Abstract
This paper analyzes the interdealer-broker market for single-name Credit Default Swaps (CDSs) using a novel dataset from the GFI trading platform. We find that CDSs exhibit reverse J-shaped patterns for trading and quoting activity in the U.S., and U-shaped patterns in Europe and Japan. We also find that CDSs trade on average 3 times a day, which is comparable to corporate bonds. To deal with the scarcity of trading data and the absence of best limits, we estimate a state-space model of bid and ask quotes to infer the dynamics of volatility and transaction costs. The estimation uses new techniques based on particle filtering and the Monte Carlo EM algorithm. Empirical results indicate that the volatility of the efficient CDS spread is highest at the beginning of the trading day and declines subsequently. In addition, transaction costs exhibit a reverse J-shaped pattern across all CDSs. Finally, we find a strong association between the heterogeneity in dealers' private costs and the magnitude of transaction costs.
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