Applications for Taught Postgraduate Programmes are accepted starting from 15 November 2017.
|Year of Entry||2018|
|Mode of Funding||Non-government-funded|
|Mode of Programme||Combined †|
|Class Schedule||Weekday evenings, Saturday afternoons plus intensive mode (i.e. 39 hours to be taught in 7 weeks in Semester A/B or 5 weeks in Summer Term)|
|Indicative Intake Target||40|
|Minimum No. of Credits Required||30|
|Normal Duration of Programme||
Full-time: 1 year (2-3 semesters);
Part-time: 2 years (4-5 semesters)
|Maximum Study Period||
Full-time: 2.5 years;
Part-time/Combined mode: 5 years
|Programme Website||Click here to open|
|Tuition Fee||Click here for more information|
31 Jan 2018 (Local & Non-local)
|Mode of processing||Applications are processed on a rolling basis. Review of applications will start before the deadline and continue until all places are filled. Early applications are therefore strongly encouraged.|
Dr Q S SONG
Wayne State University, USA
+852 3442 2926
|Deputy Programme Leader||
Dr J H WANG
University of Minnesota, USA
+852 3442 2153
+852 3442 8441 (Phone)
+852 3442 0250 (Fax)
This programme is offered by the Department of Mathematics of City University of Hong Kong. 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 its graduates in the job market. It is expected that students majoring in Financial Engineering, Actuarial Science, Mathematics, Statistics, Physics, Engineering, Computing and Information Technology, etc. as well as professionals from both finance and insurance industries will benefit from this master degree programme.
The programme aims to produce 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 over 25 full-time academic 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.
Students are required to complete a minimum of 30 credit units.
Core courses 15 credit units
Elective 15 credit units
Total 30 credit units
Students are required to take the following cores and select courses from a pool of elective courses listed below:
Financial Mathematics in Derivative Markets
Statistical Data Analysis
Stochastic Analysis in Finance
Advanced Stochastic Analysis in Finance
Statistical Modelling for Data Mining
Applied Partial Differential Equations
Numerical Partial Differential Equations
Dissertation (6 credit units)
Stochastic Interest Rate Models
Programming and Computing in Financial Engineering
Introduction to Statistical Learning
Statistical Analysis of Financial Big Data
Corporate Finance (Department of Economics and Finance)
Credit Risk Management (Department of Economics and Finance)
Statistical Modeling in Risk Management (Department of Management Sciences)