Financial Risk Analytics (FIN326)

FIN326 Financial Risk Analytics introduces students to the quantitative and modelling techniques used to assess and manage real-world financial risks within financial institutions. The course is designed from the perspective of a risk manager responsible for interpreting and communicating risk metrics in day-to-day operations. The emphasis of the course is placed on the practical implementation and interpretation of risk measures, using real-world financial data to build models that evaluate market, credit, and operational risks. Students will apply statistical and computational tools to support decision-making in areas such as capital allocation, portfolio management, and regulatory compliance. By the end of the course, students will be equipped with the analytical skills and domain knowledge required for entry-level roles in risk management, compliance, and financial supervision.

• Overview of Financial Risk Analytics
• Statistics of financial market returns
• VaR methodology - Delta
• VaR methodology - Historical Simulation
• VaR methodology - Monte Carlo Simulation
• Factor vs Asset model
• Model backtesting
• Model risks
• Scenario Analysis
• Stress Testing
• Risk attribution and reporting
• Financial data for risk measurement

• Discuss and understand the presence of various risk models in the regulatory framework of risk management.
• Debate and discuss various financial risk models with regards to their complexity, applicability and failures.
• Compare and discuss parameter uncertainties, model risks and model stability for risk management.
• Implement risk models using either Excel or Python.
• Recommend suitable risk model for a financial product.
• Calculate the associated costs and benefits of a risk mitigation plan.