The 7 Reasons Most Machine-Learning Funds Fail|Marcos López de Prado|Guggenheim Partners
The rate of failure in quantitative finance is high, and particularly so in financial ML. The few 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 will become apparent in this seminar. Over the past two decades, I have seen many faces come and go, firms started and shut down. In my experience, there is one critical mistake underlying all those failures.
This event has ended. Please view the presentation here:https://cornell.mediasite.com/Mediasite/Play/2f748a113916480fa0bddccc587a2d7d1d
and see the slides for the presentation here: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3031282