Faculty of Science
CODE
63029
SUBCODE
63029-QFM-QPM
ENTRY

Sept 2024 Entry

STUDY MODE
Mixed Mode
DURATION

1.5 years (Full-time)
3 years (Part-time)

CREDIT REQUIRED

30

FUND TYPE
Self-Financed

Non-local applicants must be registered as full-time students.

Application Deadline
Local - Mixed Mode
Sept 2024 Entry - 30-Apr-2024
Non-local - Mixed Mode
Sept 2024 Entry - 30-Apr-2024
About Programme
How to Apply
Aims & Characteristics

Programme Aims

As a leading international financial centre, Hong Kong is home to many financial institutions and is a gateway to the world. To provide innovative and stable financial services in increasingly complex financial markets, professionals require advanced knowledge in mathematics, statistics, finance and programming. This programme aims to provide in-depth coursework-based training in quantitative and analytical methods, modelling techniques, financial concepts and programming skills that will allow out graduates to professionally and competitively steer decision making under different market conditions. In addition, this programme provides students with solid training in 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 competently apply the advanced quantitative methods and latest techniques that characterise financial innovation and the 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 of the courses are taught by world-leading experts in quantitative finance, data analytics, risk management and machine learning. The programme will equip graduates with solid knowledge of quantitative methods and proficient programming skills. The programme also provides professional and career training to help students to apply principles and methodologies to real-life problems in financial services and financial technology.

Recognition & Prospects

Graduates with an MSc in Quantitative Finance and FinTech possess valuable skills such as the modelling, computational and programming skills are in high demand in the finance and technology industries. With the rapid growth of the finance and technology sectors in Hong Kong, the Greater Bay Area and around the world, pursuing this degree can lead to a wide range of exciting career opportunities. Graduates can work as quantitative analysts, financial data analysts, risk managers, financial technology consultants or developers, investment managers, entrepreneurs and more. The programme prepares graduates to succeed in a dynamic and rapidly evolving business environment, making it an excellent investment in one’s future career success.

Curriculum

Programme Structure

Students studying for the MSc award need to complete the following: 

  • (Option 1) 6 Compulsory Subjects (18 credits) and 4 Elective Subjects (12 credits); OR
  • (Option 2) 6 Compulsory Subjects (18 credits), 1 Elective Subject (3 credits) and a Dissertation (9 credits) 

 

Students who opt for the Dissertation should have completed 6 Compulsory Subjects with good academic results. Normally, only students with a GPA 3.0 or above at the end of Semester 2 will be considered for Option 2.

 

Core Areas of Study

Compulsory Subjects

  • Advanced Topics in High Frequency Trading
  • Advanced Topics in Quantitative Finance
  • Financial Markets
  • Financial Technology
  • Investment Science
  • Mathematical Models of Derivative Pricing

 

Elective Subjects

(3 credits each unless specified) 

  • Accounting for Business Analysis
  • Applications of Computing and Technology in Accounting and Finance I
  • Applications of Computing and Technology in Accounting and Finance II
  • Business Risk Management
  • Deep Learning

  • Financial Analysis and Valuation with Programming
  • Fixed-income and Credit Risk
  • Forecasting and Applied Time Series Analysis
  • Machine Learning and Applications in Finance
  • Principles of Data Science
  • Statistical Machine Learning
  • Dissertation (9 credits)
Credit Required for Graduation

30

Programme Leader(s)

Programme Leader
Prof. Dai Min
BSc, MSc, MPhil, PhD

 

Deputy Programme Leader
Dr Yu Xiang
BSc, PhD

 

Assistant Programme Leader
Dr Jiang Zhaoli
BSc, PhD

Subject Area
Quantitative Finance and FinTech
Entrance Requirements
  • A Bachelor’s degree with honours in mathematics, statistics, business, finance, science, computer science, engineering, or the equivalent. Applicants with a Bachelor’s degree in other disciplines and an adequate background in mathematics or IT will also be considered.

 

If you are not a native speaker of English, and your Bachelor's degree or equivalent qualification is awarded by institutions where the medium of instruction is not English, you are expected to fulfil the University’s minimum English language requirement for admission purpose. Please refer to the "Admission Requirements" section for details.

Enquiries

For further information, please contact:
Email: msc.qfft@polyu.edu.hk

Initial Registration Credits

3 for local students
9 for non-local students

Tuition Fee

HK$12,000 per credit for local and non-local students

Additional Documents Required
Transcript / Certificate

Required

Curriculum Vitae

Required

Personal Statement

Required

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