FRM真題練習對于考生重要嗎？這當然是重要的，尤其是備考沖刺階段，考生一定要做大量的真題練習。下面是小編列舉的相關真題，希望對備考的你有所幫助~

New copula correlation models were used by traders and risk managers during the 2007-2009 global financial crisis. This led to miscalculations in the underlying risk for structured products such as collateralized debt obligation (CDO) models. Which of the following statements least likely explains the failure of these new copula correlation models during the financial crisis?

A) The copula correlation models assumed a negative correlation between the equity and senior tranches of CDOs.

B) Correlations for equity tranches of CDOs increased during the financial crisis.

C) The correlation copula models were calibrated with data from time periods that had low risk.

D) Correlations for senior tranches of CDOs decreased during the financial crisis.

答案：D

解析：During the crisis, the correlations for both the equity and senior tranches of CDOs significantly increased causing losses in value for both. 【資料下載】[融躍財經]FRM一級ya題-pdf版

Which of the following statements about correlation and copula are correct?

I. Copula enables the structures of correlation between variables to be calculated separately from their marginal distributions.

II. Transformation of variables does not change their correlation structure.

III. Correlation can be a useful measure of the relationship between variables drawn from a distribution without a defined variance.

IV. Correlation is a good measure of dependence when the measured variables are distributed as multivariate elliptical.

A) I and IV only.

B) II, III, and IV only.

C) I and III only.

D) II and IV only.

答案：A

解析：I is true. Using the copula approach, we can calculate the structures of correlation between variables separately from the marginal distributions. IV is also true. Correlation is a good measure of dependence when the measured variables are distributed as multivariate elliptical. II is false. The correlation between transformed variables will not always be the same as the correlation between those same variables before transformation. Data transformation can sometimes alter the correlation estimate. III is also false. Correlation is not defined unless variances are finite.

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