OpenByteInc/QuantDinger
The most complete open-source, self-hosted Agentic Trading OS—AI research, Python strategies, factor discovery, backtesting, optimization, paper/live multi-asset execution, risk controls, monitoring, MCP, and multi-tenant SaaS in one auditable stack.
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
QuantDinger - Open-Source AI Quant Research Platform Turn trading ideas into Python strategies, backtests, paper trading, live execution, and monitoring — all in one self-hosted stack. QuantDinger is a product of Open Byte Inc. AI research → Strategy code → Backtest → Paper/Live execution → Monitoring SUPPORTED BY ▶ Watch the latest QuantDinger product tour on YouTube QuantDinger is an open-source AI Trading OS for independent traders, Python strategy authors, and small teams. Its local-first, self-hosted design keeps market data, strategy code, broker credentials, and deployment under the operator's control. The project combines: It is not a black-box signal service. Strategy code, risk settings, credentials, and deployment remain under the operator's control. to 40 registered technical, fundamental, TA-Lib, or Qlib factors. It uses a time-ordered holdout, out-of-sample IC retention, Benjamini-Hochberg false-discovery control, cost-aware scoring, factor-life-cycle labels, and cross-factor IC correlation. The same workflow is available from the web UI, Human…
Read the full README ↗ · Preview checked 2026-11-07T12:25:44.790Z
Inside the original README — Document outline
- Watch QuantDinger in action
- What QuantDinger is
- Strategy evolution and signal-only virtual accounts
- What changed in v5
- Architecture
- Quick start
- Fastest cloud deployment: AWS Marketplace
- Option A: prebuilt images
- Docker administrator and settings notes
- Option B: source checkout
- Production deployment
- Local endpoints
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Links from the README
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Documentation belongs to its respective authors. Reported project/model license: Apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
The most complete open-source, self-hosted Agentic Trading OS—AI research, Python strategies, factor discovery, backtesting, optimization, paper/live multi-asset execution, risk controls, monitoring, MCP, and multi-tenant SaaS in one auditable stack.
Repository facts
- Owner
- OpenByteInc
- Primary language
- Python
- Stars
- 13,592
- Forks
- 2,773
- Open issues + pull requests
- 38
- License
- Apache-2.0
- Archived
- No
- Default branch
- main
- Created
- 2025-12-28T18:39:26.000Z
- Last push
- 2026-11-06T18:09:36.000Z
Topics and intended use
Owner-supplied topics: agentic-ai, ai-agents, backtesting, crypto, finance, fintech, investment, llm, market-data, mcp, mcp-server, multi-agent, portfolio-management, python, quant, quantitative-finance, risk-management, self-hosted, stock-market, technical-analysis
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
Evaluate before installing
Review licensing and dependencies, inspect recent commits and unresolved issues, and test in an isolated environment before production use. Stars and forks alone cannot answer these questions.
Source and freshness
Source: GitHub. Metadata observed 2026-11-07T12:23:45.521Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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