Risk and Portfolio Management with Econometrics,
Spring 2009

Course Details and Schedule


Multivariate calculus (partial derivatives, multiple integrals, Lagrange multipliers, etc.), linear algebra (linear equations, solvability, eigenvalues of symmetric matrices, bases for vector spaces), calculus based probability (probability density functions for univariate and multivariate random variables, conditional and marginal density by integration, the central limit theorem, the formulas for univariate and multivariate gaussian densities), some experience with computing (see below).


Most of the assignments will involve computation using Matlab. Registered students will have access to Matlab Courant Institute computer labs, but most students will find it more convenient to use Matlab on their own computers. A student version of Matlab is available at the NYU Bookstore and is not very expensive. Students without previous exposure to Matlab should budget extra time for the first few assignments as they learn the system.


The final grade will be determined by the grades on the homework assignments and the final exam, each counting for about half the total. Homework grades will be posted on the nyuHome web site. Only registered students may submit homeworks for grading. There will be a penalty for assignments submitted late, which is an increasing but moderate and unspecified function of lateness. Within reason, it is better to submit an assignment late but complete rather than on the due date but incomplete.


There is a message board at the nyuHome web site. Sign in with your NYU netid and password, then click on the "Academics" tab, then on the class "Risk and Portfolio Management with Econometrics" link (Warning: this will not work until you register for the class.), then the "Discussion Board" button on the left, then (finally) the "Discussion board" link. Please post all academic questions or comments on the message board (questions about an assignment, answers to questions or other comments, announcements of study sessions, etc.). Always check the message board before working on an assignment, as there often will be corrections or hints. Please email an instructor or TA only for personal matters (schedule an appointment, request to submit an assignment late, etc.).


Students are encouraged to discuss homework exercises with each other. Each student must write the solutions himself or herself. Copying of solutions or allowing others to copy your solutions is considered cheating and will be handled according to NYU cheating policies. Code sharing is not allowed. You must type (or create from things you've typed using an editor) every character of code you use.

Weekly schedule (tentative)

Date Lecture topics Readings Due this class
Jan. 21 Mean variance analysis and the efficient frontier M, Sections 6.3 - 6.6, FFK, Chapter 2 none
Jan. 28 Classical statistics, parameter estimation tba HW 1
Feb 4 Classical statistics, regression tba HW 2