OVERVIEW

The course develops the analytical and quantitative knowledge for risk measurement with a particular focus on financial and banking sector

AIMS AND CONTENT

LEARNING OUTCOMES

The main objective of the course is to provide knowledge of the main methods for quantitative analysis and risk measurement in the context of financial markets

AIMS AND LEARNING OUTCOMES

Learning and applying quantitative techniques for assessing risk in financial markets are the main objectives of the course. Pricing models, sensitivity measures, statistical machine learning models and forecasting techniques can be considered among the most important topics.

PREREQUISITES

Fundamentals of mathematical, statistical, financial disciplines and programming.

TEACHING METHODS

Lectures and exercises. Alternatively, depending on the sanitary situation, on-line learning lessons on TEAMS platform.

SYLLABUS/CONTENT

1. The importance of Risk Management in the context of financial markets and the types of risk.

2. Fixed lncome instruments

- Interest rates bootstrap

- Interest rates term-structure models

- Quantitative analysis for fixed income instruments (Price, Yield, TTM, WAM, WACF)

- Risk Measures for fixed income instruments (Duration, Mod.Dur., Convexity, DV01)

- Fischer-Weil Immunization

- Insolvency, migration and counterparty risk

- Price/interest and reinvestment risk

- Exchange/currency and inflation/monetary risk

- Liquidity and marketability risk

3. Futures and Forwards

- Counterparty risk associated with forward contracts

- Collateral and Clearing House

- The cost-of-carry model and the theoretical valuation of forward/futures contracts

- Basis and Correlation Risk

- Hedging using futures and the minimum-variance hedge ratio

4. Swaps

- Fair value estimation and risk measures

- Hedging strategies

5. Credit Derivatives

- Transfer of credit risk using CDS (Credit Default Swaps)

- Trigger Events

- CDS and Bond Yield

- CDS Theoretical value

6. Options

- Closed formulas for measuring risks in vanilla and exotic options

- Lattice methods and Stochastic trees for measuring the risk in American and Bermudan options

- Monte Carlo methods for measuring the risk in Exotic options, structured products and certificates

- Historical and Implied Volatility models

- Hedging strategies using options

7. Value at Risk, Expected Shortfall and CVA/DVA

- Parametric approaches and full-evaluation method for VaR estimation    

– Stressed Scenario

- Stress Testing and Back Testing

- Expected Shortfall

- CVA (Credit Valuation Adjustment) and DVA (Debt Valuation Adjustment)

8. Machine Learning Techniques in FinTech Risk Management

9. Credit Risk

- Probability of Default (PD) estimation

- Loss Given Default (LGD) estimation

- Exposure at Default (EAD) estimation

- Rating systems and Agencies

- Logit, Probit and Structural models

RECOMMENDED READING/BIBLIOGRAPHY

Slides, multimedia supports and specific books are provided directly to students. In addition to the educational material available on the TEAMS channel (/ aulaweb) of the course, other bibliographic information will be provided upon request.

TEACHERS AND EXAM BOARD

Exam Board

PIER GIUSEPPE GIRIBONE (President)

MARCO REMONDINO

LESSONS

LESSONS START

The course begins in accordance with the teaching calendar of the second semester.

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Learning test about the fundamental methodologies, followed by an oral interview on one of the topics of the course.

ASSESSMENT METHODS

Assessment of the learning test and assessment of the understanding of specific topics during an interview.

Exam schedule