Quantocracy’s Daily Wrap for 05/14/2019

There have been numerous attempts to explain the lackluster performance of value investing so far this decade, which is currently on pace for its worst annualized performance for a decade since the 1930s: Without getting into the arguments made by others, which have been debated elsewhere, I will take a deeper look into what I think is the likeliest explanation for this phenomenon, although it is

In the summer of 2018 we attended a conference organized by Quantopian in which we heard Dr. Marcos Lopez de Prado outlined the challenges of building successful quantitative investment platforms. His book, Advances in Financial Machine Learning provides solutions to many of the problems faced by the quantitative finance community. We, however, could not find a cogent implementation of these ideas

Its been a long time folks, but we have some shiny new toys in the works. Current trends in the industry and working with data scientists has made me a believer in the benefits of using a machine learning approach. I have always been a proponent of theory-free approaches on this blog as long as they are designed with robust architecture. In contrast, strict adherence to simplistic theories

After closing at a 20-day low on Thursday, the market put in a bounce attempt on Friday. Mondays decline to a new low meant that initial bounce attempt failed. But in last nights subscriber letter we saw several studies that showed the failed bounce was more likely to see another bounce attempt than it was to sell off further. The study below triggered in yesterdays Quantifinder,