AMS 517, Quantitiative Risk Management
The course will cover structural and reduced-form approach to pricing credit default, Markovian models (or rating-based) pricing methods, statistical inference of relative risks, counting process, correlated (or dependent) default times, copula methods and pricing models for CDOs.
Prerequisites: AMS 507 and AMS 511
3 credits, ABCF grading
Required Textbooks:
"Data Science and Risk Analytics in Finance and Insurance" by Tze Leung & Haipeng Xing; October 2024; CRC/Chapman Hall, ISBN: 978-1-315-11704-1 (hard copy)
"Statistical Models and Methods for Financial Markets", by T.L. Lai and H. Xing; 2008, Springer; ISBN: 978-1-439-83948-5
Learning Outcomes:
1) Build quantitative risk models in various aspects in financial market
* Market risk;
* Credit risk;
* Operational risk.
2) Demonstrate skill with solution methods for evaluating market risk
* Value at Risk and Coherent risk measures (expected shortfall);
* Time series models;
* Factor models and principle component analysis;
* Extreme value theory;
* Delta hedging and local methods;
* Backtesting and stress testing;
* Monte Carlo methods and variance reduction techniques.
3) Demonstrate skill with solution methods for evaluating credit risk
* Cox regression;
* Genearlized linear models;
* Monte Carlo methods;
* Additive hazard regression;
* Intensity process;
* Generalized linear mixed modelstimating market and credit risks;
* Black-schole models;
* Credit derivative swaps and other credit derivatives;
* Structure models;
* Reduced form models.
5) Use computer software techniques to validate analytical solutions of market and credit risk.