Chapter 43: The Risk Management Process (2) Flashcards

1
Q

Risk Measures:

- Asset risks

A

Active risk measures include historic tracking error and forward-looking tracking error.

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2
Q

Risk Measures:

- Liability risks

A

These are commonly measured by carrying out an analysis of actual vs expected experience.

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3
Q

Risk Measures:

- Value at Risk

A

Value at Risk represents the maximum potential loss on a portfolio over a given future time period with a given degree of confidence.

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4
Q

Risk Measures:

- Expected Shortfall

A

The expected shortfall is the expectation of losses below a certain level. If the specified level is a percentile point on the distribution then this is called the Tail VaR.
The Tail VaR could also be defined as the expected shortfall, conditional on there being a shortfall.

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5
Q

3 Steps of scenario analysis

A
  • grouping of risks into broad categories
  • development of adverse scenario for each risk group
  • calculation of consequences of risk event occurring for each scenario
  • total costs calculated are taken as the financial cost of all risks represented by the chosen scenario.
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6
Q

Stress testing

A

Involves testing for weaknesses in a portfolio by subjecting it to extreme market movements.

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7
Q

2 Types of stress test

A
  • to identify “weak areas” in the portfolio and investigate the effects of localised stress situations by looking at the effect of different combinations of correlations and volatilities.
  • to gauge the impact of major market turmoil affecting all model parameters, while ensuring consistency between correlations while they are “stressed”
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8
Q

The Stochastic model is often limited by one of the following approaches: (3)

A
  • restrict the duration (or time horizon) of the model
  • limit the number of variables modelled stochastically, use a deterministic approach for the other variables
  • carry out a number of runs with a different single stochastic variable and then single deterministic run using all the worst case scenarios together.
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9
Q

Reporting on risk

A

It is usual to report on risk by quantifying the capital requirements to protect against ruin at a particular ruin probability.

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10
Q

5 Main issues facing providers of financial benefits in completing the assessment

A
  • Should the ruin probability be expressed over a single year or whole run-off of business?
  • A stochastic model with more than 2 stochastic variables is impractical, so it may be better to use a correlation matrix instead.
  • Interactions between risks should be dealt with.
  • Some risks, particularly operational, are highly subjective
  • Using past data to estimate future consequences needs to be undertaken with caution.
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11
Q

3 Ways in which to deal with low probability, high impact risks

A
  • They can only be diversified in a limited way
  • can be passed to an insurer or reinsurer, usually by some form of catastrophe insurance or whole account aggregate excess of loss cover (commonly called “stop loss” cover)
  • can be mitigated by management control procedures, such as disaster recovery planning.
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12
Q

Risk portfolio

A

The risk portfolio categorises the various risks to which the usiness is exposed.

Against each risk would be a recorded quantification of:

  • – impact
  • – probability
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13
Q

The risk portfolio can be extended to indicate how the risk as been dealt with: (4)

A
  • retained (and how much capital is needed to support it)
  • transferred
  • mitigated (and a revised assessment of the remaining risk)
  • diversified (and a revised assessment of the remaining combination of risks)
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14
Q

The most common way of measuring liability risks

A

The analysis of experience

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15
Q

Analysis of experience

A

The ratio of the actual occurrences of an event to the expected occurrences when the risk was accepted.

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16
Q

Value at Risk

A

Generalises the likelihood of underperforming by providing a statistical measure of downside risk.

17
Q

Issues with value at risk

A

Portfolios exposed to credit risk, systematic bias or derivatives may exhibit non-normal distributions.

The usefulness of VaR in these situations depends on modelling skewed or fat-tailed distributions of returns, either in the form of statistical distributions or via Monte Carlo simulations.

18
Q

Scenario analysis

A

A means of evaluating risk where a full mathematical model is inappropriate.

(frequently used when evaluating operational risks)

19
Q

Possible stress testing for a commercial bank (3)

A

A commercial bank is exposed to substantial amounts of credit risk and market risk (particularly with regards to interest rates).

Useful stress tests might include:

  • testing how the asset and liability values respond to a 3% increase in short- and long-term interest rates
  • testing the impact off a worsening of the credit rating of all borrowers
  • testing the impact of a widening of credit spreads on assets held.
20
Q

Possible stress testing for a life insurance company (2)

A

Life insurance companies are exposed to market risk, risk relative to liabilities and credit risk.
There are many other tests worthy of carrying out (eg for liquidity risk) but two examples are:
- testing solvency in the event of a fall in asset prices (eg 20% equities, 10% bonds and some allowance for currency depreciation)
- testing solvency in the event of a widening of credit spreads on assets held.

21
Q

5 main issues facing providers in completing a capital assessment

A
  • Should the ruin probability be expressed over a single year or over the whole run-off of the business?
  • A means of assessing the correlation between the risks assessed needs to be developed.
  • Interactions between risks may mean that the effect of multiple risk events is greater or less than the sum of the individual risks. A practical techniques must be developed to address this.
  • Some risks are highly subjective in their assessment.
  • Using past data to estimate future consequences of rare events needs to be undertaken with caution.
22
Q

Explain why the effect of multiple risks may be less than the sum of individual risks.

A

due to the impact of diversification or negative correlation.

23
Q

Outline 10 steps involved in stochastic modelling

A
  • specify the purpose of the investigation, including a time horizon, measurable criteria and a probability confidence limit
  • collect, group and modify data
  • choose a suitable density function for each of the variables to be modelled stochastically
  • specify correlation between variables
  • ascribe values to the variables that are not being modelled stochastically
  • construct a model based on the expected cashflows
  • check that the goodness of fit is acceptable. This can be done by running a past year and comparing the model with the actual results.
  • attempt to fit a different model if the first model does not fit well.
  • run the model many times, each time using a random sample from the chosen density function(s)
  • produce a summary of the results that shows the distribution of the modelled results after many simulations have been run