Outline

Overview

This unit provides an introduction to basic concepts in corporate finance and their application to (1) valuation of risky assets including stocks, bonds and entire corporations, (2) pricing of equity securities, and (3) corporate financial policy decisions including dividend, capital structure and risk management policies. Emphasis is placed on the application of the material studied and current practices in each of the topic areas.

Unit details and rules

Academic unit	Finance
Credit points	6
Prerequisites ?	{(BUSS1020 or ECMT1010 or ENVX1001 or ENVX1002 or DATA1001) or [(MATH1005 or MATH1015) and MATH1115] or 6 credit points in MATH units including MATH1905} and (BUSS1040 or ECON1001 or ECON1002)
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	BUSS1030
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Vycke Wu, vycke.wu@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written exam	Final Exam Closed Book Written Exam	50%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Out-of-class quiz	Early Feedback Quiz Quiz assessing the lecture content from Weeks 1 to 3. #earlyfeedbacktask	5%	Week 03	30 minutes	AI allowed
Outcomes assessed:
Written test	Mid Semester Exam A closed-book written examination designed to assess students’ understanding of concepts covered in Weeks 1–6 (inclusive).	20%	Week 08 Due date: 26 Apr 2026 at 09:40	1 hour	AI prohibited
Outcomes assessed:
Case studies	Major Group Assignment Major written report	25%	Week 12 Due date: 24 May 2026 at 23:59 Closing date: 03 Jun 2026	Varies depending on tasks	AI allowed
Outcomes assessed:
= group assignment ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Early Feedback Quiz (5%): A quiz will be scheduled in week 3 to provide you with early feedback before the census date.
Mid Semester Exam (20%): This multiple-choice test is designed to assess your understanding of concepts introduced in the first six weeks of the unit of study.
Major group assignment (25%): The major group assignment will give you the opportunity to apply your critical reasoning and analytical problem-solving skills to case studies.
Final Exam (50%): This exam will consist of short-answer and problem-solving questions. It will test your overall knowledge and understanding of the materials covered in the unit and your ability to critically apply learnt knowledge and skills to given problems.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy (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.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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 University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to Finance	Lecture (2 hr)
Week 02	Financial Mathematics I: Time value of money and Interest rate	Lecture (2 hr)
Week 02	Introduction to Finance	Tutorial (1 hr)
Week 03	Financial Mathematics II: Annuity	Lecture (2 hr)
Week 03	Financial Mathematics I: Time value of money and Interest rate	Tutorial (1 hr)
Week 04	Valuation of Debt and Equity	Lecture (2 hr)
Week 04	Financial Mathematics II: Annuity	Tutorial (1 hr)
Week 05	Risk and Return	Lecture (2 hr)
Week 05	Valuation of Debt and Equity	Tutorial (1 hr)
Week 06	Capital Asset Pricing Model (CAPM)	Lecture (2 hr)
Week 06	Risk and Return	Tutorial (1 hr)
Week 07	Company Cost of Capital and Imputation Tax System	Lecture (2 hr)
Week 07	Capital Asset Pricing Model (CAPM)	Tutorial (1 hr)
Week 08	Equity Capital Markets	Lecture (2 hr)
Week 08	Company Cost of Capital and Imputation Tax System	Tutorial (1 hr)
Week 09	Asset Market Efficiency and Behavioural Finance	Lecture (2 hr)
Week 09	Equity Capital Markets	Tutorial (1 hr)
Week 10	Capital Budgeting I: Basic Techniques	Lecture (2 hr)
Week 10	Asset Market Efficiency and Behavioural Finance	Tutorial (1 hr)
Week 11	Capital Budgeting II: Further Issues	Lecture (2 hr)
Week 11	Capital Budgeting I: Basic Techniques	Tutorial (1 hr)
Week 12	Dividend Payout Policy	Lecture (2 hr)
Week 12	Capital Budgeting II: Further Issues	Tutorial (1 hr)
Week 13	Revision	Lecture (2 hr)
Week 13	Dividend Payout Policy	Tutorial (1 hr)

Attendance and class requirements

Students are expected to attend and participate in the lecture (2 hours) and tutorial (1 hour) as scheduled by the class timetable. While lectures will be recorded and made available on Canvas, it is important to note that the Business School does not own the recording system and cannot guarantee its reliability or ensure that every class will be recorded. Tutorial sessions will not be recorded. It is expected that students attend the tutorial each week to engage in problem-solving activities facilitated by the tutor.

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

Brealey, R. A., Myers, S. C., Allen, F. and Edmans, A. (2022); Principles of Corporate Finance (14th ed.); McGraw Hill Irwin.

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. identify and explain the basic types of financial management decisions undertaken within a corporation and the role of corporate financial manager
LO2. describe and discuss the key elements of a modern financial system, including identification and discussion of the main categories of financial institutions, types of financial instruments, and functions of different financial markets
LO3. explain and apply the basic concepts underpinning the valuation of bonds and common equity securities
LO4. explain and apply the concepts of expected return, security risk, diversification, portfolio risk, ‘beta’ and the role they play underpinning asset pricing models such as the CAPM
LO5. calculate company beta, company and divisional cost of capital, and project cost of capital
LO6. explain and apply the Net Present Value (NPV) rule for corporate capital budgeting in realistic settings, as well as appraise the merits of other alternative investment criteria
LO7. discuss and explain the concept of market efficiency as well as identify instances of weak, semi-strong and strong forms of financial market efficiency.

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
Learning outcomes

Responding to student feedback

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

The course has been updated to enhance content coherence, assessment balance, and student learning outcomes. Topics have been re-ordered and consolidated, with tutorials redesigned to cover all course topics. The assessment structure has been revised by replacing four quizzes with a mid-semester examination (20%) and reducing the major group assignment weighting to 25%. The early feedback task remains at 5%, and the final examination remains at 50% to meet CPA accreditation requirements. A new textbook, Principles of Corporate Finance (14th ed.), has been adopted to align with FINC2012, offering enhanced conceptual depth and cost efficiency for students.

Additional information

Study Commitment

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

FINC2011: Corporate Finance I

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Early feedback task

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links