Skip to main content

Pricing Implications of Centrality in an OTC Derivative Market:
An Empirical Analysis Using Transaction-Level CDS Data

September 2024
Kohei Maehashi*1
Daisuke Miyakawa*2
Kana Sasamoto*3

Abstract

Using transaction-level records making up the universe of single-name credit default swap (CDS) contracts in Japan, we document whether and how the relative centrality of sellers to buyers, which proxies for their search ability and thus bargaining power, affects single-name CDS prices. Our main findings are as follows. First, our panel estimation, which comprehensively controls for the standard pricing factors considered in practice (e.g., entities' risk, counterparty risk, the notional amount, and maturity), suggests that CDS prices are higher the higher the relative centrality of sellers to buyers. Second, such centrality premium becomes more apparent under unfavorable market conditions and further increases when buyers attempt to unwind their short positions. Given the non-negligible quantitative impacts of relative centrality on CDS prices, we find that CDS prices to a large extent are determined by the bargaining power originating from the ability to search for counterparties. Third, deeper trade relations between sellers and buyers result in a centrality discount when market conditions are unfavorable and a centrality premium when market conditions are favorable. This result suggests that there is a tradeoff between the cost of maintaining relationship in periods of favorable market conditions and the benefit of securing cheaper access to CDSs in periods of unfavorable market conditions.

JEL classification
G12, G15, G18, G20, G28.

Keywords
Credit default swaps, centrality, bargaining power, search and matching frictions

The authors thank Kenji Fujita, Tomoyuki Iida, Takuji Kawamoto, Tomonori Kimata, Tomiyuki Kitamura, Jouchi Nakajima, Iichiro Uesugi, Yoshihiko Sugihara and seminar participants at the Japanese Economic Association Spring 2024 Meeting, the 32nd meeting of the Special Interest Group on Financial Informatics of the Japanese Society for Artificial Intelligence, Kwansei Gakuin-Waseda Banking and Finance Workshop, Tohoku University and Waseda University for their valuable comments and discussions. The authors gratefully acknowledge the provision of data from Japan's Financial Services Agency. Any errors in this paper are those of the authors themselves. Additionally, the views expressed herein are those of the authors and do not necessarily reflect the official views of the Bank of Japan.

  1. *1Maehashi: Senior Economist, Financial Markets Department, Bank of Japan, 2-1-1 Nihonbashi-Hongokucho, Chuo-ku, Tokyo 103-0021 JAPAN. E-mail: kouhei.maehashi@boj.or.jp.
  2. *2Miyakawa (corresponding author): Professor, Waseda University, School of Commerce. Office 1318 Building 11, 1-6-1 Nishiwaseda, Shinjuku-ku, Tokyo 169-8050 JAPAN. E-mail: damiyak@waseda.jp. Visiting Scholar, Financial Markets Department, Bank of Japan, 2-1-1 Nihonbashi-Hongokucho, Chuo-ku, Tokyo 103-0021 JAPAN. E-mail: miyakawa.daisuke@boj.or.jp.
  3. *3Sasamoto: Economist, Financial Markets Department, Bank of Japan, 2-1-1 Nihonbashi-Hongokucho, Chuo-ku, Tokyo 103-0021 JAPAN. E-mail: kana.sasamoto@boj.or.jp.