oldrichsmejkal Goto Github PK

adv_fin_ml_exercises

Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

algobox

Open Source algorithmic trading platform in Java / Python

alphapy

Automated Machine Learning [AutoML] for Python

amazfitapks

Project prepared for the development APKs watchfaces

arch

ARCH models in Python

atlas

Machine learning workflow for use with the Gryphon Framework based on Tensorflow

auto-sklearn

Automated Machine Learning with scikit-learn

auto_ml

Automated machine learning for analytics & production

awesome-systematic-trading

A curated list of insanely awesome libraries, packages and resources for systematic trading. Crypto, Stock, Futures, Options, CFDs, FX, and more | 量化交易 | 量化投资

backtrader

Python Backtesting library for trading strategies

blankly

🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package.

bonsai-dt

Programmable Decision Tree Framework

bt

bt - flexible backtesting for Python

btgym

Scalable, event-driven, deep-learning-friendly backtesting library

catalyst

An Algorithmic Trading Library for Crypto-Assets in Python

ccxt

A JavaScript / Python / PHP cryptocurrency trading library with support for more than 100 bitcoin/altcoin exchanges

codeload-demo

Demo configuration files and strategy code for QuantRocket

crypto-price-analysis

Jupyter notebooks that analyse crypto price data

crypto-rl

Deep Reinforcement Learning toolkit: record and replay limit order book data & train a DDQN agent

cryptofeed

Cryptocurrency Feed Handler with synthetic NBBO

cryptohub

cryptostore

A storage engine for cryptocurrency data

cvxportfolio

Portfolio optimization and simulation in Python

elitequant_python

Python quantitative trading and investment platform; Python3 based multi-threading, concurrent high-frequency trading platform that provides consistent backtest and live trading solutions. It follows modern design patterns such as event-driven, server/client architect, and loosely-coupled robust distributed system. It follows the same structure and performance metrix as other EliteQuant product line, which makes it easier to share with traders using other languages.

ffn

ffn - a financial function library for Python

finance_ml

Advances in Financial Machine Learning

findatapy

Python library to download market data via Bloomberg, Quandl, Yahoo etc.

finmarketpy

Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)

ftx-spot-future-arbitrage

gryphon

Powerful, proven, and extensible framework for building trading strategies at any frequency, with a focus on crypto currencies. Battle-tested with billions traded.