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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 author9s experience, 10 critical mistakes underlie those failures. TOPIC:Big data/machine learning
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Marcos López de Prado (Sat,) studied this question.
synapsesocial.com/papers/6a239056c1f1c7a6bca02d76 — DOI: https://doi.org/10.3905/jpm.2018.44.6.120
Marcos López de Prado
Cornell University
The Journal of Portfolio Management
Lawrence Berkeley National Laboratory
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