@vraj_harish_talati641

Alpaca Volatility Agent is an autonomous, quantitative options volatility trading and portfolio hedging system built for Alpaca's paper trading environment. Unlike conventional AI trading bots that rely on qualitative sentiment prompt guessing, our agent delivers a mathematically grounded volatility risk premium (VRP) harvesting engine paired with continuous greek-risk management. Core Architectural Components: 1. Regime-Conditional HMM: Utilizes a 4-state Hidden Markov Model (Range-Bound, Trend, Volatility Expansion, and Crash) to dynamically adapt posture and throttle risk multipliers. 2. Multi-Model Volatility Forecasting: Blends GARCH(1,1) and HAR-RV statistical models against live implied volatility directly scraped from Alpaca's options chain, validated using Zou-Derman Strike-Adjusted Spreads. 3. Optimal Capital Allocation: Executes fractional Kelly criterion positioning constrained by strict aggregate Gamma, Vega, and Delta portfolio caps. 4. Transaction-Cost-Aware Hedging: Performs continuous delta hedging equipped with Whalley-Wilmott no-trade bands to prevent friction and spread erosion. 5. Official CLI Tooling Compliance: All broker interaction, market queries, and order executions are strictly executed through Alpaca's official CLI tool wrapper. 6. Full Terminal & Backtesting Suite: Features an interactive backtest sandbox and live web dashboard deployed on Vercel.

💻 Online Hackathon | ⏳ Build: 48 hours | 📅 September 25–27, 2026 The official IBM Bob 2.0 hackathon. Build what's next in AI-assisted development, alongside the developers and experts shaping it. ⭐ Get help from experts throughout the event 🤝 Join a team or build solo 💰 Prize pool: $12,000 🧑🏻‍💻 Register before the Kick-Off Stream to start building with Bob

🌎 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.