The Journal of Portfolio Management Special Issue Dedicated to Stephen A. Ross 2018, 44 (6);

大多数机器学习基金失败的10大理由

作者：Marcos López de Prado（Lawrence Berkeley National Laboratory）

摘要：量化金融的失败率很高，这在金融机器学习应用中尤甚。少数成功积累大量资产的经理人为投资者提供着始终如一的卓越绩效。但是，由于作者在本文中解释的原因，这是一种罕见的结果。根据作者的经验，10个关键错误构成了这些失败的基础。

The 10 Reasons Most Machine Learning Funds Fail

Marcos López de Prado（Lawrence Berkeley National Laboratory）

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 underlie those failures.

原文链接：http://jpm.iijournals.com/content/44/6/120

翻译：黄涛