Paris Pennesi
About Paris Pennesi
Paris Pennesi serves as the Managing Director and Head of Quant Strategies at HSBC, where he has worked since 2011. He has extensive experience in quantitative finance, market microstructure, and computational finance, alongside a strong academic background in operations research and artificial intelligence.
Current Role at HSBC
Paris Pennesi serves as the Managing Director and Head of Quant Strategies at HSBC since 2011. In this role, he leads the development and implementation of quantitative strategies, focusing on advanced computational techniques and financial modeling. His work involves utilizing sophisticated methodologies to enhance trading strategies and optimize financial performance.
Academic Background and Expertise
Paris Pennesi has an extensive academic background in quantitative methods and artificial intelligence. He achieved a Post Doctoral degree in Quantitative Methods from the University of Cambridge and a PhD in Artificial Intelligence from Università Politecnica delle Marche. Additionally, he has served as a Visiting Scholar at Boston University, where he studied Manufacturing Engineering.
Previous Academic Positions
Pennesi has held several academic positions, including Honorary Associate Professor at University College London (UCL) since 2017 and Visiting Professor of Operations Research at the Free University of Bozen-Bolzano from 2009 to 2012. He also served as a Visiting Professor in Operations Research at the London School of Economics from 2012 to 2016.
Professional Experience in Finance
Prior to his current role at HSBC, Paris Pennesi gained significant experience in the finance sector. He worked as a Quantitative Investment professional at Man AHL for 11 months and as an Algorithmic Trading Quant at J.P. Morgan for one year. He also served as a Quant Strategist at RBS from 2008 to 2010 and as a Consultant Analyst at Decision Technology Ltd from 2007 to 2008.
Research and Computational Finance
Pennesi has been actively involved in computational finance, a discipline that merges computer science, statistics, and mathematical finance to address complex financial challenges. His expertise includes market microstructure, which examines the processes and outcomes of asset exchanges under specific trading rules.