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Live Demo

👉 Try it here: https://wallstreetarena.xyz/

LLM Finance Arena

Overview

LLM Finance Arena is a full-stack benchmarking platform that evaluates large-language models acting as autonomous equity portfolio managers. The React frontend renders leaderboards, telemetry, and agent drill-downs, while a Fastify-based backend runs the trading simulation loop, fetches market data, orchestrates LLM calls, and persists state for long-running seasons. The repository is open-sourced under the MIT License so you can self-host, extend, and remix it freely.

Highlights

• Multiple agent roster – Compete LLMs such as Gemini, Claude, Grok, DeepSeek, and Qwen with identical prompts, color-coded performance histories, and leaderboard comparisons.
• Flexible data sources – Toggle between simulated ticks, real-time quotes, or historical week replays via environment flags that the backend surfaces to the UI.
• Comprehensive metrics – Track account value, Sharpe, volatility, drawdown, turnover, and benchmark series pulled from the backend snapshot payload.
• Operational tooling – Built-in connection health checks, export hooks, structured logging, autosave snapshots, and rate-limit aware market data services keep seasons stable over multi-day runs.
• Durable persistence – Toggle between local JSON snapshots or managed Postgres to survive restarts and retain multi-day history for analytics.
• API-first design – The frontend talks exclusively to REST endpoints under /api, making it straightforward to host the backend separately or swap in alternative clients.

Repository Layout

├── App.tsx                   # Root React application
├── components/               # Leaderboard, charts, info panels, detail views
├── hooks/useApiState.ts      # Polling + backend orchestration
├── services/                 # API client, market/LLM helpers
├── shared/                   # Types shared between front and back ends
├── backend/                  # Fastify simulation service (TypeScript)
│   ├── src/api/              # REST handlers exposed to the UI
│   ├── src/services/         # Market data, LLM, logging, persistence helpers
│   └── src/simulation/       # Engine, scheduler, and state management
└── docs/*.md                 # Setup, deployment, and review notes

Tech Stack

• Frontend: React 19, Vite 6, Tailwind CSS, Recharts, TypeScript.
• Backend: Fastify, TypeScript, Helmet, CORS, rate limiting, and a custom simulation engine.

Getting Started (Local Simulation)

1. Install frontend dependencies

   npm install

2. Configure frontend environment

   cp .env.example .env.local

   The only frontend variable is VITE_API_BASE, which points the UI at your backend (defaults to http://localhost:8080/api).
3. Install backend dependencies

   cd backend
   npm install

4. Create backend configuration
   • Copy the backend example and fill in your secrets privately (never commit keys):

   cd backend
   cp .env.example .env

   • Provide values for OPENROUTER_API_KEY, MODE, rate intervals, and persistence paths (see Backend Setup).
5. Run the backend (new terminal)

   cd backend
   npm run dev

   The server listens on http://localhost:8080 by default and exposes REST endpoints under /api.
6. Run the frontend (from repo root)

   npm run dev

   Vite serves the UI on http://localhost:3000. The frontend polls VITE_API_BASE (defaults to http://localhost:8080/api) every five seconds for fresh simulation data.
7. Start the season via the "Start Live" control in the header. Leaderboards, charts, and agent detail panels update automatically from backend snapshots.

Tip: If your backend runs on a different host or port, set VITE_API_BASE in .env.local to point the frontend at the correct base URL.

Simulation Modes

• Simulated (default): High-frequency random ticks—no external APIs required; great for quick demos and component development.
• Real-time: Fetches live quotes through a Yahoo → Alpha Vantage → Polygon cascade. Enable by setting MODE=realtime on the backend and providing the appropriate market-data API keys.
• Historical: Replays from a specific date at accelerated speed. Set MODE=historical plus HISTORICAL_SIMULATION_START_DATE on the backend configuration.
• Hybrid (new): Starts at a historical date in accelerated mode, then automatically transitions to real-time when caught up. Perfect for backtesting from the past and continuing live. Set MODE=hybrid plus HISTORICAL_SIMULATION_START_DATE.

All modes can be configured to auto-stop after a set number of days via MAX_SIMULATION_DAYS, or run indefinitely if not set. Each mode drives the same set of REST endpoints, so the UI updates automatically when the backend switches modes.

Trading Universe, Fees, and Cadence

• What the bots can buy: The backend exposes a curated list of tickers to every agent. Control the breadth with ARENA_TICKER_COUNT (default uses the first 20 symbols from the built-in S&P heavyweights, now expanded to cover the top 100). Provide a custom ordering by setting S_P500_TICKERS=AAPL,MSFT,... in the backend environment.
• Starting capital & sizing: Agents begin with $10,000 (configurable via INITIAL_CASH) and cannot allocate more than MAX_POSITION_SIZE_PERCENT of portfolio value to any single name.
• Execution costs: Set TRADING_FEE_BPS (basis points) and MIN_TRADE_FEE to model per-trade commissions; the defaults charge 5 bps with a $0.25 floor. These fees are applied whenever the engine executes a buy or sell.
• Cadence of decisions: The scheduler asks each agent for trades on a rolling interval—TRADE_INTERVAL_MS (default 2 hours) in simulated/historical modes and REALTIME_TRADE_INTERVAL_MS (default 30 minutes) in real-time. Between those checkpoints, intraday price ticks continue to update portfolio marks.
• Mandatory activity: The shared LLM system prompt enforces at least one trade per day when cash is available, ensuring agents stay invested instead of sitting in 100% cash.

Backend API Surface

Key endpoints exposed by backend/src/api/routes.ts:

• GET /status – Health, mode, and market telemetry.
• GET /api/simulation/state – Snapshot with agents, benchmarks, and prices.
• POST /api/simulation/start / stop / reset – Control the scheduler.
• GET /api/logs – Structured log output with level filtering.

The frontend’s services/apiClient.ts wraps these endpoints; you can reuse the same client in external dashboards or automation scripts.

Security & Privacy

• Keep API keys in backend/.env or your hosting provider's secret manager; .env files are git-ignored to prevent accidental leaks.
• Price log exports (price-logs-session-*.json) are also ignored so you can safely generate them locally without committing large or sensitive artifacts.
• No personal data is required to run the simulator.

Roadmap

• Add more factor-style metrics (e.g. factor tilts)
• Plug in alternative LLM providers
• Export results as CSV/Parquet
• “Headless” mode for CI-style benchmarks

Contributing

PRs are welcome. Please:

• Open an issue describing the change
• Keep backend/ frontend types in shared/ in sync
• Add or update docs in docs/*.md where relevant

Additional Documentation

• QUICK_START.md – Screenshot-driven setup walkthrough.
• ENV_SETUP.md – Exhaustive description of frontend .env flags and deployment settings.
• BACKEND_SETUP.md – Detailed backend configuration, APIs, and deployment tips.
• DEPLOYMENT.md – Hosting recipes for Render, Railway, and Vercel.
• POSTGRES_SETUP.md – How to provision Render Postgres and wire it into the backend.

License

LLM Finance Arena is released under the MIT License. Trading activity is simulated and provided for educational purposes only—nothing here is financial advice.