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Stefano Pasquali oversees product development and research for Bloomberg’s liquidity and systemic risk solution. His team designs and implements models that use Bloomberg’s comprehensive market data library and machine-learning techniques to estimate liquidity and risk across different asset classes with particular focus in OTC markets.
Stefano has more than 15 years of experience examining and implementing innovative approaches to calculating risk and market impact. He regularly speaks at industry events about the complexity and challenges of liquidity evaluation ? particularly in the OTC marketplace. His approach to risk and liquidity evaluation is strongly influenced by his 20 years of experience working with big data, data mining, machine learning and data base management.
Stefano joined Bloomberg in 2009 as a quantitative analyst/specialist supporting Bloomberg Valuation Services (BVAL), an evaluated pricing product. In 2010 Stefano moved on to lead liquidity research for Bloomberg’s Pricing Services, which conducts fixed income market liquidity research and calibrates financial models for measuring risk and market impact. Prior to joining Bloomberg, Stefano held senior positions at several European banks and asset management firms where he oversaw risk management, portfolio risk analysis, model development and risk management committees. Stefano built a risk management process for a global asset management firm with 100 Billion+ AUM involving projects from data acquisition and normalization to model development and portfolio management support.
Before his career in finance, Stefano was a researcher in physics focusing on Theoretical and Computational Physics (in particular Monte Carlo Simulation, Solid State physics, Environment Science, Acoustic Optimization). Originally from Carrara, Italy, Stefano is a graduate of Parma University and holds master degree in Theoretical Physics, as well as research fellowships in Computational Physics at Parma University and Reading University (UK).
Disclaimer: The biographical information is as of the date of posting.
