Master of Financial Mathematics

Entry Requirements and Fees

To enter the Master of Financial Mathematics program, students must:
  • Have completed a Mathematics or Statistics major within a Bachelor of Science or Bachelor of Mathematics program, or a degree in a related area;
  • Sufficient mathematical/statistical background, and an average above 65 in relevant level III year university courses.

It is expected that successful applicants should have taken real analysis, partial differential equations, numerical methods, probability and stochastic procceses and algebra etc.

A formal application must be made using by applying online.
Prospective international students should note that they will need to meet the University's English language requirements.
A flyer with further details is available (PDF).
Entry to this program is available in March (Semester 1) only.


All coursework masters programs at UNSW are fee-paying.

For local sudents sources of postgraduate course funding please go to Commonwealth Supported Assistance.

For international students please refer to International Fees.

Program Description

The program is intended for students who have completed a Mathematics or Statistics degree in a Science and/or Mathematics program, or a degree in a related area, and who wish to further their knowledge of mathematical finance and statistics. The program offers intensive, high-level training in principles of financial modelling and its mathematical foundations, statistical techniques, risk assessment, and computational techniques of financial mathematics. The program was introduced in 2007 in order to provide students with a route to high quality careers in the financial industry and to provide the financial sector with a stream of highly trained specialists in Quantitative Finance. 

Program Structure

The program consists of ten lecture courses worth 6 units of credit (UOC) each, and a supervised research project worth 12 UOC. The project is compulsory and taken in the 3rd semester. To progress to the 3rd semester and commence the supervised project students are required to have a WAM of 70 or higher in the first 8 masters courses. Students who do not attain a WAM of 70 or higher in the first eight courses of their program are unable to progress to the compulsory project and will be awarded with the Graduate Diploma in Mathematics and Statistics (5659), providing they have passed 8 courses.
Part-time students are expected to complete the project in two consecutive semesters. The core set of compulsory courses, listed below, is designed to provide students with the fundamental areas of biostatistics.
The core set of compulsory courses, listed below, is designed to give a deep knowledge of the fundamentals of financial mathematics with the special emphasis on financial modelling and pricing of financial derivatives.
Honours graduates in Statistics may be exempted from a maximum of one third of the courses and could complete the degree with one year of full time study. 

Core Courses 36 (UoC)

  • MATH5335 Computational Methods for Finance
  • MATH5816 Continuous Time Financial Modelling
  • MATH5835 Stochastic Processes
  • MATH5965 Discrete Time Financial Modelling
  • MATH5975 Intro to Stochastic Analysis
  • MATH5985 Term Structure Modelling

Structure of Enrolment 

Semester 1 
  • MATH5965 Discrete Time Financial Modelling (6 UoC)
  • MATH5835 Stochastic Processes (6 UoC)
  • MATH5975 Introduction to Stochastic Analysis (6 UoC)
  • Approved Elective Course (6 UoC)

Semester 2

  • MATH5335 Computational Methods for Finance (6 UoC)
  • MATH5816 Continuous Time Financial Modelling (6 UoC)
  • MATH5985 Term Structure (6 UoC)
  • Approved Elective Course (6 UoC)

Semester 3

  • MATH5925 Master Project (12 UoC)
  • Approved Elective Course (6 UoC)
  • Approved Elective Course (6 UoC)
Students may choose the elective courses from a wide variety of courses within the School of Mathematics and Statistics, or elsewhere within the University.

Suggested Elective Courses 24 (UoC):

  • ACTL5302 Risk and Capital Management*
  • ACTL5303 Asset-Liability Management*
  • MATH5165 Optimization
  • MATH5806 Applied Regression Analysis
  • MATH5825 Measure, Integration & Probability
  • MATH5836 Data Minning and its Business Applications
  • MATH5845 Time Series
  • MATH5855 Multivariate Analysis
  • MATH5885 Longitudinal Data Analysis
  • MATH5895 Nonparametric Statistics
  • MATH5905 Statistical Inference
  • MATH5945 Categorical Data Analysis
  • MATH5960 Bayesian Inference & Computation
  • MATH5995 Special Topics in Financial Mathematics

* You must seek seek permission from the School of Actuarial Studies to enrol in their courses. Students wishing to take a course from Actuarial Studies the course code must be ACTL53** not ACTL51**

External Courses: With the permission of the Director of Postgraduate Studies (Coursework), a student may take courses from other disciplines at UNSW, other mathematics schools (for example, at University of Sydney), and external courses such as those taught at the AMSI Summer School.

Course Timetables

Timetables for Postgraduate Coursework courses can be found on our Timetables page, under the heading "Honours and Postgraduate Timetables".
For the convenience of part-time and full-time students, classes are typically taught from 5:00pm to 8:00pm on weekdays during semester.

The Masters Project

To commence the research project students must have a WAM of 70 or more after the first 8 masters courses. The project is a compulsory part of our master coursework programs.
Students should seek the guidance from the School at an early stage of study to ensure that the study plan being followed is best suited to lead to the project.
In addition, admission to a particular project is subject to appropriate research and supervision resources being available.
Students who do not attain a WAM of 70 or higher in the first eight courses of their program will be normally awarded with the Graduate Diploma in Mathematics and Statistics (5659), providing they pass 8 courses.
The project involves writing a thesis on the chosen topic. The project could include a literature survey and a critical analysis of the topic area; or could be a small research project. This should prepare you for the problem-solving and report-writing aspects of future employment, or for progression to a research degree. Each student works under the supervision of one or more members of the School. Members of the School are flexible about the range of areas in which they will supervise students. Prospective students should start talking to staff members about possible topics well before they start on the project. An early decision about a topic will facilitate an early start with the project. Supervision by individual staff members is dependent on staff agreement and availability.
The project will be assessed for quality in four major areas (see below), each of which is important. The written thesis will be assessed by two or three markers, one of which may be the supervisor, and each marker will provide a written assessment and grade(s) based on the following:
  • Exposition: Clarity of the presentation. Sufficient introductory and summary material. Organisation and style of the presentation.
  • Literature coverage: Adequate coverage of related material in the field. Placing the topic in a wider context.
  • Critical analysis and insight: Understanding of the problem and/or model. Quality of the discussion. Discussion of the advantages and limitations of the problem/method.
  • Originality: e.g. by modifying or extending earlier theory or methods, or by developing new examples, or by an application to a new area.
The project provides an opportunity to specialise in a particular area of Financial Mathematics. Typical projects require analysis of a substantial data set using advanced statistical software, and could include a literature survey and a critical analysis of the topic area; or they could be a small research project.

Examples of Projects

  • Daniel Drescher: Estimating GLARMA Models
  • Ava Mo: Modelling Long Memory Volatility in Financial Market Using FIGARCH and FIEGARCH on Daily and Intraday Data
  • Shu Yan Yam: Pricing of Electricity
  • Ashish Deepak: Estimating Regime-Switching Models under Bayesian and Maximum Likelihood Methods
  • Bo Wang: GLARMA Models and Stock Price Dynamics
  • Gray Negrine: Pricing Derivatives in LIBOR Models with Stochastic Volatility by Averaging
  • Vikram Mundkur: Dynamic Hedging of Credit Default Swaps
  • Nannan Yu: Information Based Modelling of Defaultable Bonds
  • Atif Khan: Pricing CDOs using Copulas
  • Yuyi Hua: Hedging of Basket Credit Derivatives in Copula-Based Models
  • Susan Mitchell: Measuring Risk of Credit Portfolios
  • Khan Youssiph: PDE Approach to Valuation and Hedging of Basket Credit Derivatives.

Program Focus

The program focuses on the following skills:
  • A sound grasp of the key concepts and methodologies of modern financial theory and related mathematical techniques;
  • An ability to apply the principles of finance, combined with knowledge of statistics and probability theory, to such topics as: modelling of market phenomena, computing prices of financial products, measuring and controlling financial risk;
  • Use of computer software, such as MATLAB, R, SPLUS and SAS, to perform computation of prices and hedges and statistical analysis of financial data;
  • Application of the knowledge and skills acquired to real-life problems arising in financial markets.

Further Assistance

Dr Gery Geenens
Director of Postgraduate Studies (Coursework)
School of Mathematics and Statistics
UNSW Australia (The University of New South Wales)
UNSW Sydney    NSW  2052 Australia
Phone: (02) 9385 7111
Fax: (02) 9385 7123
Inquiries via email must be sent to