Essays on derivatives markets and systemic risk

This dissertation contains three chapters. The first two chapters provide the first empirical studies of the historically untransparent U.S. equity swap market, while the third chapter explores a novel approach to modeling and backtesting systemic risk measures. The first chapter presents a comprehensive overview of the U.S. equity total return swap (TRS) market using a novel dataset of publicly disseminated security-based swap transaction messages under SEC Regulation SBSR. With a market size exceeding $3 trillion, this historically opaque over-the-counter market reveals substantial global activity, particularly in East Asian, European, and North American equities. Trading volume scales with market capitalization and is concentrated in the Health Care, Industrials, and Information Technology sectors. Aggregate swap trading activity exhibits notable spikes around index rebalancing, geopolitical events, and oil price shocks, while surges at the individual stock level often align with corporate announcements, industry news, and regulatory changes. The second chapter investigates the information content and price impact of equity TRS trades. Contrary to the conventional view that large institutional and derivatives trades typically convey significant price-relevant information, the information conveyed through equity swap trading is concentrated only in micro-cap stocks. Additionally, trades with delayed dissemination are associated with stronger price impacts, consistent with strategic reporting delays. This behavior suggests potential noncompliance with Regulation SBSR, which requires that transactions be reported as soon as technologically practicable. The third chapter addresses the modeling and evaluation of systemic risk measures. It proposes a robust multivariate filtered historical simulation (M-FHS) approach to estimate common risk metrics such as CoVaR, CoES, MES, and SRISK, and introduces backtesting procedures for CoES. Simulation results support the theoretical properties of the proposed tests, while an empirical application to large U.S. financial firms during recent financial crises shows that the M-FHS framework is more responsive to extreme tail risk than conventional methods. This dissertation contributes to a deeper understanding of a historically untransparent segment of the financial market, the equity swap market, through analyses of its structure and trading impact. It also introduces security-based swap transaction data to the research community, providing a valuable new resource for future empirical work. In addition, it advances the modeling and evaluation of systemic risk in financial markets by proposing a robust modeling methodology and backtesting procedures.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Finance

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Lei, Liheng

Contributors dc:contributor

• Pearson, Neil
• Pennacchi, George
• Kronlund, Mathias
• Irani, Rustom

• Equity Swap Market
• Trading Patterns
• Regulation SBSR
• Equity Total Return Swaps
• Information Content
• Institutional Trading
• Systemic Risk
• Filtered Historical Simulation
• Backtesting

Statement dc:rights

• Copyright 2025 Liheng Lei

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129457

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129457