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This research systematically evaluates 24 diverse forecasting models for company fundamentals, comparing classical statistical and modern deep learning approaches on real-world financial data. It demonstrates that automated forecasts can achieve accuracy comparable to human analysts and, when integrated into factor investment strategies, can yield competitive returns over market benchmarks.