Autogen Quant Invest Agent leverages large language models to automate the full quantitative investment pipeline. It connects to data APIs for market, fundamental, and alternative datasets, performs feature engineering and statistical analysis, and formulates algorithmic trading strategies. The agent orchestrates backtesting across historical periods, generates performance reports, and conducts risk assessments including drawdown, Sharpe ratio, and VaR. With customizable modules, users can tune strategy parameters, integrate custom indicators, and automate portfolio rebalancing rules. The framework’s modular chain-of-agents design allows seamless integration with order execution systems or data warehouses. This tool streamlines systematic research, reduces manual scripting, and empowers quantitative analysts to rapidly prototype, evaluate, and deploy investment models.

AgentSimJS is designed to simplify the creation and execution of large-scale agent-based models in JavaScript. With its modular architecture, developers can define agents with custom states, sensors, decision-making functions, and actuators, then integrate them into dynamic environments parameterized by global variables. The framework orchestrates discrete time-step simulations, manages event-driven messaging between agents, and logs interaction data for analysis. Visualization modules support real-time rendering using HTML5 Canvas or external libraries, while plugins enable integration with statistical tools. AgentSimJS runs both in modern web browsers and Node.js, making it suitable for interactive web applications, academic research, educational tools, and rapid prototyping of swarm intelligence, crowd dynamics, or distributed AI experiments.