Quantitative Finance and Risk Management Science

专业介绍

Navigating Two Seas: Finance and Statistics

The Interdisciplinary Major Programme in Quantitative Finance and Risk Management Science (QFRM) is jointly administered by the Department of Finance and the Department of Statistics and Data Science at The Chinese University of Hong Kong. It combines the strengths and features of two well-established and highly successful programmes from the respective departments: the Quantitative Finance programme and the Risk Management Science programme. The Programme is consistently one of the top programmes among all quantitatively related programmes in Hong Kong in terms of admission credentials. With our official tailor-made coaching schemes, students are also encouraged to participate in overseas exchanges and internships.

QFRM provides state-of-the-art training in business and finance, risk-management science, mathematics and statistics, and computing applications. Students are also required to take the Faculty Package and Capstone.

Faculty Package and Capstone

  • University Mathematics
  • Economics for Business Studies I & II
  • Banking and Finance Practicum
  • Practicum

Quantitative Finance

  • Financial Markets
  • Investment Analysis and Portfolio Management
  • Financial Management / Financial Management: Foundations and Analysis
  • Foundations in Financial Accounting / Introductory Financial Accounting
  • Risk Management and Insurance

Risk Management Science

  • Introduction to Risk Management
  • Simulation Methods for Risk Management Science and Finance
  • Statistical Modelling in Financial Markets
  • Risk Management with Derivatives Concepts
  • Stochastic Calculus for Finance and Risk
  • Financial Data Analytics with Machine Learning

Financial Technologies and Computing

  • Computer Principles and Programming(C / C++ / Java / Visual)
  • Business Information Systems / Data Structures and Applications / Fundamentals in Information Systems

Data Analytics and Artificial Intelligence

  • Statistical Computing
  • Statistical Principles of Deep Learning with Business Applications

Mathematics and Statistics

  • Linear Algebra I
  • Advanced Calculus I
  • Basic Concepts in Statistics and Probability I & II
  • Introduction to Stochastic Processes
  • Applied Regression Analysis
  • Multivariate Techniques with Business Applications
  • Actuarial Science
  • Time Series