Modern financial engineering: counterparty, credit, portfolio and systemic risks

Table of content;
Mathematical and Statistical Foundations:
Distributions Commonly Used in Credit and Counterparty Risk Modeling
Poisson Processes
Estimation Techniques
Finance Background and Regulatory Framework:
Basic Definitions
Banking Regulation Before the Crisis
The Financial Crisis of the XXI-st Century
Credit Risk Regulation After the Crisis
Credit Risk Modeling Essentials:
Probability of Default (PD)
Loss Given Default (LGD)
Other Credit Risk Components and Portfolio Risk
Model Validation and Audit
Counterparty Risk Modeling:
EAD Modeling
EAD-Related Issues
Correlation-Driven Issues
Portfolio Credit Risk Management Applications:
Credit Risk Models
Sector Analysis
Estimating PD and LGD for Modeling Non-Performing Loans: The Case of Italy
The Case of Italy
Credit Default Swap (CDS)
Systemic Risk Implications:
Diversifying the Economy for Systemic Risk Reduction: The Case of the Kingdom of Saudi Arabia (KSA)
Systemic Risk Regulation
Appendices:
Financial Engineering: Coding in R
Financial Engineering: Coding in Matlab
Dataset Used for Modeling Non-Performing Loans
Readership: Academics and practitioners interested in modern financial engineering.
[Mathematical and Statistical Foundations:
Distributions Commonly Used in Credit and Counterparty Risk Modeling
Poisson Processes
Estimation Techniques
Finance Background and Regulatory Framework:
Basic Definitions
Banking Regulation Before the Crisis
The Financial Crisis of the XXI-st Century
Credit Risk Regulation After the Crisis
Credit Risk Modeling Essentials:
Probability of Default (PD)
Loss Given Default (LGD)
Other Credit Risk Components and Portfolio Risk
Model Validation and Audit
Counterparty Risk Modeling:
EAD Modeling
EAD-Related Issues
Correlation-Driven Issues
Portfolio Credit Risk Management Applications:
Credit Risk Models
Sector Analysis
Estimating PD and LGD for Modeling Non-Performing Loans: The Case of Italy
The Case of Italy
Credit Default Swap (CDS)
Systemic Risk Implications:
Diversifying the Economy for Systemic Risk Reduction: The Case of the Kingdom of Saudi Arabia (KSA)
Systemic Risk Regulation
Appendices:
Financial Engineering: Coding in R
Financial Engineering: Coding in Matlab
Dataset Used for Modeling Non-Performing Loans
Readership: Academics and practitioners interested in modern financial engineering.
[https://www.worldscientific.com/worldscibooks/10.1142/12725?srsltid=AfmBOopM6GPxXGhWxxtLaRhkDmvxhGwuBuw1LhSnWn_6kRI_LCSBFcFc#t=aboutBook]

The book offers an overview of credit risk modeling and management. A three-step approach is adopted with the contents, after introducing the essential concepts of both mathematics and finance.

Initially the focus is on the modeling of credit risk parameters mainly at the level of individual debtor and transaction, after which the book delves into counterparty credit risk, thus providing the link between credit and market risks. The second part is aimed at the portfolio level when multiple loans are pooled and default correlation becomes an important factor to consider and model. In this respect, the book explains how copulas help in modeling. The final stage is the macro perspective when the combination of credit risks related to financial institutions produces systemic risk and affects overall financial stability.

The entire approach is two-dimensional as well. First, all modeling steps have replicable programming codes both in R and Matlab. In this way, the reader can experience the impact of changing the default probabilities of a given borrower or the weights of a sector. Second, at each stage, the book discusses the regulatory environment. This is because, at times, regulation can have stricter constraints than the outcome of internal models. In summary, the book guides the reader in modeling and managing credit risk by providing both the theoretical framework and the empirical tools necessary for a modern finance professional. In this sense, the book is aimed at a wide audience in all fields of study: from quants who want to engage in finance to economists who want to learn about coding and modern financial engineering.
(https://www.worldscientific.com/worldscibooks/10.1142/12725?srsltid=AfmBOopM6GPxXGhWxxtLaRhkDmvxhGwuBuw1LhSnWn_6kRI_LCSBFcFc#t=aboutBook)