The Mathematical Finance major provides the necessary theoretical framework required to price complex financial products such as derivative contracts. Mathematical finance has given tremendous impetus to research in and applications of probability theory and some other mathematics areas.
The skills acquired through this major equip students to continue to postgraduate research in mathematical finance or applied probability. Along with a solid computational foundation which can be obtained through courses available in the Major, these skills form an integral component of the attributes necessary to work as a “quant” in the banking and finance industry; for example, market makers, hedge fund analysts, statistical arbitrageurs and risk analysts in banks, central banks and regulators.
Learning Outcomes
- Demonstrate mastery of mathematical concepts and techniques to the level of advanced Analysis.
- Demonstrate mastery of the concepts and techniques of of Probability, Statistics, and Stochastic processes.
- Demonstrate mastery of the ideas and concepts of Mathematical Finance.
- Apply concepts and techniques from mathematics and statistics to finance problems.
- Obtain a deep understanding of Finance in the context of advanced mathematical frameworks.
- Think clearly, sequentially and logically, as demonstrated by the critical analysis of quantitative problems, in particular finance problems.
- Appreciate that mathematics and statistics is embedded in everyday life through its influence in various fields, in particular in finance.
- Draw on discipline based experiences of working collaboratively, communicating mathematical and economics knowledge and acting professionally and responsibility in further study, or professional pursuits.
Other Information
Which courses should you take in first year?
To complete this major students must also complete the following courses:
Academic or enrolment advice:
Students can seek further advice from the academic contact for this major (details above), or the College of Science Student Services Team (students.cos@anu.edu.au).
Back to the topRequirements
Courses marked with an asterisk (*) have 1000-level prerequisites which must be selected in the first year of study and will contribute towards satisfying the 1000-level course requirements of the Bachelor of Science or Bachelor of Science (Advanced) (Honours).
- MATH1115 or MATH1113 (prerequisite for MATH1116)
- MATH1116 (prerequisite for MATH2320)
- STAT1003 or STAT1008 (prerequisite for FINM2002)
- FINM1001 (prerequisite for FINM2002)
- COMP1110 or COMP1140 (prerequisite for COMP2100)
This major requires the completion of 48 units, of which:
36 units must come from the completion of the following compulsory courses:
*COMP2100 Software Construction (6 units)
*FINM2002 Derivatives (6 units)
*MATH2320 Advanced Analysis 1: Metric Spaces and Applications (6 units)
MATH3015 Stochastic Analysis with Financial Applications (6 units)
MATH3029 Probability Theory with Applications (6 units)
MATH3320 Advanced Analysis 2: Lebesgue Integration and Hilbert Spaces (6 units)
12 units must come from the completion of courses from the following list:
*COMP2300 Computer Organisation and Program Execution (6 units)
*COMP2310 Systems, Networks, and Concurrency (6 units)
*COMP2410 Networked Information Systems (6 units)
ECON2013 Behavioral Economics (6 units)
ECON2026 Money and Banking (6 units)
*ECON2101 Microeconomics 2 (6 units)
*ECON2102 Macroeconomics 2 (6 units)
ECON2141 Strategic Thinking: An introduction to Game Theory (6 units)
*EMET2007 Econometrics I: Econometric Methods (6 units)
FINM3003 Continuous Time Finance (6 units)
FINM3007 Advanced Derivatives Pricing and Applications (6 units)
FINM3009 Student Managed Fund (6 units)
*STAT2001 Introductory Mathematical Statistics (6 units)
*STAT2005 Introduction to Stochastic Processes (6 units)
*STAT2008 Regression Modelling (6 units)
*STAT2014 Regression Modelling for Actuarial Studies (6 units)
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