hudson-and-thames Goto Github PK

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

arbitrage_research

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.

backtest_tutorial

betting-against-beta

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

definitive_guide_to_pairs_trading

example-data

example-notebooks

guide_to_modern_portfolio_optimization

hudsonthames-sphinx-theme

Sphinx theme for Hudson and Thames documentation

interview_april

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

june_applications_21

Skillset Challenge for the Apprenticeship Program, June 2021.

marbles

Read better test failures.

march_applications_21

Skillset Challenge for the Apprenticeship Program

meta-labeling

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

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.

mlfinlab-quickstart

molecularnotes

My Obsidian Second Brain setup

oct_applications_21

Applications to the apprenticeship program, October 2021.

portfoliolab

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

pykalman

Kalman Filter, Smoother, and EM Algorithm for Python

secondbrain