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aiomoex

Asyncio client for MOEX ISS

asx_gym

Open AI Gym Env for Australia Stock Exchange (ASX)

autoscraper

A Smart, Automatic, Fast and Lightweight Web Scraper for Python

awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

erlyplayer

Erlyvideo player

example-scripts

Example Machine Learning Scripts for Numerai's Tournament

newsrecommendationsystem

This is a real time news scraping and recommendation system. The system uses a news pipeline to scrape latest news from various of sources such CNN, BBC. To render the news, I built a single-page web application using React. In addition, in order to customize news list for users, I designed and built a training pipeline for news topic modeling using Tensorflow.

patents

Parse, match (within and Compustat), and analyze USPTO patent data

pubmed_parser

:clipboard: A Python Parser for PubMed Open-Access XML Subset and MEDLINE XML Dataset

pyportfolioopt

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

scholar.py

A parser for Google Scholar, written in Python

stock-trading-environment

A custom OpenAI gym environment for simulating stock trades on historical price data.

stock-trading-ml

A stock trading bot that uses machine learning to make price predictions.

tensortrade

An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.

tradingview-watchlists

Automatically generated watchlists for TradingView

useful3

xgboost_stock_prediction

XGBoost is known to be fast and achieve good prediction results as compared to the regular gradient boosting libraries. This project attempts to predict stock price direction by using the stock's daily data and indicators derived from its daily data as predictors. As such this is a classification problem.