Giuseppe Nuti is the head of Machine Learning & AI for UBS's Global Markets. The team is focused on a range of problems: from recommendation engines to optimal execution on behalf of UBS's clients. The objective is to explore novel uses of ML in applications such as recommendation systems to match clients with specific UBS's trading axes, anomaly detection for high-throughput, noisy systems, and optimal execution where venue micro-structure morphs order quality.
Prior to this role, Giuseppe was an algorithmic trader at UBS - New York - specialized in fixed income and foreign exchange. He has worked as a trader for over eighteen years, initially in the interest-rates options and swaps market and, since 2006, in the European and US Government bond markets. He has experience working both within the primary dealer community and in the high-frequency environment (at KCG and Citadel). At UBS, he has run the U.S. Rates Trading desk, with particular focus on electronic market-making.
Giuseppe holds a Ph.D. in Computer Science with particular focus on Markov Decision Processes applied to finance from University College London and an MSc in Financial Mathematics from City University, London. He has taught various courses, including Financial Computing at UCL and has supervised a number of Ph.D. students - both at UCL and CASS Business School.
- Algorithmic Trading
- Bayesian formulation of standard Machine Learning techniques