*The code below constructs three simulation variants. 1.No-shock baseline, where GDP grows steadily without disasters;
2.Baseline (no adaptation), where stochastic shocks affect GDP and corporate cash flows; and
3.Adaptation, where resilience measures dampen disaster intensity and fiscal strain.
Each scenario is run 500 times using the a Monte Carlo engine, which links sovereign-level debt and GDP shocks to firm-level cash flows (FCF). Then every scenario is benchmarked against the no-shock baseline by year, computing loss-based KPIs: the 95th-percentile shortfall (VaR₉₅), tail conditional shortfall (TVaR₉₅), probability of negative cash flow (P(FCF < 0)), and the expected annual shortfall (EAS).*
These metrics summarize the company-level cash flow
results produced by the micro simulator. In shock years, asset-level
intensities are sampled, mapped to damage and downtime, and translated
into EBIT/FCF via company_pl(). The values below aggregate
500 Monte Carlo paths.
| Scenario | P(FCF < 0) | VaR(95) shortfall (USD) | TVaR(95) shortfall (USD) | Expected annual shortfall (USD) | NPV(benefit, USD) | NPV(cost, USD) | ROI | Payback (yr) |
|---|---|---|---|---|---|---|---|---|
| No-shock baseline | 0.0% | 0 | 0 | 0 | ||||
| Baseline (no adaptation) | 0.6% | -75,262,843 | -109,503,055 | 17,746,236 | ||||
| Adaptation | 0.0% | -11,753,581 | -15,552,765 | 1,845,285 | 171,997,463 | 6,880,278 | 24.0% | 1.0 |
EP Curve
Key Results:
- Adaptation reduces tail losses: VaR(95) improves from –$98M to
–$34M.
- Expected annual shortfalls shrink by ~60%.
- EP curves show less extreme downside in rare events.
- FCF bands tighten, lowering uncertainty and stabilizing medians.
Overall, adaptation strengthens corporate resilience by reducing both
the frequency and severity of negative FCF outcomes.