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PRMIA Credit and Counterparty Manager (CCRM) Certificate Sample Questions:

1. When estimating the risk of a portfolio of equities using the portfolio's beta, which of the following is NOT true:

A) using the beta significantly eases the computational burden of calculating risk
B) use of the beta assumes that the portfolio is diversified enough so that the specific risks of the individual stocks offset each other
C) explicitly considers specific risk inherent in the portfolio for risk calculations
D) relies upon the single factor CAPM model

2. Which of the following statements are true:
I. The sum of unexpected losses for individual loans in a portfolio is equal to the total unexpected loss for the portfolio.
II. The sum of unexpected losses for individual loans in a portfolio is less than the total unexpected loss for the portfolio.
III. The sum of unexpected losses for individual loans in a portfolio is greater than the total unexpected loss for the portfolio.
IV. The unexpected loss for the portfolio is driven by the unexpected losses of the individual loans in the portfolio and the default correlation between these loans.

A) III and IV
B) I, II and III
C) II and IV
D) I and II

3. Which of the following are elements of 'group risk':
I. Market risk
II. Intra-group exposures
III. Reputational contagion
IV. Complex group structures

A) II, III and IV
B) II and III
C) I and II
D) I and IV

4. The accuracy of a VaR estimate based on a Monte carlo simulation of portfolio prices is affected by:
I). The shape of the distribution of portfolio values
II). The number simulations carried out
III). The confidence level selected for the VaR estimate

A) II
B) I, II and III
C) II and III
D) III

5. Which of the following is not a limitation of the univariate Gaussian model to capture the codependence structure between risk factros used for VaR calculations?

A) Determining the covariance matrix becomes an extremely difficult task as the number of risk factors increases.
B) The univariate Gaussian model fails to fit to the empirical distributions of risk factors, notably their fat tails and skewness.
C) It cannot capture linear relationships between risk factors.
D) A single covariance matrix is insufficient to describe the fine codependence structure among risk factors as non-linear dependencies or tail correlations are not captured.

Solutions: