Conference Day One: 16 September 2019
Monday, September 16th, 2019
Forecasting stock returns at the firm level brings the challenge of evaluating the independent information in the entirety of many cross-sectional predictor variables, their potential interactions and non-linearities. While traditional portfolio sorts and simple linear regressions are not up to that task, machine learning algorithms are well suited for that problem. This talk gives answers on when, why and how to use ML algorithms in forecasting stock returns at the firm level.