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Translatedstock. Get stock data, calculate stock indicators, chip distribution, identify stock patterns, comprehensive stock selection, stock selection strategies, stock verification and backtesting, automatic stock trading, supports PC and mobile devices.
Algorithmic trading and quantitative trading open source platform to develop trading robots (stock markets, forex, crypto, bitcoins, and options).
🔎 📈 🐍 💰 Backtest trading strategies in Python.
📈 Get real-time stocks from TradingView
MCP server for market analysis in AI assistants: screeners, multi-timeframe technical analysis, backtests and sentiment for crypto, stocks, forex and futures. 39 tools. Self-host free, or use the hosted version, TradingMCP.
Python toolkit for quantitative finance: stock analysis, technical indicators, strategy backtesting, portfolio optimization, and financial modeling.
Algorithmic Trading in Python with Machine Learning
TranslatedVibe-Research: A research workbench for China A-shares, US and HK stocks · watchlist and holdings, daily review, industry news, industry research, in-depth stock analysis, backtesting, research report library, 168 data endpoints. Supports Claude Code, Codex, WorkBuddy subscriptions or any model API.
A Java library for technical analysis.
🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package.
Python trading framework with AI agents that actually place the trade. Backtest, paper and live trade on 12 brokers: stocks, options, futures, forex, crypto and prediction markets.
QuantJourney Backtester
Say It Simply, Test It Properly. Agent-powered strategy research with independent ledger checks and reproducible reports.
TranslatedMulti-market intelligent quantitative workbench (A-shares/Hong Kong stocks/US stocks) — secondary development based on shy3130/tickflow-stock-panel, adding multi-market support for Hong Kong and US stocks. Self-hosted stock screening + monitoring + backtesting. MIT.
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.