Description: Lecture, three hours. Limited to Master of Applied Economics students. Offers hands-on experience in forecasting of assets in capital markets. Using python students pull social media data to create leading indicators of market fundamentals. Forecasting of asset of choice using neural networks and ensemble-weighted machine learning models with fundamental indicators as inputs. S/U or letter grading.

Units: 1.0