Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Qlib | 13,295 | 1 | 10 months ago | 32 | July 18, 2023 | 193 | mit | Python | ||
Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL. | ||||||||||
White Paper | 201 | 3 years ago | 1 | mit | CSS | |||||
Simple, elegant and clean jekyll theme. | ||||||||||
Compendium | 171 | a year ago | 1 | unlicense | Jupyter Notebook | |||||
The Greatest Collection of anything related to finance and crypto | ||||||||||
Stock_cnn_blog_pub | 108 | 4 years ago | apache-2.0 | Jupyter Notebook | ||||||
This project is a loose implementation of paper "Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach" | ||||||||||
Cpsc540project | 93 | 8 years ago | 1 | Matlab | ||||||
Project on financial forecasting using ML. Made by Anson Wong, Juan Garcia & Gudbrand Tandberg | ||||||||||
Msgarch | 67 | 1 | 2 years ago | 12 | January 16, 2022 | 9 | R | |||
MSGARCH R Package | ||||||||||
Defipapers | 56 | 3 years ago | Python | |||||||
I'll try to collect all the papers related to DeFi in this repository | ||||||||||
Finance Papers | 21 | 3 years ago | mit | |||||||
Archive of my research papers in finance | ||||||||||
Ca_gmvp | 18 | 2 years ago | Python | |||||||
Codes for the paper 'Clustering Approaches for Global Minimum Variance Portfolio' | ||||||||||
Dl_forfinance | 17 | 7 years ago | Jupyter Notebook | |||||||
This git repository is based on the work of J.Heaton, N.Polson and J.Witte and their articleDeep Learning for Finance: Deep Portfolios. This paper let us explore the use of deeplearning models for problems in financial prediction and classification. Our goal isto show how applying deep learning methods to these problems can produce betteroutcomes than standard methods in finance or in Machine Learning |