Управление рисками

2023/2024

Статус: Маго-лего

Кто читает: Международный институт экономики и финансов

Когда читается: 2 модуль

Охват аудитории: для всех кампусов НИУ ВШЭ

Преподаватели: Бахтиева Камилла Азаматовна, Дорофеева Александра Владимировна, Суханов Михаил Сергеевич, Фардо Винсент Марк

Язык: английский

Кредиты: 3

Контактные часы: 48

Full 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 assessment
This 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 module
0.5 * 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

Authors

FARDEAU VINCENT MARK

Course Syllabus