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Question 1 of 10
1. Question
Which type of process gives rise to claims in a portfolio of business in general insurance?
Correct
There is a process known as the Poisson Process, which is one of the most widely-used counting processes. It is usually used where we are counting the occurrences of certain events that appear to happen at a certain rate, but completely at random without a certain structure. It gives rise to claims in a portfolio of business in general insurance.
Incorrect
There is a process known as the Poisson Process, which is one of the most widely-used counting processes. It is usually used where we are counting the occurrences of certain events that appear to happen at a certain rate, but completely at random without a certain structure. It gives rise to claims in a portfolio of business in general insurance.
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Question 2 of 10
2. Question
There are two obvious quantities of interest for general insurance risk. What are they?
Correct
In a portfolio of general insurance risk policies, two obvious quantities of interest are the number of claims arriving in a fixed time period and the sizes of those claims.
Incorrect
In a portfolio of general insurance risk policies, two obvious quantities of interest are the number of claims arriving in a fixed time period and the sizes of those claims.
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Question 3 of 10
3. Question
What do you understand by the term counting distribution?
Correct
Suitable models for claim numbers are the model of counting distributions, which is done by the distributions of discrete random variables that can assume some or all of the values in N = {0, 1, 2, . . .} and so on.
Incorrect
Suitable models for claim numbers are the model of counting distributions, which is done by the distributions of discrete random variables that can assume some or all of the values in N = {0, 1, 2, . . .} and so on.
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Question 4 of 10
4. Question
Which type of claim model will you use for the distributions which allow for occasional occurrences of very large values?
Correct
The most widely used models for claim sizes are the distributions of the continuous random variables that assume positive values only and have heavy tails that are also known as fat tails, that is distributions that allow for occasional occurrences of very large values.
Incorrect
The most widely used models for claim sizes are the distributions of the continuous random variables that assume positive values only and have heavy tails that are also known as fat tails, that is distributions that allow for occasional occurrences of very large values.
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Question 5 of 10
5. Question
How many parameters does the Poisson Process have?
Correct
There are three families of counting random variables used as models for claim numbers, one is named as the one-parameter Poisson family, the other one being the two-parameter negative binomial family, which includes the one-parameter geometric subfamily, and the third one is the two-parameter binomial family.
Incorrect
There are three families of counting random variables used as models for claim numbers, one is named as the one-parameter Poisson family, the other one being the two-parameter negative binomial family, which includes the one-parameter geometric subfamily, and the third one is the two-parameter binomial family.
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Question 6 of 10
6. Question
which of these do not provide good models for claim sizes in most practical situations?
Correct
These three models do not provide good models for claim sizes in most practical situations but are thought to be useful for reference and comparison purposes. These are named as: the two-parameter normal -Gaussian family, the one-parameter exponential family, and the two-parameter gamma family which includes the exponential as a sub-family.
Incorrect
These three models do not provide good models for claim sizes in most practical situations but are thought to be useful for reference and comparison purposes. These are named as: the two-parameter normal -Gaussian family, the one-parameter exponential family, and the two-parameter gamma family which includes the exponential as a sub-family.
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Question 7 of 10
7. Question
When do we consider mixture distributions in the claim size?
Correct
When the claim-size distribution models are extended to allow for heterogeneity of risks within a portfolio. This is done by recognizing that there is uncertainty in the value of a parameter in a claim-size distribution and then adopting a probability distribution, which’s called a mixing or prior distribution, to model that uncertainty.
Incorrect
When the claim-size distribution models are extended to allow for heterogeneity of risks within a portfolio. This is done by recognizing that there is uncertainty in the value of a parameter in a claim-size distribution and then adopting a probability distribution, which’s called a mixing or prior distribution, to model that uncertainty.
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Question 8 of 10
8. Question
What is a ‘mixing distribution’ in the claim-distribution?
Correct
When there is uncertainty found in the value of a parameter in a claim-size distribution, the adoption of a probability distribution called a “prior” or “mixing” distribution is done to model that uncertainty. The derivation of the unconditional marginal distribution of the claim-size random variable is called a “mixture” distribution.
Incorrect
When there is uncertainty found in the value of a parameter in a claim-size distribution, the adoption of a probability distribution called a “prior” or “mixing” distribution is done to model that uncertainty. The derivation of the unconditional marginal distribution of the claim-size random variable is called a “mixture” distribution.
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Question 9 of 10
9. Question
Why is a normally distributed random variable not an appropriate model for positive claim size?
Correct
A normally distributed random variable can take negative values as well as positive values, that is why it is not an appropriate model for positive claim size. However, it is sometimes used for theory because the normal distribution may be used as an approximation to many distributions and also because it arises as a limiting distribution.
Incorrect
A normally distributed random variable can take negative values as well as positive values, that is why it is not an appropriate model for positive claim size. However, it is sometimes used for theory because the normal distribution may be used as an approximation to many distributions and also because it arises as a limiting distribution.
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Question 10 of 10
10. Question
What are the benefits of mixing distribution?
Correct
The approach provides motivation for the use of particular families of claim-size distributions and is also itself a source of fat-tailed distributions.
Incorrect
The approach provides motivation for the use of particular families of claim-size distributions and is also itself a source of fat-tailed distributions.