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PRMIA 8011 (Credit and Counterparty Manager (CCRM) Certificate) Exam is a certification program designed for professionals who work in the credit and counterparty risk management field. 8011 exam is offered by the Professional Risk Managers' International Association (PRMIA), a non-profit organization that provides training, certification, and networking opportunities for risk management professionals worldwide. The CCRM certificate program aims to equip professionals with the knowledge and skills necessary to manage credit and counterparty risk effectively in a dynamic and complex financial environment.

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PRMIA 8011 CCRM Certificate is recognized globally as a benchmark for excellence in credit and counterparty risk management. It is a valuable credential for professionals who work in the financial services industry, including risk managers, credit analysts, portfolio managers, and traders. By earning this certification, individuals demonstrate their commitment to professional development and their expertise in credit and counterparty risk management.

PRMIA Credit and Counterparty Manager (CCRM) Certificate Exam Sample Questions (Q62-Q67):

NEW QUESTION # 62
Which of the following can be used to reduce credit exposures to a counterparty:
I. Netting arrangements
II. Collateral requirements
III. Offsetting trades with other counterparties
IV. Credit default swaps

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

Answer: C

Explanation:
Offsetting trades with other counterparties will not reduce credit exposure to a given counterparty. All other choices represent means of reducing credit risk. Therefore Choice 'c' is the correct answer.

NEW QUESTION # 63
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. I, II and III
B. II
C. III
D. II and III

Answer: A

Explanation:
VaR calculations look at the lower part of the distribution of future portfolio values, for example, if the desired confidence level is 95%, the cut-off for the VaR calculation will be at the bottom 5%; similarly at 1% for a 99% confidence level. The number of observations that will end up in these bottom ranges will be few and sparse, and therefore their accuracy will generally be lower than, say, the average where observations are more likely to be concentratred. If the shape of the distribution of future portfolio values is not symmetrical and has a long tail to the left, then this problem gets further exacerbated as there may be even fewer and less reliable simulated numbers at the 5% or 1% quintiles. Thus the shape of the distribution will affect the accuracy of a VaR estimate. The distribution for a short option position, for example, will have a long tail to the left, and the VaR number will be quite significantly affected by a few simulations. On the other hand, for a long option position where the long tail is to the right, and we are interested in the left tail which is better defined and ends at zero we are more likely to get a better VaR estimate. Therefore Statement I is correct.
The number of simulations carried out directly affects the standard error, which is inversely proportional to the square root of the sample size (ie the number of simulations). THe accuracy of the VaR estimate can be increased by increasing the sample size (or reduced by reducing the sample size). Therefore Statement II is correct.
The confidence level selected for the VaR estimate also affects the accuracy of the estimate. Tointuitively understand this, consider this extreme example where the desired confidence level is 99.9% and there are
1000 observations. Therefore the VaR will be determined by the last value in the sample, and will therefore be quite fickle and dependent upon what chance produces as the lowest value in the simulation. But if for the same sample the confidence level desired were to be 90%, there would be 100 observations beyond the 90% cut-off and this would be a much more stable and accurate number. Therefore the confidence level selected for the VaR estimate is also a determinant of the accuracy of the VaR estimate derived from the simulation.
Statement III is correct.
Thus all statements are correct and Choice 'b' is the correct answer.

NEW QUESTION # 64
Under the standardized approach to determining operational risk capital, operations risk capital is equal to:

A. a fixed percentage of the latest gross income of the bank
B. a fixed percentage (different for each business line) of the gross income of the eight specified business lines, averaged over three years
C. 15% of the average gross income (considering only the positive years) of the past three years
D. a varying percentage, determined by the national regulator, of the gross revenue of each of the bank's business lines

Answer: B

Explanation:
Choice 'd' is the correct answer, as laid down in the Basel II document. The other choices are incorrect.

NEW QUESTION # 65
A cumulative accuracy plot:

A. measures rating accuracy
B. measures accuracy of default probabilities observed empirically
C. is a measure of the correctness of VaR calculations
D. measures the accuracy of credit risk estimates

Answer: A

Explanation:
A cumulative accuracy plot measures the accuracy of credit ratings assigned by rating agencies by considering the relative rankings of obligors according to the ratings given. Choice 'd' is the correct answer.

NEW QUESTION # 66
A bank expects the error rate in transaction data entry for a particular business process to be 0.005%. What is the range of expected errors in a day within +/- 2 standard deviations if there are 2,000,000 such transactions each day?

A. 90 to 110 errors in a day
B. 80 to 120 errors in a day
C. 60 to 80 errors in a day
D. 0 to 200 errors in a day

Answer: B

Explanation:
Error rates are generally modeled using the Poisson distribution. Recall that the Poisson distribution has only one parameter -#- which is its mean and also its variance.
In the given case, the mean number of errors is 2,000,000 x 0.005% = 100. Since this is the variance as well, the standard deviation is #100 = 10. Therefore the range of outcomes within 2 standard deviations of the mean is 100 +/- (2*10) = 80 to 120 errors in a day.

NEW QUESTION # 67
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8011 Trustworthy Exam Content & Test 8011 Dumps Pdf

Free PDF 2025 8011: High-quality Credit and Counterparty Manager (CCRM) Certificate Exam Trustworthy Exam Content

PRMIA Credit and Counterparty Manager (CCRM) Certificate Exam Sample Questions (Q62-Q67):