Mathematics 16:643:625 Portfolio Theory and Applications


The course is offered during the Fall semester.

  • Class meeting dates: Please visit the University's academic calendar.
  • Schedule and Instructor: Please visit the University's schedule of classes for the instructor, time, and room.
  • Instructor and Teaching Assistant Office Hours: Please visit the Mathematical Finance program's office hour schedule.

Course Abstract

The course will introduce discuss quantitative portfolio theory and related topics. It will begin with classical Markowitz theory and related analytics in a variety of real-world contexts - constrained optimization, benchmark/active optimization, risk-managed, etc. Following this, topics will include Bayesian mathematics, Black-Litterman, parameter estimation, and alternative risk measures. A heavy emphasis will be placed on programming and analytics; students will construct and manage their own portfolios under a variety of assumptions. Applications discussed during the course are implemented in MATLAB (see software section below).


Math 16:643:621 and Econ 16:220:607 or Stat 16:960:563 (or equivalent graduate course on regression analysis).


Econ 16:220:608 or Stat 16:960:565 (or equivalent graduate course on time series) recommended but not required.


All course content – lecture notes, homework assignments and solutions, exam solutions, supplementary articles, and computer programs – are posted on Sakai and available to registered students.


Subject to instructor confirmation, the grades will be based on exams, as well as a semester-long programming project.

Class Policies

Please see the MSMF common class policies.

Weekly Lecturing Agenda and Readings

This will be provided on Sakai.

Library Reserves

All textbooks referenced on this page should be on reserve in the Hill Center Mathematical Sciences Library (1st floor). Please contact the instructor if reserve copies are insufficient or unavailable.

Additional Textbooks

There is no required textbook. The texts below provide general background. Additional background on the subject may be found in Rutgers Mathematical Finance Reference Texts.

  1. H. Markowitz, Mean-Variance Analysis in Portfolio Choice and Capital Markets, Wiley, 2000
  2. Bodie, Kane, and Marcus, Investments, 7th Edition, McGraw-Hill, 2008
  3. A. Meucci, Risk and Asset Allocation, Springer, 2008
  4. R. Grinold and R. Kahn, Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk, second Edition, McGraw-Hill, 1999


Excel and Matlab, are required for the course. In particular, students will need the Matlab statistics and optimization toolboxes, as well toolboxes such as excel link and/or database, that facilitate the transfer of data to and from Matlab. Please visit the Quantitative Finance Software or Rutgers University Software