chicagobooth.edu/review | Technical traders have long searched for distinctive shapes in stock-price charts in order to predict returns. As artificial intelligence systems become better and better at recognizing visual patterns—for applications such as self-driving cars—can they uncover similar insights based on the shapes found in data? Chicago Booth’s Dacheng Xiu and his coauthors find that they can, producing strategies that are reliably more profitable and less risky than other well-known trading patterns.
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