phoenix-advanced-forecasting

Probabilistic forecasting overlays Monte Carlo simulations atop a validated deterministic foundation to model uncertainty in outcomes. This Skill builds living models that combine graduation rates, MOIC analysis, and scenario management with seedable randomization, enforcing 6-decimal precision and Excel parity for deterministic constraints before layering probabilistic components.

Deterministic modeling produces single-point forecasts using fixed inputs and assumptions; probabilistic modeling runs thousands of scenarios with varying inputs to show outcome distributions and risk. This Skill enforces deterministic phase constraints (JSON validation, Excel alignment) as a foundation before applying probabilistic techniques like Monte Carlo to generate decision-support insights.

Yes. Monte Carlo simulations generate outcome distributions across scenarios, enabling portfolio ranking by probability-weighted performance and reserves optimization by modeling failure rates and exit scenarios. This Skill integrates graduation and MOIC variants with scenario management to support both ranking and reserves calculations.

Validation requires enforcing deterministic core constraints: 6-decimal precision, JSON truth-case matching, and Excel parity across calculations. This Skill's phase-1 architecture validates the deterministic fund engine before phase-2 probabilistic components are added, ensuring model integrity before Monte Carlo randomization.

Probabilistic financial modeling requires high-precision deterministic inputs (6-decimal accuracy minimum) and structured formats for scenario definitions, graduation rates, and MOIC assumptions. This Skill enforces JSON validation and Excel alignment to ensure input consistency, then applies Monte Carlo with seedable randomization for reproducible probabilistic outputs.

Scenario management lets you compare constructed (what-if) versus current (baseline) outcomes by isolating specific assumption changes; Monte Carlo shows full outcome distributions under random variation. This Skill supports both—scenario construction for hypothesis testing and Monte Carlo for comprehensive risk assessment and decision-support analysis.