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NEW QUESTION: 1
A company wants to design an internal website for the purpose of managing its numerous social events.
The site will not have heavy traffic, but will require state to be persisted in a database. You have been tasked to complete this action item in your spare time.
Which two Java EE-based approaches are best suited for quick development?
A. Use an Enterprise javaBeans (EJB) container to service-inject the domain model and support a JPA deployment.
B. Use JPA in the web tier only.
C. Use your domain model components as JavaServer Faces (JSF) managed beans.
D. Use message-driven beans to manage the posting of events.
Answer: B,C
NEW QUESTION: 2
In a metro Wi-Fi design and deployment project, which task is expected to require the most hours of work?
A. deployment planning
B. design review
C. readiness workshop
D. physical installation
Answer: D
NEW QUESTION: 3
Which of the following steps are required for computing the total loss distribution for a bank for operational risk once individual UoM level loss distributions have been computed from the underlhying frequency and severity curves:
I. Simulate number of losses based on the frequency distribution
II. Simulate the dollar value of the losses from the severity distribution III. Simulate random number from the copula used to model dependence between the UoMs IV. Compute dependent losses from aggregate distribution curves
A. All of the above
B. I and II
C. III and IV
D. None of the above
Answer: B
Explanation:
Explanation
A recap would be in order here: calculating operational risk capital is a multi-step process.
First, we fit curves to estimate the parameters to our chosen distribution types for frequency (eg, Poisson), and severity (eg, lognormal). Note that these curves are fitted at the UoM level - which is the lowest level of granularity at which modeling is carried out. Since there are many UoMs, there are are many frequency and severity distributions. However what we are interested in is the loss distribution for the entire bank from which the 99.9th percentile loss can be calculated. From the multiple frequency and severity distributions we have calculated, this becomes a two step process:
- Step 1: Calculate the aggregate loss distribution for each UoM. Each loss distribution is based upon and underlying frequency and severity distribution.
- Step 2: Combine the multiple loss distributions after considering the dependence between the different UoMs. The 'dependence' recognizes that the various UoMs are not completely independent, ie the loss distributions are not additive, and that there is a sort of diversification benefit in the sense that not all types of losses can occur at once and the joint probabilities of the different losses make the sum less than the sum of the parts.
Step 1 requires simulating a number, say n, of the number of losses that occur in a given year from a frequency distribution. Then n losses are picked from the severity distribution, and the total loss for the year is a summation of these losses. This becomes one data point. This process of simulating the number of losses and then identifying that number of losses is carried out a large number of times to get the aggregate loss distribution for a UoM.
Step 2 requires taking the different loss distributions from Step 1 and combining them considering the dependence between the events. The correlations between the losses are described by a 'copula', and combined together mathematically to get a single loss distribution for the entire bank. This allows the 99.9th percentile loss to be calculated.
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