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advances-in-financial-machine-learning

Using Dask, a Python framework, I handle 900 million rows of S&P E-mini futures trade tick data directly on a local machine. Through exploratory data analysis, continuous series creation, and bar sampling, inspired by Marcos Lopez de Prado's work, I demonstrate efficient alternatives to costly data processing methods.

algotrading

Use the zipline and pyfolio to analyze trades.

alphalens

Performance analysis of predictive (alpha) stock factors

applied-ml

📚 Papers and blogs by organizations sharing their work on data science & machine learning in production.

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.

dash-analytics-app

Dash Analytics App

dash-multi-page-app-template

data-visualization-using-python

Contains the different projects and assignments that I am going to do for my Data visualization class at Stevens FE

deep-reinforcement-learning-in-trading

This repository provides the code for a Reinforcement Learning trading agent with its trading environment that works with both simulated and historical market data. This was inspired by OpenAI Gym framework.

elk-stack-docker

financial-machine-learning

A curated list of practical financial machine learning tools and applications.

m4-methods

Data, Benchmarks, and methods submitted to the M4 forecasting competition

machine-learning-nanodegree-program

Projects carried out as part of the Machine Learning Nanodegree program offered by Udacity.com

microservices-based-algorithmic-trading-system

MBATS is a docker based platform for developing, testing and deploying Algorthmic Trading strategies with a focus on Machine Learning based algorithms.

microservices-based-algorithmic-trading-system-v-2.0

MBATS is a docker based platform for developing, testing and deploying Algorthmic Trading strategies with a focus on Machine Learning based algorithms. This repository is an advanced version of the MBATS infrastructure without any of the business logic. Compared to MBATs, here are the changes that are made in this version.

monte-carlo-simulation-using-heston-model-in-gpu

pandas-ml-quant

Master repository for the pandas-ml modules

pipeline-live

Pipeline Extension for Live Trading

pyfolio

Portfolio and risk analytics in Python

quant-trading-cloud-infrastructure

quant_infra

r-projects

research_public

Quantitative research and educational materials

simple-python-docker-debugger

stock-pattern-recorginition

think-or-swim-trade-analysis

Success leaves traits, let me see if I can find that traits of the competition winners

trading-gym

Trading Gym is an open source project for the development of reinforcement learning algorithms in the context of trading.

two-sigma-competition