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Hi David,

I am having trouble understanding the purpose of the copula. As I understand it, we map a uniform distribution to a normal since we can correlate multiple marginal normals to create a multivariate normal distributions to see how loans default simultaneously. Isn’t this what we do in the simulation in structured credit risk by Maltz?

However, when calculating the portfolio UL in Schroeck we can sum the individual UL and the pairwise correlations to get the portfolio UL. If the portfolio is to large this creates a problem with dimensionality and we can assume constant correlation.

Why can we simply sum the pairwise correlation in one case and we have to use the copula in the other? If the problem is the number of pairwise correlations I don’t see how the copula solves that problem since we still need a correlation matrix. What am I missing?

I am having trouble understanding the purpose of the copula. As I understand it, we map a uniform distribution to a normal since we can correlate multiple marginal normals to create a multivariate normal distributions to see how loans default simultaneously. Isn’t this what we do in the simulation in structured credit risk by Maltz?

However, when calculating the portfolio UL in Schroeck we can sum the individual UL and the pairwise correlations to get the portfolio UL. If the portfolio is to large this creates a problem with dimensionality and we can assume constant correlation.

Why can we simply sum the pairwise correlation in one case and we have to use the copula in the other? If the problem is the number of pairwise correlations I don’t see how the copula solves that problem since we still need a correlation matrix. What am I missing?

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