18. Modelling Flashcards

1
Q

Obtaining models

A
  • Commercial purchase
  • Modify existing model
  • New model
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2
Q

Constructing models

A
  1. Must fit purpose
  2. Operational issues to be considered
    - Well documented
    - Easily communicable, with clearly displayed results
    - Have sensible behaviour of variables
    - Capable of independent verification
    - Not be overly complex/time consuming to run
    - Be capable of development and refinement
    - Be capable of being implemented in range of ways
    - Have appropriate time period between projected cashflows, balancing reliability of output with speed of running model
  3. Stochastic vs Deterministic / combination
  4. Must be dynamic
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3
Q

Dynamic model

A

Allows for interaction between parameters and variables affecting cashflows

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4
Q

Steps in developing model

A
  1. Purpose
  2. Obtain and adjust data
  3. Set parameters/assumptions incl dynamic links
  4. Construct model cashflows
  5. Check accuracy and fit; amend if necessary
  6. Run many times
  7. Output and summarise results
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5
Q

Model point

A

Representative policy in a relatively homogeneous group of policies

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6
Q

Discount rate

A

Used to discount future cashflows

Allows for:

  • Required return
  • Level of statistical risk (assessed by sensitivity analysis, stoch model or comparing market data)
  • Can use stochastic discount rate
  • Can use different rates for each cashflow to better reflect risks, but not done due to simplicity of using one
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7
Q

Considerations after modelling premiums/ charges

A
  1. Product design
  2. Distribution channel(s)
  3. Profit requirement
  4. Size of market
  5. Whether to launch product
  6. Appropriateness given business strategy and capital requirements
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8
Q

Uses for models

A
  • Setting premiums/charges
  • Setting future financing strategies by benefit schemes
  • Risk management to determine capital requirements
  • Valuations
  • Pricing options and guarantees
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9
Q

Sensitivity analysis

A

Changing one parameter at a time to determine sensitivity of results to that parameter

  • llustrates potential variability of results and identify impact of mis-estimation of parameter values
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10
Q

Scenario testing

A

Changine many parameters together to see effect on results

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11
Q

Reducing model error

A

Goodness of fit tests

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12
Q

Alternative ways of allowing for statistical risk associated with parameter values

A
  • Allow for in discount rate and/or

- margins in parameter values

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