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ArbitrageLab is a python library that enables traders who want to exploit mean-reverting portfolios by providing a complete set of algorithms from the best academic journals.
Code base for the meta-labeling papers published with the Journal of Financial Data Science
MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.
Limit Order Book Implemented in Python
This repository contains a real-world electricity consumption dataset of a hospital building.
MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.
This is a non-official implementation of the trend labeling method proposed in the paper "A Labeling Method for Financial Time Series Prediction Based on Trends".
Zama's Homomorphic Processing Unit implementation on FPGA
Small footprint and configurable Ethernet core
Open source platform for the machine learning lifecycle
Scalable data pre processing and curation toolkit for LLMs
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Vitis AI is Xilinx’s development stack for AI inference on Xilinx hardware platforms, including both edge devices and Alveo cards.
Construct a structured DataFrame from the Reuters news corpus
Python toolkit for quantitative finance
Foundry is a blazing fast, portable and modular toolkit for Ethereum application development written in Rust.
TCP/HTTP/UDP/QUIC client/server with Reactor over Netty
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
AI's query engine - Platform for building AI that can answer questions over large scale federated data. - The only MCP Server you'll ever need