Abstract

The rate of failure in quantitative finance is high, particularly in financial machine learning applications. The few managers who succeed amass a large amount of assets and deliver consistently exceptional performance to their investors. However, that is a rare outcome, for reasons that the author explains in this article. In the author's experience, 10 critical mistakes underline those failures.

TOPIC: Big data/machine learning

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