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PRMIA 8011 Certification Exam covers a range of topics related to credit and counterparty risk management, including credit analysis, risk assessment, credit derivatives, collateral management, and default management. 8011 exam is designed to test the candidate's understanding of these topics and their ability to apply them in real-world situations.

The Professional Risk Managers' International Association (PRMIA) is a non-profit organization dedicated to promoting best practices in risk management. One of their key initiatives is the PRMIA certification program, which offers a range of certifications for professionals in the risk management industry. Among these certifications is the PRMIA 8011 Credit and Counterparty Manager (CCRM) Certificate, which is designed to validate the knowledge and skills of professionals in the field of credit and counterparty risk management.

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PRMIA Credit and Counterparty Manager (CCRM) Certificate Exam Sample Questions (Q324-Q329):

NEW QUESTION # 324
The estimate of historical VaR at 99% confidence based on a set of data with 100 observations will end up being:

• A. the extrapolated returns of the last 1.64 observations
• B. the weighted average of the top 2.33 observations
• C. None of the above
• D. the worst single observation in the data set

Answer: D

Explanation:
The VaR in this case will be the top quintile of observations. In this case, since there are exactly 100 observations, this would mean the worst return would become the VaR. Therefore Choice 'b' is the correct answer. Choice 'a' and Choice 'c' make no sense. This highlights that at higher confidence levels, fewer and fewer observations impact the VaR if we are using historical simulation based VaR.

NEW QUESTION # 325
Calculate the 1-year 99% credit VaR of a portfolio of two bonds, each with a value of $1m, and the probability of default of 1% each over the next year. Assume the recovery rate to be zero, and the defaults of the two bonds to be uncorrelated to each other.

• A. 0
• B. 1
• C. 2
• D. 3

Answer: B

Explanation:
This question requires the calculation of the credit VaR of the bonds - note that in the real exam the question may not refer to 'credit' VaR, but that can be inferred from the context, ie because the probability of default is provided, it can only be asking for the credit VaR. (Note the difference from the market risk VaR which is driven by interest rate changes affecting the value of the bonds - there are other questions addressing that calculation).
Credit VaR = Expected Value - Worst case portfolio value at the selected percentile (ie the confidence level) Thus if we know the distribution of the portfolio value in the future, we can find out the value at the required percentile (in this case 99%), and the VaR will be the difference between this value and the expected value of the portfolio.
An important piece of information provided is that the defaults are independent, ie they are not correlated.
This means joint probabilities of default or survival can be easily found by multiplying the relevant probabilities. The following outcomes are possible:
1. Both bonds default: Probability = 1% * 1% = 0.01%. Portfolio value = $0 (because both bonds have defaulted & there is zero recovery)
2. One bond defaults and the other survives: Probability = 2 * 1% * 99% = 1.98%. Portfolio value = $1m (because one bond survives with a value of $1m and the defaulted bond has a value of $0). (Note that because there are two ways in which this can happen, ie bond 1 defaults, bond 2 survives; and bond 1 survives, bond 2 defaults, we need to multiply the probability by 2).
3. Both bonds survive: Probability = 99% * 99% = 98.01%. Portfolio value = $2m.
Expected value is therefore $1.98m (which is equal to 2 * $1m * (1 - 1%), or alternatively can also be obtained by multiplying the probabilities in the above three outcomes with the value associated with each).
The future distribution of the value of the portfolio can be constructed from the three outcomes outlined above:
a. Upto the 98.01th percentile the value of the portfolio is $2m, and the VaR is zero (being greater than the expected value, so there is nothing to lose) b. From the 98.01th percentile to the 99.99th percentile (98.01+ the next 1.98%), the value of the portfolio is
$1m. VaR in this range is $0.98m (=$1.98m - $1m)
c. From the 99.99th to the 100th percentile the value of the portfolio is $0, and the VaR is $1.98m.
Since the question is asking for VaR at the 99% confidence level, it lies in the range in 'b' above, and therefore the VaR is $0.98m.
Therefore Choice 'c' is the correct answer and the rest are incorrect.

NEW QUESTION # 326
When modeling operational risk using separate distributions for loss frequency and loss severity, which of the following is true?

• A. Loss severity and loss frequency are considered independent
• B. Loss severity and loss frequency distributions are considered as a bivariate model with positive correlation
• C. Loss severity and loss frequency are modeled as conditional probabilities
• D. Loss severity and loss frequency are modeled using the same units of measurement

Answer: A

Explanation:
When modeling operational loss frequency distribution (which, for example, may be based upon a Poisson distribution) and a loss severity distribution (for example, based upon a lognormal distribution), it is assumed that the frequency of losses and the severity of the losses are completely independent and do not impact each other. Therefore Choice 'a' is correct, and the others are not valid assumptions underlying the operational loss modeling.
Once each of these distributions has been built, a random number is drawn from each to determine a loss scenario. The process is repeated many times as part of a Monte Carlo simulation to get a the loss distribution.

NEW QUESTION # 327
Which of the following event types is hacking damage classified under Basel II operational risk classifications?

• A. External fraud
• B. Technology risk
• C. Damage to physical assets
• D. Information security

Answer: A

Explanation:
Choice 'b' is the correct answer. All other answers are incorrect.
Refer to the detailed loss event type classification under Basel II (see Annex 9 of the accord). You should know the exact names of all loss event types, and examples of each.

NEW QUESTION # 328
The returns for a stock have a monthly volatilty of 5%. Calculate the volatility of the stock over a two month period, assuming returns between months have an autocorrelation of 0.3.

• A. 8.062%
• B. 5%
• C. 10%
• D. 7.071%

Answer: A

Explanation:
The square root of time rule cannot be applied here because the returns across the periods are not independent.
(Recall that the square root of time rule requires returns to be iid, independent and identically distributed.) Here there is a 'autocorrelation' in play, which means one period's returns affect the returns of the other period.
This problem can be solved by combining the variance of the returns from the two consecutive periods in the same way as one would combine the variance of different assets that have a givencorrelation. In such cases we know that:
Variance (A + B) = Variance(A) + Variance(B) + 2*Correlation*StdDev(A)*StdDev(B).
The standard deviation can be calculated by taking the square root of the variance.
Therefore the combined volatility over the two months will be equal to =SQRT((5%