DUCKQUANT / THE QUANT & AI DIRECTORY
14,444 resources, ranked by in-directory PageRank
Showing 7,489–7,524 of 14,444 resources
AI-Powered Personal Finance Assistant - Transforming bill images into intelligent financial insights with Vision LLM technology
FinWorld: An All-in-One Open-Source Platform for End-to-End Financial AI Research and Deployment
Collection of impressive LLM apps with a focus on the financial sector
US stock analysis skills for LLMs (Claude code, Gemini ...) AI
An open-source AI financial advisor that learns your situation and gets smarter every conversation
AI agent skill that answers macro questions — housing, gold, BTC, geopolitics — with probability estimates mined from 13 financial data sources (Polymarket
TensorTrade-NG is an open source Python framework for building, training, evaluating, and deploying robust trading algorithms using reinforcement learning
Reinforcement Learning for Automated Trading
This is the code implementation of the paper "Financial Trading as a Game: A Deep Reinforcement Learning Approach"
Tries to predict if a stock will rise or fall with a certain percentage through giving probabilities of what events it thinks will happen
Stock trading strategies play a critical role in investment. However, it is challenging to design a profitable strategy in a complex and dynamic stock…
The work aims to explore Value based, Deep Reinforcment Learning (Deep Q-Learning and Double Deep Q-Learning) for the problem of Optimal Trade Execution. The
Developed a deep learning model that allows trading firms to analyze large patterns of stock market data and look for possible permutations to increase…
Another attempt to use Deep-Learning in the financial markets
This is the project for deep learning in stock market prediction
68 trading, DeFi, and quantitative finance Agent Skills. Works with Claude Code, Cursor, Codex, Gemini CLI, and 30+ other tools
Agent-first CLI for trading on Solana — 18 DEX adapters, 12 SWQoS TX landing processors. Buy, sell, lp, snipe, create pool, launch coin, and…
Practical Deep Reinforcement Learning Approach for Stock Trading. NeurIPS 2018 AI in Finance
This project uses Deep Reinforcement Learning (DRL) to develop and evaluate stock trading strategies. By implementing agents like PPO, A2C, DDPG, SAC, and TD3
Attention-based Deep Reinforcement Learning framework for portfolio allocation on S&P 500 equities. Includes custom environment, policy architecture with
Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell
AI trading research engine for Claude Code. Analyze stocks (technical, fundamental, sentiment, risk, thesis), options strategies, sector rotation, portfolio
This is a project on "Stock-Market-Analysis-And-Forecasting-Using-Deep-Learning" using Pytorch, python, deep learning, gru, plotly
An RL model that uses double deep Q learning to generate an optimal policy of stock market trades
Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert
This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices
Galformer: A Transformer with Generative Decoding and a Hybrid Loss Function for Multi-Step Stock Market Index Prediction
A proof-of-concept AI-powered hedge fund that simulates trading decisions using multiple AI agents. Designed to explore algorithmic investing through
IBKR trading platform integration with AI hedge fund
AI-assisted trading desk for short-term technical analysis on stocks & ETFs via Robinhood MCP. Deterministic Python engines score each asset on a three-pillar
The skills for trading, to make your agent earn for you
DeFi toolkit for AI agents and coding assistants — deposit funds, execute trades, and manage crypto wallets. Works with Claude Code, Cursor, Windsurf
Production multi-agent trading platform with rigorous walk-forward validation. TSMOM momentum (1.097 Sharpe) + GEX regime filtering. Interactive CLI
AI-agent workspace for quantitative trading — backtest, validate, and paper trade strategies with multi-agent collaboration
An end-to-end stock factors mining neural network framework
Deep Q-Learning Applied to Algorithmic Trading
