Hudson and Thames Quantitative Research

mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

arbitragelab

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.

portfoliolab

PortfolioLab is a python library that enables traders to take advantage of the latest portfolio optimisation algorithms used by professionals in the industry.

backtest_tutorial

meta-labeling

Code base for the meta-labeling papers published with the Journal of Financial Data Science

arbitrage_research

Jupyter Notebook examples on how to use the ArbitrageLab - pairs trading - python library.

SecondBrain

march_applications_21

Skillset Challenge for the Apprenticeship Program

example-notebooks

june_applications_21

Skillset Challenge for the Apprenticeship Program, June 2021.

betting-against-beta

This project is based upon the paper: Frazzini, A. & Pedersen, L. (2014). Betting against beta.

definitive_guide_to_pairs_trading

guide_to_modern_portfolio_optimization

interview_april

Interview question for the jr Data Science / Machine Learning Engineer.

pykalman

Kalman Filter, Smoother, and EM Algorithm for Python

marbles

Read better test failures.

a-practitioners-guide-to-the-ONC-algorithm

Code base for the practitioner's guide to the ONC algorithm paper published with the Journal of Financial Data Science

hudsonthames-sphinx-theme

Sphinx theme for Hudson and Thames documentation

mlfinlab-quickstart

oct_applications_21

Applications to the apprenticeship program, October 2021.

MolecularNotes

My Obsidian Second Brain setup

example-data