Explanation:
Default correlation has NO impact on the expected loss of a credit portfolio. According to the property of linearity of expectation, the expected value of a sum of random variables is equal to the sum of their expected values (), regardless of whether the variables are correlated or independent. Correlation only affects the portfolio's variance, unexpected loss, and tail risk measures (like Credit VaR). Options A, C, and D are all true statements regarding the implications and modeling challenges of default correlation.
Ultimate access to all questions.
No comments yet.
309.2. According to Malz,¹ each of the following is an important implication of default correlation in models of portfolio credit risk EXCEPT for:
A
Default correlation is hard to measure or estimate using historical default data
B
Default correlation exhibits too much sway on ("has a tremendous impact on") the credit portfolio's expected loss
C
Default correlations are small in magnitude such that an "optically" small correlation can have a rather large impact
D
The problem created by a portfolio with (n) credits, which require n*(n-1)/2 pairwise correlations, is often solved by assuming all pairwise correlations equal to a single parameter, but that parameter must be non-negative