New Students

Congratulations on being admitted to the Masters of Financial Mathematics Program!

As soon as possible, register for your Fall classes (usually ECG 528, ST 521, and ISE 711). We cannot guarantee seats in courses, so early registration is very important.

It is your responsibility to make sure you have the pre-requisites for the courses you take at NCSU. You were admitted based on your quantitative ability, and your background may be missing some areas that are required to complete the program.

Computer account (Unity ID and password) information is available from NCSU's Information Technology Department (IT). You can obtain your Unity ID by sending a request to help@ncsu.edu that includes your Student ID number (000______).

Core courses and prerequisite notes

Asset Pricing (ECG 528) requires knowledge of Differential Equations (MA 341), Linear Algebra (MA 405), and Probability/Statistics (MA 421 or ST 511/512). An understanding of elementary economics is recommended (EC 201, 202, 205).

Capital Investment Economic Analysis (ISE 711) requires a good foundation in mathematics and introductory Statistics (ST 511/512).

Statistical Theory II* (ST 521) requires Analysis (MA 425) and Linear Algebra (MA 405). A working knowledge of Statistics (ST 511/512) is a good idea.

In Spring, Computational Methods in Economics and Finance (ECG/MA 790C) requires Asset Pricing (ECG 528), Statistical Theory II (ST 521), and a working knowledge of Matlab (MA 116).

What you can do

NCSU Summer School. NCSU offers ST 511 and 512 on campus, and MA 501 and 502 both live and through distance education. (The course listings can be confusing -- contact the Graduate Secretary for guidance.)

Summer School at another institution.

Self Study. Contact the Director for suggestions for textbooks and/or other study aids.

General Information

The Arrival Survival guide from the Graduate School provides information about registering for classes, places to live, etc.

 

*ST 521 aims to provide a theoretical treatment on the basics of probability and statistical inferences, including random variables, transformations, common distribution families, laws of large numbers, and convergence concepts.