Machine-learning-enhanced systemic risk measure: a two-step supervised learning approach

• Main Authors: Liu, Ruicheng, Pun, Chi Seng
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2022
• Subjects: Science::Mathematics; Systemic Risk Measure; Machine Learning
• Online Access: https://hdl.handle.net/10356/161971
• Institution: Nanyang Technological University

This paper explores ways to improve the existing systemic risk measures by incorporating machine learning algorithms into the measurement. We aim to overcome the shortcomings of existing methods that rely on restricted modeling and are difficult to tap into various data resources. To this end, this...