MFE1102 — Project in Quantitative risk management
Course description
Project in Quantitative Risk Management is designed to equip students with the ability to analyze and manage financial risks using quantitative methods in real-world institutional settings such as banks, financial institutions, and investment firms. The course emphasizes the application of advanced knowledge in Mathematics, Statistics, Econometrics, and Financial Modeling to identify, measure, and control various types of risks.
Through a project-based learning approach, students will implement a full risk management cycle, including:
Risk Identification, Data Collection and Preprocessing, Quantitative Risk Modeling (e.g., market risk, credit risk, liquidity risk), Risk Measurement and Stress Testing, and Risk Reporting and Visualization.
Students will engage with practical datasets and case studies from the banking, insurance, and financial markets, and may interact with industry practitioners to gain insights into how quantitative risk models are applied in regulatory compliance (Basel III/IV), internal risk control, and strategic decision-making.
Upon completion of the course, students are required to develop a quantitative risk product (e.g., risk model, stress-testing framework, VaR/ES report, or risk dashboard) and submit a comprehensive project report that documents the methodology, empirical results, risk assessment, and data-driven risk management recommendations.
Course requirements
Attendance Regulations
Students are responsible for attending all Seminars, instructor guidance sessions, and team activities.
Students absent for more than 3 sessions (or not contributing to the group project) will be considered as failing the course and will receive a grade of 0.
Submission Regulations
Project products (Code, Data, Dashboard) must be uploaded to the Class Repository (GitHub/Google Drive) on time.
Copying code/reports from other groups or old projects is strictly prohibited. Any plagiarism will be handled according to University regulations.
Teams that do not submit reports on time will not be allowed to participate in the defense.
Lecturers
- Dr. Hoang Duc Manh
- Dr. Nguyen Thi Lien
Teaching plan
Week 1
Week 3
Week 4
Learning resources
- 1. Textbooks
- 2. Reference Materials
- . Quantitative Risk Management: Concepts — McNeil, A. J., Frey, R., & Embrechts, P., Techniques and Tools. Princeton University Press, 2015
- . Value at Risk: The New Benchmark for Managing Financial Risk. McGraw-Hill — Jorion, P., 2007
- . Risk Management and Financial Institutions. Wiley — Hull, J. C., 2021
- 3. Software