1.4 KiB
1.4 KiB
OpenImpact
OpenImpact is a privacy-preserving market-impact modeling stack for multi-venue execution research.
It provides:
- deterministic synthetic venue generation for safe stress testing
- a temporary-impact regression model
- federated training across venues with masked aggregation
- a SQLite governance ledger for model-update audit trails
- deterministic replay with venue-specific latency
- an evaluation path for RMSE, latency, and a simple leakage bound
What This Repo Ships
TemporaryImpactModel: fits a linear temporary-impact model from local order requests.FederatedTrainer: trains per-venue models and aggregates coefficients without exposing raw requests.GovernanceLedger: stores update metadata in SQLite.DeterministicReplayEngine: replays the same request stream reproducibly.SyntheticMarketConfig/generate_synthetic_market: builds repeatable venue datasets.evaluate_federated_setup: returns benchmark metrics against a pooled baseline.
Quick Start
python3 -m pip install -e ".[dev]"
pytest
python3 -m openimpact
Package Metadata
This project is published as idea141-openimpact-privacy-preserving and uses this README.md as its long description.
Repository Rules
- Keep the synthetic market deterministic by seed.
- Preserve the public API exported from
openimpact/__init__.py. - Update tests for every behavior change.
- Keep
test.shworking; it must run tests andpython3 -m build.