The course illustrates the issues, modeling and operational techniques of the segment of professional management of investment portfolios for institutional investors. The course analyzes all the techniques suitable for the definition of strategic and tactical asset allocation of portfolios, from the classical theory of Modern Portfolio Theory, implemented in order to solve the problem of estimation error, to Post Modern Portfolio Theory, to approaches related to risk budgeting, factor and smart beta investing.
The course is completed by the operational techniques of asset allocation analysis, management styles, identification of factors for the purposes of multifactor portfolios, and the topics always examined from an operational perspective of climate investing and ESG. The course ends with a presentation of the basic techniques of machine learning in asset allocation. The course includes the use of Excel and Matlab.

At the end of the Asset Allocation course, students will have acquired:

(a) advanced knowledge regarding domestic and international portfolio management regulations (knowledge and understanding);
b) knowledge of traditional and innovative issues in asset allocation, through textbooks and academic or professional articles (learning skills).
c) knowledge of the main advanced models for measuring and managing securities portfolios, mainly from the perspective of management by institutional investors (knowledge and understanding)
d) the ability to apply advanced models of measurement and management of securities portfolios (applying knowledge and understanding);

Students are provided with exercises and are assigned a project work that allows them to develop the ability to search for data and information to be processed, to decide on the most useful modeling to answer research questions and to develop advanced quantitative models arriving at conclusions regarding the management of portfolios (making judgments); to work in a team and to organize and manage a project (learning skills) and communication with the teacher; to improve the ability to communicate results, revealing critical points and analyzing outputs using autonomy of judgment (communication skills), managing Excel and programming languages (communication skills).