DUCKQUANT / THE QUANT & AI DIRECTORY
2,336 resources, ranked by in-directory PageRank
Reliable Reinforcement Learning Implementations
PyQL | Python , Cython | - Python wrapper of the famous pricing library QuantLib QuantLib.jl | Julia | - Quantlib implementation in pure…
Publication: Model-based Reinforcement Learning for Predictions and Control for Limit Order Books. Published Oct 9, 2019.
Publication: Neural networks with late-phase weights. Published Jul 25, 2020.
Publication: Deep Learning for Financial Applications : A Survey. Published Feb 9, 2020.
Python React A-shares - Local-first quantitative research and backtesting platform with data synchronization, multi-asset screening, factor analysis, portfolio
C++ - Deterministic offline PineScript v6 C++ backtest runtime, validated trade-for-trade against TradingView (245/246 strict, 0 engine bugs). Runs locally via…
AI forecasting-accountability lab: every forecast is locked pre-event, Bitcoin-timestamped (OpenTimestamps), and Brier-scored against prediction markets in…
We are committed to the open-sourcing quantitative knowledge, aiming to bridge the information gap between the domestic and international quantitative finance…
AI-driven crypto trading intelligence terminal for derivatives positioning, DEX flow, on-chain risk, narrative rotation, token discovery, and agent-ready...
FinRL®: Financial Reinforcement Learning.
AI-assisted trading workflow with Pine Script, MQL5, and cTrader coding agents, financial research tools, market screening, strategy optimization, and...
Cryptocurrency technical analysis indicators (MACD, RSI, Bollinger Bands) via CCXT for AI trading agents
🧮 A collection of resources to learn mathematics for machine learning
Explore this resource at its source website for documentation and current information.
Multi-agent crypto-trading system; Binance real-time execution adaptive strategy switching; combines ideas from TradingAgents and nof1.ai
"Claude Code for finance"; LangChain + LangGraph multi-agent investment workbench; integrates Agents · MCPs · Skills in one repo
Introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies
Xiao, Y., Sun, E., Luo, D., & Wang, W. (2024). TradingAgents: Multi-Agents LLM Financial Trading Framework. arXiv preprint arXiv:2412.20138
A Model Context Protocol (MCP) implementation for Financial Modeling Prep, enabling AI assistants to access and analyze financial data, stock information
High performance and scalable deep reinforcement learning for quantitative finance. ACM International Conference on AI in Finance, ICAIF 2021
. Michaël Karpe, Jin Fang, Zhongyao Ma, Chen Wang. International Conference on AI in Finance (ICAIF’20), September 2020
Open-source autonomous AI trading agent from the nof1 family; TypeScript port
Official Korea Investment & Securities Open API with MCP and LLM integration for Korean equity market trading
Integrates Tushare (Chinese A-shares, funds, bonds, macro) and Binance (crypto) for LLM financial data access
AKShare API for Chinese stock market: historical prices, real-time quotes, financial reports, and news
Personal stock analysis MCP server: technical indicators, earnings calendars, options flow, and insider trades
13-tool unified real-time and historical market data across Forex, US/HK/CN stocks, and crypto
Direct SEC EDGAR access for AI assistants: 10-K, 10-Q, 8-K filings, and insider trading data
Federal Reserve Economic Data (FRED) MCP server: access 800,000+ macroeconomic time series
Official Kraken AI-native CLI with built-in MCP support for spot trading, portfolio management, and market data
22-tool MCP server for 60+ EVM-compatible networks: token balances, smart contracts, and DeFi operations
Bitcoin and macroeconomic market briefings through REST and MCP, with a permanent free tier of six briefings, 30-day history, 60 requests per hour and…
Institutional-grade financial statements API with AI extraction from SEC filings — not XBRL. Covers domestic and foreign filers (20-F, 6-K, 40-F), normalized
Real-time Polymarket trading alerts with multi-AI analysis (Groq, Claude, Gemini). Track whale bets, volume spikes, coordinated wallets, and 12 signal types.…
Multi-agent reinforcement learning for liquidation strategy analysis, and . Workshop on Applications and Infrastructure for Multi-Agent Learning, ICML 2019
