Sample Report
DevAfri Private Foundation — Three-Portfolio Comparison
$500M Private Foundation · 10-Year Horizon · 1,000,000 Simulations
Each portfolio was run through EndowCast's simulation engine using 1,000,000 Monte Carlo paths with Cholesky-decomposed correlated asset returns. All three portfolios share identical capital market assumptions and random seeds — ensuring that differences in outcomes reflect only the effect of asset allocation, spending policy, and rebalancing strategy.
Traditional 60/40
$536.0M
Diversified Endowment Model
$571.1M
Growth-Oriented Alternatives
$587.1M
Key Metrics Comparison
| Metric | Traditional 60/40 | Diversified Endowment Model | Growth-Oriented Alternatives |
|---|---|---|---|
| Median Final Value | $536.0M | $571.1M | $587.1M▲ |
| Annualized Return | 5.72% | 6.36% | 6.68%▲ |
| Annualized Volatility | 9.10%▲ | 10.37% | 11.44% |
| Sharpe Ratio | 0.34 | 0.37 | 0.37▲ |
| Sortino Ratio | 0.20 | 0.31 | 0.35▲ |
| Max Drawdown | 18.96%▲ | 19.71% | 21.09% |
| Probability of Depletion | 0.0%▲ | 0.0%▲ | 0.0%▲ |
Across all 1,000,000 scenarios, the Growth-Oriented Alternatives portfolio (Portfolio C) delivers the highest median terminal value at $587.1M — a 9.53% premium over the Traditional 60/40. However, this comes with 11.44% annualized volatility versus 9.10% for the 60/40, and a maximum drawdown of 21.09% versus 18.96%. The Diversified Endowment Model (Portfolio B) occupies a middle ground — capturing much of the upside ($571.1M) while maintaining a Sharpe ratio of 0.37. The trade-off between return potential and capital preservation is material: Portfolio C has a 15.6% probability of losing 30% or more of purchasing power over the decade, versus 13.1% for the 60/40. Investment committees should weigh this tail risk against the $310.9M in cumulative spending capacity Portfolio C provides — $20.3M more than the 60/40 for mission deployment.
Three-Portfolio Comparison — Median Projections
Individual Portfolio Fan Charts
Traditional 60/40
Diversified Endowment Model
Growth-Oriented Alternatives
Percentile Value Table ($M)
| Year | P10 | P25 | Median | P75 | P90 |
|---|---|---|---|---|---|
| Portfolio A: Traditional 60/40 | |||||
| Year 0 | $500M | $500M | $500M | $500M | $500M |
| Year 1 | $480M | $499M | $518M | $539M | $559M |
| Year 2 | $460M | $497M | $535M | $579M | $622M |
| Year 5 | $399M | $488M | $586M | $701M | $813M |
| Year 10 | $304M | $463M | $675M | $922M | $1155M |
| Portfolio B: Diversified Endowment Model | |||||
| Year 0 | $500M | $500M | $500M | $500M | $500M |
| Year 1 | $478M | $501M | $525M | $551M | $578M |
| Year 2 | $454M | $500M | $550M | $605M | $664M |
| Year 5 | $376M | $491M | $623M | $779M | $953M |
| Year 10 | $268M | $456M | $738M | $1103M | $1505M |
| Portfolio C: Growth-Oriented Alternatives | |||||
| Year 0 | $500M | $500M | $500M | $500M | $500M |
| Year 1 | $476M | $500M | $525M | $555M | $586M |
| Year 2 | $448M | $498M | $552M | $615M | $681M |
| Year 5 | $351M | $480M | $635M | $829M | $1026M |
| Year 10 | $223M | $433M | $781M | $1276M | $1762M |
Spending Risk Statistics
| Metric | Traditional 60/40 | Diversified Endowment Model | Growth-Oriented Alternatives |
|---|---|---|---|
| Spending Policy Method | Simple Market Value | Rolling Average (3 yr) | Hybrid (70/30 CPI) |
| Total Cumulative Spending | $290.6M | $303.0M | $310.9M▲ |
| Spending Volatility | 9.20% | 10.47% | 8.08%▲ |
| Negative Spend Years | 45.38% | 42.92% | 41.45%▲ |
| Avg Spend Drawdown | 21.19% | 22.17% | 19.04%▲ |
| Max Spend Drawdown | 78.36% | 77.81%▲ | 78.38% |
Median Annual Spending Trajectory
The spending analysis reveals a central trade-off in endowment policy design. Portfolio C's Hybrid policy — blending a 70% CPI-linked baseline with a 30% market value component — delivers the lowest spending volatility (8.08%) and the lowest average spending drawdown (19.04%), despite Portfolio C carrying the highest asset-level risk. This is the Hybrid policy's structural advantage: the CPI-anchored baseline maintains grantmaking continuity during market downturns. Portfolio A's Simple Market Value policy — while generating the highest negative spend year frequency (45.38%) — also provides the most direct link between portfolio performance and spending, ensuring distributions contract quickly in bear markets to preserve long-term purchasing power. Portfolio B's Rolling Average policy occupies an intermediate position but generates the highest total cumulative spending ($303.0M invested in mission over the decade — $12.4M more than the 60/40). Foundations prioritizing grantee predictability should examine Portfolio C's Hybrid approach; those maximizing total mission deployment should consider Portfolio B; those concerned primarily with long-term corpus preservation may prefer the discipline of Portfolio A's market-linked rule.
Rebalancing Impact
Traditional 60/40
Strategy: No rebalancing. Asset class weights drift freely with market returns — serving as the baseline for comparison.
$536.0M
Endowment Model
Strategy: Annual rebalancing — 10 events over the projection horizon. Restores portfolio weights to policy targets each year.
+$3.5M (+0.61%)
P10 downside improved from $364.6M to $367.3M. Volatility reduced by 6.38%.Growth Alternatives
Strategy: Threshold-based (5% drift tolerance). Triggers only when allocations deviate beyond bands — fewer events, lower turnover.
+$2.0M (+0.34%)
P10 downside improved from $357.2M to $358.8M. Volatility reduced by 2.68%.How EndowCast Calculates Rebalancing Impact
EndowCast uses a dual-run counterfactual methodology to isolate rebalancing impact. Each portfolio configuration is simulated twice against identical market return paths — once applying the configured rebalancing strategy and once allowing the portfolio to drift freely without any rebalancing. The difference between the two runs represents the pure contribution of the rebalancing strategy, separated from all other variables including asset returns, spending policy, and fee structure. This approach is methodologically more rigorous than estimating rebalancing impact from back-of-the-envelope formulas.
Rebalancing Impact — Detailed Comparison
| Metric | A: 60/40 | B: Endowment Model | C: Growth Alt. |
|---|---|---|---|
| Rebalancing Strategy | None | Annual | Threshold (5%) |
| Median Final Value — With Rebal. | $536.0M | $571.1M | $587.1M |
| Median Final Value — No Rebal. | $536.0M | $567.6M | $585.1M |
| Net Rebalancing Impact ($) | — (baseline) | +$3.5M | +$2.0M |
| Net Rebalancing Impact (%) | — | +0.61% | +0.34% |
| P10 Downside — With Rebal. | — | $367.3M | $358.8M |
| P10 Downside — No Rebal. | — | $364.6M | $357.2M |
| Max Drift Prevented | — | 30.9% | 30.9% |
Both rebalancing strategies added measurable value over the projection horizon. Annual rebalancing (Portfolio B) contributed +$3.5M to median terminal value while reducing downside dispersion — the P10 outcome improved by $2.7M relative to the no-rebalancing counterfactual. Threshold-based rebalancing (Portfolio C) added +$2.0M with fewer rebalancing events, lowering turnover while still preventing up to 31% allocation drift. Portfolio A, simulated without rebalancing, serves as the baseline — its asset class weights, particularly the 60% public equity allocation, drifted proportionally with relative asset class performance over the decade.
Probability of Principal Loss by Threshold
IRS §4942 Compliance
Traditional 60/40
>99.9%
In all 1,000,000 simulation paths, qualifying distributions met or exceeded the required distributable amount in every year of the projection. The 5% spending rate, combined with positive expected returns, eliminates §4942 shortfall risk over this horizon.
Diversified Endowment Model
>99.9%
In all 1,000,000 simulation paths, qualifying distributions met or exceeded the required distributable amount in every year of the projection. The 5% spending rate, combined with positive expected returns, eliminates §4942 shortfall risk over this horizon.
Growth-Oriented Alternatives
>99.9%
In all 1,000,000 simulation paths, qualifying distributions met or exceeded the required distributable amount in every year of the projection. The 5% spending rate, combined with positive expected returns, eliminates §4942 shortfall risk over this horizon.
Risk Metrics Comparison
| Risk Metric | Traditional 60/40 | Diversified Endowment Model | Growth-Oriented Alternatives |
|---|---|---|---|
| Sharpe Ratio | 0.34 | 0.37 | 0.37▲ |
| Sortino Ratio | 0.20 | 0.31 | 0.35▲ |
| CVaR (95%) | -42.87% | -43.39% | -45.97%▲ |
| Max Drawdown | 18.96%▲ | 19.71% | 21.09% |
| Probability of Loss | 40.79% | 35.04% | 33.98%▲ |
| Prob. of Depletion | 0.0%▲ | 0.0%▲ | 0.0%▲ |
The risk analysis reveals a clear risk-return gradient. Portfolio C carries the most severe tail risk — a 15.6% probability of losing 30% or more of purchasing power over the decade, meaning in roughly 1 in 6 market environments, the foundation would experience severe capital impairment. For a foundation with committed multi-year grant obligations, this tail risk may be unacceptable despite the higher expected return. Portfolio A's 13.1% probability of a 30% loss represents a more conservative risk posture. The Sortino ratios — 0.20, 0.31, and 0.35 respectively — indicate that Portfolio C most efficiently compensates for its downside risk, but the absolute magnitude of that downside (21.09% max drawdown) may exceed what many investment committees are willing to accept.
Portfolio Configurations
Traditional 60/40
Asset Allocation| Asset Class | Weight | Value |
|---|---|---|
| Public Equity | 60% | $300.0M |
| Public Fixed Income | 40% | $200.0M |
Method: Simple
Rate: 5.00%
RebalancingDisabled
Diversified Endowment Model
Asset Allocation| Asset Class | Weight | Value |
|---|---|---|
| Public Equity | 45% | $225.0M |
| Private Equity | 15% | $75.0M |
| Public Fixed Income | 20% | $100.0M |
| Real Assets | 10% | $50.0M |
| Diversifying Strategies | 7% | $35.0M |
| Private Credit | 3% | $15.0M |
Method: Rolling
Rate: 5.00%
Period: 3 years
RebalancingAnnual
Growth-Oriented Alternatives
Asset Allocation| Asset Class | Weight | Value |
|---|---|---|
| Public Equity | 35% | $175.0M |
| Private Equity | 25% | $125.0M |
| Public Fixed Income | 10% | $50.0M |
| Real Assets | 15% | $75.0M |
| Diversifying Strategies | 10% | $50.0M |
| Private Credit | 5% | $25.0M |
Method: Hybrid
Rate: 5.00%
Blend: 70% CPI / 30% Market Value
Rebalancingundefined
Capital Market Assumptions
| Asset Class | Expected Return | Volatility |
|---|---|---|
| Public Equity | 7.50% | 15.00% |
| Private Equity | 10.50% | 22.00% |
| Public Fixed Income | 4.00% | 4.00% |
| Real Assets | 5.00% | 9.00% |
| Diversifying Strategies | 5.50% | 8.00% |
| Private Credit | 7.00% | 10.00% |
| Cash | 3.00% | 0.50% |
Correlation Matrix
| Pub Eq | Priv Eq | Fixed Inc | Real Ast | Div Strat | Priv Cred | Cash | |
|---|---|---|---|---|---|---|---|
| Pub Eq | 1.0 | 0.7 | 0.2 | 0.5 | 0.6 | 0.5 | 0.1 |
| Priv Eq | 0.7 | 1.0 | 0.1 | 0.4 | 0.6 | 0.6 | 0.1 |
| Fixed Inc | 0.2 | 0.1 | 1.0 | 0.2 | 0.1 | 0.2 | 0.3 |
| Real Ast | 0.5 | 0.4 | 0.2 | 1.0 | 0.4 | 0.3 | 0.1 |
| Div Strat | 0.6 | 0.6 | 0.1 | 0.4 | 1.0 | 0.5 | 0.1 |
| Priv Cred | 0.5 | 0.6 | 0.2 | 0.3 | 0.5 | 1.0 | 0.1 |
| Cash | 0.1 | 0.1 | 0.3 | 0.1 | 0.1 | 0.1 | 1.0 |
Methodology
This simulation used 1,000,000 Monte Carlo paths with Cholesky-decomposed correlated asset returns to preserve the correlation structure between all seven asset classes. Annual returns were sampled from a multivariate normal distribution calibrated to the capital market assumptions above. The simulation incorporates the configured spending rule applied to each path's portfolio value sequence, threshold-based rebalancing evaluated annually, liquidity constraints preventing forced selling of illiquid assets, and IRS §4942 compliance evaluation comparing projected qualifying distributions against the calculated distributable amount in each year and path. Rebalancing impact is calculated by running each portfolio twice against identical market return paths — once applying the configured rebalancing strategy and once allowing the portfolio to drift freely — isolating the pure contribution of rebalancing from all other variables.
Important Disclaimer
This report is a hypothetical illustration generated by EndowCast for demonstration purposes only. It does not represent actual investment results or advice. The Clearwater Family Foundation is a fictional entity. All portfolio values, returns, allocations, percentiles, and statistics are illustrative. Capital market assumptions are hypothetical and do not reflect any specific investment consultant's or OCIO's published assumptions. Past performance does not guarantee future results. Monte Carlo simulation results are inherently dependent on the input assumptions and should not be interpreted as predictions. Any foundation considering changes to its spending policy, asset allocation, or investment strategy should consult with its investment advisor, legal counsel, and tax professionals.