Advanced Investments (FNCE40002)
HonoursPoints: 12.5On Campus (Parkville)
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
Additional details
- Two assignments not more than 500 words each, first due by end of week 6 and second due end of week 12, (9% each for total of 18%)
- Two on-line trading laboratory tasks, during 3rd and 5th week. The trading takes 1 hour with approximately 3 hours preparation. No report - only performance in the trading session assessed. (5% each for total of 10%)
- Eleven weekly online, in-class quizzes of 10 minutes each, weeks 2-12 (2% each for a total of 22%)
- One quantitatively-based report of 1000 words evaluating the quality of a robo-advisor on the basis of advanced investments knowledge (10%)
- 120 minute end-of-semester exam, end of semester (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 26 February 2018 to 27 May 2018 Last self-enrol date 9 March 2018 Census date 31 March 2018 Last date to withdraw without fail 4 May 2018 Assessment period ends 22 June 2018 Semester 1 contact information
Last updated: 3 November 2022
Further information
- Texts
- Related Handbook entries
- Available to Study Abroad and/or Study Exchange Students
Last updated: 3 November 2022