Investing in Credit: How Good is Your Information?
Lisa R. Goldberg
University of California, Berkeley; Aperio Group
Risk, Vol. 17, No. 1, pp. S16-S18, January 2004
We describe a class of quantitative credit risk models that take account of the unavoidable gaps in investors' information. These incomplete information models are structural/reduced form hybrids. They combine the best features of both traditional approaches while avoiding many of their shortcomings.
Number of Pages in PDF File: 3
Keywords: Credit risk, incomplete information, default, recovery, risk premium, power curve
JEL Classification: G33, C52, C53, G12, G13, G14
Date posted: February 28, 2004