis to test the hypothesis of whether financially more distressed firms are rewarded by higher returns. Our results provide mixed findings. The existence of distress risk premium puzzle depends on many factors, including the way we construct the distressed p0l1folios and the selection of probability of default measurement as a proxy of distress risk. Finally, we twist our credit risk analysis to consider credit risk spillover effect and provide a measure of the risk-spillover connectedness within European investment banking system. We use the methodology advanced by Diebold and Yilmaz (2009,2013) and Greenwood-Nimmo el al. (2013) and apply the Vector Autoregression (VAR) model and Forecast Error Variance Decomposition (FE VD) to the credit default spread (CDS) data of the most liquid and actively traded nine European investment banks. Our various connectedness measurement results indicate that the inter-connectedness among European investment banks are extremely dynamic due to individual bank's idiosyncratic risk factors and the wider macroeconomic situations. Hence, supervisory institutions need la understand the time-varying dynamic nature of the connectedness among banks and be prepared to adjust policies to prevent accelerating of the systemic risk.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.614643  DOI: Not available
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