S6001 - Master of Financial Mathematics - 2017

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.

Students 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.

These course outcomes are aligned with the Australian Qualifications Framework level 9 and Monash Graduate AttributesAustralian Qualifications Framework level 9 and Monash Graduate Attributes (http://monash.edu.au/pubs/handbooks/alignmentofoutcomes.html).

Upon successful completion of this course you will be able to:

1. apply critical thinking, problem solving, and research skills within the finance and insurance context
2. apply sophisticated stochastic modelling skills within the context of financial markets and the insurance industry
3. apply advanced statistical techniques and skills to the analysis of financial and insurance data
4. utilise high-level computational methodology to tackle complex financial and insurance problems
5. convey ideas and results effectively to technical and non-technical audiences alike and in a variety of formats
6. work competently, independently and in a collaborative manner in an interdisciplinary professional context.

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. Students admitted to the course who have a recognised honours degree or graduate diploma or graduate certificate in a cognate discipline including mathematics or statistics, will receive credit for this part however, should they wish to complete a 24 point research project they should consult with the course coordinator.

The course comprises 96 points structured into three parts: Part A. Orientation studies (24 points), Part B. Specialist studies (48 points) and Part C. Applied professional practice (24 points).

• Students admitted at entry level 1 complete 96 points, comprising Part A, Part B and Part C.
• Students admitted at entry level 2 complete 72 points, comprising Part B and Part C.
• Students admitted at entry level 3 complete 48 points, comprising Part B.

Note: Students eligible for credit for prior studies may elect not to receive the credit and complete one of the higher credit-point options.

The course progression mapcourse progression map (http://www.monash.edu.au/pubs/2017handbooks/maps/map-s6001.pdf) will assist you to plan to meet the course requirements, and guidance on unit enrolment for each semester of study.

Units are 6 points unless otherwise stated.

Part A: Orientation studies (24 points)

Students complete two units from the following:

• MTH3051 Introduction to computational mathematics
• MTH3230 Time series and random processes in linear systems
• MTH3251 Financial mathematics
• MTH3260 Statistics of stochastic processes

Plus two from the following list of units or from the list above not previously completed:

• ETC3400 Principles of econometrics
• ETC3420 Applied insurance methods
• ETC3460 Financial econometrics
• MTH3011 Partial differential equations
• MTH3060 Advanced ordinary differential equations
• MTH3140 Real analysis
• MTH3241 Random processes in the sciences and engineering
• MTH3310 Applied mathematical modelling

Part B: Specialist studies (48 points)

Students complete:

• MTH5210 Stochastic calculus and mathematical finance
• MTH5510 The mathematics of finance: From derivatives to risk
• MTH5520 Interest rate modelling
• MTH5530 Computational methods in finance

Four units from the following:

• BFF5230 Global financial markets
• ETC5460 Financial econometrics 2
• MTH5112 Partial differential equations in finance
• MTH5220 The theory of martingales in discrete time
• MTH5230 Markov chains and random walks
• MTH5540 Statistical learning in finance
• MTH5550 Market micro-structure

Part C: Applied professional practice (24 points)

Students complete one of the following:

• MTH5840 Minor industry placement (12 points) and MTH5820 Minor industry research project (12 points)
• MTH5830 Industry placement (24 points)
• MTH5810 Industry research project (24 points)

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 after successful completion of 24 points of study with at least 18 points of units at level 4 or above, including at least 12 points of core units from Part B and no more than 12 points of electives from Part B
• Graduate Diploma in Financial Mathematics after successful completion of 48 points of study with at least 36 points of units at level 4 or above, including at least 12 points of core units from Part B, plus at least 12 points of electives from Part B, plus a 12-point industry project, with the remaining 12 points taken from Part B.

Students who have achieved a distinction average (70 per cent) over all Part B units in the Master of Financial Mathematics and completed MTH5810 (Industry research project) with a distinction (70 per cent) will be eligible to apply for admission to the Doctor of Philosophy (PhD).