Abstract
Recent criticisms suggest that Machine Learning-based approaches only suite predicting very short-term price movements. Tony Guida and Guillaume Coqueret apply well-known ML algorithms to systematic equity investment, presenting a methodology which shows a critical stage of feature and label engineering, a stet that helps uncover hidden structures in the equity market space. Only then, the authors argue, can a modern quantitative approach make accurate long-term predictions.
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