Giacomo Gaggero is a third-year PhD candidate in Economics and Quantitative Methods at the University of Genoa. His research interests focus on finance, specifically in the areas of risk management, forecasting, and portfolio optimization.

He has published a paper in AIFIRM Magazine (Vol. 19, Issue 1, 2024) on portfolio optimization, examining the application of Hierarchical Risk Parity (HRP) and Logic Learning Machine (LLM) methodologies.

He is currently working on two main research projects. The first involves Value at Risk (VaR) modeling for option portfolios using Monte Carlo simulations, which has been presented at the Aon Operational Research Conference at the Technical University of Denmark (Copenhagen, June 2024) and at the New Frontiers in Banking and Capital Markets Conference at LUISS University (Rome, December 2024). 

The second project focuses on yield curve modeling using artificial intelligence techniques, including Genetic Algorithms and Gaussian Process Regression. This research has been presented at the International Risk Management Conference (IRMC) at Bocconi University (Milan, July 2024) and at the 5th CGRM International Conference at the University of Bari (July 2024).

Additionally, he is conducting research on demand forecasting for a manufacturing company, developing a framework to classify different product time series and match them with the most suitable forecasting models based on their characteristics. This project combines various methodologies including SARIMA, RNN, and Croston's method.