Mathematical Computing for Finance (MATH3311)

MATH3311 is a Mathematics Level III course.

Units of credit: 6

Prerequisites: (MATH2121 or MATH2221 or MATH2111) and (MATH2501 or MATH2601) and (MATH2801 or MATH2901 or MATH2871)

Exclusion courses: MATH5335

Cycle of offering: Term 2 

Graduate attributes: The course will enhance your research, inquiry and analytical thinking abilities.

More information: The course outline contains information about course objectives, assessment, course materials and the syllabus.

Important additional information as of 2023

UNSW Plagiarism Policy

The University requires all students to be aware of its policy on plagiarism.

For courses convened by the School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.

If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.

The Online Handbook entry contains up-to-date timetabling information.

If you are currently enrolled in MATH3311, you can log into UNSW Moodle for this course.

Ultimately finance is concerned with making definite numerical recommendations, typically only achievable using high-speed computers to analyse sophisticated models. This course studies the design, implementation and use of computer programs to solve practical mathematical problems relevant to finance, insurance and risk management.

During the course, students undertake a review of MATLAB, floating point numbers, rounding error and computational complexity. We explore a selection of topics, including approximation and parameter estimation, Fourier series and the FFT, finite difference approximations, partial differential equations (heat equation), sparse linear systems, non-linear algebraic equations, trees, Monte Carlo methods and simulation, random numbers and variance reduction, numerical integration, and computing environments for mathematical finance. We also look at practical examples and programming assignments using MATLAB.