BFF5270 Chap.3 Capital Market Assumptions
Capital Market Assumptions
Capital-market assumptions estimate expected returns, risks and correlations for portfolio decisions. This chapter examines risk-free foundations, historical and model-based risk-premium methods, country adjustments, forecast windows and economic overlays. The key discipline is to keep the method attached to the number, maintain consistent units and show how uncertainty in the input could change the allocation.
Sensitivity analysis converts disagreement between methods into a decision range rather than hiding it behind false precision. Each estimate should remain traceable to its evidence, horizon and review trigger.
What this chapter covers
- 01
Risk-free foundation
- 02
Equity risk premium
- 03
Historical extrapolation
- 04
Economic overlay
- 05
Country adjustment
- 06
Volatility scaling
- 07
Survey forecast
Worked example · free
Scale a base-market equity premium
- 1Convert the volatilities to consistent decimal units: 0.16 and 0.23.
- 1Calculate the volatility ratio: 0.23 divided by 0.16 = 1.4375.
- 1Scale the base premium: 4.8% times 1.4375 = 6.9%.
- 1Subtract the base premium: 6.9% minus 4.8% = 2.1 percentage points.
- 1State that the estimate depends on the selected volatility window and method.
Key terms
- Market Assumptions
- Capital-market assumptions are forward-looking estimates of return, risk and correlation.
- Default Spread
- A default spread is yield compensation associated with the possibility that a borrower will not pay as promised.
- Historical Premium
- A historical premium estimates compensation from realised returns over a selected past sample.
- Economic Overlay
- An economic overlay adjusts a baseline forecast using a stated view about the coming regime.
- Forecast Horizon
- A forecast horizon is the future period over which an assumption is intended to apply.
Capital Market Assumptions FAQ
Why is a government yield not automatically risk free?
The analyst must consider default risk, currency, maturity, liquidity and the decision horizon. Some sovereign yields contain compensation for risks that a genuine risk-free foundation should exclude. A quoted government rate can be convenient and still be mismatched to the liabilities or cash flows being analysed.
What is wrong with using only a historical average?
A historical average depends on the chosen sample, market composition, valuation starting point and economic regime. A short sample is noisy, while a long sample can mix structures that no longer resemble the forecast period. History should be combined with a stated economic rationale and sensitivity range.
How should forecast methods be combined?
Use each method to expose a different assumption. History provides distributional evidence, economic models connect drivers, implied methods reflect current prices and surveys provide an external comparison. Differences across methods should be explained rather than hidden inside an uncritical average that creates false precision.
Exam move
For every assumption, write the method, horizon, currency, data window and limitation. Recompute one country-premium example with consistent units, then change the volatility ratio to confirm the direction. Compare a short historical window, long historical window and economic overlay in words. Finish by explaining which input uncertainty matters most for the allocation decision.
Build an assumption register with separate rows for the risk-free rate, risky expected returns, volatilities and correlations. The risk-free row should state default quality, maturity and currency. The expected-return rows should show the risk-premium method rather than only a final percentage. The risk rows should use the same forecast horizon as the return rows.
Work the volatility-scaling calculation twice: first with percentages converted to decimals, then with the ratio formed from matching percentage values. The ratio should agree because it is dimensionless. Label the target premium and incremental country component separately so percent and percentage points are not confused.
For historical extrapolation, compare a short recession-heavy window with a longer expansion-heavy window. Write what each sample overweights and propose a transparent economic overlay for the expected regime. Do not average two forecasts until you can explain what information each adds.
Add a sensitivity column showing how the proposed allocation changes if the premium is lower, volatility is higher or correlation rises in stress. This turns uncertainty into a portfolio consequence. During final review, test internal consistency: a high expected return paired with implausibly low risk deserves challenge, and diversification claims should weaken when correlations converge.
End by writing one sentence that distinguishes an estimate from a fact and names the next event that should trigger a forecast review. Build a final comparison note with four headings: historical, intrinsic or economic, country-risk and survey evidence. Under each heading, write one strength, one weakness and one condition that would make the method unsuitable. Then reconcile the range without hiding it.
If the proposed allocation changes across plausible inputs, report the sensitivity openly and recommend a decision that remains workable across more than one forecast path.
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