jjjerome Goto Github PK
Name: Joseph Jerome
Type: User
Bio: A quant researcher working at the intersection of machine learning and high-frequency finance.
Twitter: rl4mm
Joseph Jerome's Projects
abides
ABIDES: Agent-Based Interactive Discrete Event Simulation
academic-page
A beautiful, simple, clean, and responsive Jekyll theme for academics
alpha_avellaneda_stoikov
Phd repo
deep-reinforcement-learning-hands-on
Hands-on Deep Reinforcement Learning, published by Packt
glassnode-api-python-client
The official Python client library for Glassnode's API – https://docs.glassnode.com
hftbacktest
A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.
intro-to-data-science-in-python
Introduction to Data Science in Python / Jupyter
introtodeeplearning
Lab Materials for MIT 6.S191: Introduction to Deep Learning
jjjerome.github.io
A web page for Joseph Jerome
machine-learning-books-with-python
Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python
machine-learning-by-andrew-ng-in-python
Documenting my python implementation of Andrew Ng's Machine Learning course
machine-learning-for-trading
Code and resources for Machine Learning for Algorithmic Trading, 2nd edition.
mbt_gym
mbt_gym is a module which provides a suite of gym environments for training reinforcement learning (RL) agents to solve model-based high-frequency trading problems such as market-making and optimal execution. The module is set up in an extensible way to allow the combination of different aspects of different models. It supports highly efficient implementations of vectorized environments to allow faster training of RL agents.
ml_finance_codes
Machine Learning in Finance: From Theory to Practice Book
odsc_sota
State of the art methods with Tensorflow workshop at ODSC 2020
probabilistic-programming-and-bayesian-methods-for-hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
python-for-finance-cookbook
Python for Finance Cookbook, published by Packt
reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
rl4mm
A repository for simulating limit order book dynamics from historical data and using it to train a reinforcement learning agent to make markets.
stochastic
Generate realizations of stochastic processes in python.
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