Outline

Overview

This unit applies all aspects of finance theory to the general problem of valuing companies and other financial assets. This requires a synthesis of the concepts of present value, cost of capital, security valuation, asset pricing models, optimal capital structures and some related accounting concepts. The subject aims to reach a level of practical application that allows students to understand both the theoretical frameworks and institutional conventions of real-world corporate valuations.

Unit details and rules

Academic unit	Finance
Credit points	6
Prerequisites ?	FINC2012
Corequisites ?	None
Prohibitions ?	FINC3005
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Wei Cui, wei.cui@sydney.edu.au
Lecturer(s)	Wei Cui, wei.cui@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 The final exam will cover the topics studied throughout the semester. The final exam will be closed book. Details of the format for the final exam will be provided on Canvas.	35%	Formal exam period	2 hours	AI prohibited
Outcomes assessed:
Case studies	Individual Case Study Report Examination of a listed company with a focus on pro-forma modelling.	35%	Week 06 Due date: 02 Apr 2026 at 23:59 Closing date: 12 Apr 2026	To be advised in assignment brief.	AI allowed
Outcomes assessed:
Case studies	Group Assignment Prepare a research report and a recorded presentation analysing a listed company.	30%	Week 11 Due date: 15 May 2026 at 23:59 Closing date: 25 May 2026	To be advised in assignment brief.	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

These assessments will examine a student’s ability to carry out a valuation giving consideration to structure, valuation conventions, and methodological issues.

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.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

As prescribed by the University and Business School.

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	Introductory concepts in financial valuations (mainstream valuation techniques)	Lecture (2 hr)
Week 02	Accounting for Valuation Analysis	Lecture (2 hr)
	Accounting for Valuation Analysis	Tutorial (1 hr)
	Workshop 2: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 03	Financial Statement Analysis (FSA) and Pro-forma statement building	Lecture (2 hr)
	Financial Statement Analysis (FSA) and Pro-forma statement building	Tutorial (1 hr)
	Workshop 3: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 04	Analysing firm environment and operations	Lecture (2 hr)
	Analysing firm environment and operations	Tutorial (1 hr)
	Workshop 4: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 05	Forecasting and valuing cash flows (FCF)	Lecture (2 hr)
	Forecasting and valuing cash flows (FCF)	Tutorial (1 hr)
	Workshop 5: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 06	Alternative Valuation Models and Risk (sensitivity / scenario) analysis	Lecture (2 hr)
	Alternative Valuation Models and Risk (sensitivity / scenario) analysis	Tutorial (1 hr)
	Workshop 6: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 07	The cost of capital (cost of equity / cost of debt)	Lecture (2 hr)
	The cost of capital (cost of equity / cost of debt)	Tutorial (1 hr)
	Workshop 7: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 08	The cost of capital (cost of equity / cost of debt)	Lecture (2 hr)
	The cost of capital (cost of equity / cost of debt)	Tutorial (1 hr)
	Workshop 8: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 09	Relative valuation and the market for comparables	Lecture (2 hr)
	Relative valuation and the market for comparables	Tutorial (1 hr)
	Workshop 9: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 10	Enterprise valuation	Lecture (2 hr)
	Enterprise valuation	Tutorial (1 hr)
	Workshop 10: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 11	Valuation in a Private Equity Setting	Lecture (2 hr)
	Valuation in a Private Equity Setting	Tutorial (1 hr)
	Workshop 11: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 12	Special Topic: Valuation of Digital Assets	Lecture (2 hr)
	Special Topic: Valuation of Digital Assets	Tutorial (1 hr)
	Workshop 12: Excel Modelling (Online)	Self-directed learning (1 hr)
Week 13	Review and Final Exam Preparation	Lecture (2 hr)
	Review and Final Exam Preparation	Tutorial (1 hr)
	Workshop 13: Excel Modelling (Online)	Self-directed learning (1 hr)

Attendance and class requirements

Lectures and tutorials will be conducted on a face-to-face basis Attendance to your designated session is highly recommended.

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

All readings for this unit will be placed on Canvas. The following reference text(s) are recommended:

Titman, S. and Martin, J.D, “Valuation: The Art and Science of Corporate Investment Decisions” (3rd Edition), Pearson, 2020.
Pinto, J., Henry, E., Robinson, T., Stowe, J., “Equity Asset Valuation (3rd Edition), 2015. ISBN-13: 978-1119104261

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. Explain the approaches to and solve practical financial problems using a range of valuation techniques
LO2. Critically evaluate the models and approaches covered in this Unit of Study
LO3. Use Microsoft Excel effectively to model and solve valuation problems
LO4. Effectively communicate valuation results through a range of quantitative and qualitative outputs
LO5. Work collaboratively in a team to address and resolve complex valuation problems, while sharpening negotiation and influencing skills

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.

Improvements are part of the evolution of this course. For this semester we have made a number of changes to the structure of the course, course content, and assessment structure. These will be communicated throughout the course of the semester.

Additional information

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

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

FINC3015: Financial Valuation: Case Study Approach

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

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

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