Machine learning and Big Data tools are being increasingly employed for risk management. This webinar, presented by Imperial Professor of Finance Robert Kosowski, demonstrates how machine learning can be applied for the purpose of equities risk management.
Robert will talk about applying machine learning, fundamental equity variables and big data equity sentiment variables to forecast systematic stock risk. This will include findings on how machine learning algorithms are better at forecasting future stock beta than linear models.
Big data variables such as stock level sentiment and news volume are significant in several models in addition to other fundamental variables. Robert will talk you through how machine learning forecasts can be used to improve a stock trading strategy.