The finance honours specialisation is a program offered within the Research School of Finance, Actuarial Studies and Applied Statistics that offers students who have excelled in their undergraduate studies a challenging but rewarding year of study in finance. We seek outstanding students who are keen to undertake independent finance research with the guidance from academic staff. Past students graduating from the Honours in Finance program have been highly successful in professional practice with jobs in the leading investment banks around the world.
Relevant Degrees
Admission Requirements
1. A major or equivalent in one of the following:
Asian Capital markets major
Capital Markets major
Finance Major
Mathematical Finance major
Quantitative Finance major
2. with a weighted average mark equivalent to an ANU 75 per cent calculated from the 36 units (i.e. 0.75 EFTSL) of courses with highest final marks, excluding 1000-level courses (i.e. introductory undergraduate courses), from courses from one of the majors specified above;
3. and with the written approval of the Honours Convener.
The number of places available in the program may be limited by the Dean due to supervisory capacity.
Requirements
This Honours specialisation requires the completion of 48 units, which must consist of:
42 units from completion of the following course(s):
| Code | Title | Units |
|---|---|---|
| FINM4015 | Advanced Corporate Finance | 6 |
| FINM4106 | Advanced Investments | 6 |
| FINM4500 | Finance Honours Thesis | 6-24 |
| STAT4010 | Managing the Research Process | 6 |
6 units from completion of the following course(s):
| Code | Title | Units |
|---|---|---|
| FINM4017 | Trading and Markets | 6 |
| STAT4018 | Stochastic Modelling | 6 |
| STAT4026 | Graphical Data Analysis | 6 |
| STAT4027 | Statistical Inference | 6 |
| STAT4029 | Design of Experiments and Surveys | 6 |
| STAT4030 | Generalised Linear Modelling | 6 |
| STAT4040 | Statistical Learning | 6 |
| STAT4102 | Applied Time Series Analysis | 6 |
| STAT4116 | Introduction to Bayesian Data Analysis | 6 |
