The Determinants of Global Bank Credit-Default-Swap Spreads

Abstract

Using a sample of 161 global banks in 23 countries, we examine the applicability of market-based structural models and accounting-based bank fundamentals to price global bank credit risk. First, we find that variables predicted by structural models are significantly associated with bank CDS spreads. Second, some CAMELS indicators contain incremental information for bank CDS prices. We find no evidence in favor of one model over the other, while the combined structural and CAMELS model performs better than each individual model. Moreover, leverage and asset quality have had a stronger impact on bank CDS since the onset of the recent financial crisis. Banks in countries with lower stock market volatility, fewer entry barriers, and/or more financial conglomerate restrictions tend to have lower credit risk. Deposit insurance appears to have an adverse effect on bank CDS spreads, indicating a moral hazard problem.

Informed Trading and the Dynamics of Client-dealer Connections in Corporate Bond Markets

“…Our prior is that CDS investors are better informed about the credit risk of the issuer, which is the primary determinant of credit spreads in normal market conditions (see, for example, Ericsson, Jacobs, and Oviedo, 2009;Hasan, Liu, and Zhang, 2016). Therefore, we expect that the informational role of connections is more pronounced for investors who hold CDS contracts written on the bond issuer, compared to investors without this information edge.…”

Large EU banks’ capital and liquidity: Relationship and impact on credit default swap spreads

“…If this is true, a hybrid model using both accounting ratios and market-based variables should better predict CDS spread changes. Hasan et al (2015) investigate the effect of both structural variables and balance-sheet ratios on bank CDS spreads, while controlling for market factors. The authors find that balance-sheet ratios increase the explanatory power of structural variables.…”

“…Following Kanagaretnam et al (2016), Hasan et al (2015), Chiaramonte et al (2013), we include in the model these variables: the ratio of non-performing loans to total loans as a measure of asset quality; the return on assets as a measure of performance; the interest income over total income to control for traditional banking activities; and (the natural log of) total assets as a proxy for size. We also control for structural variables and market-wide factors.…”

“…First, to the best of our knowledge, it is the first to provide not only an empirical investigation of the contemporaneous interaction between capital and liquidity for a sample of European banks but also to extend the analysis to the impact of these variables on CDS spread changes. This approach differs from other studies as they typically focus on either the interrelations between capital and liquidity (e.g., Distinguin, Roulet, and Tarazi, 2013) or the determinants of CDS spread changes (Chiaramonte and Casu, 2013;Hasan, Liuling, and Zhang, 2015). Examining both aspects allows us to shed light on the importance of the nexus between capital and liquidity, and on the extent to which they are priced risk factors on the CDS market.…”

“…Finally, we contribute to the literature on the usefulness of CDS spreads in capturing bank risk positions. In particular, we add to the previous works by Hasan et al (2015) and Kanagaretnam, Zhang, and Zhang (2016) on the applicability of market-based variables and accounting-based bank fundamentals to explain CDS spread changes. The accounting information used in those studies is mostly based on CAMEL 2 indicators in which only asset liquidity is considered.…”