arthurasenheimer Goto Github PK

followers: 25.0 following: 410.0 repos: 28.0 gists: 1.0

Name: Arthur Asenheimer

Type: User

Twitter: artasen_

Location: Germany

Blog: [email protected]

👋 Hi, I’m Arthur
👀 I’m interested in algorithmic trading and quantitative finance.
💻 I'm currently working on several projects related to automated trading systems which are based on the LEAN framework.
📫 You can find me on:
- Twitter
- Upwork

Arthur Asenheimer's Projects

alphalens

Performance analysis of predictive (alpha) stock factors

arthurasenheimer

Config files for my GitHub profile.

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

computer-science

:mortar_board: Path to a free self-taught education in Computer Science!

datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

faust

Python Stream Processing

ib_insync

Python sync/async framework for Interactive Brokers API

ibc

Automation of Interactive Brokers TWS. You can download the latest release here: https://github.com/ibcalpha/ibc/releases/latest

lean

Lean Algorithmic Trading Engine by QuantConnect (C#, Python, F#)

lean-cli

CLI for running the LEAN engine locally and in the cloud

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.

obsidian-releases

Community plugins list, theme list, and releases of Obsidian.

order-book

Fast Limit order book implementation using AVL binary trees

portfoliolab

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

pyportfolioopt

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

pysystemtrade

Systematic Trading in python

qc-strategies

Algorithmic Trading Strategies using QuantConnect/LEAN and Python

qf-lib

Modular Python library that provides an advanced event driven backtester and a set of high quality tools for quantitative finance.

research_public

Quantitative research and educational materials

sdv

Synthetic Data Generation for tabular, relational and time series data.

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.