AMS 603 Risk Measures for Finance and Data Analysis
Risk analysis is an important to quantitative finance, insurance, commercial credit and many areas of data analysis. We emphasize risk analysis methods that capture observed features of risk, such as heavy tails, and validation of risk models against observed data. Students will be graded on the basis of projects drawn from multiple asset classes considered in the course work, including fixed income, options, portfolio optimization and foreign exchange. Professional standards for software development will be followed. Guest lectures by industry leaders will be included. Participation via conferencing software will be available as an option to class attendance.
3 credits, ABCDF grading
Participation via conferencing software will be available as an option to class attendance.
Textbooks:
Required:
“The Mathematics of Financial Derivatives, A Student Introduction" by Paul Wilmott, Sam Howison and Jeff Dewynne; 1st edition, published by Cambridge University Press, 1995, ISBN: 978-0521497893
Recommended for Supplementary Reading:
"Derivatives: The Theory and Practice of Financial Engineering (Wiley Frontiers in Finance Series)" by Paul Wilmott; published by John Wiley & Sons, Ltd.; 1998; ISBN: 978-0471983897
"Machine Learning: An Applied Mathematics Introduction" by Paul Wilmott; publisehd by Panda Ohana Publishing; 2013, ISBN: 978-1916081604
"Levy Processes and Stochastic Calculus" by David Applebaum; Cambridge University Press, 2nd edition, January 2019, ISBN: 9780511809781
"Credit Risk Modeling: Theory and Applications" by David Lando; Princeton University Press, 2004; ISBN: 9780691089294
"Levy Processes in Credit Risk: by Wim Schoutens and Jessica Caribani; John Wiley & Sons, 2010, ISBN: 9780470685068