A curated monorepo of nine independent AI-powered trading systems covering quantitative research, listed options, prediction markets, multi-agent orchestration, and social sentiment. Each subdirectory is a self-contained codebase with its own dependencies, configuration, and documentation—brought together here as a single portfolio artifact for study, extension, and experimentation.
Maintainer: John Anthony (@anthonyjohn17)
Modern agentic trading spans many surface areas: LLM-orchestrated research graphs, broker-facing execution, RAG over proprietary or public canon, and workflow automation in CI. Rather than a single “one size fits all” bot, this stack showcases multiple architectures and risk postures side by side—from paper-only Claude Code playbooks to production-style gate pipelines and live prediction-market agents—so you can compare patterns and reuse what fits your constraints.
For a structured roadmap of possible upgrades per project, see POSSIBILITY_MAP.md.
| Directory | Focus | Highlights |
|---|---|---|
agent-quant |
Autonomous quant research | Gemini-driven strategy proposals, walk-forward validation, Streamlit UI |
ai-trader-sim |
Multi-model trading competition | MCP toolchain, US / A-share / crypto arenas, benchmark-oriented design |
kalshi-ai-trading-bot |
Prediction markets | Grok-driven multi-agent flow, Kelly-style sizing, Kalshi integration |
options-engine-crewai |
Audit-style options workflow | CrewAI agents, Schwab-oriented pipeline, “observe → measure → decide” cycles |
options-radar |
Real-time options stack | FastAPI + WebSocket, dual strategies (sentiment regime + momentum scalping) |
options-trading-bot |
Options premium / gates | Thompson sampling, 15+ gates, RAG lessons, Alpaca execution |
reddit-ai-stock-research-agent |
Social + research agents | r/wallstreetbets pipeline, GPT workflows, automation-friendly layout |
trading-agents-claude-dev |
Claude Code toolkit | 24 agents, slash-command style workflows, education / paper bias |
trading-agents |
Research-grade multi-agent graph | LangGraph debates, memory, pluggable data vendors (see upstream citation below) |
Each folder includes a README.md and a CAPABILITY_MAP.md with deeper capability notes.
┌─────────────────────────────────────────────────────────────────────────────┐
│ AI TRADING AGENTS STACK │
├─────────────────────────────────────────────────────────────────────────────┤
│ RESEARCH & SIMULATION │ EXECUTION & OPTIONS │
│ agent-quant │ options-trading-bot · options-radar │
│ ai-trader-sim │ options-engine-crewai │
│ trading-agents │ │
├─────────────────────────────────┼────────────────────────────────────────────┤
│ MARKETS & SENTIMENT │ TOOLING & IDE │
│ kalshi-ai-trading-bot │ trading-agents-claude-dev │
│ reddit-ai-stock-research-agent │ │
└─────────────────────────────────────────────────────────────────────────────┘
- Python 3.10+ (several projects target 3.11; see each
README.md/pyproject.toml). - API keys as required per project (Alpaca, OpenAI, Anthropic, Google AI, Kalshi, broker APIs, etc.). Never commit secrets—use
.envfiles and your host’s secret store. - Optional: Node.js where a subproject includes a frontend (e.g.
options-radar).
git clone https://github.com/anthonyjohn17/ai-trading-agents-stack.git
cd ai-trading-agents-stackPick a project and follow its README—for example:
cd agent-quant
# See agent-quant/README.md for Streamlit and Gemini setupcd options-trading-bot
# See options-trading-bot/README.md for Alpaca and orchestration setupcd trading-agents-claude-dev
# See trading-agents-claude-dev/README.md for Claude Code layout and commandsThere is no single shared virtualenv at the root; each codebase evolved independently. Isolate environments per directory to avoid dependency skew.
| Layer | Examples in this stack |
|---|---|
| LLM orchestration | LangChain, LangGraph, CrewAI, agent prompts + tools |
| Brokers / venues | Alpaca, Schwab (options-engine), Kalshi |
| Data | yfinance, news/sentiment APIs, vendor-specific feeds |
| UI | Streamlit, FastAPI + React (options-radar) |
| Automation | GitHub Actions (where configured in subprojects) |
- Gate pipelines (
options-radar,options-trading-bot,options-engine-crewai) — sequential hard/soft checks before capital is deployed. - Multi-agent debate (
trading-agents,options-trading-bot) — bull/bear or risk debates before a final action. - Regime awareness (
agent-quant, several options projects) — VIX/momentum or sentiment-based context for strategy selection. - RAG over “lessons learned” (
options-trading-bot) — durable memory of failures and post-mortems alongside model reasoning. - MCP and tool-first agents (
ai-trader-sim) — explicit tool contracts for repeatable agent behavior.
This collection aggregates and adapts work from multiple public lineages. The following references are preserved for credit and for anyone chasing original papers, releases, or issue trackers:
| Project / lineage | Typical upstream | Notes |
|---|---|---|
| TradingAgents (research framework) | TauricResearch/TradingAgents | Academic multi-agent trading graph; citation in trading-agents/README.md |
| AI-Trader simulation lineage | HKUDS/AI-Trader | Multi-market simulation; see ai-trader-sim/README.md |
| AgentQuant-style research agent | OnePunchMonk/AgentQuant | Named in agent-quant/README.md as upstream reference |
Subprojects may contain additional third-party references (papers, books, APIs). Those are attribution to authors, not ownership of this repo.
- Not financial advice. All code is for education, research, and engineering experimentation.
- Live trading can result in total loss. Use paper accounts and small notional sizes first.
- Laws and brokerage terms vary by jurisdiction; you are responsible for compliance.
- Rotate credentials if you ever accidentally leak keys; use repository secrets and pre-commit hooks where available.
| File | Purpose |
|---|---|
This README.md |
Portfolio overview and navigation |
POSSIBILITY_MAP.md |
Enhancement ideas across subprojects |
<project>/README.md |
Install and run instructions |
<project>/CAPABILITY_MAP.md |
Deeper capability inventory |
Issues and PRs are welcome on github.com/anthonyjohn17/ai-trading-agents-stack. Please scope changes to a single subproject per PR when possible, keep commit messages descriptive, and respect each subdirectory’s existing tests and lint rules.
Root LICENSE is MIT. Individual packages may declare their own license (MIT, Apache-2.0, etc.); check each subdirectory before redistributing or merging into commercial work.
Last updated: May 2026