Quantitative analysis, strategies and backtests
updated at Nov. 17, 2024, 8:07 p.m.
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
updated at Nov. 17, 2024, 8:04 p.m.
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace.
updated at Nov. 17, 2024, 7:06 p.m.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)
updated at Nov. 17, 2024, 6:58 p.m.
Python Backtesting library for trading strategies
updated at Nov. 17, 2024, 6:43 p.m.
Investment Research for Everyone, Everywhere.
updated at Nov. 17, 2024, 6:11 p.m.
High-performance TensorFlow library for quantitative finance.
updated at Nov. 17, 2024, 5:59 p.m.
FinRL: Financial Reinforcement Learning. 🔥
updated at Nov. 17, 2024, 5:49 p.m.
Quant/Algorithm trading resources with an emphasis on Machine Learning
updated at Nov. 17, 2024, 5:49 p.m.
A curated list of practical financial machine learning tools and applications.
updated at Nov. 17, 2024, 5:44 p.m.
📈Lightweight k-line chart that can be highly customized. Zero dependencies. Support mobile.（可高度自定义的轻量级k线图，无第三方依赖，支持移动端）
updated at Nov. 17, 2024, 5:14 p.m.
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
updated at Nov. 17, 2024, 4:44 p.m.
上海期货交易所CTP接口 Shanghai Future CTP Interface CTP Python API Wrapper
updated at Nov. 17, 2024, 2:38 p.m.