Gloria Polinesi is a PhD student in Economics at the Department of Economic and Social Sciences of the Marche Polytechnic University. She has a Master Degree in Finance and currently working in the graph theory applied to Fintech services, especially Robot-Advisors. Her research interests involve statistics, econometrics, cluster analysis, neural networks and finance, author of a publication in the Annals of Operations Research Journal. She also has experience in data analysis and pre-processing which she undertook at the offices of the Marche Region.
In this paper, the authors show how to exploit the available data to build portfolios that better fit the risk profiles of investors. This is made possible, on the one hand, by constructing groups of homogeneous risk profiles based on user responses to…