Master of Financial Mathematics

The only maths masters of its kind in Melbourne

COURSE INTRODUCTION

Across the world, talented mathematicians are highly sought-after by banks and other financial institutions to help manage the increasingly complex and risky financial sector. Particularly valued today are those who are able to combine technical knowledge and mathematical problem-solving ability with fluency in the language of finance, in order to solve practical problems in the industry such as complex derivatives pricing, quantitative risk management and portfolio allocation.

The Monash Master of Financial Mathematics is a mathematics course designed for application in a business context. It is designed for graduates from across the globe with an aptitude and passion for mathematics and statistics, as well as a keen interest in finance and insurance. This is not a course for generalists; this is a highly specialised degree for students seeking a future in the world of professional quantitative finance.

You will be taught by mathematicians who are leading researchers in areas such as probability, stochastic processes and statistics, computational mathematics and machine learning, and with connections across the financial and insurance industries. You will have access to the state-of-the-art teaching facilities, including a Bloomberg data terminal lab. Industry projects and placements, being a core component of the degree, will provide you with an opportunity to gain valuable workplace experience and kickstart your career.

PATHWAYS AND OUTCOMES

Alternative exit(s)

Students may exit this course early and apply to graduate with the following, provided they have satisfied the requirements for that award: Graduate Certificate in Financial Mathematics Graduate Diploma in Financial Mathematics.

Further studies

Upon completion of the Master of Financial Mathematics, depending on level of achievement, students may be eligible to apply for admission to the Doctor of Philosophy (PhD).

COURSE STRUCTURE


Modern finance relies on deep mathematical concepts and techniques, assembled in what has come to be known as financial mathematics or quantitative finance.

The core of the program is mathematics, with concepts and techniques from probability, stochastic modelling, differential equations, statistics and computational mathematics. These tools are then connected with and applied to practical problems in finance, supplemented by state of the art knowledge in econometrics, investment and trading, as well as skills in quantitative analysis, data analytics, programming and machine learning.

The industry project and placement component leverages our close relationships with banks, investment firms, traders, and research organisations, under the guidance of our expert world-leading researchers in financial mathematics.

Core units

Elective units

Quantitative Research

Elective units

Investing and Trading

Elective units

Data Analytics

Part A.

Orientation studies
(6 months)
2 core units
+
2 electives

MTH3251 Financial mathematics
MTH3241 Random processes in the sciences and engineering
MTH3260 Statistics of stochastic processes

MTH3140 Real analysis
MTH3160 Metric spaces, Banach spaces, Hilbert spaces
MTH3230 Time series and random processes in linear systems

ETC3400 Principles of econometrics
ETC3420 Applied insurance methods
ETC3460 Financial econometrics

MTH3051 Introduction to computational mathematics
MTH3320 Computational linear algebra
MTH3330 Optimisation and operations research

Part B.

Specialist studies
(1 year)
5 core units
+
3 electives

MTH5210 Stochastic calculus and mathematical finance
MTH5510 Quantitative risk management
MTH5520 Interest rate modelling
MTH5530 Computational methods in finance
MTH5550 Quantitative trading and market microstructure
MTH5560 Partial differential equations for finance

MTH5220 The theory of martingales in discrete time
MTH5230 Markov chains and random walks
MTH5540 Statistical learning in finance

ETC5460 Financial econometrics 2
BFF5270 Funds management
BFX5260 Treasury and financial markets

MTH5331 Optimisation for data analytics
FIT5197 Statistical data modelling
FIT5201 Machine learning
FIT9136 Algorithms and programming foundations in Python

Part C.

Applied professional practice
(6 months)

MTH5810 Industry research project
OR
MTH5830 Industry placement
OR
MTH5820 Minor industry research project or MTH5840 Minor industry placement + 2 additional Part B electives

Standard duration is 2 years full time, 4 years part time. Students have a maximum of four years to complete this course.​ Depending upon prior qualifications and experience, you may receive credit for Part A or Part C or a combination of the two and shorten your study duration.

ENTRY REQUIREMENTS

For entry to Monash University, you must meet the minimum English language requirements.

Minimum entrance requirements for admission to Monash University Australia.

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GET IN TOUCH

If you have more questions, please get in touch!

Contact:
Book a one-on-one phone or Zoom consultations with the Course Director or Course Coordinator

Future student enquiries:
Australian citizens, permanent residents and New Zealand citizens
T: 1800 MONASH (666 274)  
E: future@monash.edu
monash.edu/study/contact

International students
Australia freecall tel: 1800 181 838
Tel: +61 3 9903 4788 (outside Australia)
Email: study@monash.edu
monash.edu/study/contact/international
Wechat: MonashUniAus
Youku: Monash 蒙纳士大学

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