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Advanced Investments (FNCE40002)
HonoursPoints: 12.5On Campus (Parkville)
For information about the University’s phased return to campus and in-person activity in Winter and Semester 2, please refer to the on-campus subjects page.
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Semester 1
Please refer to the LMS for up-to-date subject information, including assessment and participation requirements, for subjects being offered in 2020.
Overview
Availability | Semester 1 |
---|---|
Fees | Look up fees |
At a theoretical level, the subject teaches principles of strategic and tactical asset allocation, and their potential impact on market-wide phenomena such as asset prices and trading volume (“asset pricing theory”). At the practical level, the subject provides students with opportunities to attempt implementing investment choices in purposely controlled online markets. Students will experience the effect of their actions on commonly used performance evaluation statistics. Mistakes will be put into perspective against recent advances in behavioural finance. Special attention will be paid to market-wide effects of such mistakes, if they exist, and whether these are easily recognisable in real-world financial markets. Lastly, students will investigate to what extent and how trading can be automated (algorithmic trading). Students with programming background (Python) have the option to test their algorithms live in controlled online markets.
Intended learning outcomes
On successful completion of this subject students should be able to:
- Put into practice commonly used techniques in tactical and strategic asset allocation;
- Understand to what extent common actions and mistakes impact market-wide phenomena such as prices and volume;
- Recognise and avoid (for oneself and others) common behavioural biases in the context of investments;
- Learn what forces behind prices and volume that one cannot see in historical data, by confronting theory with data from controlled experiments;
- Evaluate to what extent (and for those with programming skills, how) investment can be automated;
- Form an informed opinion about major issues in investments, such as portfolio performance evaluation, the efficient markets hypothesis, dark markets, and algorithmic trading.
Generic skills
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High level of development: written communication; interpretation and analysis; critical thinking.
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Moderate level of development: collaborative learning; problem solving; team work; application of theory to practice; accessing data and other information from a range of sources.
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Some level of development: oral communication; statistical reasoning; synthesis of data and other information; evaluation of data and other information; use of computer software.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Admission into BH-COM and
Code | Name | Teaching period | Credit Points |
---|---|---|---|
FNCE30001 | Investments |
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
Please refer to Prerequisites and Corequisites.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 3 November 2022
Assessment
Due to the impact of COVID-19, assessment may differ from that published in the Handbook. Students are reminded to check the subject assessment requirements published in the subject outline on the LMS
Semester 1
Description | Timing | Percentage |
---|---|---|
On-line trading laboratory task. The trading takes 1 hour with approximately 3 hours preparation. No report - only performance in the trading session assessed.
| Week 3 | 5% |
On-line trading laboratory task. The trading takes 1 hour with approximately 3 hours preparation. No report - only performance in the trading session assessed.
| Week 5 | 5% |
Take home mid-term exam and 15-minute online discussion
| Week 6 | 40% |
One quantitatively-based report evaluating the quality of a robo-advisor on the basis of advanced investments knowledge, normally in groups of 3-5 students.
| 10% | |
End-of-semester examination
| During the examination period | 40% |
Last updated: 3 November 2022
Dates & times
- Semester 1
Principal coordinator Peter Bossaerts Mode of delivery On Campus (Parkville) Contact hours Three hours of lectures and seminars per week Teaching period 2 March 2020 to 7 June 2020 Last self-enrol date 13 March 2020 Census date 30 April 2020 Last date to withdraw without fail 5 June 2020 Assessment period ends 3 July 2020 Semester 1 contact information
Last updated: 3 November 2022
Further information
- Texts
Prescribed texts
You will be advised of prescribed texts by your lecturer.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Master of Commerce (Accounting) - Available to Study Abroad and/or Study Exchange Students
This subject is available to students studying at the University from eligible overseas institutions on exchange and study abroad. Students are required to satisfy any listed requirements, such as pre- and co-requisites, for enrolment in the subject.
Last updated: 3 November 2022