S6001 - Master of Financial Mathematics

There is a more recent version of this academic item available.

Overview

Modern finance relies on deep mathematical concepts and techniques, assembled in what has come to be known as financial mathematics or quantitative finance. Financial institutions have developed an ever-increasing appetite for graduates with the right mix of advanced quantitative methods and modelling.

Monash offers a unique blend of expertise spread over four academic units (economics, econometrics, finance and mathematics). All units contribute to the master's program and maintain a close relationship with banks, investment firms, and research organisations in financial mathematics.

The master's program is designed to suit graduates with a sound foundation in mathematics and statistics. The program offers training in the core areas of stochastic, financial and insurance modelling, statistical analysis and computational methodology, as well as in a wide range of elective topics from economics, econometrics, finance, mathematics and probability. Graduates of the program will gain a comprehensive understanding of stochastic and statistical analysis, partial differential equations and computational methods in finance, financial econometric techniques, and financial and risk modelling.

You will develop the quantitative, mathematical, statistical and computing skills needed in financial, insurance and other related careers.

The master's program has three entry points. Depending on the level of mathematics gained, applicants may be admitted in the 96-point, the 72-point or the 48-point program.

Mode and location

On campus

Learning outcomes

These course outcomes are aligned with the Australian Qualifications Framework and Monash Graduate Attributes.

Upon successful completion of this course it is expected that you will be able to:

apply critical thinking, problem solving, and research skills within the finance and insurance context

apply sophisticated stochastic modelling skills within the context of financial markets and the insurance industry

apply advanced statistical techniques and skills to the analysis of financial and insurance data

utilise high-level computational methodology to tackle complex financial and insurance problems

convey ideas and results effectively to technical and non-technical audiences alike and in a variety of formats

work competently, independently and in a collaborative manner in an interdisciplinary professional context.

Structure

The course is structured in three parts: Part A. Orientation studies, Part B. Specialist studies, Part C. Applied professional practice. All students complete Part B. Depending upon prior qualifications, you may receive credit for Part A or Part C or a combination of the two.

Part A. Orientation studies

These studies provide an orientation to the field of financial mathematics. You will choose studies that complement your current knowledge relevant to financial mathematics, including principles of econometrics, mathematical methods and stochastic processes.

Part B. Specialist studies

These studies will provide you with advanced knowledge and skills relevant to thoughtful, innovative and evidence-based practice in financial modelling and analysis. You will acquire core knowledge of and skills in financial econometrics, and advanced mathematical modelling and computational methods in finance. You will complement these with study in areas of your choice, including interest rate modelling, Markov processes, statistical learning in finance, and global financial markets.

Part C. Applied professional practice

These studies will provide you with the opportunity to apply your knowledge skills developed in Part A and B to 'real life' problems, through completing an industry project or an industry internship. If you are admitted to the course with a recognised honours degree or graduate diploma or graduate certificate in a cognate discipline including mathematics or statistics, you will receive credit for this part however, should you wish to complete a 24 point research project you should consult with the course coordinator.

Course progression map

The course progression map provides guidance on unit enrolment for each semester of study.

Requirements
96 credit points

Part A: Orientation studies24 credit points

Core12 credit points

Additional orientation studies units12 credit points

You must complete 12 credit points from the following list of units or from the list above not previously completed:

Overview

Mode and location

Learning outcomes

Structure

Requirements96 credit points

Alternative exit(s)

Progression to further studies

Organisational contact information

Requirements
96 credit points