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The Professional Risk Managers' International Association (PRMIA) is a non-profit organization that promotes sound risk management practices globally. The organization provides a range of educational programs and certifications, including the Credit and Counterparty Manager (CCRM) Certificate, which is designed for professionals who work in credit and counterparty risk management. The PRMIA 8011 Exam is the certification exam that candidates must pass to obtain the CCRM certificate.
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PRMIA Credit and Counterparty Manager (CCRM) Certificate Exam Sample Questions (Q15-Q20):
NEW QUESTION # 15
Which of the following is a valid approach to determining the magnitude of a shock for a given risk factor as part of a historical stress testing exercise?
I. Determine the maximum peak-to-trough change in the risk factor over the defined period of the historical event II. Determine the minimum peak-to-trough change in the risk factor over the defined period of the historical event III. Determine the total change in the risk factor between the start date and the finish date of the event regardless of peaks and troughs in between IV. Determine the maximum single day change in the risk factor and multiply by the number of days covered by the stress event
- A. I and III
- B. I, II and IV
- C. II and IV
- D. IV only
Answer: A
Explanation:
Stress events rarely play out in a well defined period of time, and looking back it is always difficult to put exact start and end dates on historical stress events. Even after that is done, the question arises as to what magnitude of a change in a particular risk factor (for example interest rates, spreads, or exchange rates) are reasonable to consider for the purposes of the stress test.
Statements I and III correctly identify the two approaches that are acceptable and used in practice - the risk manager can either take the maximum adverse move - from peak to trough - in the risk factor, or alternatively he or she could consider the change in the risk factor from the start of the event to the end as defined for the purposes of the stress test. Between the two, the approach mentioned in statement III is considered slightly superior as it produces more believable shocks.
Statement II is incorrect because we never want to consider the minimum, and statement IV is not correct as it is likely to generate a shock of a magnitude that is not plausible. Therefore Choice 'b' is the correct answer.
NEW QUESTION # 16
According to Basel II's definition of operational loss event types, losses due to acts by third parties intended to defraud, misappropriate property or circumvent the law are classified as:
- A. Third party fraud
- B. Execution delivery and system failure
- C. Internal fraud
- D. External fraud
Answer: D
Explanation:
Choice 'c' is the correct answer. 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 # 17
If the full notional value of a debt portfolio is $100m, its expected value in a year is $85m, and the worst value of the portfolio in one year's time at 99% confidence level is $60m, then what is the credit VaR?
- A. $25m
- B. $40m
- C. $15m
- D. $60m
Answer: A
Explanation:
Credit VaR is the difference between the expected value of the portfolio and the value of the portfolio at the given confidence level. Therefore the credit VaR is $85m - $ 60m = $25m. Choice 'b' is the correct answer.
Note that economic capital and credit VaR are identical at a risk horizon of one year. Therefore if the question asks for economic capital, the answer would be the same.
[Again, an alternative way to look at this is to consider the explanation given in III.B.6.2.2: Credit Var = Q(L)
- EL where Q(L) is the total loss at a given confidence interval, and EL is the expected loss. In this case Q(L)
- $100-$60 = $40, and EL = $100-$85=$15. Therefore Credit VaR = $40-$15=$25.]
NEW QUESTION # 18
Which of the following formulae describes Marginal VaR for a portfolio p, where V_i is the value of the i-th asset in the portfolio? (All other notation and symbols have their usual meaning.) A)
B)
C)
D)
All of the above
- A. Option A
- B. Option C
- C. Option D
- D. Option B
Answer: C
Explanation:
Marginal VaR of a component of a portfolio is the change in the portfolio VaR from a $1 change in the value of the component. It helps a risk analyst who may be trying to identify the best way to influence VaR by changing the components of the portfolio. Marginal VaR is also important for calculating component VaR (for VaR disaggregation), as component VaR is equal to the marginal VaR multiplied by the value of the component in the portfolio.
Marginal VaR is by definition the derivative of the portfolio value with respect to the component i. This is reflected in Choice 'a' above. Using the definitions and relationships between correlation, covariance, beta and volatility of the portfolio and/or the component, we can show that the other two choices are also equivalent to Choice 'a'.
Therefore all the choices present are correct.
NEW QUESTION # 19
Which of the following assumptions underlie the 'square root of time' rule used for computing VaR estimates over different time horizons?
I. the portfolio is static from day to day
II. asset returns are independent and identically distributed (i.i.d.)
III. volatility is constant over time
IV. no serial correlation in the forward projection of volatility
V. negative serial correlations exist in the time series of returns
VI. returns data display volatility clustering
- A. I and II
- B. I, II, III and IV
- C. I, II, V and VI
- D. III, IV, V and VI
Answer: B
Explanation:
The square root of time rule can be used to convert, say a 1-day VaR to a 10-day VaR, by multiplying the known number by the square root of time to get the VaR over a different time horizon. However, there are key assumptions that underlie the application of this rule, and statements I to IV correctly state those assumptions.
Statements V and VI are not correct, because the application of the square root of time rule requires the absence of serial correlations, and also the absence of volatility clustering (ie independence). Therefore Choice 'c' is the correct answer.
The square root of time rule is also applied to convert volatility or standard deviation for one period to the volatility for a different time period. Remember that VaR is just a multiple of volatility, and therefore the assumptions that apply to the square root of time rule for VaR also apply to the same rule when used in the context of volatilities or standard deviation.
NEW QUESTION # 20
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