2026-09-25T09:21:25Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/129681 2026-02-05 col_2142_5131 col_2142_17364 com_2142_5130 com_2142_17363 com_2142_9216

application/pdf en text Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01 The student, Belinda Chen, accepted the attached license on 2025-04-07 at 10:53. The student, Belinda Chen, submitted this Dissertation for approval on 2025-04-07 at 10:57. This Dissertation was approved for publication on 2025-04-08 at 11:10. DSpace SAF Submission Ingestion Package generated from Vireo submission #21719 on 2025-10-19 at 19:52:47 Three essays on financial market networks Chen, Belinda 2025-04-08 Kiku, Dana Kiku, Dana Kargar, Mahyar Pearson, Neil Plante, Sebastien Financial Market Network eng This dissertation explores the growing importance of network structures in financial markets by examining how firm-level interconnections shape risk transmission and aggregate outcomes. Through three essays, it highlights the role of production-based input-output networks in amplifying idiosyncratic shocks and driving both aggregate volatility and asset pricing dynamics. The first essay develops a dynamic model linking firm-level volatility spillovers to market-wide uncertainty, introducing novel network-based risk factors that are both predictive and priced. The second essay applies Graph Neural Networks to firm credit risk prediction, demonstrating how incorporating inter-firm network features enhances predictive power and interpretability. The final essay provides a theoretical foundation for how persistent, interconnected firm-level risks can generate macroeconomic tail events, even in the absence of large individual shocks. Together, these studies underscore the critical role of financial market networks in understanding modern economic and financial phenomena. 2025-05 Thesis https://hdl.handle.net/2142/129681 Copyright 2025 Belinda Chen Finance Finance University of Illinois Urbana-Champaign Ph.D. Dissertation