FINC3017: Investments and Portfolio Management
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FINC3017: Investments and Portfolio Management
Overview
This unit is designed to provide a comprehensive analytical approach to the modern theory of investments. Topics covered include: mean-variance analysis; Markowitz type portfolio analysis; portfolio construction; asset pricing theories; market efficiency and anomalies; hedge funds and investment fund performance evaluation. Although analytical aspects of investments theory are stressed, there is also an equal amount of coverage on the practical aspects of portfolio management. Current research on investments is emphasised in the course.
· Assignments: Assignments are to be completed individually and will require you to prepare a report that contains responses to a combination of written and numerical problems drawn from real-world application of the topics studied in class. You will be assessed on your technical application to quantitative questions as well as your critical discussion of key issues.
· Final online exam: The final exam will cover the topics studied throughout the semester. There will be a mix of quantitative and conceptual questions.
· Further details on all assessments will be provided on Canvas
Late submission
In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:
· Deduction of 5% of the maximum mark for each calendar day after the due date.
· After ten calendar days late, a mark of zero will be awarded.
Special consideration
If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.
Academic integrity
The Current Student website provides information on academic honesty, academic dishonesty, and the resources available to all students.
The University expects students and staff to act ethically and honestly and will treat all allegations of academic dishonesty or plagiarism seriously.
We use similarity detection software to detect potential instances of plagiarism or other forms of academic dishonesty. If such matches indicate evidence of plagiarism or other forms of dishonesty, your teacher is required to report your work for further investigation.
Weekly schedule
WK |
Topic |
Learning activity |
Learning outcomes |
Week 01 |
Introduction & Math Preliminaries |
Lecture (2 hr) |
LO1 LO2 LO3 |
Week 02 |
Financial Assets & Decisions under Uncertainty |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO5 |
Week 03 |
Markowitz Portfolio Theory |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO5 |
Week 04 |
CAPM |
Lecture and tutorial (3 hr) |
LO1 LO3 LO5 |
Week 05 |
Factor Models |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO5 |
Week 06 |
Arbitrage Pricing Theory |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO5 |
Week 07 |
Screening & Factor Replication |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO4LO5 |
Week 08 |
Anomalies & Smart Beta |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO4LO5 |
Week 09 |
Performance evaluation |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO4LO5 |
Week 10 |
Frictions, Rebalancing and Risk Management |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO4LO5 |
Week 11 |
Asset Pricing |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO4LO5 |
Week 12 |
Trading Volatility |
Lecture and tutorial (3 hr) |
LO1 LO2 LO3 LO4LO5 |
Week 13 |
Review |
Lecture and tutorial (3 hr) |
LO1 LO2 LO4 LO5 |
Study commitment
Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.
Required readings
See Canvas for weekly required reading list.
Prescribed textbook: Bodie, Z., Kane, A. and Marcus, A.J. (2018), Investments, 11th edition,McGraw Hill, ISBN 9781259277177 (denoted BKM on the reading list).
Chapters from the textbook will be supplemented by journal articles and other online materials. Journal articles can be accessed through the Library.
Learning outcomes
Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University’s graduate qualities and are assessed as part of the curriculum.
· Outcomes
· Graduate qualities
At the completion of this unit, you should be able to:
· LO1. apply the fundamentals of investment theory to construct portfolios and evaluate their performance
· LO2. interpret current academic research and identify how it guides investment decision making and portfolio construction in practice
· LO3. use Microsoft Excel to solve and analyse investment problems
· LO4. communicate clearly and succinctly in writing
· LO5. critique asset pricing models and portfolio management strategies
Closing the loop
The weekly topics have been slightly updated to reflect recent developments in the field.
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
·
Enrolment, course planning, fees, graduation, support services, student IT
·
· Expectations of student conduct
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
·
Academic appeals process, special consideration, rules and guidelines, advice and support
·
· Learning and teaching policy
Policy register, policy search
·
Scholarships, interest free loans, bursaries, money management
·
Learning Centre, faculty and school programs, Library, online resources
·
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing
·
Disclaimer
The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.
This unit of study outline was last modified on 05 Jul 2022.
To help you understand common terms that we use at the University, we offer an online glossary.
2022-07-20