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.

To be eligible for admission, you must satisfy the General Entrance Requirements and the following programme-specific entrance requirement:

• have 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, Actuarial Science); or equivalent.

Applicants whose entrance qualification is obtained from an institution where the medium of instruction is NOT English should also fulfill the following minimum English proficiency requirement:

• a score of 79 (Internet-based test) in the Test of English as a Foreign Language (TOEFL)^@#; or
• an overall band score of 6.5 in International English Language Testing System (IELTS)^@; or
• a score of 450 in the Chinese mainland’s College English Test Band 6 (CET-6); or
• other equivalent qualifications.

^@ TOEFL and IELTS scores are considered valid for two years. Applicants are required to provide their English test results obtained within the two years preceding the start of the University's application period.

^# Applicants are required to arrange with the Educational Testing Service (ETS) to send their TOEFL results directly to the University. The TOEFL institution code for CityU is 3401.

Students are required to complete a minimum of 30 or 31 credit units.

Course Type    

Core courses  15 credit units
Elective            15 or 16 credit units
Total                  30 or 31 credit units

Students are required to take the following core courses and select courses from a pool of elective courses listed below:

Cores

Financial Mathematics in Derivative Markets
Statistical Data Analysis
Stochastic Analysis in Finance
Advanced Stochastic Analysis in Finance
Statistical Modelling for Data Mining

Electives

Applied Partial Differential Equations
Numerical Partial Differential Equations
Project (1 credit unit)
Dissertation (6 credit units)
Stochastic Interest Rate Models
Programming and Computing in Financial Engineering
Introduction to Statistical Learning
Special Topics
Statistical Analysis of Financial Big Data
Statistical Methods and Calibration in Finance and Actuarial Science
Corporate Finance (Department of Economics and Finance)
Credit Risk Management (Department of Economics and Finance)
Times Series Analysis (Department of Biostatistics)

* All courses to be offered or not will be subject to host department's final decision and may vary from term to term.

Course Descriptions 
Department of Mathematics 
College of Science