Underdetermination and variability of the results in macro-to-micro stress tests: A machine learning approach

Author's Biography

Alexander Denev is currently Head of Quantitative Research at IHS Markit. Alexander has previously worked as a Senior Advisor to Risk Dynamics, a risk advisory part of McKinsey & Company. Prior to that he was a Senior Team Leader in the Royal Bank of Scotland, where his responsibilities included development of the stress testing methodology, country risk ranking and early warning indicators. Before joining RBS, Alexander was in charge of the Basel II/III implementation project for the European Investment Bank (EIB) and European Investment Fund (EIF). He participated in the engineering of both the EFSF (European Financial Stability Facility) and the ESM (European Stability Mechanism). Alexander holds an MSc in Mathematical Finance from the University of Oxford where he is currently a Visiting Lecturer. He also holds an MSc in Theoretical Physics from the University of Rome. He has written several papers and two books on topics ranging from stress testing and scenario analysis to asset allocation.

Orazio Angelini is a research associate at IHS Markit and PhD student in Mathematics at King’s College. He holds an MSc degree in Theoretical Physics and has previously worked as a researcher at La Sapienza University in Rome on the topic of Economic Complexity.