Counterparty choice in the UK credit default swap market: an empirical matching approach

Gerardo Ferrara, Jun Sung Kim, Bonsoo Koo, Zijun Liu

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Adopting a novel empirical matching game framework, we investigate how market participants determine their trading partners in credit default swap transactions, which has received less attention in the literature. Using UK regulatory data at the transaction and identity levels for years 2012–2014, we find evidence that market participants prefer trading with organisations with larger total assets and more market activities. Our findings explain the too-big-to-fail problem in the credit default swap market, where market participants believe that regulators may not allow organisations with too many affected creditors to fail. Additionally, dealers with more intermediation activities are more likely selected as trading partners, implying the self-reinforcing nature of the market, which could exacerbate the too-big-to-fail problem. Counterparty risk also plays a significant role in trade pairing, but its effect differs across organisation types. For example, hedge funds prefer trading with risky counterparties before 2014, leading to a greater contagion risk.

Original languageEnglish
Pages (from-to)58-74
Number of pages17
JournalEconomic Modelling
Volume94
DOIs
Publication statusPublished - Jan 2021

Keywords

  • Counterparty choice
  • Counterparty risk
  • Credit default swap
  • Empirical matching
  • Financial networks

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