Umberto Cherubini

Umberto Cherubini, PhD

Adjunct Professor, Master of Arts in Global Risk Program

SAIS Europe
Bologna, Italy

Expertise

Topics
  • Risk Analysis and Modeling
Languages
  • Italian

Background and Education

Associate Professor of Financial Mathematics, University of Bologna. Professor Cherubini studied at the "Cesare Alfieri" Social Sciences Institute of the University of Florence and New York University. He worked at the Economics Research Department at BCI Milan (COMIT) before moving to academia in 1998. Since then he has taught financial mathematics and risk management at the University of Bologna, where he currently directs the graduate program in Quantitative Finance. He has been a member of the Scientific Committee of AIFIRM (the Italian Association of Financial Risk Professionals) and of Abiformazione (the education branch of the Italian Banking Association). Cherubini has lectured extensively on risk management topics at in-house courses in Italy (Bank of Italy, CONSOB), and abroad. Cherubini carries out consulting work for Italian city councils on the use and valuation of financial derivatives. He is the author of 8 books and approximately 50 papers in economics, financial mathematics and risk management. His field of expertise is copula functions, and his contribution to this research has been recognized at the international level.


2017-10-31 00:00:00 
...
Spring 2018 
We will introdu...
We will introduce and discuss the concepts of uncertainty and of risk, eliciting the mechanisms of decision making in the context of policy-making, legislation, supervision and regulation, economics and finance. We will address the issue of how risk can be assessed subjectively and measured quantitatively: to that end, we will move from probability theory and the value of information to assess scenarios for the uncertain future. We will introduce the concept of validation of risk models by testing their ability to capture uncertain events through historical and stochastic (i.e. Monte Carlo) simulations. Both types of simulations will be useful as a tool to explore a probabilistic model and the connection between prior assumptions and the ensuing outcomes (underlying the distinction between linear and nonlinear models). We will discuss the concept of extreme events and present case studies where the occurrence of unassessed scenarios brought down the risk models used. The class will be involved in the discussion of practical situations where the use of a risk model is helpful to reach a decision: we will use a mixture of group and individual work.