Corporate Credit Risk Premia

51 Pages Posted: 22 Jan 2018

See all articles by Antje Berndt

Antje Berndt

Australian National University (ANU) - Research School of Finance, Actuarial Studies and Applied Statistics

Rohan Douglas

Cornell University

Darrell Duffie

Stanford University - Graduate School of Business; National Bureau of Economic Research (NBER)

Mark Ferguson

Independent

Multiple version iconThere are 2 versions of this paper

Date Written: January 2018

Abstract

We measure credit risk premia - prices for bearing corporate default risk in excess of expected default losses - using Markit CDS and Moody’s Analytics EDF data. We find dramatic variation over time in credit risk premia, with peaks in 2002, during the global financial crisis of 2008-09, and in the second half of 2011. Even after normalizing these premia by expected default losses, median credit risk premia fluctuate over time by more than a factor of ten. Credit risk premia comove with macroeconomic indicators, even after controlling for variation in expected default losses, with higher premia per unit of expected loss during times of market-wide distress. Countercyclical variation of premia-to-expected-loss ratios is more pronounced for investment-grade issuers than for high-yield issuers.

Suggested Citation

Berndt, Antje and Douglas, Rohan and Duffie, James Darrell and Ferguson, Mark, Corporate Credit Risk Premia (January 2018). NBER Working Paper No. w24213, Available at SSRN: https://ssrn.com/abstract=3106603

Antje Berndt (Contact Author)

Australian National University (ANU) - Research School of Finance, Actuarial Studies and Applied Statistics ( email )

Canberra, ACT 0200
Australia

HOME PAGE: http://www.cbe.anu.edu.au/about/staff-directory/?profile=Antje-Berndt

Rohan Douglas

Cornell University

Ithaca, NY 14853
United States

James Darrell Duffie

Stanford University - Graduate School of Business ( email )

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National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
United States

Mark Ferguson

Independent ( email )

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