Persistence of Bank Credit Default Swap Spreads

Xin Huang

doi:10.3390/risks7030090

Abstract

Credit default swap (CDS) spreads measure the default risk of the reference entity and have been frequently used in recent empirical papers. To provide a rigorous econometrics foundation for empirical CDS analysis, this paper applies the augmented Dickey–Fuller, Phillips–Perron, Kwiatkowski–Phillips–Schmidt–Shin, and Ng–Perron tests to study the unit root property of CDS spreads, and it uses the Phillips–Ouliaris–Hansen tests to determine whether they are cointegrated. The empirical sample consists of daily CDS spreads of the six large U.S. banks from 2001 to 2018. The main findings are that it is log, not raw, CDS spreads that are unit root processes, and that log CDS spreads are cointegrated. These findings imply that, even though the risks of individual banks may deviate from each other in the short run, there is a long-run relation that ties them together. As these CDS spreads are an important input for financial systemic risk, there are at least two policy implications. First, in monitoring systemic risk, policymakers should focus on long-run trends rather than short-run fluctuations of CDS spreads. Second, in controlling systemic risk, policy measures that reduce the long-run risks of individual banks, such as stress testing and capital buffers, are helpful in mitigating overall systemic risk.

Highlights

Since their launch, credit default swaps (CDS) have been a frequent research topic
The empirical sample consists of daily CDS spreads of six large U.S banks that have been designated as global systemically important financial institutions (G-SIFIs)
The main findings of this paper are that it is log, not raw, CDS spreads that are unit root processes, and that the log CDS spreads of large U.S banks are cointegrated

Summary

Introduction

Credit default swaps (CDS) have been a frequent research topic. Researchers apply methods similar to those for other types of securities—such as stocks—to the empirical analysis of CDS spreads. Given the intrinsically different natures of stocks and CDS, as well as the importance of CDS in both empirical research and systemic risk analysis, a rigorous time-series analysis of CDS spreads is needed. The empirical sample consists of daily CDS spreads of six large U.S banks that have been designated as global systemically important financial institutions (G-SIFIs). The main findings of this paper are that it is log, not raw, CDS spreads that are unit root processes, and that the log CDS spreads of large U.S banks are cointegrated These findings imply that, even though the risks of individual banks may deviate from each other in the short run, there is a long-run relation that ties them together. They are the reference entities of the first traded corporate CDS contracts since the launch of CDS trading in the early 2000s Their CDS spread time series are among the longest available, which facilitates the unit root study. The above statistics all suggest a potential unit root for the daily log CDS spreads

Covariance Stationary versus Unit Root

Cointegration

Findings

Conclusions