Chapter 29: Modelling Flashcards Preview

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Flashcards in Chapter 29: Modelling Deck (23)
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1
Q

Requirements of a good model

A

A good model will:
- be valid, rigorous and well documented
- be communicable and the output verifiable
- not be overly complex or time consuming to run
- be capable of development and refinement
- be capable of being implemented in a range of ways.
- reflect the risk profile of the business being modelled
- allow for all the significant features of the business
being modelled
- have appropriate input parameters and parameter values

A model needs to allow for all the cashflows that may arise, including:
- guaranteed and discretionary benefits e.g.
reversionary and terminal bonuses
- cashflows arising from any supervisory requirement to
hold provisions
- the potential cashflows arising from options and
guarantees

2
Q

Dynamic model

A

Allows for the interaction between the parameters and variables affecting the cashflows

3
Q

Steps involved in running a deterministic model

A
  • specify the purpose
  • collect, group and modify the data
  • choose the form of model
  • identify the parameters and variables
  • ascribe the parameter values
  • construct a model based on expected cashflows
  • check the goodness of fit is acceptable
  • fit a new model if the first choice does not fit well
  • run the model using selected values of the variables and values that will apply in the future
  • sensitivity test the parameters
4
Q

Steps involved in running a stochastic model

A
  • specify the purpose
  • collect, group and modify the data
  • choose a suitable density function for each stochastic variable
  • specify the correlations between the variables
  • construct a model based on expected cashflows
  • check the goodness of fit is acceptable
  • fit a new model if the first choice does not fit well
  • run the model many times using randomly generated values of the stochastic variables
  • produce a summary of the results
5
Q

Risk discount rate could allow for

A
  • the return required by the company

- the level of statistical risk (assessed analytically or by sensitivity analysis or from a stochastic model)

6
Q

Premiums resulting from the model may need to be considered relative to the market, which may require reconsideration of:

A
  • product design
  • distribution channels
  • profit requirement
  • size of the market
  • whether to go ahead with the product
7
Q

Define a model

A

A cut-down, simplified version of reality
…. that captures the essential features of a problem
…. and aids in:
—- understanding of the problem.
—- producing (potential) answers to the problem.

8
Q

3 Approaches to obtaining a model

A
  • a commercial modelling product could be purchased
  • an existing model could be reused, possibly after modification
  • a new model could be developed
9
Q

The merits of the modelling approaches will depend on (5)

A
  • the level of accuracy required
  • the “in-house” expertise available
  • the number of times the model is to be used
  • the desired flexibility of the model
  • the cost of each option
10
Q

The prime objective in building a model

A

To enable a provider of financial products to be run in a sound financial way.

11
Q

Merits of a deterministic model

A
  • more readily explicable to a non-technical audience, since the concept of variables as probability distributions is not easy to understand.
  • it is clearer what economic scenarios have been tested
  • the model is usually easier to design and quicker to run.
12
Q

Disadvantage of a deterministic model

A

it requires thought as to the range of economic scenarios that should be tested.

13
Q

Merits of a stochastic model. what are stochastic models particularly good at?

A

Tests a wider range of economic scenarios.

Stochastic models are particularly important in assessing the impact of financial guarantees.

14
Q

Disadvantage of a stochastic model

A

The programming is more complex and the run time longer.

15
Q

What is meant by a “dynamic” model

A

The asset and liability parts are programmed to interact as they do in reality

and the assumptions affecting assets and liabilities (for example inflation and interest rates) are consistent.

16
Q

Model point

A

A representative policy.

It is usual to identify model points, which represent relatively homogeneous underlying groups of policies.

17
Q

The risk discount rate could allow for (2)

A
  • the return required by the company

- the level of statistical risk (assessed analytically or by sensitivity analysis or from a stochastic model)

18
Q

Considering the resulting premiums from the model relative to the market requires consideration of (5)

A
  • product design
  • distribution channel
  • profit requirement
  • size of market
  • whether to go ahead with the product.
19
Q

Statistical risk (3 parts)

A

Comprises:

  • model risk
  • parameter risk
  • random fluctuation risk
20
Q

The level of statistical risk could be assessed in 4 ways

A
  • analytically, by considering the variances of the individual parameter values (this is a proxy to assess the possible magnitude of deviation from the model in reality)
  • by using sensitivity analysis, with deterministically addressed variations in the parameter values.
  • by using stochastic models for some, or all, of the parameter values and simulation
  • by comparison with any available market data.
21
Q

Why is a model necessary in the first place?

A

Some problems cannot be solved by closed-form solutions, they are too complex.
Need some simplification to get insight into the problem.

22
Q

How would a model aid in understanding the problem? (4)

A
  • What are the essential features
  • Interactions
  • What can happen (possible output)
  • Often just the act of producing a model, highlights issues
23
Q

A rigorous model

A

One that produces realistic (and hence useful) results under a wide range of circumstances and conditions.

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