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Purpose of Our Work

QuantWave was built to solve a real problem in quantitative finance:

Most existing libraries force you to choose between performance and ease of use.
Python-only libraries are slow on large datasets and live streams.
Pure Rust crates are fast but painful to integrate into modern Polars-based research workflows.

We decided to build something better.

Our Mission

To create the fastest, most complete, and most Polars-native quantitative toolkit in existence — combining:

  • 150+ technical indicators with perfect TA-Lib parity
  • Full Ehlers Digital Signal Processing suite (the most advanced cycle and trend tools available in open source)
  • Zero-copy, vectorized Polars expressions that run at Rust speed
  • Seamless batch + streaming modes for both research and live trading
  • Future-proof architecture ready for options pricing, Greeks, risk engines, and beyond

Why This Matters

Whether you are: - A quantitative researcher backtesting thousands of instruments - A systematic trader running live strategies - A hedge fund building institutional-grade tooling - A student or hobbyist who refuses to compromise on speed

…QuantWave gives you one library that works everywhere — from Jupyter notebooks to production trading systems — without ever leaving the Polars ecosystem.

Our Promise

  • Performance first — Rust under the hood, zero compromises
  • Correctness first — every indicator validated against gold-standard references
  • Developer experience first — beautiful Python API + clean Rust API
  • Community driven — MIT licensed, fully open, built for you

We are just getting started.
Options Greeks, implied volatility solvers, advanced risk metrics, and portfolio tools are already on the roadmap.

Welcome to the next generation of open-source quant tooling.

Made with ❤️ for the quant community
— The QuantWave Team