CFDL

Scenarios & Run Configs

A compiled model (IR) is evaluated under a run config — so the same model answers base case, stress case, and sensitivity questions without editing the model file.

Base + stress in one run

run.json:

{
  "deterministic": {
    "annual_discount_rate": 0.10,
    "parameters": { "stream.cre.lease.base_rent:amount": 1000.0 }
  },
  "scenarios": {
    "stress": {
      "annual_discount_rate": 0.12,
      "parameters": { "stream.cre.lease.base_rent:amount": 800.0 }
    }
  }
}
cfdl run my-deal/ir.json --config run.json --out results.json

Results carry the deterministic block plus one block per scenario — same metrics, directly comparable.

Override keys

  • stream.<dotted_stream_name>:amount — replace a stream's amount.
  • cfg.<path> — set values expressions read via cfg.<path>; this is the idiomatic knob for parameters the model deliberately externalizes.

Sensitivity sweeps

Generate configs programmatically (they're plain JSON) or drive sweeps from the Python SDK, where results.scenarios() lands each scenario as a DataFrame row.

Monte Carlo

The monte_carlo section (trials, seed, optional distribution overrides) turns the same IR into a distribution — see Stochastic Modeling and the run-config reference.

Reference links