AMS 515, Case Studies in Machine Learning and Finance (Starting Spring 2023)

The course will cover applications of Quantitative Finance to risk assessment, portfolio management, cash flow matching, securities pricing and other topics. Particular attention will be paid to machine learning approaches, such as neural networks and support vector machines, data collection and analysis, the design and implementation of software. We will study differences between theory and practice in model application, including in-sample and out-of-sample analysis.
3 credits, ABCF grading 

Textbooks:  There are NO REQUIRED textbooks

Supplemental reading:
Zabarankin, M. and S. Uryasev. Statistical Decision Problems. Selected Concepts and Portfolio Safeguard Case Studies. Optimization and Its Applications, Vol. 85, Springer, 2014. Print ISBN: 978-1-4614-8470-7, Electronic ISBN: 978-1-4614-8471-4 .

http://www.springer.com/mathematics/applications/book/978-1-4614-8470-7