Determinants of Credit Spreads of Financial Institutions

Table of Contents

1 Introduction

2 Theoretical Principles

2.1 Literature Review

2.1.1 Determinants of CDS Spreads

2.1.2 The CreditGradesTM Framework

2.2 Model Description

2.2.1 The Classical CreditGradesTM Model

2.2.2 Extensions to the CreditGradesTM Model

3 Descriptive Analysis

3.1 Data

3.2 Calibration

3.3 Descriptive Statistics

4 Empirical Analysis

4.1 The Extended CreditGradesTM Model

4.2 Case Study Analysis

4.3 Cointegration across Equity and CDS Markets

4.3.1 Credit Spreads Long-Run Pricing Equilibrium

4.3.2 Price Discovery across Equity and CDS Markets

4.3.3 Cointegration in the Peripheral Eurozone

4.4 Analysis of the Credit Spread Deviations

5 Conclusion and Outlook

A Appendix - Definitions

B Appendix - Summary Statistics

Bibliography

Research Objectives and Themes

The primary purpose of this study is to explore the determinants of credit risk for the global banking universe and to evaluate the robustness of these determinants during volatile and structurally changing market environments. By employing the CreditGrades™ structural model, the research investigates the model's ability to track market-observed Credit Default Swap (CDS) prices and identifies significant deviations caused by governmental interventions and sovereign-bank interdependencies.

• Application of the CreditGrades™ framework to a global banking dataset.
• Comparative analysis of historical versus option-implied equity volatility as model inputs.
• Evaluation of the Too-Big-To-Fail (TBTF) hypothesis during the Global Financial Crisis.
• Investigation of cointegration and price discovery dynamics between equity and CDS markets.
• Analysis of sovereign risk impact on bank credit spreads during the European Sovereign Debt Crisis.

Excerpt from the Book

Summary of Chapters

1 Introduction: This chapter outlines the motivation for the study, focusing on credit risk in global banks during the Global Financial Crisis and the Sovereign Debt Crisis, and introduces the research objectives.

2 Theoretical Principles: This chapter reviews the literature on credit spread determinants and provides a detailed technical introduction to the CreditGrades™ framework, including necessary extensions for financial firms.

3 Descriptive Analysis: This chapter details the data collection, filtration processes, and calibration methodology used to prepare the global banking dataset for empirical analysis.

4 Empirical Analysis: This chapter presents the results of the model performance testing, including case studies, cointegration analysis between equity and credit markets, and panel regressions to explain spread deviations.

5 Conclusion and Outlook: This chapter summarizes the key empirical findings and discusses the implications for structural models in pricing bank credit risk, while suggesting future research directions.

Keywords

Credit Default Swap, CreditGrades™, Structural Model, Global Financial Crisis, Sovereign Debt Crisis, Equity Volatility, Too-Big-To-Fail, Bank Credit Risk, Cointegration, Price Discovery, Leverage, Default Barrier, Market Deviations, Financial Institutions, Risk Management.

Frequently Asked Questions

What is the core focus of this Master's Thesis?

The thesis focuses on determining the drivers of credit risk for global banks and testing the efficacy of the CreditGrades™ structural model in pricing their Credit Default Swap (CDS) spreads.

What are the primary themes investigated in the study?

The research centers on structural models, the impact of governmental interventions during the Global Financial Crisis, the influence of sovereign risk on bank credit, and the relationship between equity and CDS markets.

What is the main objective of the research?

The objective is to explore the determinants of credit risk for the global banking universe and to investigate how well these determinants maintain robustness during periods of high volatility and structural change.

Which methodology is utilized for the analysis?

The study utilizes a calibrated CreditGrades™ structural model, applying statistical methods such as cointegration analysis and panel regressions to evaluate model performance and explain deviations between market and model-implied spreads.

What topics are covered in the main body of the work?

The work covers literature reviews on credit spreads, the technical implementation of the CreditGrades™ model, descriptive statistics of the banking data, and an extensive empirical analysis of model accuracy and market linkages.

Which keywords define this research?

Key terms include Credit Default Swap, CreditGrades™, Global Financial Crisis, Sovereign Debt Crisis, Too-Big-To-Fail, and bank credit risk.

How does the Sovereign Debt Crisis affect the model's accuracy?

The research finds that during the Sovereign Debt Crisis, the model tends to significantly underestimate market spreads, suggesting that sovereign risk acts as a missing factor that is more prominently priced in CDS markets than in equity markets.

What findings relate to the "Too-Big-To-Fail" (TBTF) hypothesis?

The study finds empirical evidence supporting the TBTF hypothesis, particularly during the Global Financial Crisis, where implicit governmental guarantees led to divergences between risk perceptions in equity and credit markets.