C04373v2 Master of Quantitative Finance
Award(s): Master of Quantitative Finance (MQF)CRICOS code: 088930G
Commonwealth supported place?: Yes
Load credit points: 72
Course EFTSL: 1.5
Location: City campus
Notes
Commonwealth Supported Places
There are a limited number of Commonwealth Supported Places (CSPs) available in this course, which are competitive and awarded based on merit. To be considered for a CSP, applicants must:
- Indicate their interest in a CSP on their application.
- Apply on time in line with CSP deadlines (it is recommended applicants apply early as applications are assessed progressively).
Eligible applicants must accept their offer by the lapse date to retain their place. For application deadlines and information, please refer to Postgraduate courses with Commonwealth Supported Places.
30% Postgraduate Scholarship
There is a 30% Postgraduate Scholarship available in 2024. Eligible students must commence one of the Master's postgraduate quantitative finance courses in the Faculty of Science:
- C04373 - Master of Quantitative Finance; or
- C04418 - Master of Data Science in Quantitative Finance; or
- C04419 - Master of Mathematics and Quantitative Finance.
For more details, refer to the UTS Quantitative Finance Postgraduate Scholarship.
Overview
Career options
Course intended learning outcomes
Admission requirements
Recognition of prior learning
Course duration and attendance
Course structure
Course completion requirements
Course program
Articulation with UTS courses
Other information
Overview
Major regulatory changes and the emergence of new types of financial risks mean that skilled quantitative finance professionals are more in demand than ever. The UTS postgraduate Quantitative Finance program is recognised in Australia and overseas as a leading qualification for aspiring and established quantitative finance professionals.
Designed by industry experts and leading UTS quantitative finance academics, it combines the theoretical learning, hands-on experience and professional competencies required to perform at the cutting edge of this specialist discipline. Whether students are just starting out or looking to deepen their quantitative expertise, this course will equip them with the knowledge and skills to measure and manage risk in today’s complex financial markets.
Explore our quantitative finance degrees
UTS offers a suite of postgraduate quantitative finance degrees, each with a different area of focus. Students considering the Master of Quantitative Finance may also be interested in the following courses:
Course content is comprised of nine subjects that have been specifically designed for this degree and that are frequently updated to keep pace with industry need.
Students engage with the in-depth study of derivative securities, financial market instruments, probability theory, credit risk, market risk, and numerical and computational methods, among others. They also learn to apply their theoretical learning to industry-relevant assignments in areas such as risk management, valuation of financial instruments, hedging of risks and model implementation.
Career options
Graduates are highly sought after by leading financial institutions, management consulting companies, energy and mining companies, regulatory bodies, government organisations and other organisations seeking advanced quantitative expertise.
They can work as quantitative analysts, risk management analysts, quantitative structurers, quantitative developers, forecasters, traders, investment analysts and financial engineers in organisations of all sizes, from multinationals to boutique firms.
Course intended learning outcomes
| 1.1 | Appraise advanced knowledge and critically evaluate the information's source and relevance, with a focus on applications of mathematical methodologies to quantitative finance problem solving. |
| 2.1 | Investigate complex and challenging real-world problems in the areas of quantitative finance by critically evaluating information and solutions and conducting appropriate approaches to independent research. |
| 3.1 | Practice professionally adhering to confidentiality requirements, ethical conduct, data management, and organisation and collaborative skills in the context of applying mathematical and statistical modelling to quantitative finance problems. |
| 4.1 | Reflect and evaluate the value, integrity, and relevance of multiple sources of information to derive responsive, innovative solutions, show creativity, innovation and application of technologies in complex quantitative finance problems. |
| 5.1 | Develop and present complex ideas and justifications using appropriate communication approaches from a variety of methods (oral, written, visual) to communicate with mathematicians, data analysts, scientists, industry, and the general public. |
Admission requirements
To be eligible for admission to this course, applicants must meet the following criteria.
Applicants must have one of the following:
- Completed Australian bachelor's degree or higher qualification, or overseas equivalent, in Mathematical Sciences, Physics and Astronomy, Civil Engineering, Electrical and Electronic Engineering and Technology, Banking, Finance, Economic and Econometrics, or a related field of study
OR
- Completed Australian bachelor's degree or higher qualification, or overseas equivalent, with a strong mathematical background awarded at honours level
The English proficiency requirement for international students or local applicants with international qualifications is: IELTS Academic: 6.5 overall with a writing score of 6.0; or TOEFL iBT: 79-93 overall with a writing score of 21; or AE5: Pass; or PTE: 58-64 with a writing score of 50; or C1A/C2P: 176-184 with a writing score of 169.
Eligibility for admission does not guarantee offer of a place.
International students
Visa requirement: To obtain a student visa to study in Australia, international students must enrol full time and on campus. Australian student visa regulations also require international students studying on student visas to complete the course within the standard full-time duration. Students can extend their courses only in exceptional circumstances.
Recognition of prior learning
Students may be granted a maximum of 24 credit points of recognition of prior learning.
Course duration and attendance
The course is normally completed in one year of full-time study or three years of part-time study.
Course structure
The course comprises 72 credit points of core subjects.
Course completion requirements
| STM91515 Core Subjects (M Quantitative Finance) | 72cp | |
| Total | 72cp |
Course program
Typical full-time and part-time programs are provided below, showing a suggested study sequence for students undertaking the course with Autumn and Spring session commencements.
| Autumn commencing, full time | ||
| Year 1 | ||
| Autumn session | ||
| 37007 Probability Theory and Stochastic Analysis | 8cp | |
| 37011 Financial Market Instruments | 8cp | |
| 37010 Statistics and Financial Econometrics | 8cp | |
| Spring session | ||
| 37004 Interest Rates and Credit Risk Models | 8cp | |
| 37005 Fundamentals of Derivative Security Pricing | 8cp | |
| 37009 Risk Management | 8cp | |
| December session | ||
| 37003 Application of Numerical and Computational Approaches A | 8cp | |
| Summer session | ||
| 37008 Quantitative Portfolio Analysis | 8cp | |
| Year 2 | ||
| January Session | ||
| 37006 Application of Numerical and Computational Approaches B | 8cp | |
| Spring commencing, full time | ||
| Year 1 | ||
| Spring session | ||
| 37004 Interest Rates and Credit Risk Models | 8cp | |
| 37005 Fundamentals of Derivative Security Pricing | 8cp | |
| 37009 Risk Management | 8cp | |
| December session | ||
| 37003 Application of Numerical and Computational Approaches A | 8cp | |
| Summer session | ||
| 37008 Quantitative Portfolio Analysis | 8cp | |
| Year 2 | ||
| January Session | ||
| 37006 Application of Numerical and Computational Approaches B | 8cp | |
| Autumn session | ||
| 37007 Probability Theory and Stochastic Analysis | 8cp | |
| 37011 Financial Market Instruments | 8cp | |
| 37010 Statistics and Financial Econometrics | 8cp | |
| Autumn commencing, part time | ||
| Year 1 | ||
| Autumn session | ||
| 37011 Financial Market Instruments | 8cp | |
| 37007 Probability Theory and Stochastic Analysis | 8cp | |
| Spring session | ||
| 37005 Fundamentals of Derivative Security Pricing | 8cp | |
| 37009 Risk Management | 8cp | |
| December session | ||
| 37003 Application of Numerical and Computational Approaches A | 8cp | |
| Summer session | ||
| 37008 Quantitative Portfolio Analysis | 8cp | |
| Year 2 | ||
| January Session | ||
| 37006 Application of Numerical and Computational Approaches B | 8cp | |
| Autumn session | ||
| 37010 Statistics and Financial Econometrics | 8cp | |
| Spring session | ||
| 37004 Interest Rates and Credit Risk Models | 8cp | |
| Spring commencing, part time | ||
| Year 1 | ||
| Spring session | ||
| 37005 Fundamentals of Derivative Security Pricing | 8cp | |
| 37009 Risk Management | 8cp | |
| Summer session | ||
| 37008 Quantitative Portfolio Analysis | 8cp | |
| Year 2 | ||
| Autumn session | ||
| 37011 Financial Market Instruments | 8cp | |
| 37007 Probability Theory and Stochastic Analysis | 8cp | |
| Spring session | ||
| 37004 Interest Rates and Credit Risk Models | 8cp | |
| December session | ||
| 37003 Application of Numerical and Computational Approaches A | 8cp | |
| Year 3 | ||
| January Session | ||
| 37006 Application of Numerical and Computational Approaches B | 8cp | |
| Autumn session | ||
| 37010 Statistics and Financial Econometrics | 8cp | |
Articulation with UTS courses
This course is part of an articulated program comprising the Graduate Diploma in Quantitative Finance (C07132) and the Master of Quantitative Finance.
Other information
Further information is available from:
UTS Student Centre
telephone 1300 ask UTS (1300 275 887)
or +61 2 9514 1222
Ask UTS