Master of Science in Quantitative Finance and FinTech
Entrance Year Sept 2025
Programme Code 63029
Stream Code
QFM (Full-time)
QPM (Part-time)
Mode of Study Mixed Mode
Normal Duration
1.5 years (Full-time)
3 years (Part-time)
Fund Type Self-Financed
Credits Required for Graduation
31
Initial Registration Credits
3 for local students
9 for non-local students
Local Application Deadline 30 Apr 2025 * Early Round Application Deadline: 2024-11-21; Main Round Application Deadline: 2025-04-30
Non-Local Application Deadline 30 Apr 2025 * Early Round Application Deadline: 2024-11-21; Main Round Application Deadline: 2025-04-30
Tuition Fees
HK$12,900 per credit for local and non-local students
(Note: There is no tuition charge for the 1-credit Academic Integrity and Ethics subject.)
Programme Leader(s)
Programme Leader
Dr Yu Xiang
BSc, PhD
Deputy Programme Leader
Dr Jiang Zhaoli
BSc, PhD
Assistant Programme Leader
Dr Fan Jiacheng
BSc, PhD
Remarks
Non-local applicants must be registered as full-time students.
Entry scholarships will be granted to applicants with excellent academic achievements. Please refer here for further details.
Aims and Characteristics
Programme Aims
As one of the leading international financial centres, Hong Kong is the home for many financial institutions and a gateway for the country to the world. To provide innovative and stable financial services in the face of more complex financial markets, advanced knowledge in mathematics, statistics, finance, and programming are imminently required. This programme aims to provide in-depth coursework-based training in quantitative and analytical methods, modeling techniques, financial concepts and programming skills that allow the graduates to steer the decision making professionally and competitively under different market environment. In addition, this programme also targets at solid training of students on a variety of new skills and techniques demanded by the new era of financial technology including artificial intelligence, blockchain, cloud computing and big data. Our graduates will become leading professionals in the financial industry and related fields and will be competent in applying the advanced quantitative methods and latest techniques in financial innovation and development of financial technology.
Characteristics
The programme is hosted by the Department of Applied Mathematics and supported by the School of Accounting and Finance, meeting the multi-disciplinary nature of quantitative finance and financial technology. All courses are taught by leading experts in quantitative finance, data analytics, risk management and machine learning. The programme will equip graduates with solid knowledge in quantitative methods and proficient skills in programming. The programme also provides professional and career training to help students to apply principles and methodologies in formulating and solving real-life problems in financial services and financial technology.
Dual Master of Science in Financial Engineering and Quantitative Finance & FinTech offered by New York University and The Hong Kong Polytechnic University
We are excited to announce the launch of a groundbreaking dual Master's degree programme in Financial Engineering and Quantitative Finance & FinTech, offered in collaboration between the Department of Finance and Risk Engineering at the Tandon School of Engineering, New York University (NYU), and the Department of Applied Mathematics at The Hong Kong Polytechnic University (PolyU). Starting in the 2024/25 academic year, this innovative program is open for applications from the 2024/25 intake cohort. The first group of PolyU students will have the unique opportunity to study at NYU during the 2025/26 academic year. This dual degree programme combines the strengths of both institutions, providing students with a comprehensive education that bridges the fields of finance, engineering, and technology, preparing them for leadership roles in the rapidly evolving financial landscape.
For details, please check out DUAL MASTER'S DEGREE session.
Enquiry
Ms Elki Wong
- TU732, Block T, PolyU
- (852) 3400 3747
- msc.qfft@polyu.edu.hk