Upon completion of this program, participants will be able to:

• Explain the theoretical foundations of Strategic Asset Allocation (SAA) and the role of Modern Portfolio Theory (MPT).
• Apply the **Mean-Variance Optimization (MVO)** technique to construct the efficient frontier for reserve assets.
• Design a customized, risk-aligned **Benchmark** that reflects the portfolio's strategic objectives.
• Integrate advanced risk-budgeting techniques into the SAA process.
• Evaluate the role of non-traditional assets (e.g., equities, gold) in enhancing the portfolio's risk-adjusted return.
• Understand the legal and governance requirements for formal SAA review and implementation.
• Develop a framework for estimating long-term asset class returns, volatility, and correlations.
• Formulate a comprehensive SAA proposal and its corresponding benchmark for a central bank reserve portfolio.

• Central Bank Reserves Strategists and Quantitative Analysts
• Investment Committee Members and Senior Management
• Government Investment Fund Portfolio Managers
• Fixed Income and Multi-Asset Portfolio Managers
• Academics and Consultants specializing in Asset Allocation
• Middle Office Risk Management Professionals

MVO portfolio optimization exercises (software-based), Group project on benchmark design and customization, Risk budgeting allocation workshops, Case studies on SAA performance during crisis periods, Technical deep dives into covariance modeling, Discussions on ESG integration in SAA.

Unit 1: SAA Foundations and Objectives

• The role of SAA as the main driver of long-term returns and risk.
• Review of **Modern Portfolio Theory (MPT)** and the concept of the efficient frontier.
• Defining the long-term investment horizon and policy constraints for reserve assets.
• The integration of liquidity and safety mandates into the risk-return framework.

• Methodologies for estimating expected long-term returns for key reserve asset classes (e.g., government bonds, inflation-linked bonds).
• Estimating historical and forward-looking volatility and correlation matrices.
• The use of Black-Litterman and other advanced models to incorporate market views.
• Challenges in modeling non-linear risk and tail events.

Unit 2: SAA Methodologies

• The mathematical process of constructing the **efficient frontier** using MVO.
• Applying practical constraints to the MVO (e.g., liquidity limits, credit quality floors).
• Interpreting the output of the MVO (Sharpe Ratio, risk contribution, capital allocation line).
• Limitations of MVO (e.g., sensitivity to input estimates, normal distribution assumption).

• The principles of **Risk Parity** and its application in reserves management.
• Liability-Driven Investing (LDI) and its relevance for reserve liabilities.
• Integrating dynamic or time-varying risk factors into the allocation process.
• The concept of **Risk Budgeting** and its use in managing portfolio risk contribution.

Unit 3: Benchmark Setting and Implementation

• The role of the benchmark: measuring performance, controlling risk, and guiding active management.
• Criteria for a valid benchmark (e.g., unambiguous, measurable, appropriate).
• Designing a customized benchmark that aligns with the SAA and liquidity tranches.
• The policy for formal review and rebalancing of the benchmark.

• Translating the SAA into an operational **Policy Portfolio**.
• The process of rebalancing the portfolio to the SAA (drift tolerance, frequency).
• Defining the bounds for **Tactical Asset Allocation (TAA)** deviations from the SAA.
• Middle office control: monitoring risk against the SAA and benchmark.

Unit 4: Future Trends and Policy Integration

• Incorporating **ESG (Environmental, Social, Governance)** and climate change risk into SAA models.
• Analyzing the impact of geopolitical fragmentation on currency and country allocation.
• The role of non-traditional assets (e.g., equities, corporate credit) in strategic reserves.
• Impact of Central Bank Digital Currency (CBDC) on asset class returns and liquidity.