Project CEMAPRE internal
| Title | Explainable machine learning models in financial economics |
| Participants | João Bastos (Principal Investigator) |
| Summary | Machine learning based predictive techniques are increasingly being adopted in finance and economics. However, due to their complexity and high number of degrees of freedom, their predictions are often difficult to explain and validate. This is referred to as the “black box” problem. In financial economics, we often want to know which factors drove a particular decision, which would preclude the use of opaque models. In this project, we will investigate several approaches for "x-raying" black-box models, and their viability to address problems in financial economics. |