@ishpreet0101560

Aegis Alpha is an autonomous and explainable options-trading agent built using Alpaca’s paper-trading environment. It analyzes five-minute SPY and QQQ market data using EMA trends, session VWAP, RSI, and realized volatility to classify the market as bullish, bearish, or neutral. When conditions are suitable, the agent constructs defined-risk bull-call or bear-put debit spreads. A constrained AI ranker may select only from these valid candidates. It cannot invent contracts, change position size, modify risk limits, or directly authorize an order. Every proposal must pass deterministic Python controls covering maximum loss, aggregate exposure, position count, quote freshness, liquidity, cooldowns, duplicate orders, daily drawdown, and trading time. If any required check fails, the agent returns NO_TRADE. Alpaca-py provides market data and paper-trading access, while Alpaca CLI supplies an independent account, position, and order view for reconciliation. Any disagreement blocks new orders. Alpaca MCP is reserved for judge-facing inspection outside the execution path. A public Streamlit dashboard displays market regimes, AI reasoning, risk checks, decisions, trade lifecycle information, and offline verification evidence without exposing credentials. The current package passes 38 automated tests with 74% measured coverage and correctly classifies five synthetic market scenarios. These results validate the software and decision pipeline; they are not presented as evidence of live-market profitability.

🌎 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.