How AI Learns to Read Market Data

Artificial intelligence can process enormous amounts of market data, but processing information is not the same as understanding it. Market data contains patterns, noise, missing information, changing conditions, and unexpected events. A useful AI system therefore needs more than historical prices. The first challenge is preparing the data. Features must be selected carefully, timestamps must be aligned, and information that would not have been available at the time of a decision must be excluded. The second challenge is interpretation. Models can identify relationships in historical data, but those relationships can weaken or disappear as market conditions change. This is why responsible AI research focuses not only on model performance, but also on limitations, validation, and failure analysis. At AAT, our goal is to study these methods and make the underlying ideas easier to understand.