@chusiujeh128

Our project is an autonomous AI trading agent designed to research, validate, and execute trading strategies through Alpaca. Rather than relying on a single fixed strategy, the agent treats different trading methodologies as competing strategy families and evaluates them using systematic backtesting, walk-forward validation, market-regime analysis, and risk controls. It then translates validated market views into options strategies, evaluates liquidity and risk, and can autonomously decide to trade, hold, exit, or stay out of the market. A deterministic risk layer protects the portfolio while the AI handles research and decision-making. Every decision, rationale, execution, and outcome is recorded in an auditable trading journal. The goal is an adaptive trading system that prioritizes robust evidence and disciplined risk management over blindly maximizing historical backtest returns.

🌎 Online Hackathon | 💻 Dates: 28 August–4 September 2026 | 🏆 $6,000 Prize Pool Build AI trading agents on Alpaca — autonomous agents and trading apps using Alpaca's Trading API, MCP server and CLI. 🌍 Fully online hackathon. Join and build from anywhere in the world.