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Unit of study_

QBUS6820: Business Risk Management

This unit provides the basic knowledge and tools needed to understand and manage risk. It includes business cases to illustrate the nature of risk and risk management strategies. The main focus is on quantitative approaches to analysing risk through understanding the probability distributions involved. Topics covered include: Value at Risk calculations; Utility theory for decisions; Prospect theory for decisions under risk; Extreme value theory; Monte-Carlo simulation; Stochastic optimization; Robust optimization; Credit scoring; Real options.


Academic unit Business Analytics
Unit code QBUS6820
Unit name Business Risk Management
Session, year
Semester 2, 2022
Attendance mode Normal day
Location Camperdown/Darlington, Sydney
Credit points 6

Enrolment rules

ECMT5001 or QBUS5001
Assumed knowledge

Knowledge of basic probability theory and familiarity with spreadsheet modelling

Available to study abroad and exchange students


Teaching staff and contact details

Coordinator Edward Anderson,
Lecturer(s) Edward James Anderson ,
Type Description Weight Due Length
Final exam (Record+) Type B final exam Final exam
Written exam
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Small test Quizzes
Multiple choice quiz answered online through Canvas.
30% Multiple weeks 25 mins
Outcomes assessed: LO4
Assignment group assignment Measuring risk assignment
Essay on business risk plus a question on data analysis
15% Week 05 1500 words
Outcomes assessed: LO1
Assignment group assignment Stochastic optimisation assignment
Data analysis and optimisation with written report
15% Week 10 12 pages
Outcomes assessed: LO4
group assignment = group assignment ?
Type B final exam = Type B final exam ?
  • Measuring risk assignment: In groups of four, students will be required to answer two questions. The first will require an essay to be written on a real example of operational risk, analysing the factors that contributed to this. The second question will require an analysis of stock returns and their relationship to overall market returns.
  • Short quizzes: There will be 6 short quizzes each of 25 minutes delivered through Canvas that will examine the unit content from weeks 2-8 inclusive. These quizzes will assess the student’s ability to understand and estimate tail behaviour and different risk measures; to model decision choices in an expected utility framework; to model the way that people actually make decisions in risky environments; and to use the tools of stochastic optimization. 
  • Stochastic optimisation assignment: This task will involve looking at real data and testing out different stochastic optimisation approaches. Calculations for this assignment can be carried out in an Excel spreadsheet.
  • Final exam: This exam will primarily focus on the tools of robust optimisation; real option theory; and credit risk, as well as the material covered in other parts of the unit. This is an open book exam.

  Detailed information for each assessment can be found 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


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. 


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.


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.


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. 


0 - 49

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

For more information see

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.

WK Topic Learning activity Learning outcomes
Week 01 What is risk management? Lecture (2 hr)  
Week 02 What is risk management? Tutorial (1 hr)  
The structure of risk Lecture (2 hr)  
Week 03 The structure of risk Tutorial (1 hr)  
Measuring risk Lecture (2 hr)  
Week 04 Measuring risk Tutorial (1 hr)  
Understanding tail behaviour Lecture (2 hr)  
Week 05 Understanding tail behaviour Tutorial (1 hr)  
Making decisions with risk Lecture (2 hr)  
Week 06 Making decisions with risk Tutorial (1 hr)  
Risk behaviour 1 Lecture (2 hr)  
Week 07 Risk behaviour 1 Tutorial (1 hr)  
Risk behaviour 2 Lecture (2 hr)  
Week 08 Risk behaviour 2 Tutorial (1 hr)  
Stochastic optimisation 1 Lecture (2 hr)  
Week 09 Stochastic optimisation 1 Tutorial (1 hr)  
Stochastic optimisation 2 Lecture (2 hr)  
Week 10 Stochastic optimisation 2 Tutorial (1 hr)  
Robust optimisation Lecture (2 hr)  
Week 11 Robust optimisation Tutorial (1 hr)  
Real options Lecture (2 hr)  
Week 12 Real options Tutorial (1 hr)  
Credit risk Lecture (2 hr)  
Week 13 Credit risk Tutorial (1 hr)  

Attendance and class requirements

Lecture recordings: All lectures and seminars are recorded and will be available on Canvas for student use. Please note the Business School does not own the system and cannot guarantee that the system will operate or that every class will be recorded. Students should ensure they attend and participate in all classes.

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 can be accessed through the Library eReserve, available on Canvas.

  • E.J. Anderson, Business Risk Management: Models and Analysis, Wiley, Chichester, 2014.

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. classify different types of risk and discuss how they may be addressed in practice
  • LO2. calculate value at risk and expected shortfall, and analyse risk with different types of tail behaviour
  • LO3. build models of decision choices, including the use of prospect theory to describe decisions made in practice in risky environments
  • LO4. use the tools needed for stochastic optimisation, including Monte Carlo simulation, and carry out calculations based on robust optimisation and real options
  • LO5. construct and analyse a credit scorecard.

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
No changes have been made since this unit was last offered.


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