Alphanume Strategy Lab

March 1, 2026 · View on GitHub

The Alphanume Strategy Lab contains production-ready quantitative trading research powered by Alphanume market data APIs.

This repository demonstrates how Alphanume datasets can be integrated into real-world systematic trading workflows — from cross-sectional strategies to event-driven research and risk regime modeling.

Each folder contains:

  • Research context and assumptions
  • Fully reproducible Python code
  • API integration examples
  • Backtest or modeling workflows

The goal is not to publish theoretical notebooks, but to provide production-oriented examples of how practitioners can build directly on Alphanume endpoints.

What This Repository Is

  • A demonstration of real quantitative trading use cases
  • A reference implementation for API-based research pipelines
  • A foundation for systematic strategy development

What This Repository Is Not

  • Investment advice
  • A signal service
  • A black-box strategy vault

All research is fully transparent and reproducible.

Data Provider

All datasets used in this repository are sourced from:

Alphanume — Market Data APIs for Quantitative Trading

Available datasets include:

  • Historical market capitalization
  • Optionable stock history
  • Dilution events (historical + live)
  • Risk regime signals
  • Event-driven datasets

Access to the API is required to reproduce research in this repository.

Learn more: Alphanume — Market Data APIs for Quantitative Trading

Getting Started

  1. Obtain an API key
  2. Install required dependencies
  3. Run the example workflows inside each strategy folder

Each folder is self-contained and includes instructions specific to that research subject.

Philosophy

We built Alphanume because we needed datasets that did not exist in structured, accessible API form.

Strategy Lab reflects how we actually use these datasets in quantitative trading research.