INVESTMENT MANAGEMENT GAME (IMAG)

Lesson 4: Strategic Asset Allocation

IMAG — Investment Management Game

Learning Outcomes

By the end of this lesson you will be able to:

  • Derive long-run capital market assumptions (returns, risks, correlations)
  • Design macro scenarios and assign probabilities
  • Construct an efficient SAA consistent with your IPS
  • Translate the SAA into Cesim Invest decision inputs

Teaching chapters: Drivers of Asset Prices · Data, Forecasting & Scenario Design · Strategic Research Toolkit · Strategic Asset Allocation

Capital Market Assumptions

What Are Capital Market Assumptions?

  • Long-run (10-year) forecasts of: expected returns · volatility · correlations
  • The foundation of every SAA decision
  • Sources: historical data, factor models, building-block approach, survey consensus
  • Must be consistent with your macro view and the IPS return objective

→ Content: CMA table for IMAG asset classes (to be filled with Cesim data).

The Building-Block Approach

\[\text{Expected Return} = r_f + \text{Risk Premium}\]

Asset class Components
Equities Risk-free + equity risk premium + regional premium
Corp. bonds Risk-free + term premium + credit spread
Commodities Risk-free + convenience yield + roll return

→ Content: calibrated estimates using current Cesim Economic Outlook data.

Estimating Volatility & Correlations

  • Historical volatility: rolling 3- and 5-year windows
  • Correlation instability: correlations rise during crises (diversification fails when needed)
  • Shrinkage estimators: blend historical with prior (reduces estimation error)
  • Correlation matrix visualisation (heatmap)

→ Content: worked example with IMAG asset data.

Scenario Design

Why Scenarios?

  • Point forecasts are always wrong — scenarios capture uncertainty
  • Force structured thinking about tail risks
  • Enable stress-testing of the SAA before committing
  • Required by many regulatory frameworks (IORP II, Solvency II)

A Three-Scenario Framework

Scenario Probability Description
Base case 60% Moderate growth, inflation normalising
Upside 25% Strong recovery, risk-on environment
Downside 15% Recession, credit stress, flight to quality

→ Content: fill with IMAG-specific macro assumptions per scenario.

Scenario Returns by Asset Class

→ Content: table of expected returns per asset class under each scenario; probability-weighted expected return column.

Stress Testing the SAA

  • Apply downside scenario to candidate SAA
  • Check: does portfolio breach IPS risk constraints?
  • If yes: reduce risk → revisit return objective → update IPS

→ Content: stress test template; link to Cesim back-testing tools if available.

Building the SAA

Mean-Variance Optimisation

  • Classic Markowitz framework: maximise return for a given level of risk
  • Inputs: expected returns, volatility, correlation matrix
  • Output: efficient frontier — the set of optimal portfolios

→ Content: efficient frontier diagram; locate the IPS-consistent portfolio.

Practical Constraints on the Optimiser

  • No short-selling (long-only constraint)
  • Minimum and maximum weights per asset class (IPS constraints)
  • Turnover limit (transaction cost management)
  • ESG constraint: minimum portfolio ESG score

Tip

Unconstrained optimisation produces extreme corner solutions. Always impose realistic bounds.

From Efficient Frontier to Strategic Weights

  • Select the portfolio that maximises expected return subject to the IPS risk budget
  • Round weights to practical increments (e.g. nearest 5%)
  • Check consistency with IPS: return target, risk limit, ESG score, liquidity

→ Content: final SAA weights table for IMAG (to be completed by each team).

Rebalancing Policy

  • Calendar rebalancing: restore weights monthly/quarterly regardless of drift
  • Threshold rebalancing: trigger when any weight drifts > X% from target
  • Transaction costs vs. tracking error trade-off
  • Document policy in IPS

→ Content: comparison of rebalancing strategies; recommendation for IMAG.

SAA in the IMAG Simulation

Entering Your SAA in Cesim

  • Navigate to: Strategy → Strategic Asset Allocation
  • Enter target weights for each eligible asset class
  • The system enforces that weights sum to 100%

→ Content: annotated screenshot of the Cesim SAA input screen.

What Happens Each Round

  • Your SAA is the long-run anchor — you will deviate from it tactically in Lesson 5
  • Cesim calculates benchmark return based on your SAA weights
  • Active return = portfolio return minus SAA benchmark return

Key Takeaways

  • The SAA drives 80–90% of long-run portfolio return variation
  • Scenario analysis prevents over-confidence in point forecasts
  • Every SAA weight must be justified by your IPS and CMA

Simulation Task — Lesson 4

Deliverable: Your SAA

  1. Build your capital market assumptions table (use Cesim Economic Outlook + own research)
  2. Design three scenarios with probabilities
  3. Run mean-variance optimisation (use provided template or Excel)
  4. Define final SAA weights — consistent with your IPS
  5. Submit SAA in Cesim before the round deadline

Further Reading

  • Chapter: Drivers of Asset Prices
  • Chapter: Data, Forecasting & Scenario Design
  • Chapter: Strategic Research Toolkit
  • Chapter: Strategic Asset Allocation