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Clarabel.rs: Interior-point solver for convex conic optimisation problems in Rust.
A collection of tutorials for the MOSEK package
These are companion notebooks written in Julia and Python for: "Introduction to Applied Linear Algebra" by Boyd and Vandenberghe.
Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.
ArbitrageLab is a python library that enables traders who want to exploit mean-reverting portfolios by providing a complete set of algorithms from the best academic journals.
A sample market maker to demonstrate the usage of python-okx SDK
The Thalesians' Time Series Analysis (TSA) library
A collection of scripts and notebooks to help you get started quickly.
Material accompanying the MOSEK Portfolio Optimization Cookbook
A Library for Advanced Deep Time Series Models.
The Regularization Cookbook, published by Packt
A collection of AWESOME things about mixture-of-experts
list of papers, code, and other resources
experiments with pair trading
A data visualization and analytics component, especially well-suited for large and/or streaming datasets.
Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data.
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
Vizro is a low-code toolkit for building high-quality data visualization apps.
Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.
A fast L2/L3 orderbook data structure, in C, for Python
Solutions to Active Portfolio Management (Second Edition) by Grinold and Kahn
Additional linear models including instrumental variable and panel data models that are missing from statsmodels.
Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop
Neural Additive Models (Google Research)