Master of Science in Finance and Banking

Updated A.Y. 2017-2018

Credit Risk Models
M.Sc. Finance and Banking
Prof. Stefano Herzel

This course, addressed to advanced Master and PhD students, provides an introduction to modeling, measuring and pricing credit risk.

It is divided into two parts: sovereign debt and corporate debt.

It will show how to model corporate and sovereign credit risk by applying structural and intensity based models.

The theory requires a fair understanding of some tools from probability and stochastic processes.

I will provide

The course is elective, and will be offered during the second semester, if there are enough students interested, over six consecutive weeks, for a total of 36 hours of lectures.

Upon completion of the course students will know and understand the following topics:
1. Corporate debt
• Theory of the Firm (Modigliani-Miller)
• Structural models for Corporate Credit Risk (Merton and Black-Cox models)
• Evaluation of Subordinated Debt
• Estimating Asset Value and Asset Volatility from Observed Equity Prices
• Distance to Default, the KMV approach
• Endogenous Default Boundaries and Optimal Capital Structure (the Leland model)
2. Sovereign debt

Short rate models

Libor Market Model
Swap Market Model

• Introduction to Poisson Processes • Modeling the default intensity
• Sovereign Credit Risk
• Bond and CDS pricing

Students will apply their knowledge  to real market data, using the platform Eikon-Datastream and implementing the models using Matlab.

 

Prerequisities:

Basic knowledge of:
probability and stochastic calculus (e.g. Brownian Motion and Ito’s Lemma)
theory of arbitrage asset pricing (e.g. the Black Scholes model).
risk-free interest rate model (e.g. the Vasicek model)
Some familiarity with one programming language (e.g. Matlab)

All prerequisites are covered in the  “Asset Pricing” course.

Textbook: David Lando, Credit Risk Modeling Theory and Applications,

The final grade will be determined by class participation (25%) and a final written exam (75%)

Updated A.Y. 2016-2017

Credit Risk Models
M.Sc. Finance and Banking
Prof. Stefano Herzel

This course, addressed to advanced Master and PhD students, provides an introduction to modeling, measuring and pricing credit risk.

It is divided into two parts: sovereign debt and corporate debt.

It will show how to model corporate and sovereign credit risk by applying structural and intensity based models.

The theory requires a fair understanding of some tools from probability and stochastic processes.

I will provide

The course is elective, and will be offered during the second semester, if there are enough students interested, over six consecutive weeks, for a total of 36 hours of lectures.

Upon completion of the course students will know and understand the following topics:
1. Corporate debt
• Theory of the Firm (Modigliani-Miller)
• Structural models for Corporate Credit Risk (Merton and Black-Cox models)
• Evaluation of Subordinated Debt
• Estimating Asset Value and Asset Volatility from Observed Equity Prices
• Distance to Default, the KMV approach
• Endogenous Default Boundaries and Optimal Capital Structure (the Leland model)
2. Sovereign debt
• Introduction to Poisson Processes • Modeling the default intensity
• Sovereign Credit Risk
• Bond and CDS pricing

Students will apply their knowledge  to real market data, using the platform Eikon-Datastream and implementing the models using Matlab.

 

Prerequisities:

Basic knowledge of:
probability and stochastic calculus (e.g. Brownian Motion and Ito’s Lemma)
theory of arbitrage asset pricing (e.g. the Black Scholes model).
risk-free interest rate model (e.g. the Vasicek model)
Some familiarity with one programming language (e.g. Matlab)

All prerequisites are covered in the  “Asset Pricing” course.

Textbook: David Lando, Credit Risk Modeling Theory and Applications,

The final grade will be determined by class participation (25%) and a final written exam (75%)

Updated A.Y. 2015-2016

1 Course Description Credit Risk Models Stefano Herzel This course, addressed to advanced Master and PhD students, provides an introduction to modeling, measur- ing and pricing credit risk. It is divided into two parts: sovereign debt and corporate debt. It will show how to model corporate and sovereign credit risk by applying structural and intensity based models. The theory requires a fair understanding of some tools from probability and stochastic processes. We plan to provide examples and applications to real data, using the platform Eikon-Datastream and implementing the models on the computer using Matlab or other softwares. The course will be offered during the second term of 2016, over six consecutive weeks, for a total of 36 hours of lectures. I temptatively aim at covering the following list of arguments: 1. Corporate debt • Theory of the Firm (Modigliani-Miller) • Structural models for Corporate Credit Risk (Merton and Black-Cox models) • Evaluation of Subordinated Debt • Estimating Asset Value and Asset Volatility from Observed Equity Prices • Distance to Default, the KMV approach • Endogenous Default Boundaries and Optimal Capital Structure (Leland model) 2. Sovereign debt • Introduction to Poisson Processes • Modeling the default intensity • Sovereign Credit Risk • Bond and CDS pricing References David Lando, Credit Risk Modeling Theory and Applications, Princeton University Press (2004). Additional references will be provided during the course. Prerequisites – Basic knowledge of probability and stochastic calculus (e.g. Brownian Motion and Ito’s Lemma). – Basic knowledge of the theory of arbitrage asset pricing (e.g. the Black Scholes model). – Basic knowledge of risk-free interest rate model (e.g. the Vasicek model). – Some familiarity with one programming language (e.g. Matlab) Evaluation The final grade will be determined by a final written exam.

Updated A.Y. 2014-2015

 Course Description

This course, addressed to advanced Master and PhD students, provides an introduction to modeling, measuring and pricing credit risk. It is divided into two parts: sovereign debt and corporate debt. It will show how to model corporate and sovereign credit risk by applying structural and intensity based models.
The theory requires a fair understanding of some tools from probability and stochastic processes.

We plan to provide examples and applications to real data, using the platform Eikon-Datastream and implementing the models on the computer using Matlab or other softwares.
The course will be offered during the second term of 2015, over six consecutive weeks starting on the first week of February, for a total of 36 hours of lectures.
We temptatively aim at covering the following list of arguments:

- Sovereign debt
• Stochastic Calculus for Credit Risk Models (review) • Poisson Processes
• Modeling the default intensity
• Sovereign Credit Risk
• Bond and CDS pricing

- Corporate debt
• Theory of the Firm (review)
• Structural models for Corporate Credit Risk (Merton and Black-Cox models)
• Evaluation of Subordinated Debt
• Estimating Asset Value and Asset Volatility from Observed Equity Prices
• Distance to Default, the KMV approach
• Endogenous Default Boundaries and Optimal Capital Structure (Leland model)

References
David Lando, Credit Risk Modeling Theory and Applications, Princeton University Press (2004). Additional references will be provided during the course.

 Prerequisites
– Basic knowledge of probability and stochastic calculus (e.g. Brownian Motion and Ito’s Lemma). – Basic knowledge of the theory of arbitrage asset pricing (e.g. the Black Scholes model).
– Basic knowledge of risk-free interest rate model (e.g. the Vasicek model).
– Some familiarity with one programming language (e.g. Matlab)

 Evaluation
The final grade will be determined by a final written exam.
We will assign jobs which may substitute parts of the final written exam and contribute to the final grade.