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Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering

Rust library for quantitative finance.

Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.

Python AutoML for Trading Systems and Sports Betting

Korea Investment & Securities Open API Github

The official Python client library for the Massive.com REST and WebSocket API.

A TD Ameritrade API client for Python. Includes historical data for equities and ETFs, options chains, streaming order book data, complex order construction, and more.

A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.

Portfolio optimization with deep learning.

Kelp is a free and open-source trading bot for the Stellar DEX and 100+ centralized exchanges

Alpaca’s official MCP Server lets you trade stocks, ETFs, crypto, and options, run data analysis, and build strategies in plain English directly from your favorite LLM tools and IDEs

Modular Python library that provides an advanced event driven backtester and a set of high quality tools for quantitative finance. Integrated with various data vendors and brokers, supports Crypto, Stocks and Futures.

Asynchronous, event-driven algorithmic trading in Python and C++

Model Context Protocol (MCP) to enable AI LLMs to trade using MetaTrader platform

Python-based framework for backtesting trading strategies & analyzing financial markets [GUI :neckbeard:]

C++ 17 based library (with sample applications) for testing equities, futures, currencies, etfs & options based automated trading ideas using DTN IQFeed real time data feed and Interactive Brokers (IB TWS API) for trade execution. libtorch/lstm/cuda demo. Support for Alpaca & Phemex. Notifications via Telegram.

A composable, real time, market data and trade execution toolkit. Built with Elixir, runs on the Erlang virtual machine

Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models

Open Source Algorithmic Trading Engine

Python framework for quantitative financial analysis and trading algorithms on decentralised exchanges

A fixed income library for pricing bonds and bond futures, and derivatives such as interest rate swaps (IRS), cross-currency swaps (XCS) and FX swaps. Contains tools for full curveset construction with market standard optimisers and automatic differentiation (AD) and risk sensitivity calculations including delta and cross-gamma.

Forex algorithmic trading framework using OANDA REST API.

Pipeline Extension for Live Trading

Quantitative systematic trading strategy development and backtesting in Julia

A python library for computing technical analysis indicators on streaming data.

From Idea to Execution - Manage your trading operation across a distributed cluster

Aggregate trade data into user-defined candles using information driven rules

Python library for backtesting technical/mechanical strategies in the stock and currency markets

Zigma is an algorithmic trading framework built with the Zig programming language, leveraging an actor-based concurrency model. It aims to provide an efficient, low-latency system for algorithmic trading through components handling market data, strategy execution, order management, risk, and data persistence.

A zero-alloc, compile-time hardened FIX engine built for sub-100ns execution.