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PRMIA 8008 Exam Syllabus Topics:

PRMIA PRM Certification - Exam III: Risk Management Frameworks, Operational Risk, Credit Risk, Counterparty Risk, Market Risk, ALM, FTP - 2015 Edition Sample Questions:

1. When fitting a distribution in excess of a threshold as part of the body-tail distribution method described by the equation below, how is the parameter 'p' calculated.

Here, F(x) is the severity distribution. F(Tail) and F(Body) are the parametric distributions selected for the tail and the body, and T is the threshold in excess of which the tail is considered to begin.

A) p is a parameter estimated using either the sum of least squares or maximum likelihood estimation
B) If there are K observations up to the tail threshold, then p = k*n
C) If there are N observations, of which K are up to T, then p = k/N
D) p is a function of the reporting threshold and determined by the log-likelihood functional

2. A risk analyst peforming PCA wishes to explain 80% of the variance. The first orthogonal factor has a volatility of 100, and the second 40, and the third 30. Assume there are no other factors. Which of the factors will be included in the final analysis?

A) First and Second
B) First, Second and Third
C) Insufficient information to answer the question
D) First

3. Which of the following statements is true in relation to a normal mixture distribution:
I. Normal mixtures represent one possible solution to the problem of volatility clustering II. A normal mixture VaR will always be greater than that under the assumption of normally distributed returns III. Normal mixtures can be applied to situations where a number of different market scenarios with different probabilities can be expected

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

4. Which of the following are considered counterparty based credit enhancements?
I. Collateral
II. Credit default swaps
III. Close out netting arrangements
IV. Guarantees

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

5. Which of the following statements are true in relation to Principal Component Analysis (PCA) as applied to a system of term structures?
I. The factor weights on the first principal component will show whether there is common trend in the system II. The factors to be applied to principal components are obtained from eigenvectors of the correlation matrix III. PCA is a standard method for reducing dimensionality in data when considering a large number of correlated variables IV. The smallest absolute eigenvalues and their associated eigenvectors are the most useful for explaining most of the variation

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

Solutions: