a high-performance, easy-to-use, multi-symbol, multi-strategy, multi-period, multi-account event-driven trading bot

Using the famous cnn model in Pytorch, we run benchmarks on various gpu.

Compute fractional differentiation super-fast. Processes time-series to be stationary while preserving memory. cf. "Advances in Financial Machine Learning" by M. Prado.

LOBCAST is a Python-based open-source framework for stock market trend forecasting using Limit Order Book (LOB) data.

Portfolio management with RL

C++那些事

A high-frequency trading and market-making backtesting tool accounts for limit orders, queue positions, and latencies, utilizing full tick data for trades and order books.

Resources about time series forecasting and deep learning.

The Mojo Programming Language

Generating sets of formulaic alpha (predictive) stock factors via reinforcement learning.

When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, yo…

Stock prediction using RWKV NN. Until now most of the usage done with RWKV was for LM.

Deep Transformer Q-Networks for Partially Observable Reinforcement Learning

This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).

Learn the Zig programming language by fixing tiny broken programs.

A Python library that implements ״Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting״

This repository compares the performance of 8 different regression loss functions used in Time Series Forecasting using Temporal Fusion Transformers.

GoPlus - The Go+ language for engineering, STEM education, and data science

Tutorials for GoPlus (The Go+ Language)

Cython 3.0 中文文档