Master Meetings

Have you decided on which Master programme to study? Would you like more information on the contents and teaching methods at USI? Register at our Master Meetings to attend courses.
The various Master Meetings offer you the opportunity to follow lectures together with the current master students. Guided by a USI student, you can visit the campus and make up your mind as to whether the contents correspond to your study ambitions.

Next appointment: 9-13 May 2022. Registration is required.

Registration form

10.05.2022  
8:30-10:15
Room A12
Red Building

Corporate Banking
Prof. Degeorge, Prof. Casati

This course presents state-of-the-art concepts of finance theory and applies them to practical corporate financing issues. The theoretical part of the course will briefly review standard corporate financing theory, then move on to the concepts of asymmetric information and agency costs, and how they play into the practical issue of raising long-term funds for a company.

The applied part of the course will use case studies to bring together the major corporate finance concepts studied during the Master´s program.

8:30-10:15
Room A22
Red Building

Risk Management
Prof. Plazzi

We begin by defining the various types of financial risks and stress the need for their management through the analysis of losses and defaults of financial institutions in the recent past. We next turn to the computation of Value-at-Risk measures for portfolios of equity, bond, and option positions. We discuss the estimation of the main inputs surrounding the calculation of VaR, and elaborate on models for time-varying volatility and correlations. We cover both local-valuation models based on derivatives, as well as full-valuation models such as historical simulation and Monte Carlo methods. We also discuss alternative metrics to VaR and Extreme Value Theory. Finally, we examine models for liquidity and operational risk management.

10:30-12:15
Room D1.14
East Campus

Machine Learning
Prof. Alippi

The course will address the following topics: Supervised learning: linear and nonlinear models for regression and prediction, statistical theory of learning, feature extraction and model selection. Deep learning: architectures including autoencoders, convolutional neural networks and learning procedures. Model performance assessment: cross validation, k-fold cross validation, leave-one-out, bootstrap. Unsupervised learning: K-means clustering, fuzzy C-means, principal component analysis.

14:30-16:15
Room 250
Main Building

Trading and Market Microstructure
Prof. Kaul

The course discusses the functioning of financial markets and trading and price determination in these markets. Topics covered include order submission and trading strategies, market structure and quality, settlement, transaction costs and liquidity, bubbles and crashes, price formation and technical analysis. The lectures will draw on academic and practitioner research as well as information from markets. The course is technical at some points but I will emphasize intuition and practical applications.

16:30-18:15
Room A22
Red Building

Banking Strategies & Wealth Management
Prof. Soncini, Prof. Vergani

The course provides an introduction to the elaboration of a Strategy for a Financial Institution, starting from the understanding of the financial environment and the macro trends characterizing the banking processes, down to client’s segments, products and services, and business areas (retail banking, private banking, commercial banking, investment banking and asset management with a specific focus on wealth management). Complementary to finance and investments tracks, this course mainly focuses on a holistic, cross-disciplinary wealth management approach, and provides content on wealth governance, family advisory, wealth structuring and succession planning. Moreover, it adopts a value chain based approach, analyzing and challenging the current business model while re-assessing the role of the relationship management.
Some “case study” will be analyzed in class, giving students the possibility to learn from more than 25 years of experiences accumulated by the lecturer.

In the Autumn Semester 2021, prospective students joined the classes: