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quantlab

A quant lab for normal people. Describe a trading idea in plain English; get a real backtest in seconds.

quantlab landing

  • Plain English is the interface. "Buy AAPL when its 50-day average crosses above its 200-day, sell when it crosses back below" turns into a full backtest.
  • Bring your own LLM key (OpenAI / Anthropic / Google). Never persisted server-side; it lives only in your browser.
  • The LLM emits a structured strategy DSL, not code. No code generation, no eval.
  • Pure-TypeScript backtest engine with free market data: Yahoo Finance (stocks, ETFs, crypto) and Polymarket (prediction markets).
  • Benchmark or it didn't happen. Every result is compared to buy-and-hold.

Quick start

npm install
npm run dev

Open http://localhost:3000, click Settings to paste your LLM API key, then describe a strategy. No key handy? Click "See an example backtest" to render a full result with demo data.

There are no environment variables to set. The key is entered in the browser and sent per-request to your provider.

Full walkthrough with screenshots: docs/USER_GUIDE.md

Scripts

Command Description
npm run dev Dev server on :3000
npm run build / npm run start Production build / serve
npm run test Vitest suite
npm run typecheck tsc --noEmit
npm run lint next lint

Architecture

  • src/lib/strategy/ · strategy DSL schema (Zod) + interpreter
  • src/lib/backtest/ · engine, metrics, trade simulator, buy-and-hold benchmark
  • src/lib/data/ · market data adapters (Yahoo Finance, Polymarket)
  • src/lib/llm/ · multi-provider LLM adapter (Vercel AI SDK)
  • src/app/api/ · server routes (compile strategy, run backtest)
  • src/app/ + src/components/ · UI (idea input, charts, metrics, trade log)

Strategy DSL

The LLM emits JSON like:

{
  "name": "SMA crossover",
  "asset": "AAPL",
  "timeframe": "1d",
  "indicators": [
    { "id": "fast", "type": "SMA", "source": "close", "period": 10 },
    { "id": "slow", "type": "SMA", "source": "close", "period": 50 }
  ],
  "entries": [
    { "side": "long", "when": { "op": "crosses_above", "left": "fast", "right": "slow" } }
  ],
  "exits": [
    { "when": { "op": "crosses_below", "left": "fast", "right": "slow" } }
  ],
  "risk": { "positionSizePct": 100, "stopLossPct": 5, "takeProfitPct": 10 }
}

This data, not code, drives the backtester · no sandbox required.

Disclaimer

Backtests model what would have happened, not what will. This is a tool to learn with, not investment advice.