44 Pages Posted: 6 Sep 2017 Last revised: 4 Oct 2018

Date Written: September 2, 2017

Abstract

The rate of failure in quantitative finance is high, and particularly so in financial machine learning. 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 will become apparent in this presentation. Over the past two decades, I have seen many faces come and go, firms started and shut down. In my experience, there are 7 critical mistakes underlying most of those failures.

This paper is partly based on the book Advances in Financial Machine Learning (Wiley, 2018). A full paper can be downloaded at: http://ssrn.com/abstract=3104816.