Quant Guide 2020: Collegio Carlo Alberto, University of Turin

Turin, Italy

 

The Master in Finance, Insurance and Risk Management at the University of Turin’s Collegio Carlo Alberto has one of the smallest cohorts in this year’s quant guide. With just 13 students and an average class size of 10, the candidates are outnumbered by faculty. The programme, which runs from September to June, is led by academic director and professor of financial economics Giovanna Nicodano. It has 19 instructors with industry affiliations, and is guided by a 20-strong scientific committee, which includes Nicodano herself and practitioners from Italian financial companies.

The degree’s strong practitioner presence appears to have served recent graduating classes well. The programme reports a 96% average employment rate in financial services over the last four years, the majority of its former students having taken positions in banking.

Like some other programmes, Carlo Alberto’s master’s splits its course into a number of predesigned tracks. The first of these is the foundation track, in which students take introductory courses like mathematics for finance, econometrics and programming, coding in Python and R, and two machine learning modules. The common track contains classes in asset pricing, fixed income, credit risk and financial engineering. The finance track features modules like quantitative asset allocation, operational risk management, and banking law and regulation. There is an insurance and risk management track and, lastly, the professional courses track, which involves classes in applied machine learning, roboadvising, private banking and systemic risk management.

Almost every class in the professional courses track is taught by an instructor from the world of practice. The hedge funds and alternative assets module, for example, is taught by Luca Vaiani, head of investment strategy at Milan-based asset manager Fideuram Investimenti. Recent course additions include a new fintech sequence, with its own host of modules. These include a Python coding class and three machine learning courses.

View this institution’s entry in the 2017 guide

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