Production

Value · Risk

Risk analysis

A stochastic engine runs every Monte Carlo draw through the full DCF — with expert-elicited flex tables and a genuine Bayesian price/grade calibration — reported in the P10/P50/P90 convention lenders and ICs expect.

See it

What it does

Full-DCF Monte Carlo

Each sample runs through the enterprise DCF (tax, loss carryforward, interrelated revenues) — not a reduced-form NPV.

Expert flex tables

Discrete priors sampled by inverse-CDF to preserve skew and honour min/max bounds.

Bayesian price calibration

A mean-reverting (Schwartz/OU) process with a dense-grid posterior produces per-year price cones.

Correlated commodities + grade

Composite multi-commodity price paths with copula correlation, plus an AR(1) grade cone across years.

Exceedance reporting

P10/P50/P70/P90, credible intervals, probability NPV positive, survival curves and tornado.

Covenant risk

DSCR-breach and liquidity-breach probabilities per period; fixed seed + calibration snapshot saved for audit.

How it works — the engineeringTechnical detail

NumPy prior-predictive Monte Carlo through the full DCF, inverse-CDF discrete sampling, an OU/Schwartz mean-reversion with a grid posterior, and Gaussian-copula correlation — reported in exceedance statistics. The result is a defensible NPV distribution, not a single point.

enterprise_finance/services/ · enterprise_risk_bayesian · price_calibration · calculation_engine_risk_v3