POSTGRADUATE PROGRAMMES
MSc in Financial Mathematics
and Statistics (MSFMS)
TitleAdmission
General Information
| Programme Code | P68 |
| Mode of Study | Combined Mode |
| Normal Study Period | 1 year (full-time) 2 years (part-time / combined mode) |
| Credit Units Required for Award | 30 or 31 |
| Programme Leader | Prof Heng LIAN |
| Deputy Programme Leader | Prof Pierre NOLIN |
| Programme Leaflet | Download pdf (2025 Entry) |
Programme Details
Title
Title
Introduction
The programme emphasizes the development of students’ ability to evaluate and develop financial business and statistical models. It also provides students with the theoretical knowledge necessary for complex financial and insurance operations. Furthermore, the programme enhances their mathematical and computational skills in Financial Mathematics and Risk Management.
Graduates should be able to price various modern financial and insurance products and to assess and manage financial and insurance risks. The programme will significantly enhance the competitiveness of our graduates in the job market. It is expected that students majoring in areas like Financial Engineering, Actuarial Science, Mathematics, Statistics, Physics, Engineering, Computing and Information Technology, as well as professionals from both finance and insurance industries will benefit from this master degree programme.
Unique Features
– The programme aims at producing analytical graduates with business awareness as well as solid background in financial engineering and risk management, and to equip students with relevant theoretical knowledge as well as statistical and computational skills in a global business context.
– Students will conduct research projects with faculty members. Through classroom learning and interaction with their supervisors, students will understand the new cutting-edge techniques and develop their interests in research. Such experience will serve as the foundation for students to pursue a PhD degree.
– Graduates will be equipped with mathematical skills, contemporary finance theory and information technology knowledge, and be ready for a professional career in finance/statistical industries.
Department of Mathematics at City University of Hong Kong
The Department specializes in applied and computational mathematics. It possesses a strong team of faculty members who are experts in a wide range of applied topics. They are active researchers with excellent track records. The Department provides ideal learning environment for students and trains them in practical problem solving.
Programme Structure
Students are required to complete a minimum of 30 credit units*:
| Course type | Credit Units |
|---|---|
| Cores | 15 |
| Electives | 15 or 16 |
| Total | 30 or 31 |
* Each course carries 3 credit units, except MA6616 Project (1 credit unit) and MA6617 Dissertation (6 credit units).
Course List 2024/2025
Students are required to take the following core courses and select courses from a pool of elective courses listed below.
Core Courses
Elective Courses
| Course Code | Course Title | Credit Unit | Semester | ||||
|---|---|---|---|---|---|---|---|
| MA5601 | Applied Partial Differential Equations | 3 | A | ||||
| MA6612 | Numerical Partial Differential Equations | 3 | - | ||||
| MA6616 | Project | 1 | B & S | ||||
| MA6617 | Dissertation | 6 | A & B & S | ||||
| MA6622 | Statistical Methods and Calibration in Finance and Actuarial Science | 3 | B | ||||
| MA6627 | Stochastic Interest Rate Models | 3 | B | ||||
| MA6628 | Programming and Computing in Financial Engineering | 3 | A | ||||
| MA6630 | Introduction to Statistical Learning | 3 | B | ||||
| MA6631 | Special Topics | 3 | - | ||||
| MA6632 | Statistical Analysis of Financial Big Data | 3 | - | ||||
| MA6633 | Statistical Modelling for Data Mining | 3 | B | ||||
| MA6634 | Reinforcement Learning and Its Applications in Finance | 3 | B | ||||
| BIOS6900 | Time Series Analysis | 3 | B | ||||
| EF5042 | Corporate Finance | 3 | A & B | ||||
| EF5340 | Credit Risk Management | 3 | B |
Credit Transfer / Exemption
If applicants have completed equivalent courses at a university level, they may be eligible to apply for credit transfer (at a maximum of 9 credit units) or exemption from some programme requirements upon admission to the University. In such cases, the standard application fee will be charged in accordance with the University’s policy.
Mode of Study
Courses will be delivered on weekday evenings and Saturdays. Some courses may be taught in intensive mode by visiting experts (i.e. 39 hours to be taught in 7 weeks in Semester A/B or 5 weeks in Summer Term). Since full-time students may also take some courses along with part-time students, they may have to attend classes in the evenings and weekends.
Normative Study Period
– 2-3 semesters (full-time)
– 4-5 semesters (part-time)
Class Starts
Around September
Entrance Requirements
To be eligible for admission, the applicants must hold a first degree or a postgraduate degree in science and engineering (Mathematics, Physics, Statistics, Computer Science, Engineering, etc.), or in a related discipline (Economics, Finance, and Actuarial Science), or equivalent.
Online Application
Fees
Application fee: HK$500
Tuition fee: HK$8,200 per credit unit (subject to yearly review)
Graduation fee: HK$400
Successful applicants will be required to pay a deposit equivalent to 5 credit units.
Application Deadline (tentative)
31 January 2025
Education Loan
Successful applicants may apply for the Government’s Non-means-tested Loan Scheme. Application forms are obtainable from each District Office and the Student Financial Assistance Agency.
Enquiries: +852 2150-6222
Website: wfsfaa.gov.hk/sfo/en/index.htm
The Department of Mathematics Scholarships for Outstanding Graduates of MSFMS
A maximum of two scholarships shall be awarded to the top two students of the graduating class of Master of Science in Financial Mathematics and Statistics (MSFMS) who have achieved the best academic performance (in terms of CGPA) while meeting a minimum CGPA threshold.
Enquiries
Department of Mathematics, CityUHK
Room Y5123, Yeung Kin Man Academic Building City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong