QuantTools is AIML Solutions’ quantitative engineering lane for multisource asset data, derivatives analytics, portfolio research, and strategy infrastructure.
It is a portfolio-facing proof point for Python quant engineering, LEAN research workflows, options/greeks analysis, Pydantic data validation, canonical JSON normalization, and agent-ready query surfaces.
- Executes LEAN backtests and strategy research workflows
- Ingests multisource market, derivatives, macro, broker, and on-chain records into normalized JSON and PostgreSQL
- Validates provider payloads with Pydantic before downstream analysis
- Maintains an asset-master approach for targeted equities, ETFs, crypto assets, crypto-linked ETFs, options, futures, and rates references
- Exposes query surfaces through GraphQL and JSON-RPC
- Provides hooks for MCP-enabled agent tooling
- Supports options/greeks analytics, portfolio calculations, paper-trading ledgers, and scenario research
- Local validation suite with documented project metrics
- Multisource fixture normalization and Pydantic validation models
- Opt-in no-auth smoke checks for selected public endpoints
- Dry-run source matrix for planning provider usage without uncontrolled pulls
- LEAN, GraphQL, JSON-RPC, and local data-stack workspaces documented for continued hardening
| Area | Status | Notes |
|---|---|---|
| LEAN research workflows | Scaffold/active | Strategy workspaces are included under lean-cli/; paid/cloud runs require explicit approval |
| Market data ingestion | Scaffold/active | Broker, macro, crypto, equities, options, and on-chain ingestion paths are organized under services/ingestion/ and services/blockchain/ |
| Validation models | Active | Pydantic validation paths exist under services/validation/ and services/ingestion/ |
| Query surfaces | Scaffold/active | JSON-RPC and GraphQL-facing plans/examples exist; production hardening remains a next step |
| Options/greeks | Scaffold/active | Framework notes and VIX/options research paths exist; expand with tested calculators and examples next |
| Asset master | Planned/active | A canonical target-universe model is being formalized for provider mappings, asset tags, and portfolio research |
| On-chain analytics | Scaffold/active | Bitcoin/Ethereum/EVM tracing and Solidity review tools are organized under services/blockchain/ |
| Public dashboard | Active | GitHub Pages frontend artifacts summarize selected quant research outputs |
This repository is the strongest current technical proof point in the AIML Solutions portfolio. See docs/PROJECT-METRICS.md for the current evidence snapshot and caveats.
- docs/architecture.md
- docs/runbook.md
- docs/data-sources-and-market-hours.md
- docs/MULTISOURCE_ASSET_PIPELINE.md
- docs/AGENTIC_RESEARCH_CONTROL.md
- docs/SOURCE_SELECTION_STRATEGY.md
- docs/QUANTCONNECT_DATASET_MAP.md
- docs/PROJECT-METRICS.md
- docs/PRODUCTION_QUALITY_GATE.md
- docs/DATA_PIPELINE_SPEC.md
- docs/OPTIONS_GREEKS_PLAYBOOK.md
- docs/graphql-examples.md
- docs/ROADMAP.md
# LEAN auth
lean login
lean whoami
# bring up infra
cd infra
cp .env.example .env
docker compose up -d
# run baseline local backtest
cd ../lean-cli
lean backtest "baseline-strategy" --no-updateGenerate a dry-run source matrix without touching provider APIs:
python3 -m services.orchestration.source_matrix --purpose daily_baselineOptional no-auth public smoke tests are disabled by default:
ENABLE_NETWORK_TESTS=1 python3 -m services.ingestion.network_smoke --jsonGenerate a compact public-safe smoke report artifact:
python3 -m services.ingestion.smoke_report --out examples/smoke-report.latest.jsonlean-cli/— LEAN projects + generated backtestslean/— setup + ingestion scriptsinfra/— compose + schema bootstrapservices/validation/— Pydantic modelsservices/rpc/— JSON-RPC scaffoldservices/mcp/— MCP integration notesservices/options-greeks/— pricing framework notesservices/blockchain/— cross-lane chain analytics bridge
See CONTRIBUTING.md.
MIT — see LICENSE.