AI-powered investing is the future of stock trading, and new research is proving that data-limited stock selection methods can be just as accurate as those that rely on complex data sets. A recent study by researchers at the University of California, Berkeley, has found that a data-limited AI-powered stock selection method can be just as accurate as one that relies on large data sets. This method, which is based on reinforcement learning, uses minimal data to make stock predictions and could be used to improve the accuracy of stock trading. The team’s findings show that data-limited selection methods can be just as accurate as those that rely on large data sets, and provide a viable alternative for investors who may not have access to the same resources.

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source: Phys.org