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

Gerardo Ferrara (), Jun Sung Kim, Bonsoo Koo and Zijun Liu

Economic Modelling, 2021, vol. 94, issue C, 58-74

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.

Keywords: Credit default swap; Counterparty choice; Empirical matching; Counterparty risk; Financial networks (search for similar items in EconPapers)
JEL-codes: C14 D40 G10 G20 (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1016/j.econmod.2020.08.020

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