QuantLab - Backend Service

QuantLab Backend is a modular, structured API built with FastAPI. It handles quantitative strategy design, statistical analysis, backtesting, and real-time paper trading simulations.

This repository is optimized for deployment on Render, while the frontend repository (QuantLab_Frontend) is designed to be deployed on Vercel.

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Directory Structure

• 01_backtesting_engine/: Event-driven simulation engine with full portfolio accounting, commissions, and slippage.
• 02_strategies/: Concrete strategy implementations (Mean Reversion, Momentum, Pairs Trading, Multi-Factor).
• 03_data_pipeline/: Robust data download (yfinance), cleaning, and feature engineering pipeline.
• 04_research_notebooks/: Statistical tests (ADF, Cointegration) and pre-development experimentation.
• 05_risk_metrics/: Risk-adjusted performance metrics (Sharpe, Sortino, Drawdown, position sizing).
• 06_live_or_paper/: Real-time simulated execution module with structured logging.
• main.py: FastAPI entrypoint hosting the REST API endpoints.
• run_pipeline.py: CLI pipeline to run strategies locally.

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Local Setup & Run

1. Install dependencies:

   pip install -r requirements.txt

2. Run the API locally:

   uvicorn main:app --reload --port 8000

   The interactive Swagger documentation will be available at http://127.0.0.1:8000/docs.

3. Run a local backtest CLI:

   python run_pipeline.py

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Deployment to Render (Backend)

You can deploy this API to Render either as a native Python Web Service or using the included Dockerfile.

Option 1: Native Python Web Service (Recommended)

1. Sign in to Render and click New > Web Service.
2. Connect this repository (QuantLab_Backend).
3. Set the following configuration details:
   • Runtime: Python 3 (or choose Python matching your workspace)
   • Build Command: pip install -r requirements.txt
   • Start Command: uvicorn main:app --host 0.0.0.0 --port $PORT
4. Add the following Environment Variables (under the "Env" tab) if you want custom paths:
   • DATA_CACHE_DIR: data
   • PAPER_TRADING_LOG: paper_trading.log

Option 2: Dockerized Web Service

1. Create a New > Web Service on Render.
2. Connect this repository and set:
   • Runtime: Docker
3. Render will automatically build the container using the root Dockerfile and expose the port.

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Connecting with QuantLab_Frontend (Vercel)

When deploying your frontend QuantLab_Frontend to Vercel:

1. Copy your Backend URL from the Render dashboard (e.g., https://quantlab-backend.onrender.com).
2. In your frontend repository, configure the environment variable or configuration file to point to this URL.
   • For example, if using React/Vite, set:

     VITE_API_BASE_URL=https://quantlab-backend.onrender.com

   • Ensure the frontend fetch calls point to ${VITE_API_BASE_URL}/api/backtest and other endpoints.
3. Note: The backend has CORS enabled for all origins (*) by default in main.py, making it ready to receive requests from your Vercel URL.