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Gap addressed: existing investment tooling often relies on opaque, hard-to-audit solver code, with limited offline testing, restricted data-sharing, and weak cross-venue governance. There is a need for a lightweight, open, end-to-end toolchain that l
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README.md

APPS: Algebraic Portfolio Provenance Studio

Overview

  • Lightweight, end-to-end DSL for assets, objectives, risk budgets, and per-step plan deltas.
  • Verifiable, audit-friendly backtesting with offline-first capabilities and a minimal Graph-of-Contracts registry scaffold.
  • MVP: Python-based implementation suitable for local testing, with deterministic backtests and two toy adapters.

How to run

  • Install tooling: python -m pip install -e .
  • Run tests: pytest -q
  • Build package: python -m build

Project layout (high level)

  • algebraic_portfolio_provenance_studio_ve/: core library (dsl, simulator, registry, adapters)
  • tests/: unit tests for MVP
  • AGENTS.md: architecture and testing commands
  • test.sh: test runner script (generated in this repo)
  • READY_TO_PUBLISH: marker for publishing (created at finish)