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Unit outline_

FINC3017: Investments and Portfolio Management

Semester 1, 2022 [Normal day] - Camperdown/Darlington, Sydney

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.

Unit details and rules

Academic unit Finance
Credit points 6
Prerequisites
? 
FINC2012
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

Introductory statistics, calculus and microeconomics

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Guanglian Hu, guanglian.hu@sydney.edu.au
Type Description Weight Due Length
Final exam (Record+) Type B final exam Final online exam
Online exam
40% Formal exam period 1.5 hours
Outcomes assessed: LO1 LO2 LO4 LO5 LO3
Assignment Assignment 1
Written report
30% Week 06 TBA - see Canvas
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Assignment Assignment 2
Written report
30% Week 12 TBA - see Canvas
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Type B final exam = Type B final exam ?

Assessment summary

  • 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

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Distinction

75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Credit

65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Pass

50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

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.

Academic integrity

The Current Student website provides information on academic integrity 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 integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 Introduction Lecture (2 hr) LO1 LO2 LO3
Week 02 Asset Classes and Financial Instruments Lecture and tutorial (3 hr) LO1 LO2 LO3 LO5
Week 03 Risk-return relation and portfolio analysis Lecture and tutorial (3 hr) LO1 LO2 LO3 LO5
Week 04 Markowitz Model Lecture and tutorial (3 hr) LO1 LO3 LO5
Week 05 Single Index Model Lecture and tutorial (3 hr) LO1 LO2 LO3 LO5
Week 06 CAPM Lecture and tutorial (3 hr) LO1 LO2 LO3 LO5
Week 07 Testing CAPM Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5
Week 08 Anomalies Lecture and tutorial (3 hr) LO1 LO3 LO4 LO5
Week 09 Performance evaluation Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5
Week 10 Asset Pricing Theory Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5
Week 11 Current Research: Return Predictability Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5
Week 12 Current Research: Trading volatility Lecture and tutorial (3 hr) LO1 LO2 LO3 LO4 LO5
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 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.

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

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

The weekly topics have been slightly updated to reflect recent developments in the field.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.