We show that the COVID-19 pandemic triggered a surge in the elasticity of non-financial corporate to sovereign credit default swaps in core EU countries, characterized by strong fiscal capacity. For peripheral countries with lower budgetary slackness, the pandemic had essentially no impact on...

We find that the degree and dynamics of sovereign bond market integration across 21 developed and 18 emerging countries is significantly heterogeneous. We show that better spanning can significantly enhance market integration through dissipating local risk premiums. Integration of the sovereign...

In recent years, a liquid market for options on a broad credit default swap index (CDX) has developed. We study the extent to which these options are priced consistently with options on a broad equity index (SPX). We consider a rich structural credit risk model in which firm assets follow a...

This paper shows that FED policy announcements lead to a significant increase in international co-movement in the cross-section of equity and particularly sovereign CDS market. The effect is strongest for emerging markets, when the FED relaxes unconventionary monetary policies, and for countries...

We examine time varying integration of developed (DM) and emerging (EM) market government bonds. Although we find an upward trend for most countries and maturity bands, we do observe reversals and negative trends among both DMs and EMs and for some maturities during the financial crisis. We...

We investigate the compensation of counterparty exposure in the prices of structured products. Our analysis reveals that product issuers do not compensate retail investors for counterparty exposure before the Lehman default. Post-Lehman, retail prices no longer neglect this risk. We also measure...

The internal ratings-based (IRB) approach maps banks’ risk profiles more adequately than the standardized approach. After switching to IRB, banks’ risk-weighted asset (RWA) densities are thus expected to diverge, especially across countries with different supervisory strictness and risk...

This paper proposes a machine learning approach to estimate physical forward default intensities. Default probabilities are computed using artificial neural networks to estimate the intensities of the inhomogeneous Poisson processes governing default process. The major contribution to previous...