Course Outline

Module 1: Introduction to Investment Risk Modeling

• Overview of investment risk modeling and its importance for pension funds
• Key concepts and terminologies in risk modeling (e.g., volatility, correlation, value at risk)
• Introduction to risk modeling frameworks and tools
• Case Study: Risk Modeling Overview – Analyze a pension fund’s current risk profile using basic risk modeling techniques and identify key areas for improvement.

Module 2: Quantitative Risk Assessment Techniques

• Techniques for quantifying investment risk (e.g., variance-covariance method, historical simulation)
• Understanding and applying quantitative measures of risk (e.g., Value at Risk, Conditional Value at Risk)
• Using statistical methods to model and forecast risk
• Case Study: Quantitative Risk Analysis – Perform a quantitative risk assessment of a sample investment portfolio and develop recommendations for risk management.

Module 3: Stress Testing and Scenario Analysis

• Methods for conducting stress testing and scenario analysis
• Designing and implementing stress tests to evaluate investment portfolios under extreme conditions
• Analyzing the results of stress tests and incorporating insights into risk management strategies
• Case Study: Stress Testing Simulation – Conduct stress tests and scenario analyses on a pension fund’s portfolio to assess its resilience under various market conditions.

Module 4: Advanced Risk Modeling Approaches

• Exploration of advanced risk modeling approaches (e.g., Monte Carlo simulations, copulas)
• Techniques for modeling complex risk factors and interactions
• Applying advanced models to enhance risk assessment and management
• Case Study: Advanced Modeling Exercise – Develop and apply an advanced risk model to a pension fund’s investments, including Monte Carlo simulations or copulas.

Module 5: Integrating Risk Models with Investment Strategies

• Strategies for integrating risk modeling insights into investment decision-making
• Techniques for optimizing investment portfolios based on risk modeling results
• Best practices for aligning risk management with overall investment goals
• Case Study: Portfolio Optimization – Use risk modeling insights to optimize an investment portfolio for a pension fund, balancing risk and return objectives.