入门资料整理：1.多因子股票量化框架开源教程 2.学界和业界的经典资料收录 3.AI + 金融的相关工作，包括LLM, Agent, benchmark(evaluation), etc.

QuantMind is an intelligent knowledge extraction and retrieval framework for quantitative finance.

An open-source, lightweight, and blazing-fast financial machine learning library built with Numba. Process raw trades, generate advanced bars, features, and labels for quantitative research.

Autonomous quantitative trading research platform that transforms stock lists into fully backtested strategies using AI agents, real market data, and mathematical formulations, all without requiring any coding.

End-to-end RL trading framework with PPO agent, self-attention neural network, custom Gym environment, and advanced backtesting.

Real-time forex trading system with modular architecture, multi-timeframe signal generation, GMM-based regime detection, Kelly-based risk management, and CLI tools for backtesting, monitoring, and performance analysis.

Extracted financial data(equity, commodity) via APIs and web scraping. Created technical indicators(MA, MACD, RSI) and conducted fundamental analysis. Designed, backtested and assessed trading strategies to calculate KPIs(Sharpe, Sortino etc.). Implemented ML strategies to achieve full automation

A modular Python toolkit for advanced options pricing, volatility modeling, Greeks computation, and risk analysis. Includes Monte Carlo and Black-Scholes models, machine learning volatility surfaces, and interactive visualizations via Streamlit.

We consider the execution of portfolio transactions with the aim of minimizing a combination of risk and transaction costs arising from permanent and temporary market impact.

This is for the capstone project "Optimal Execution of a VWAP order".

ABIDES: Agent-Based Interactive Discrete Event Simulation

World Quant 101 alphas的计算和策略化

Generate realizations of stochastic processes in python.

Short Term Alpha Model

Constraint-based leverage feasibility frontier under interest-rate and occupancy stress scenarios.

High Frequency Analysis Based On Level-2 Data（Limit Order Book& Transaction Data)

Deep Q-Learning for Market Making

Module for statistical learning, with a particular emphasis on time-dependent modelling

An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.