Master of Quantitative Finance and Risk Management | metrics table at end of article
Students on this English-language master’s at Bocconi University can learn directly from senior professionals at some of the world’s best-known banks. Teaching staff in the 2016–17 academic year included: Fabrizio Anfuso, who leads collateral modelling at Credit Suisse; Pietro Virgili, head of risk analysis and pricing models at Intesa Sanpaolo; Andrea Fabbri, in charge of Italian institutional clients in the capital markets business at BNP Paribas; and a well-known figure in quantitative finance, Massimo Morini, who heads up interest rate and credit models at Banca IMI.
Practitioners mostly teach optional modules; students pick six from a list of about 10 courses – for example, derivatives credit risk management, term structure modelling, and market and counterparty risk management. Twelve mandatory courses are taught mainly by academics and include econometrics, stochastic calculus and time series analysis. From next academic year, R, a programming language, will feature more prominently in the econometrics module.
At the end of the 10-month programme – also known as Mafinrisk – students write a short thesis. If, as is often the case, the student is doing an internship or has already been hired, the thesis should summarise the main features of the placement or the job, exploring in particular the links with what was learnt on the programme.
Alternatively, the thesis can expand on a topic covered during the programme. “This is usually a very focused applied work whose aim is to implement as realistically as possible some of the tools developed during the master’s,” says programme director Francesco Corielli.
In addition to industry practitioners, current teaching staff on the master’s includes Marcello Minenna from Italy’s markets regulator Consob, and lecturers from other universities. Applicants to the programme require the equivalent of a bachelor’s degree in economics, finance, business or management or a quantitative subject such as mathematics, statistics, physics or engineering.