Master of Financial Mathematics (8161)

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Modern finance heavily relies on mathematical modelling, for instance for managing investment portfolios, financial planning, pricing of financial products, or analysing business risk. The UNSW Master of Financial Mathematics program was introduced in 2007 in order to provide the financial sector (banks, insurance companies, investment companies) with a stream of highly trained specialists in quantitative finance. It offers high-level training in principles of modern finance and its mathematical foundations, stochastic analysis, risk assessment, and relevant computational techniques. It is suitable for students who combine an aptitude for mathematics and statistics with a keen interest in finance, and are looking for a route to a high quality career in the financial industry.

Entry Requirements

To enter the Master of Financial Mathematics program, students must:

  • have completed a Bachelor’s degree (or equivalent) in Mathematics or a Bachelor’s degree (or equivalent) in Science or in Finance with a major in mathematics or statistics; and
  • have sufficient mathematical and/or statistical background, as indicated by an average of 65% or above in relevant level III mathematics and/or statistics university courses.

Prospective international students should note that this program has English language requirements as well.


A formal application must be made online. It must include a copy of the past academic transcripts of the applicant, as well as any relevant information (work experience, certificates, etc.) evidencing the aptitude of the applicant to undertake the program.

Entry to this program is available in February (Term 1) only. Applicants must be aware of the application closing dates.


All coursework masters programs at UNSW are fee-paying.

All the postgraduate programs offered by the UNSW School of Mathematics and Statistics are Commonwealth Supported, meaning that domestic students may benefit from a contribution of the Australian Government towards the cost of their education.

For international applicants, please refer to International Fees.

Program structure and courses

The program consists of 72 units of credit (UoC). This comprises 5 compulsory core courses (30 UoC), 5 elective courses (30 UoC) and a compulsory supervised research project worth 12 UoC.


The compulsory core courses are:

The 5 elective courses are normally chosen from the list of postgraduate courses offered by the School of Mathematics and Statistics (all MATH5XXX courses, except for MATH5846 and MATH5856). Those courses include, but are not limited to:

  • MATH5165 Optimisation
  • MATH5171 Linear & Discrete Optimization
  • MATH5305 Computational Mathematics
  • MATH5805 Special Topics in Statistics
  • MATH5806 Applied Regression Analysis
  • MATH5825 Measure, Integration & Probability
  • MATH5826 Statistical Methods in Epidemiology
  • MATH5836 Data Mining 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
  • MATH5985 Term Structure Modelling
  • MATH5995 Special Topics in Financial Mathematics

Note that only a subset of those courses are offered in any given term and year. The list of courses offered in the current year can be found here.

Students may also choose up to a maximum of 18 UoC (i.e., normally 3 courses) of external courses from other disciplines at UNSW Sydney. Those courses include, but are not limited to:

  • ACCT5910 Business Analysis and Valuation
  • ACCT5930 Financial Accounting*
  • ACTL5105 Life Insurance and Superannuation*
  • ACTL5301 Models for Risk Management
  • ACTL5302 Risk and Capital Management*
  • ACTL5303 Asset-Liability Management
  • COMP6714 Information Retrieval and Web Search
  • COMP9021 Principles of Programming
  • COMP9024 Data Structures and Algorithms
  • COMP9044 Software Construction: Techniques and Tools
  • COMP9153 Algorithmic Verification
  • COMP9311 Database Systems
  • COMP9313 Big Data Management
  • COMP9417 Machine Learning and Data Mining
  • COMP9418 Advanced Topics in Statistical Machine Learning
  • COMP9444 Neural Networks and Deep Learning
  • COMP9801 Extended Design & Analysis of Algorithms
  • ECON5106 Financial Economics
  • ECON5206 Financial Econometrics
  • ECON5248 Business Forecasting*
  • FINS5513 Investments and Portfolio Selection
  • FINS5530 Financial Institution Management*
  • FINS5535 Derivatives and Risk Management Techniques
  • FINS5536 Fixed Income Securities and Interest Rate Derivatives
  • FINS5541 Advanced Investment and Advanced Funds Management
  • FINS5542 Applied Funds Management
  • FINS5574 Empirical Asset Pricing

*= conditions apply. 

External courses may also include courses taken from other Schools of Mathematics and/or Statistics in Australia (for instance, at the University of Sydney), or courses taught within the Summer School of the Australian Mathematical Sciences Institute (AMSI).

Any choice of external courses must be approved by the School of Mathematics and Statistics Director of Postgraduate Studies (Coursework) (as well as by the relevant course authority).

Program structure

An example of program structure for a full-time student starting in Term 1 is as follows:

Year 1


Year 2

Term 1

Term 2

Term 3


Term 1

Term 2















The number of elective courses undertaken on each term remains at the discretion of the student, provided that it does not exceed the normal full load of study (maximum18 UoC on any given term, maximum 48 UoC on any given year). This structure is flexible. In particular, part-time students are free to reshape it over more than 5 terms in the most suitable way for them, provided that it stays in agreement with the relevant University policies.

Any proposed program of study which substantially deviates from the above example requires the approval of the School of Mathematics and Statistics Director of Postgraduate Studies (Coursework).

Components MATH5005 and MATH5006 in the above structure correspond to the Masters project. The project is taken over the last two consecutive terms of the program, and after completing at least 36 UoC (typically, 6 courses). Students need to have maintained a WAM of 70 or higher in their program to progress to the project. 

Students who do not achieve the required WAM will be awarded with the Graduate Diploma in Mathematics and Statistics (program 5659) providing they pass 8 courses (or with the Graduate Certificate in Mathematics and Statistics (program 7659) provided they pass 4 courses). The Master Project Guidelines are provided here for information. Enrolment in the project is conditional on the approval of the program authority, i.e. the Director of Postgraduate Studies (Coursework), and is subject to appropriate supervision resources being available.

The Master project

The project is a compulsory part of any Master program, and is worth 12 Units of Credit (UoC). It gives the student an opportunity to make practical use of the knowledge gained through their Master and to learn to work independently. It prepares the student for the problem-solving and report-writing aspects of future employment, or for progression to a research degree.

The project involves writing a thesis, i.e. a coherent written exposition of a chosen topic. Each student works under the supervision of one academic staff member. 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 as early as possible. Supervision by individual staff members is conditional on staff agreement. Ideally, a decision as to the supervisor and the topic should be made before the start of the first term of the project. The thesis could include a literature survey and a critical analysis of the topic area, or could be a small research project.

The thesis will be assessed for quality in four major areas, each of which being equally important:

  • Exposition: structure and presentation of the thesis, including definition of the problem, organisation of the argument, clarity in terms of writing style and illustrative materials;
  • Literature coverage: sufficient introductory and summary material, position of the topic in a  wider context, review and critique of relevant literature in the field;
  • Critical analysis and insight: understanding of the problem and/or model, justification and implementation of the appropriate method and techniques, quality of the discussion (analysis and interpretation), appropriateness of conclusions and recommendations;
  • Originality: new contribution by way of modifying or extending earlier methods, by developing new examples, or by application to a new area.

At the end of their project, the student gives an oral presentation of 15 minutes on their thesis to staff members of School, interested visitors and other students. A short session of Questions & Answers follows. The presentation is worth 20% of the final project mark. The presentation will be assessed on: engagement; knowledge displayed; motivation presented for the study of the topic; description of contributions/achievements; description of results; clarity of verbal discussion; clarity of slides/figures; keeping to time; and responses to questions.

Further Assistance


Dr Jakub Stoklosa
Director of Postgraduate Studies (Coursework)
School of Mathematics and Statistics
UNSW Sydney NSW 2052 Australia

Inquiries via email must be sent to