The course focuses on the mathematical models and the empirical methodologies advanced in the finance literature for measuring and managing market risk and credit risk. Lectures will be held in a computer room. About 30% of the time will be dedicated to the practical implementation of the models.
Definition of market risk, credit risk, liquidity risk, operational risk. Measuring and managing financial risk. Case study. Regulation.
2. Market risk
Basics of immunization techniques. Methods for the estimation of volatility and correlation (exponential moving average, Garch models, implied volatility, realized volatility). Market risk and Value-at-Risk (VaR) models. VaR models: parametric approach (portfolio-normal, asset-normal, delta-normal, delta-gamma-normal, beta-normal), non-parametric approach (historical simulation, filtered historical simulation, Monte Carlo simulation). Stress testing and backtesting.
3. Credit risk
Basic variables: default probability, loss given default, expected loss, unexpected loss, transition matrices. Credit risk measurement: structural models; intensity-based models; credit scoring models; portfolio models. Credit derivatives. Systemic risk.
- J. HULL, Options, futures, and other derivatives, (VII edition). Prentice Hall, NJ, 2008.
- A. RESTI - A. SIRONI, Risk management and shareholders' value in banking, (I edition). Egea, Milan, 2007.
(chapters 6-15 and 19-21).
- Slides downloadable from the course website "http://dse.univr.it/berardi/mqrm/mqrm.htm".
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