UnitLevel 5Postgraduate

ETF5330 Quantitative methods for financial markets

Faculty of Business and Economics

ETF5330 Quantitative methods for financial markets is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics, offered in 2025 in Semester 2 at Caulfield. It needs ETW2510, ETC3440, ETF2100, ETF5910 or ETC2410 and unlocks 1 unit.

Credit points
6
Offered in 2025
Semester 2
Caulfield
Assessment
Exam 50%
and 3 other tasks
Workload
144 hours
per semester

This is the 2025 handbook entry. See the 2027 entry.

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Requisites

Overview

This unit covers statistics and econometric tools to assess the time series properties and distributional properties of financial series. It teaches how to model and estimate the single-factor and multiple-factor capital asset pricing models; and conduct diagnostic checks and reliable statistical inferences on various risk-return relationships and financial market hypotheses. It also introduces recent literature on modelling, estimating and forecasting financial markets' volatility; and parametric and nonparametric methods to estimate the value at risk and expected shortfall. Statistical software will be used to carry out financial data analysis and applied research projects.

Offerings in 2025

Teaching periodCampusMode
Second semesterCaulfieldOn campus

Assessment

  • Quiz / Test
    10%
  • Exercise
    20%
  • Project
    20%
  • ExaminationThreshold hurdle
    50%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    analyse and interpret the time series patterns and distributional characteristics of financial data to gain insights into market trends

  2. 2

    assess the relationship between risk and return for various financial assets to make data-driven investment decisions

  3. 3

    apply statistical methods to test market hypotheses and evaluate asset pricing models

  4. 4

    analyse and model the volatility of financial returns, and utilise measures such as value-at-risk (VaR) to assess and manage potential risks associated with investment portfolios

  5. 5

    demonstrate proficiency in applying statistical software such as R to perform statistical analysis and derive meaningful insights from financial data for business applications.

Workload and teaching

  • Tutorials12 hours
  • Seminars24 hours
  • Workshops12 hours
  • Teaching approachActive 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.

Learning resources

Technology resources

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.

Where it fits

ETF5330 is part of 1 area of study in the 2025 handbook.

Contacts

Chief Examiners
Dr Wei Wei

Common questions

What are the prerequisites for ETF5330?

You need ETW2510, ETC3440, ETF2100, ETF5910 or ETC2410 before you enrol.

What can I take after ETF5330?

ETF5330 is a prerequisite or corequisite for 1 unit, including ETX5460.

When is ETF5330 offered?

In 2025, ETF5330 runs in Semester 2 at Caulfield.

How much work is ETF5330?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Does ETF5330 have an exam?

Yes. The exam is worth 50% of the final mark, alongside 3 other tasks.

Which majors and minors include ETF5330?

ETF5330 is part of Data analytics for business.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Business and Economics
Organisational unit
Department of Econometrics and Business Statistics
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 1
Study abroad
Available