Financial Mathematics and Statistics

Study in the discipline of Financial Mathematics and Statistics is offered by the School of Mathematics and Statistics in the Faculty of Science. Units of study in this major are available at standard and advanced level.

About the major

Financial mathematics and statistics is designed to meet the needs of a particularly popular area of employment for our mathematics graduates. Mathematics is the foundation of the financial world. It allows investors, traders and bankers to make optimal decisions and to distribute risk in a rational way. The mathematics behind finance is, however, not simple and relies heavily on ideas from mathematical theory of probability, analysis, differential equations and statistics.

Financial Mathematics and Statistics will give you a broad introduction to the methods and ideas of mathematical finance and will prepare you for employment in the financial sector or for honours and further study in the field.

Requirements for completion

The Financial Mathematics and Statistics major and minor requirements are listed in the Financial Mathematics and Statistics unit of study table.

Contact and further information

sydney.edu.au/science/schools/school-of-mathematics-and-statistics

First year enquiries:


Other undergraduate enquiries:


All enquiries: +61 2 9351 5787

Major coordinator
Dr Zhou Zhou
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Learning Outcomes

Students who graduate from Financial Mathematics and Statistics will be able to:

1. Exhibit a broad and coherent body of knowledge in fundamental areas in mathematics and statistics, with a particular focus on optimisation, risk analysis and stochastic processes.
2. Interpret information communicated in mathematical or statistical form.
3. Identify and address gaps in knowledge and skills by independently sourcing, collating and synthesising appropriate resources that extend their understanding of concepts in financial mathematics and statistics.
4. Communicate mathematical information, reasoning and conclusions through a range of modes, to diverse audiences, using evidence-based arguments that are robust to critique.
5. Construct logical, clearly presented and justified arguments in mathematics and statistics, including incorporating deductive or evidence-based reasoning.
6. Formulate and model practical and abstract problems in mathematical and statistical terms using a variety of methods.
7. Address practical and abstract problems in mathematics and statistics with a focus on the financial sector, using a range of concepts, techniques and technologies, working responsibly and ethically and with consideration of cross-cultural perspectives, within collaborative and interdisciplinary teams.