All activities that form part of this course will be delivered remotely in Sem 2 2020.
The aim of this course is twofold. The first is to introduce modern finance theory. Topics covered include optimal asset allocation, capital asset pricing model, arbitrage pricing theory, efficient market hypothesis, and event study. The second is to study the econometric implications of the finance theory for asset returns and to review a variety of empirical applications.
The theoretical part of this course focuses mainly on the derivation and interpretation of the asset pricing models. The derivation can be very mathematical, so the course puts more emphasis on the interpretation so students can obtain the basic skills for using the models in practice. The empirical part of this course introduces the application of finance theories to real data then discusses econometric methodology to test these theories. In addition, students will be required to conduct several computer exercises for some of the empirical applications using the real data and econometric applications such as Excel and EViews.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Demonstrate a working knowledge of concepts in finance
- Understand and critically engage in theory of modern finance
- Apply techniques required for asset pricing models to real data sets
- Demonstrate the required skills to interpret results of empirical analysis
Indicative Assessment
- Assignments (10) [LO 1,2,3,4]
- Mid-term examination (40) [LO 1,2,4]
- Final examination (50) [LO 1,2,4]
In response to COVID-19: Please note that Semester 2 Class Summary information (available under the classes tab) is as up to date as possible. Changes to Class Summaries not captured by this publication will be available to enrolled students via Wattle.
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
The course consists of 12 weeks of lectures (2 hours per week) including weekly computer lab/tutorial sessions.
Inherent Requirements
Not applicable
Prescribed Texts
Bodie, Z., Kane, A. and Marcus, A.J. (2013), Investments (10th ed.), McGraw Hill.
Fees
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 3
- Unit value:
- 6 units
If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees. Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2020 | $4500 |
- International fee paying students
| Year | Fee |
|---|---|
| 2020 | $6000 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 7808 | 27 Jul 2020 | 03 Aug 2020 | 31 Aug 2020 | 30 Oct 2020 | In Person | View |
