ETF5952 Quantitative methods for risk analysis
Faculty of Business and Economics
ETF5952 Quantitative methods for risk analysis is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics, offered in 2027 in Semester 1 at Caulfield. It has no prerequisites and unlocks 1 unit, leading on to 3 units in all.
- Credit points
- 6
- Offered in 2027
- Semester 1
- Caulfield
- Assessment
- Exam 40%
- and 3 other tasks
- Workload
- 144 hours
- per semester
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Requisites
Before ETF5952
No prerequisites or corequisites.
After ETF5952
1 unit list ETF5952 as a prerequisite or corequisite.
Overview
This unit equips you with a comprehensive understanding and the practical skills necessary to identify, analyse, and manage financial risks. The unit builds on foundational statistical knowledge and introduces key financial concepts essential for risk management. Additionally, you will engage in hands-on exercises and projects to perform risk analysis and modelling using the R programming language, preparing them for professional roles in finance and risk management. No prior knowledge of R or programming is required.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Caulfield | On campus |
Assessment
- Exercise25%
- Project25%
- Quiz / Test10%
- Examination40%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
identify and characterize risk using probability and statistics
- 2
quantify risk using measures such as Value-at-Risk (VaR) and Expected Shortfall (ES), and understand how risk affects investment decisions by applying the concepts of utility theory and risk-aversion
- 3
implement risk models, including historical simulation, Monte Carlo simulation, and volatility models, to compute risk measures and evaluate their effectiveness using backtesting and stress testing
- 4
apply theoretical knowledge and state-of-the-art quantitative techniques to real-world financial data using R and communicate risk analysis results clearly and effectively.
Workload and teaching
- Workshops36 hours
- Teaching approachActive learning
- Teaching approachProblem-based learning
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.
This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.
This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.
Learning resources
Technology resources
All students need access to Microsoft Excel with Excel’s “Data Analysis” add-in facility activated. (If this is already activated, it will appear on the Data tab in Excel.)
R is a free software for data analysis. For regression analysis, we will use R and RStudio.
Palisade DecisionTools Suite
We use three software packages ( StatTools , @Risk and PrecisionTree ) from Palisade Corporation’s DecisionTools Suite 7 . Each is an “add-in” to Microsoft Excel. The DecisionTools Suite is compatible with all 32-bit and 64-bit versions of Microsoft Windows from Windows XP to Windows 10, and from Excel 2007 to Excel 2016. Palisade software is not compatible with Mac OS or Office for Mac, though it is compatible with Windows Excel and Project running on Windows emulators.
There may be an additional cost associated with purchasing a physical and/or virtual calculator. Specific details will be provided in the Learning Management System by commencement of Orientation week.
All teaching material is oriented towards PCs. It does not cater to Apple, OS/2 Linux or Unix. (Mac users, please see some notes in the “EXCEL”.)
Where it fits
ETF5952 is part of 2 areas of study in the 2027 handbook.
Contacts
- Chief Examiners
- Dr Wei Wei
Common questions
What are the prerequisites for ETF5952?
ETF5952 has no prerequisites.
What can I take after ETF5952?
ETF5952 is a prerequisite or corequisite for 1 unit, including ETF5231. Those lead on to 3 units in all.
When is ETF5952 offered?
In 2027, ETF5952 runs in Semester 1 at Caulfield.
How much work is ETF5952?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does ETF5952 have an exam?
Yes. The exam is worth 40% of the final mark, alongside 3 other tasks.
Which majors and minors include ETF5952?
ETF5952 is part of Data analytics for business and Financial analytics.