Risk Evaluation Methods

Question 1

General

Answer 1

• More data = more accurate parameterisation = easier to set up models (particularly stochastic).
• Inconsistent data – some parameters may be easier to analyse than others – consider common
• Het data = different trends may complicate model = scenario analysis may be more appropriate

Question 2

Scenario analysis Method

Answer 2

• For each group of risks a representative plausible scenario is developed.
• For each scenario the consequences of the event occurring are calculated.
• A number of different scenarios may be considered.

Question 3

Scenario analysis Advantages

Answer 3

• Scenario analysis is useful when a full mathematical model is inappropriate.
• For the risks being modelled it will be possible to pull together plausible scenarios (including particularly adverse scenarios).
• Removes risk of using many subjective parameters
• Easier to communicate than other approaches.
• Useful for capital assessment review, eg failure of new product

Question 4

Scenario analysis Disadvantages

Answer 4

• The consequences of scenarios occurring may be more difficult than constructing the scenario.
• Likelihood of different outcomes is not apparent.
• Choice of scenarios requires external input, this in turn is critical.

Question 5

Stress testing Method

Answer 5

• Modelling of extreme changes and scenarios.
• Will be looking at correlations and volatilities which are observed to simultaneously increase during extreme events.
• Aim to identify weak areas by looking at effect of different combinations of correlations and volatilities.
• Key area is constructing appropriate stress test scenarios.
• Must be able to consider interaction with other parameters (e.g. financial) to check for weaknesses in portfolio.

Question 6

Stress testing Advantages

Answer 6

• Identifying the key risks to be tested will enable stress testing to show weak areas in the portfolio.
• Appropriate for extreme, wide-ranging scenarios

Question 7

Stress testing Disadvantages

Answer 7

• Difficulty in identifying appropriate correlations for other parameters
• Need to consider sensitivity of portfolio to extreme movements in parameters, which may be difficult to model.

Question 8

Stochastic modelling Method

Answer 8

• Variables are modelled using probability distributions.
• Dynamic interaction between variables.
• The result will be a distribution of outcomes.

Question 9

Stochastic modelling Advantages

Answer 9

• Shows a distribution of possible outcomes, which provides a more complete picture than other approaches.
• By only allowing some parameters to vary stochastically it may be possible to focus on the particular risks which are of interest.
• Allows user to understand likelihood that a guarantee will bite and the financial impact of the guarantee

Question 10

Stochastic modelling Disadvantages

Answer 10

• Require a probability distribution to be applied to parameters which may be difficult to derive, and will require expert judgement (may be subjective/ arbitrary)
• Also requires correlation and interaction between parameters to be set up which may present further difficulties.
• Computationally intensive approach which increases costs.