@article {L{\'o}pez de Prado120, author = {Marcos L{\'o}pez de Prado}, title = {The 10 Reasons Most Machine Learning Funds Fail}, volume = {44}, number = {6}, pages = {120--133}, year = {2018}, doi = {10.3905/jpm.2018.44.6.120}, publisher = {Institutional Investor Journals Umbrella}, 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{\textquoteright}s experience, 10 critical mistakes underlie those failures.TOPIC: Big data/machine learning}, issn = {0095-4918}, URL = {https://jpm.pm-research.com/content/44/6/120}, eprint = {https://jpm.pm-research.com/content/44/6/120.full.pdf}, journal = {The Journal of Portfolio Management} }