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 published methods into libraries, notebooks, and lessons that practitioners can use.
RiskLabAI in Python and Julia
Python is the current reference implementation. The Julia library is actively being expanded to narrow the remaining differences in coverage and interface.
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.
An actively developed implementation for numerical and scientific computing. Work is continuing to expand its methods and align its interface with the Python reference.
Learn & explore
Everything from first principles to runnable code.
Lessons
Mathematical ideas, visual explanations and worked examples.
Open →MIF notebooks
Public notebooks for the Machine Intelligence for Finance lessons.
Open →CIM notebooks
Public notebooks for the Causal Investment Management lessons.
Open →Software
Install the packages, browse the full method stack and read the source.
Open →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.