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PRMIA 8011 (Credit and Counterparty Manager (CCRM) Certificate) Exam is a globally recognized certification program that focuses on credit risk management and counterparty risk management. The program is designed to provide professionals with the skills and knowledge necessary to identify, measure, monitor, and manage credit and counterparty risks in financial institutions. The program is ideal for professionals working in credit risk management, counterparty risk management, loan origination, credit analysis, and other related areas.

PRMIA 8011 exam is targeted towards professionals who are involved in credit and counterparty risk management, such as credit analysts, credit risk managers, and credit portfolio managers. 8011 Exam is also suitable for professionals who work in related fields, such as investment banking, corporate finance, and risk consulting. 8011 exam is rigorous and requires a deep understanding of the principles and practices of credit and counterparty risk management. Successful completion of the exam demonstrates a high level of expertise in this area and can lead to increased career opportunities and advancement.

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PRMIA Credit and Counterparty Manager (CCRM) Certificate Exam Sample Questions (Q237-Q242):

NEW QUESTION # 237
The difference between true severity and the best approximation of the true severity is called:

A. Approximation error
B. Total error
C. Estimation error
D. Fitting error

Answer: A

Explanation:
This question relates to fitting a distribution to the true severity of the operational risk loss we are trying to model. The quality of the fit, or the precision of the fit, has two elements to the difference between the severity as represented by our model and the true severity. To understand this, consider the three data points below:
a. The true severity,
b. The best approximation of the true severity in the model space, and
c. The fit based on the dataset.
- True severity is what we are trying to model.
- The model space refers to the collection of analytical distributions (log-normal, burr etc) that we are considering to arrive at the estimate of the severity.
- The 'best approximation of the true severity in the model space' is reached by estimating the parameters of the distribution that optimizes the risk functional.
- The 'fit' is the actual parameter estimates we settle for with the distribution we have determined best fits the true estimate of our severity. When estimating parameters, we have various methods available for estimation - the least squares method, the maximum likelihood method, for example, and we can get different estimates depending upon the method we choose to use.
Our severity model will be different from the true severity, and the total difference can be split into two types of errors:
1. Fitting error, represented by 'c - b' above: The difference between the fit based on the dataset and the best approximation of the true severity is called 'fitting error', ie, a measure of the extent to which we could have estimated the parameters better.
2. Approximation error, represented by 'b - a' above: Approximation error is the difference between the true severity, and the best approximation of the true severity that can be achieved within the model space is called
'approximation error'.
One can reduce the approximation error by expanding the model space by adding more distributions. This will reduce the approximation error, but generally has the effect of increasing the fitting error because the complexity of the model space increases, and there are more ways to fit to the true severity.

NEW QUESTION # 238
Which of the following objectives are targeted by rating agencies when assigning ratings:
I. Ratings accuracy
II. Ratings stability
III. High accuracy ratio (AR)
IV. Ranked ratings

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

Answer: A

Explanation:
Rating agencies target both accuracy and stability when they assign ratings. These two objectives can sometimes conflict, so a balance needs to be struck between the two. Rating agencies do not target any particular 'accuracy ratio' or rankings. Therefore Choice 'c' is the correct answer.

NEW QUESTION # 239
The largest 10 losses over a 250 day observation period are as follows. Calculate the expected shortfall at a
98% confidence level:
20m
19m
19m
17m
16m
13m
11m
10m
9m
9m

A. 18.2
B. 0
C. 14.3
D. 19.5

Answer: A

Explanation:
For a dataset with 250 observations, the top 2% of the losses will be the top 5 observations. Expected shortfall is the average of the losses beyond the VaR threshold. Therefore the correct answer is (20 + 19 + 19 + 17 +
16)/5 = 18.2m .
Note that Expected Shortfall is also called conditional VaR (cVaR), Expected Tail Loss and Tail average.

NEW QUESTION # 240
Which of the following is true in relation to the application of Extreme Value Theory when applied to operational risk measurement?
I. EVT focuses on extreme losses that are generally not covered by standard distribution assumptions II. EVT considers the distribution of losses in the tails III. The Peaks-over-thresholds (POT) and the generalized Pareto distributions are used to model extreme value distributions IV. EVT is concerned with average losses beyond a given level of confidence

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

Answer: A

Explanation:
EVT, when used in the context of operational risk measurement, focuses on tail events and attempts to build a distribution of losses beyond what is covered by VaR. Statements I, II and II are correct. Statement IV describes conditional VaR (CVAR) and not EVT.
Choice 'c' is the correct answer.

NEW QUESTION # 241
What does a middle office do for a trading desk?

A. Reconciliations
B. Transaction data entry
C. Risk analysis
D. Operations

Answer: C

Explanation:
The 'middle office' is a term used for the risk management function, therefore Choice 'd' is the correct answers. The other functions describe what the 'back office' does (IT, accounting). The 'front office' includes the traders.

NEW QUESTION # 242
......

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