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AMS 515, Case Studies in Computational Finance 
Actual applications of Quantitative Finance to problems of risk assessment, product design, portfolio management, and securities pricing will be covered. Particular attention will be paid to data collection and analysis, the design and implementation of software, and, most importantly, to differences that occur between theory and practice in model application, and to the development of practical strategies for handling cases in which model failure makes the naive use of quantitative techniques dangerous. Extensive use of guest lecturers drawn from the industry will be made. 
3 credits, ABCF grading 

 

 

Textbooks for Spring 2021 semester:

There are NO REQUIRED textbooks

 

Suggested References:

"Methods of Information Geometry (Translations of Mathematical Monographs), Volume 191" by Shun-Ichi Amari and Hiroshi Nagaoka, UK. ed edition, 1993, American Mathematical Society and Oxford University Press; ISBN: 978-0821843024

"First Steps in Differential Geometry: Riemannian, Contact, Symplectic" by Andrew McInerney, 2013, Springer Publishing; ISBN: 978-1461477310 (hard cover)

"The EM Algorithm and Extensions" by  Geoffrey J. McLachlan and Thriyambakam Krishnan, 2nd edition, 2008, Wiley Publishing; ISBN: 978-0471201700 (hard cover)

"Mathematical Statistics: Basic Ideas and Selected Topics, Volume II" by Peter J. Bickel & Kjell A. Doksum, 1st edition, Chapman & Hall/CRC Texts in Statistical Science Book 119); ISBN: 978-1498722681 (eTextbook)

"Time Series Analysis: Forecasting and Control" by George E.P. Box, Gwilym M. Jenkins, Gregory C. Reinsel, Greta M. Ljung, 5th edition, 2016, Wiley Series in Probability and Statistics; ISBN: 978-1118675021 (eTextbook)

"Convex Optimization" by Stephen Boyd & Lievan Vandenberghe, 2004, Cambridge University Press; ISBN: 978-7302297567 (paperback)

"Strategic Learning and Its Limits / (Ryde Lectures)" by H. Peyton Young, 2005, Oxford University Press: ISBN: 978-0199269181 (hard cover)