Our Mission
RiskLab is an international network of research centers headquartered in Toronto and founded by Luis Seco. We bridge the gap between academic research and practical quantitative finance, building transparent, reproducible, open-source tools for financial machine learning that turn peer-reviewed methods into libraries, notebooks, and a research handbook practitioners can actually use.
Two languages, one API
Our methods ship as open-source packages in both Python and Julia, sharing a consistent API, so a technique you learn in one language transfers directly to the other.
The reference implementation: a mature, tested library covering the full method stack, with numba-accelerated hot paths and an extensible component registry built on the NumPy and SciPy ecosystem.
A performance-oriented port that mirrors the Python API for numerical and scientific computing, adding an elegant parametric bar-type taxonomy and native speed for heavy quantitative workloads.
Learn & explore
Everything from first principles to runnable code.
Build on rigorous, reproducible quant finance
From information-driven bars to Deep-BSDE PDE solvers, explore the methods and then put them to work in your own research.