“Using a random seed makes the whole system deterministic.”
Not quite.A seed controls one randomness source; ordering, parallelism, libraries, hardware, and external data can still change results.
Architecture & Systems
Run Configuration and Determinism
A valuation run is defined by its configuration; determinism follows from controlling every input.
Mental model
A run is reproducible when every material input and source of randomness is controlled.
Run configuration fixes the set of trades, market snapshot, model IDs, and pricer settings (tolerances, seeds, paths).
A unique run ID ties configuration, code version, and outputs into a single reproducible artefact.
Explore the mechanism
Which explicit inputs and hidden environmental states can change the result of the same run?
This panel compares two valuation runs, A and B, as configurations: a stack of inputs feeding a Monte Carlo estimate. Change the scenario to see when runs agree bit-for-bit, when they differ only by sampling noise, and when they differ because the configuration has changed.
Differing config fields: 0
Numbers
price A ≈ 9.9763 · price B ≈ 9.9763
Difference Δ ≈ +0.0000 (+0.0 bps)
MC stderr A ≈ 0.0453 · B ≈ 0.0453
Config fields that differ: 0
Interpretation
When all configuration fields match (including the seed), Monte Carlo is bitwise deterministic: reruns are identical up to floating-point quirks. If only the seed changes, price differences stay on the scale of a few standard errors and shrink as you increase the number of paths.
Changing snapshot/model or tolerances creates structuraldifferences in the configuration. Those are the differences that should survive into a run ID and into audit trails. The practitioner’s rule: do not blame “Monte Carlo noise” for differences that actually come from changed configuration; control seeds and log everything you vary.
UNDERSTAND
What to notice
Deterministic Monte Carlo requires explicit seeding, not hidden random number generators.
Re-running with the same configuration and artefacts should produce identical results up to numerical tolerances.
Where it appears
- reproducible Monte Carlo valuation
- controlled batch risk production
- debugging environment-dependent differences
Where the intuition breaks
What this view leaves out
- Deterministic execution does not guarantee correctness, and exact reproducibility can still be affected by hardware, concurrency, or external services.
Common mistakes
Where this concept sits
Follow the strongest prerequisites, applications, extensions, and contrasts.
Connections for Run Configuration and Determinism
Run Configuration and DeterminismYOU ARE HERE
Used byReplay of Valuation RunsReplay is only meaningful when the original configuration, seeds and other deterministic settings are recoverable.
Used byRun ID and ProvenanceA run identifier should resolve to the configuration that produced the result.
UsesMarket Snapshots as BundlesDeterministic reruns require stable market inputs in addition to stable configuration and code.
Used by · Replay of Valuation Runs
Replay is only meaningful when the original configuration, seeds and other deterministic settings are recoverable.
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