Through lectures, workshops, round-table discussions, case studies and expert sharing from industry practitioners, this inter-disciplinary programme taught by both Finance and Management Information Systems faculty, will widen and deepen your understanding of the rapidly changing landscape and the impact of new technologies on traditional finance models. You will be empowered with knowledge in Finance, FinTech, Financial Analytics, Machine Learning, Financial Computing, Textual Analysis, Cybersecurity, Privacy, Blockchain, Cryptocurrency, Algorithmic Trading, Financial Fraud, and Regulatory Compliance. Get well-prepared for the fast-growing demand of today’s data-driven economy, and develop new insights and perspectives towards emerging technologies and harness them to take the Financial Industry to the next level.
Academic Qualification
A Bachelor degree with honours from a recognized university or comparable institution, or a professional qualification deemed to be equivalent.
A satisfactory score on the Graduate Management Admission Test (GMAT)/Graduate Record Examination (GRE) is encouraged but not mandatory.
Language Proficiency Requirement
A minimum IELTS overall band score of 6.5; or
TOEFL score of 550 (paper-based)/79 (internet-based); or
The equivalent score of other tests.
It is mandatory for students to possess basic training/experience in Finance, Mathematics or Computer Science before embarking on the program. This requirement can be satisfied by the possession of a prior academic degree with major/minor in one of the required fields, by the completion of a substantial number of courses in these fields or by related previous working experience. Applicants who do not possess these qualifications will be required to satisfactorily complete specific preparatory courses covering areas such as quantitative methods (Mathematics, Statistics), Finance and Economics. The students should gain a “pass” in the required preparatory courses before being officially admitted to the Programme.
Qualified applicants will be required to attend an admission interview as part of the selection process.
| 序号 | 课程介绍 | Curriculum |
| 1 | 金融科技 | Financial Technology |
| 2 | 金融数据机器学习 | Machine Learning for Financial Data |
| 3 | 公司金融 | Corporate Finance |
| 4 | 投资管理 | Investment Management |
| 5 | 使用Python和R进行金融计算 | Financial Computing with Python and R |
| 6 | 区块链和加密货币 | Blockchain and Cryptocurrency |
| 7 | 金融衍生品与风险管理 | Financial Derivatives and Risk Management |
| 8 | 金融网络安全、隐私和监管技术 | Cybersecurity, Privacy and RegTech for Finance |
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