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.