Free PRMIA 8010 Exam Questions
Absolute Free 8010 Exam Practice for Comprehensive Preparation
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PRMIA 8010 Exam Questions
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Provided By: PRMIA
- Exam: Operational Risk Manager (ORM)
- Certification: PRM
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Total Questions: 242
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Updated On: Apr 14, 2026
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Rated: 4.9 |
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Online Users: 484
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Question 1
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The frequency distribution for operational risk loss events can be modeled by which of the followingdistributions:I. The binomial distributionII. The Poisson distributionIII. The negative binomial distributionIV. The omega distribution
Answer: A
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Question 2
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Which of the following statements are true:I.Top down approaches help focus management attention on the frequency and severity of loss events, whilebottom up approaches do not.II. Top down approaches rely upon high level data while bottom up approaches need firm specific risk data toestimate risk.III. Scenario analysis can help capture both qualitative and quantitative dimensions of operational risk.
Answer: B
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Question 3
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For a hypotherical UoM, the number of losses in two non-overlapping datasets is 24 and 32 respectively. The
Pareto tail parameters for the two datasets calculated using the maximum likelihood estimation method are 2
and 3. What is an estimate of the tail parameter of the combined dataset?
Answer: A
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For a hypotherical UoM, the number of losses in two non-overlapping datasets is 24 and 32 respectively. The
Pareto tail parameters for the two datasets calculated using the maximum likelihood estimation method are 2
and 3. What is an estimate of the tail parameter of the combined dataset?
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Question 4
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Which of the following decisions need to be made as part of laying down a system for calculating VaR:I. The confidence level and horizonII. Whether portfolio valuation is based upon a delta-gamma approximation or a full revaluationIII. Whether the VaR is to be disclosed in the quarterly financial statementsIV. Whether a 10 day VaR will be calculated based on 10-day return periods, or for 1-day and scaled to 10days
Answer: C
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Question 5
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Whichof the following statements are true in relation to Historical Simulation VaR?I. Historical Simulation VaR assumes returns are normally distributed but have fat tailsII. It uses full revaluation, as opposed to delta or delta-gamma approximationsIII. Acorrelation matrix is constructed using historical scenariosIV. It particularly suits new products that may not have a long time series of historical data available
Answer: A
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