Arnott, Harvey: machine learning dangerous when data thin

Experts warn ML should be used “for its correct purpose” – not for prying long-term strategies from sparse information

Wrong tool for the job
Machine learning as a tool must be used appropriately, say two experts

Rob Arnott and Campbell Harvey – two of the best known experts in quant investing – have warned investors against using machine learning to derive investment strategies from too-thin data.

According to Arnott, using sparse data to train “powerful” machine learning algorithms is akin to driving a Ferrari on an off-road dirt track.

“If you visit the data often enough and in enough depth [using machine learning], you’ll find all sorts of things that look marvellous,” Arnott says. “It doesn’t mean

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