Model misfires raise questions over training data
Quants wrestle with how far into the past their machine learning models should peer
Wisdom accumulated over many decades is highly prized in most cultures. Less so for machine learning in investing, it would seem.
Algorithms that use long histories of data to build their understanding of markets flopped during the Covid-19 pandemic. Such models failed “pretty spectacularly” in the extreme events of 2020, says Michael Heldmann, head of multi-factor equity investing for North America at Allianz Global Investors, citing research conducted by the firm.
“They have been hammered
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