ZONAL is designed to unify analysis across multiple charts, symbols, and indicators into a single, structured data environment. Instead of treating each chart as an isolated snapshot, ZONAL ingests and normalizes outputs from multiple indicators across multiple markets, creating a consistent, comparable dataset. This allows users to analyze how different instruments behave under similar structural conditions, identify recurring patterns across symbols, and validate ideas at scale rather than relying on anecdotal chart review.

The true power of this approach emerges through historical logging. Every indicator state, structural interaction, and contextual variable is captured and stored over time, building a growing research-grade dataset of market behavior. This historical record enables deep, condition-based analysis — such as evaluating outcomes by regime, measuring performance as timing windows expand or contract, or isolating which structural features consistently precede favorable moves. Instead of asking what happened on this chart, users can ask what tends to happen when markets behave this way.

By combining multi-chart analysis with long-term data retention, ZONAL transforms discretionary observation into systematic research. Users gain the ability to test assumptions, refine rules, and uncover statistically meaningful behaviors that are invisible in real-time trading alone. This foundation supports advanced analytics, continuous strategy improvement, and future AI-driven insights — making ZONAL not just a trading tool, but a long-term market intelligence platform.

ZONAL — How it Works