We study markets as dynamic, information-rich systems — compressing streams of data to reveal their underlying structure. From these compressed representations, we extract algorithms that evolve through observation, hypothesis testing, and feedback. Each trading decision is an experiment. Our framework unites scientific rigor with real-world execution, turning raw market behavior into adaptive, self-improving strategies. In essence, we’re building a living model of the market — one that learns, iterates, and trades with the precision of research and the intuition of experience.