2023/2024

# Risk Management

Type:
Mago-Lego

Delivered by:
International College of Economics and Finance

When:
2 module

Open to:
students of all HSE University campuses

Instructors:
Vincent Fardeau,
Дорофеева Александра Владимировна,
Суханов Михаил Сергеевич,
Бахтиева Камилла Азаматовна

Language:
English

ECTS credits:
3

Contact hours:
48

### Course Syllabus

#### Abstract

Prerequisites First year courses of the MSc in Financial Economics, in particular Financial Economics I (asset pricing). Abstract This course deals with the ways in which risks are quantified and managed by financial institutions. It consists of two parts, one on market risk and one on credit risk. The first part of the course studies how to model the risk of portfolios emanating from fluctuations in market prices, or market risk. A parametric structure on the distribution of returns may be imposed, or the realised distribution of returns can be used to generate a non-parametric distribution of returns. With the parametric or non-parametric distribution of returns in hand, the risk of particular portfolios can be studied and optimised with reference to the likelihood of losses (Value-at-Risk or Expected Short-fall). Finally applications and short-comings of market risk management tools in banking and financial stability regulation will be studied, and in particular the evolution of the Basel regulation. The second part of the course gives an introduction to commonly used models of credit risk. Credit risk is the risk of loss due to a debtor's non-payment of a bond or a loan. Models of default risk of a single counterparty are studied, and then extended to the case of portfolios of bond or loans. The major complication with portfolios is the correlation of defaults. Regulation of credit risk in the Basel II Accord and its transition to Basel III is presented briefly. Finally, financial instruments used to mitigate credit risk, in particular credit derivatives, are discussed. This part of the course is designed to strike a balance between a practical approach to the most popular credit risk models and their theoretical underpinnings.

#### Learning Objectives

- The course provides students with the tools of risk management and an introduction to the regulatory framework. The course presents the technical aspects of risk management but also insists on the economics of risk management (traders' incentives, general equilibrium effects of regulation, etc.).
- At the end of the course, students should be familiar with, and be able to assess critically, the main techniques and metrics of market risk management, the rationale for and development over time of the regulatory framework, and the main instruments and models used to manage credit risk.
- As the emphasis is laid in the course not only on technical aspects, but also on an intuitive understanding of the economics of risk management and regulation, class and lecture discussions include elements of soft skill developments, in particular communication abilities. These skills are assessed in the problem sets, mid-term test and exam though conceptual (i.e. not only numerical, problem-solving) questions and questions designed to assess the economic intuition of the students. They are also assessed during student group presentations.

#### Expected Learning Outcomes

- To analyze the regulatory environment for market risk and its recent developments
- To assess the aggregate effects of the regulation on prices and portfolio choice
- To assess the challenges and benefits of stresstesting methodologies
- To backtest a risk management model
- To be able to hedge bonds, futures, plain-vanilla options
- To be able to use credit derivatives for hedging
- To calculate Value at Risk and Expected Shortfall using different methods
- To compare different methods and models to forecast volatility (GARCH-type models, realized volatility, implied volatility)
- To distinguish different types of risk
- To evaluate the strengths and limitations of these models
- To explain how deviations from Modigliani Miller theorem generate a rationale for hedging
- To explain how regulation can foster endogenous risk
- To explain intensity models of credit risk
- To explain ratings-based models of credit risk
- To explain the notion of coherent risk measure
- To explain the Vasicek model and how it underpins the regulatory framework for credit risk
- To implement structural models of credit risk using KMV methodology
- To outline stylized facts about volatility
- To outline the determinants of Value at Risk and Expected Shortfall
- To use standard tests about he violation ratio and the independence of violations
- Tooutline stylized facts about asset returns
- To understand the nature of key credit risk parameters
- To understand the idea of risk based pricing
- To be able to develop a model of assessment of default probability based on binary classification
- To understand how models of assessment of default probability are integrated into bank processes

#### Course Contents

- The case for Risk Management
- Risk measures
- Volatility modeling
- Backtesting and stress testing
- Value-at-Risk and regulation
- Credit Risk on a Single Counterparty
- Credit Risk on Portfolios
- Credit Derivatives
- Practical module on credit risk assessment

#### Assessment Elements

- Final exam
- Mid-term test
- Student presentations
- Practitioner's assessmentThis module will be implemented as a competition between teams of students. After lecture students will be divided into groups, which represent banks, and develop models for assessment of default probability and suggest conditions for its application to maximize profit. During evaluation students solutions will be applied to clients data and profit of each bank will be calculated. At the last seminar each team will give a short presentation of their solutions.

#### Interim Assessment

- 2023/2024 2nd module0.5 * Final exam + 0.2 * Mid-term test + 0.15 * Practitioner's assessment + 0.15 * Student presentations

#### Bibliography

#### Recommended Core Bibliography

- Christoffersen, P. F. (2003). Elements of Financial Risk Management. Amsterdam: Academic Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=104701
- Hull, J. (2015). Risk Management and Financial Institutions (Vol. Fourth Edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=963813

#### Recommended Additional Bibliography

- Credit scoring and its applications, Thomas, L., 2017
- Duffie, D., & Singleton, K. J. (2003). Credit Risk : Pricing, Measurement, and Management. Princeton, N.J.: Princeton University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=329732
- Lando, D. (2004). Credit Risk Modeling : Theory and Applications. Princeton, NJ: Princeton University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=329697
- Saunders, A., & Allen, L. (2002). Credit Risk Measurement : New Approaches to Value at Risk and Other Paradigms (Vol. 2nd ed). New York: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=74090