New 2021 8008 Dumps for PRM Certification Certified Exam Questions & Answer
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NEW QUESTION 11
Which of the following introduces model error when basing VaR on a normal distribution with a static mean and standard deviation?
- A. Heavy tails
- B. All of the above
- C. Volatility clustering
- D. Autocorrelation of squared returns
Answer: B
Explanation:
Explanation
When VaR is based on an assumption of normality with a static mean and volatility, it means anything that violates these assumptions will introduce model error. Volatility clustering implies a non-static volatility.
Heavy tails imply non-normality of the shape of the distribution. Autocorrelation of squared returns implies that returns are not independent and identically distributed. Therefore all of these introduce model error.
Choice 'd' is therefore the correct answer.
NEW QUESTION 12
Which of the following are valid techniques used when performing stress testing based on hypothetical test scenarios:
I. Modifying the covariance matrix by changing asset correlations
II. Specifying hypothetical shocks
III. Sensitivity analysis based on changes in selected risk factors
IV. Evaluating systemic liquidity risks
- A. I and II
- B. I, II and III
- C. II, III and IV
- D. I, II, III and IV
Answer: A
Explanation:
Explanation
Each of these represent valid techniques for performing stress testing and building stress scenarios. Therefore d is the correct answer. In practice, elements of each of these techniques is used depending upon the portfolio and the exact situation.
NEW QUESTION 13
The results of 'desk-level' stress tests cannot be added together to arrive at institution wide estimates because:
- A. Desk-level stress tests tend to focus on extreme movements in risk parameters (such as volatility) without considering economy wide scenarios that may represent more realistic and consistent situations for the institution.
- B. Desk-level stress tests focus on desk specific risks that may be minor or irrelevant in the larger scheme at the institution level.
- C. All of the above
- D. Desk-level stress tests tend to ignore higher level risks that are relevant to the institution but completely outside the control of the individual desks.
Answer: A
Explanation:
Explanation
All the above listed reasons are valid explanations as to why an institution level stress test cannot be estimated by merely summing up the results of the stress tests of the individual desks.
NEW QUESTION 14
CreditRisk+, the actuarial model for calculating portfolio credit risk, is based upon:
- A. the exponential distribution
- B. the log-normal distribution
- C. the Poisson distribution
- D. the normal distribution
Answer: C
Explanation:
Explanation
CreditRisk+ treats default as a binary event, ignoring downgrade risk, capital structures of individual firms in the portfolio or the causes of default. It uses a single parameter, or the mean default rate, and derives credit risk based upon the Poisson distribution. Therefore Choice 'c' is the correct answer.
NEW QUESTION 15
Which of the following is closest to the description of a 'risk functional'?
- A. A risk functional assigns a penalty value for the difference between a model distribution and a risk's severity distribution
- B. A risk functional is the distribution that models the severity of a risk
- C. Risk functional refers to the Kolmogorov-Smirnov distance
- D. A risk functional is a model distribution that is an approximation of the true loss distribution of a risk
Answer: A
Explanation:
Explanation
For operational risk modeling, both frequency and severity distributions need to be modeled. Modeling severity involves finding an analytical distribution, such as log-normal or other that approximates the distribution best represented by known data - whether from the internal loss database, the external loss database or scenario data. A 'risk functional' is a measure of the deviation of the model distribution from the risk's actual severity distribution. It assigns a penalty value for the deviation, using a statistical measure, such as the KS distance (Kolmogorov-Smirnov distance).
The problem of finding the right distribution then becomes the problem of optimizing the risk functional. For example, if F is the model distribution, and G is the actual, or empirical severity distribution, and we are using the KS test, then the Risk Functional R is defined as follows:
Note that supx stands for 'supremum', which is a more technical way of saying 'maximum'. In other words, we are calculating the maximum absolute KS distance between the two distributions. (Note that the KS distance is the max of the distance between identical percentiles of the two distributions using the CDFs of the two.) Once the risk functional is identified, we can minimize it to determine the best fitting distribution for severity.
NEW QUESTION 16
An operational loss severity distribution is estimated using 4 data points from a scenario. The management institutes additional controls to reduce the severity of the loss if the risk is realized, and as a result the estimated losses from a 1-in-10-year losses are halved. The 1-in-100 loss estimate however remains the same.
What would be the impact on the 99.9th percentile capital required for this risk as a result of the improvement in controls?
- A. Can't say based on the information provided
- B. The capital required will decrease
- C. The capital required will increase
- D. The capital required will stay the same
Answer: C
Explanation:
Explanation
This situation represents one of the paradoxes in estimating severity that one needs to be aware of - the improvement in controls reduces the weight of the body/middle of the distribution and moves it towards the tails (as the total probability under the curve must stay at 100%) and the distribution becomes more heavy tailed. As a result, the 99.9th percentile loss actually increases. instead of decreasing, creating a counterintuitive result. Therefore the correct answer is that the capital required will increase.
If scenario analysis produces such a result, the analyst must question if the 1 in 100 year loss severity is still accurate. If the new control has reduced the severity in the body of the distribution, the question as to why the more extreme losses have not changed should be raised.
NEW QUESTION 17
Under the contingent claims approach to measuring credit risk, which of the following factors does NOT affect credit risk:
- A. Volatility of the firm's asset values
- B. Maturity of the debt
- C. Leverage in the capital structure
- D. Cash flows of the firm
Answer: D
Explanation:
Explanation
Under the contingent claims approach, credit risk is modeled as the value of a put option on the value of the firm's assets with a strike equal to the face value of the debt and maturity equal to the maturity of the obligation. The cost of credit risk is determined by the leverage ratio, the volatility of the firm's assets and the maturity of the debt. Cash flows are not a part of the equation. Therefore Choice 'a' is the correct answer.
NEW QUESTION 18
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. II and III
- B. II
- C. I, II and III
- D. III
- E. B
Answer: E
Explanation:
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. To intuitively 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 19
A bank's detailed portfolio data on positions held in a particular security across the bank does not agree with the aggregate total position for that security for the bank. What data quality attribute is missing in this situation?
- A. Data extensibility
- B. Data integrity
- C. Auditability
- D. Data completeness
Answer: B
Explanation:
Explanation
The term 'data quality' has multiple elements, ie, data in order to be considered of a high quality must have multiple attributes such as completeness, timeliness, auditability etc. Because this is not an exact science, every expert or text book will have a different view of what goes into data quality. For our purposes however, we will stick to what the PRMIA study material specifies, and according to the study material the following are the elements that can be considered attributes that make for quality data:
1. Integration
2. Integrity
3. Completeness
4. Accessibility
5. Flexibility
6. Extensibility
7. Timeliness
8. Auditability
I am not going to describe each of these here as that would be repetitive of the study material, but suffice it to say that the break-down of a number into its constituents should tie to the aggregate total. If that is not true, then the data lacks integrity - and therefore Choice 'b' is the correct answer. The other choices address other aspects of data quality but not this, and therefore are not correct.
NEW QUESTION 20
A Monte Carlo simulation based VaR can be effectively used in which of the following cases:
- A. When returns data cannot be analytically modeled
- B. Where analytical methods are too complex to effectively use
- C. All of the above
- D. D
- E. When returns are discontinuous or display large jumps
Answer: D
Explanation:
Explanation
Monte Carlo simulations can be effectively used in all cases where an analytical estimate of the VaR cannot be made for any reason - which may include complexity of portfolios, discontinuities or non-linearity in returns or just the plain unavailability of closed form analytical models. Therefore Choice 'd' is the correct answer.
NEW QUESTION 21
Which of the following represents a riskier exposure for a bank: A LIBOR based loan, or an Overnight Indexed Swap? Which of the two rates is expected to be higher?
Assume the same counterparty and the same notional.
- A. A LIBOR based loan; OIS rate will be higher
- B. Overnight Index Swap; LIBOR rate will be higher
- C. A LIBOR based loan; LIBOR rate will be higher
- D. Overnight Index Swap; OIS rate will be higher
Answer: C
Explanation:
Explanation
A LIBOR based loan requires cash to move from the lender to the borrower in the amount of the notional. The Overnight Index Swap requires only the exchange of interest payments, and therefore represents less risk.
Therefore the LIBOR based loan is a riskier exposure.
The LIBOR is generally higher than the OIS. In fact, the difference between the two, the LIBOR-OIS spread, is a standard measure of the risk premium in the market that goes up when the risk of default by counterparty banks is considered high. This is because when the market perceives the risk of default to be high, the participants need a risk premium to take on the default risk which is considerably lesser with the OIS.
NEW QUESTION 22
The diversification effect is responsible for:
- A. total VaR numbers being greater than the sum of the individual VaRs for underlying portfolios
- B. VaR being applicable only to short term horizons
- C. the sub-additivity property of market risk VaR assessments
- D. the super-additivity property of market risk VaR assessments
Answer: C
Explanation:
Explanation
Any good risk measure has the property that it is sub-additive, which means the whole is less than the sum of the parts. In the case of VaR, sub-additivity arises due to the diversification effect, or said differently, due to the correlation between different assets being less than one. Therefore Choice 'd' is the correct answer.
Super-additivity is just the opposite of sub-additivity, ie, the whole is greater than the sum of the parts. Good risk measures do not have super-additivity. Therefore Choice 'b' is incorrect.
Choice 'c' states the same thing as Choice 'b' in different words, and is incorrect. Choice 'a' is non-sensical and incorrect.
NEW QUESTION 23
Which of the following statements is true in relation to the Supervisory Capital Assessment Program (SCAP):
I. The SCAP is an annual exercise conducted by the Treasury Department to determine the health of key financial institutions in the US economy II. The SCAP was essentially a stress test where the stress scenarios were specified by the regulators III. Capital buffers calculated under the SCAP represented the amount of capital that the institutions covered by SCAP held in excess of Basel II requirements IV. The SCAP focused on both total Tier 1 capital as well as Tier 1 common capital
- A. I, II and IV
- B. I and III
- C. II and IV
- D. I and III
Answer: C
Explanation:
Explanation
In the February of 2009, the Federal Reserve (which is the US central bank system) and other US banking regulators embarked on a simultaneous assessment of the capital held by the 19 largest US bank holding companies. This was an unprecedented exercise of a kind never undertaken before, and was known as the Supervisory Capital Assessment Program (SCAP). The purpose of the exercise was to determine the amount of additional capital (called the 'capital buffer') each of the institutions covered would need to ensure that it would have sufficient capital if the economy weakened more than was then expected. The idea was that these financial institutions would then raise additional capital equal to their respective capital buffers by the fourth quarter of 2009.
Statement I is false on two counts: firstl the SCAP was conducted by the US central bank and other regulators, and not the 'Treasury Department' (the Treasury Department in the US is the equivalent of the Ministry of Finance in may other countries). Second, the SCAP was a one time exercise, and not annual.
Statement II is correct. The regulators prescribed rates of losses on credit assets of different kinds and other macro-economic assumptions, and asked the banks to determine the extent of losses they would need to bear (in addition to calculating them independently too). Therefore the SCAP was a stress test where the scenario was prescribed by the regulators.
Statement III is false. Capital buffer under the SCAP referred to the additional capital the banks would need to have certain ratios of capital, and not 'excess' capital.
Statement IV is correct. The SCAP envisaged two capital targets: a Tier 1 capital ratio in excess of 6% at the end of 2010; and a Tier 1 common capital ratio in excess of 4%. Therefore both the total Tier 1 capital and Tier 1 common capital were targeted.
Therefore Choice 'c' is the correct answer.
NEW QUESTION 24
If an institution has $1000 in assets, and $800 in liabilities, what is the economic capital required to avoid insolvency at a 99% level of confidence? The VaR in respect of the assets at 99% confidence over a one year period is $100.
- A. 0
- B. 1
- C. 2
- D. 3
Answer: B
Explanation:
Explanation
The economic capital required to avoid insolvency is just the asset VaR, ie $100. This means that if the worst case losses are realized, the institution would need to have a buffer equivalent to those losses which in this case will be $100, and this buffer is the economic capital.
The actual value of liabilities is not relevant as they are considered 'riskless' from the institution's point of view, ie they will be taken at full value. In this particular case, the institution has $200 in capital which is more than the economic capital required.
Therefore Choice 'c' is the correct answer.
NEW QUESTION 25
Which of the following statements are true in relation to Historical Simulation VaR?
I. Historical Simulation VaR assumes returns are normally distributed but have fat tails II. It uses full revaluation, as opposed to delta or delta-gamma approximations III. A correlation matrix is constructed using historical scenarios IV. It particularly suits new products that may not have a long time series of historical data available
- A. I and IV
- B. II and III
- C. II
- D. A
- E. All of the above
Answer: D
Explanation:
Explanation
Historical Simulation VaR is conceptually very straightforward: actual prices as seen during the observation period (1 year, 2 years, or other) become the 'scenarios' forming the basis of the valuation of the portfolio. For each scenario, full revaluation is performed, and a P&L data set becomes available from which the desired loss quantile can be extracted.
Historical simulation is based upon actually seen prices over a selected historical period, therefore no distributional assumptions are required. The data is what the data is, and is the distribution. Statement I is therefore not correct.
It uses full revaluation for each historical scenario, therefore statement II is correct.
Since the prices are taken from actual historical observations, a correlation matrix is not required at all.
Statement III is therefore incorrect (it would be true for Monte Carlo and parametric Var).
Historical simulation VaR suffers from the limitation that if enough representative data points are no available during the historical observation period from which the scenarios are drawn, the results would be inaccurate.
This is likely to be the case for new products. Therefore Statement IV is incorrect.
NEW QUESTION 26
Which of the following are considered asset based credit enhancements?
I. Collateral
II. Credit default swaps
III. Close out netting arrangements
IV. Cash reserves
- A. I, II and IV
- B. I and IV
- C. I and III
- D. II and IV
Answer: C
Explanation:
Explanation
Credit enhancements come in two varieties: counterparty based, where the exercise of the credit enhancement requires a third party to pay, and this includes guarantees and CDS contracts. Asset based credit enhancements are based upon a physical asset in possession, and these include collateral and balances owed on other trades or transactions, and availed through close out netting arrangements.
Of the listed choices, I and III are asset based credit enhancements, and II is third party based. Cash reserves are not credit enhancements (unless held as collateral).
NEW QUESTION 27
Random recovery rates in respect of credit risk can be modeled using:
- A. the omega distribution
- B. the beta distribution
- C. the normal distribution
- D. the binomial distribution
Answer: B
Explanation:
Explanation
The beta distribution is commonly used to model recovery rates. It is a distribution for variables whose values lie between 0 & 1, and the parameters of the distribution can be estimated using the mean and standard deviation of the data. Therefore Choice 'a' is correct and the others are wrong.
Refer to the tutorial on distributions for an Excel model of the beta distribution.
NEW QUESTION 28
For a security with a daily standard deviation of 2%, calculate the 10-day VaR at the 95% confidence level.
Assume expected daily returns to be nil.
- A. 0.1471
- B. 0.104
- C. 0.02
- D. None of the above.
Answer: B
Explanation:
Explanation
If the daily standard deviation is 2%, the 10-day standard deviation will be 2%* 10 = 0.063245. The value of Z at the 95% confidence level is 1.64485. Therefore the VaR value is 1.64485 * 0.063245 = 10.4%. The other choices are incorrect.
NEW QUESTION 29
Which of the following statements are true:
I. Top down approaches help focus management attention on the frequency and severity of loss events, while bottom up approaches do not.
II. Top down approaches rely upon high level data while bottom up approaches need firm specific risk data to estimate risk.
III. Scenario analysis can help capture both qualitative and quantitative dimensions of operational risk.
- A. III only
- B. II and III
- C. I only
- D. II only
Answer: B
Explanation:
Explanation
Top down approaches do not consider event frequency and severity, on the other hand they focus on high level available data such as total capital, income volatility, peer group information on risk capital etc. Bottom up approaches focus on severity and frequency distributions for events. Statement I is therefore not correct.
Top down approaches do indeed rely upon high level aggregate data and tend to infer operational risk capital requirements from these. Bottom up approaches look at more detailed firm specific information. Statement II is correct.
Scenario analysis requires estimating losses from risk scenarios, and allows incorporating the judgment and views of managers in addition to any data that might be available from internal or external loss databases.
Statement III is correct. Therefore Choice 'b' is the correct answer.
NEW QUESTION 30
Which of the following are measures of liquidity risk
I. Liquidity Coverage Ratio
II. Net Stable Funding Ratio
III. Book Value to Share Price
IV. Earnings Per Share
- A. I and IV
- B. I and II
- C. II and III
- D. III and IV
Answer: B
Explanation:
Explanation
In December 2009 the BIS came out with a new consultative document on liquidity risk. Given the events of
2007 - 2009, it has been clear that a key characteristic of the financial crisis was the inaccurate and ineffective management of liquidity risk The paper two separate but complementary objectives in respect of liquidity risk management: The first objective relates to the short-term liquidity risk profile of institution, and the second objective is to promote resiliency over longer-term time horizons. The paper identifies the following two ratios - you should be aware of these - though I am not sure if these will show up in the PRMIA exam:
1. Liquidity Coverage Ratio addresses the ability of an institution to survive an acute liquidity risk stress scenario lasting one month. It is calculated as follows:
Liquidity Coverage Ratio = Stock of high quality liquid assets/Net cash outflows over a 30-day time period
2. Net Stable Funding Ratio has been developed to capture structural issues related to funding choices.
Net Stable Funding Ratio = Available amount of stable funding/Required amount of stable funding Both ratios should be equal to or greater than 1. The statement contains detailed definitions of what is included or excluded from each of the terms used in the calculations for each of the ratios. In addition, the standard also describes the what the 'acute' scenario should include (things such as a 3 notch credit downgrade, reduction in retail deposits etc) Therefore Choice 'b' is the correct answer. Book Value to Share Price and Earnings Per Share are accounting measures unrelated to liquidity.
NEW QUESTION 31
Which of the following is true for the actuarial approach to credit risk modeling (CreditRisk+):
- A. The number of defaults is modeled using a binomial distribution where the number of defaults are considered discrete events
- B. The approach considers only default risk, and ignores the risk to portfolio value from credit downgrades
- C. The approach is based upon historical rating transition matrices
- D. Default correlations between obligors are accounted for using a multivariate normal model
Answer: B
Explanation:
Explanation
The actuarial model considers defaults to follow a Poisson distribution with a given mean per period, and these are binary in nature, ie a default happens or it does not happen. The model does not consider the loss of value from credit downgrades, and focuses only on defaults. The model also does not consider default correlations between obligors. Therefore Choice 'c' is the correct answer.
The other choices are not true statements that would apply to the actuarial approach.
NEW QUESTION 32
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