Table Of ContentCover Page: i
Half Title Page: i
Series Page Page: ii
Title Page Page: iii
Copyright Page Page: iv
Table of Contents Page: v
Preface Page: xi
Author Page: xiii
Introduction: Starting with Credit Risk Page: xv
Chapter 1 ▪ Background of Credit Risk and Java Visualization for Expected Exposure Page: 1
1.1 Financial Risk Page: 1
1.2 Credit Risk Page: 2
1.3 Credit Risk Measure Page: 3
1.4 Monte Carlo Page: 4
1.5 Interest Rate Swap Page: 4
1.6 Analytical Methodology Page: 4
Bibliography Page: 5
Chapter 2 ▪ Theoretical Phase of a Real-World Case Study Page: 7
2.1 Introduction to the Theoretical Phase Page: 7
2.2 Preliminary Notes Page: 7
2.3 Internal Model Method and Exposure Page: 7
2.4 Exposure Regulatory Measures Used Page: 9
Bibliography Page: 11
Chapter 3 ▪ Real-World Case of the Practical Phase for Generating Exposure Regulatory Measures in a Specific Bank with an Internal Model Method Page: 13
3.1 Introduction to a Real-World Case Page: 13
3.2 Calculation Tools Used Page: 13
3.3 Flow to Generate Expected Positive Exposure (EPE) Value Page: 14
3.4 Methodology for the Calculation of EPE Page: 15
3.5 Results of the Calculation Page: 15
Bibliography Page: 17
Chapter 4 ▪ Theoretical Approach of the Real-World Case Phase Related to the Methodology of Scenario Simulation Used for Generating Exposure Regulatory Measures Page: 19
4.1 Introduction of the Theoretical Approach Page: 19
Bibliography Page: 20
Chapter 5 ▪ Generation of a Simulation of a Real-World Case for Generating Exposure Regulatory Measures Page: 23
5.1 Introduction to a Real-World Simulation Page: 23
5.2 Interest Rate Swaps Portfolio Page: 23
5.3 Choice of Observation Days Corresponding to Time Steps Page: 23
5.4 Methodology of Scenario Simulation Page: 26
5.5 Inspect Scenario Prices Page: 27
Bibliography Page: 27
Chapter 6 ▪ Compute Exposure by Counterparty Page: 29
6.1 Introduction to Computation Page: 29
6.2 Portfolio Exposure Profiles Page: 31
6.3 Counterparty Alpha Ltd. Exposure Profile Page: 31
6.4 Counterparty Beta Ltd. Exposure Profile Page: 32
6.5 Counterparty Gamma Ltd. Exposure Profile Page: 34
Bibliography Page: 35
Chapter 7 ▪ First Quantitative Analysis of Portfolio Exposure Profiles Page: 37
7.1 Introduction to the First Analysis Page: 37
Bibliography Page: 39
Chapter 8 ▪ Further Analysis on Portfolio Exposure Profiles Using Zero Rate Vector 0.03 Page: 41
8.1 Portfolio EPE, Portfolio Eff. EPE, and Portfolio MPFE Using Zero Rate Vector 0.03 Page: 41
8.2 Portfolio for Counterparties Alpha Ltd., Beta Ltd., and Delta Ltd.: EPE, Eff. EPE, and MPFE Profiles Using a Different Zero Rate Vector 0.03 Page: 43
8.3 Counterparty Alpha Ltd.: EPE, Eff. EPE, and MPFE Profiles Using Zero Rate Vector 0.03 Page: 45
8.4 Counterparty Beta Ltd.: EPE, Eff. EPE, and MPFE Profiles Using Zero Rate Vector 0.03 Page: 47
8.5 Counterparty Gamma Ltd.: EPE, Eff. EPE, and MPFE Profiles Using Zero Rate Vector 0.03 Page: 48
Bibliography Page: 50
Chapter 9 ▪ Further Analysis of Portfolio Exposure Profiles with Zero Rate Vector 0.06 Page: 51
9.1 Portfolio EPE Profiles Using a Different Zero Rate Vector 0.06 Page: 51
9.2 Portfolio EPE, Eff. EPE, and MPFE Profiles Using Zero Rate Vector 0.06 Page: 51
9.3 Portfolio for Counterparty Alpha Zero Rate 0.06 Page: 53
9.4 Portfolio for Counterparty Beta Zero Rate 0.06 Page: 55
9.5 Portfolio for Counterparty Gamma Zero Rate 0.06 Page: 56
9.6 Portfolio EPE, Eff. EPE, and MPFE Profiles Using a Different Zero Rate Vector 0.06 Page: 57
Bibliography Page: 60
Chapter 10 ▪ Generalization of Analysis on Portfolio Exposure Profiles with Zero Rate Vectors 0.01, 0.03, and 0.06 Page: 61
10.1 Analysis of Previous Generated Data Page: 61
Bibliography Page: 63
Chapter 11 ▪ Risk Perspective of Credit Valuation Adjustment Page: 65
11.1 Definition of the Start Portfolio for Credit Valuation Adjustment Page: 65
11.2 Regulatory Risk Perspective of CVA Page: 66
11.3 Mathematical Risk Perspective of CVA Page: 67
11.4 Further Study on CVA Using the Previous Expected Exposure Data Page: 68
Bibliography Page: 68
Chapter 12 ▪ Further Work Page: 69
12.1 Further Work: Description and Explanation of the Project Page: 69
12.2 Brief Description Page: 69
12.3 Explanation of the Project Page: 69
12.4 Purpose of the Research Project Page: 70
12.5 Structure and Methodology of the Investigation Page: 71
12.6 Reasons for Adopting Certain Methodologies Instead of Others Page: 71
12.7 Emphasis on the Rigour Required for the Methodology Proposed Page: 71
12.8 Originality and Innovation of the Project Page: 72
12.9 Importance of the Project Page: 72
12.10 Completion Time Page: 72
12.11 First Phase Page: 72
12.12 Second Phase Page: 73
12.13 Third Phase Page: 73
Bibliography Page: 73
Chapter 13 ▪ MATLAB Source Code Strategy and Analysis for Generation of Time Step Set of Data Page: 75
13.1 Portfolio Expected Exposure Data Generated by MATLAB Page: 75
13.2 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 1 Page: 88
13.3 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 2 Page: 90
13.4 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 3 Page: 92
13.5 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 4 Page: 95
13.6 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 5 Page: 98
13.7 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 6 Page: 101
13.8 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 7 Page: 105
13.9 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 8 Page: 109
13.10 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 9 Page: 113
13.11 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 10 Page: 118
13.12 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 11 Page: 123
13.13 Detailed Analysis of the Part of Source Code from Grid Number 0 to Grid Number 12 Page: 128
Bibliography Page: 135
Chapter 14 ▪ Expected Exposure Visualization List of Java Code Packages Page: 137
14.1 Java Expected Exposure Visualization Source Code Index Web Page Page: 137
14.2 Java Code Package Estrazione Page: 142
14.3 Java Code Package Grafica Page: 187
14.4 Java Code Package Strutturedati Page: 207
14.5 Java Code Package Utilità Page: 237
Bibliograpy Page: 270
Chapter 15 ▪ Expected Exposure Visualization List of UML Diagram Page: 273
15.1 Expected Exposure Visualization List of MyEclipse War Folders Page: 273
Bibliography Page: 457
Chapter 16 ▪ Credit Models Using Google Cloud Page: 459
16.1 Definition of the Software Used Page: 459
16.2 Upload and Use MATLAB Files on the Cloud Page: 459
16.3 Uploading the MyEclipse Java Project to the Google Cloud Page: 460
Bibliography Page: 461
Chapter 17 ▪ Conclusion Page: 463
Index Page: 465
Description:Introduction to Credit Risk focuses on analysis of credit risk, derivatives, equity investments, portfolio management, quantitative methods, and risk management. In terms of application, this book can be used as an important tool to explain how to generate data rows of expected exposure to counterparty credit risk. The book also directs the reader on how to visualize, in real time, the results of this data, generated with a Java tool. Features Uses an in-depth case study to illustrate multiple factors in counterparty credit risk exposures Suitable for quantitative risk managers at banks, as well as students of finance, financial mathematics, and software engineering Provides the reader with numerous examples and applications Giulio Carlone has an MBA, a PhD, and a Master’s degree in Computer Science from the University of Italy. He is a member of the software system engineering staff of the Department of Computer Science at University College London. He has 20 years of practical experience in technical software engineering and quantitative finance engineering in the commercial sector. His research interests include the use of communication strategies and the implementation of plans and projects using financial software for requirement specifications, requirements analysis, and architectural design.
