
Black Swan news and market simulator is an advanced, real-time neuro-symbolic simulation engine built for the AMD Hackathon. At its core, the platform explores the intersection of generative AI, social sentiment, and complex financial systems by modeling how macroeconomic news dynamically impacts global equity markets. Powered by Google's Gemma foundation models (specifically gemma-4-31b-it and gemma-4-26b-it), the system simulates dozens of distinct behavioral retail cohorts and automated corporate PR desks that react contextually to user-defined market scenarios—such as a major technological breakthrough or a sudden supply chain disruption. Rather than relying on arbitrary price walks or fake mathematical noise, every single price movement in the simulation is 100% driven by AI agents reasoning over the incoming news feed and placing logical limit orders based on their risk tolerance and cash balances. These orders are cleared through a custom-built Python Continuous Double Auction (CDA) matching engine, while local TimesFM foundation models act as institutional quant funds performing high-speed time-series forecasting. The frontend is a sleek, highly interactive Next.js dashboard featuring a real-time generative news feed, global market visualizations, and a timeline scrubber that allows users to seamlessly travel back and forth through the simulation history to analyze exact market triggers. By unifying generative LLM workflows, time-series forecasting, and high-performance financial matching, this project provides a stunning, interactive sandbox for stress-testing market psychology and exploring AI-driven economic volatility.
13 Jul 2026