Chapter 29: Risk measurement and reporting Flashcards
(30 cards)
What are the 2 key features to assess for all risk events?
- The probability of the event occurring
- The expected loss if the event occurs
Describe how the risk identification “brainstorming” approach can be extended to obtain a subjective assessment of risk exposure
The probability and severity of each risk event are both estimated (separately) using a simple scale.
The product of the probability and severity assessments gives a score on a scale. This provides an assessment of each risk event and allows them to be ranked and prioritised.
The assessment would be carried out with and without possible risk controls
Outline how a model could be used to assess a risk event
Distributions need to be assigned to both the probability and severity of the risk event (unless the latter is a fixed amount rather than a RV, such as for a without profit term assurance policy).
To quanitfy the risk simply, the company could define an event and then use historical data to determine a probability distribution for that event. Alternatively, the frequency of the event could be defined and this could be used to determine the loss parameter.
A decision needs to be made as to whether a stochastic or deterministic model is appropriate.
The availability of data to parameterise the model may influence the decision as to which model (if any) is used. This is particularly important when considering rare events
Suggest features of a risk that could make it more appropriate to model using a stochastic rather than a deterministic approach
- The risk has a high score (high severity and / or frequency) and therefore is a high priority to assess carefully
- Has a highvariability of possible outcomes
- Has a lot of experience data on which to base the probability distributions
- Relates to financial guarantees or options
- Involves the mismatching of assets and liabilities.
State 6 categories into which operational risks might be divided for the purpose of scenario analysis
- Fraud
- Loss of key personnel
- Mis-selling of financial products
- Calculation error in the computer system
- Loss of business premises
- Loss of company email access
State 5 ways of evaluating risks
- Scenario analysis
- Stress testing
- Combined stress and scenario testing
- Reverse stress testing
- Stochastic modelling
Outline 4 steps that should be involved in a scenario analysis to evaluate operational risk
A scenario analysis looks at the financial impact of a plausible and possibly adverse set of events or sequences of events. It is also a deterministic method of evaluating risk.
Scenario analysis involves a number of steps:
1. Group risks into broad categories. This should involve input from a wider range of senior individuals in the organisation
2. Develop a plausible adverse scenario of risk events for each group of risks, which is representative of all the risks in the group.
3. Calculate the consequences / costs of the risk event occurring for each scenario, again involving senior staff.
4. Calculate the total costs of all risks represented by the scenario.
Note: Scenario analysis is limited to quantifying the severity of the scenario but not the probability of it occurring.
What is stress testing?
Stress testing is a deterministic method of modelling extreme risk events. It is commonly used to model extreme market movements, but can be applied to other risks (e.g. credit, liquidity)
In relation to market risk it involves subjecting a portfolio to extreme market movements by radically changing the underlying assumptions and characteristics - including changing asset class correlations and volatilities, which are often observed to increase during extreme market events.
Outline 2 types of stress scenario test
Two types of tests are designed to:
1. 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
2. Guage the impact of major market turmoil affecting all model parameters while ensuring consistency between correlations while they are stressed
Explain what is meant by reverse stress testing
Reverse stress testing is the construction of a severe stress scenario that just allows the firm to be able to continue to operate its business plan.
Equivalently, it is the scenario which would just be enough to stop them doing so.
This scenario might be financial or non-financial
Although, it might be an extreme scenario, it must be plausible
Describe how a stochastic model could be used to evaluate a particular risk
The variables that gives rise to the risk are treated as RVs with probability distributions.
The model must be dynamic, with full interactions / correlations between variables
The model can be run to determine the amount of capital that it needs to (just) avoid ruin with a given probability
Outline 3 approaches to limiting the ideal scope of a stochastic model in order to make the model more practical
- Restrict the time horison that the model projects
- Limit the number of variables that are modelled stochastically and model the other variables deterministically with scenario testing
- Carry out a number of runs each with a different single stochastic variable, followed by a single deterministic run using all the worst case scenarios together.
Explain why the effect of multiple risks may be less than the sum of the individual risks
The overall combined impact may be less than the sum of that for the individual risks due to the impact of diversification or less than perfect (or even negative) correlation.
Less than perfect correlation (i.e. some independence) between the individual risks means that they are very unlikely to occur all at the same time.
Outline how the overall capital requirement for a combination of risks relates to the individual risk capital requirements, if the risk events are:
* fully dependent
* fully independent
* partially dependent
Fully dependent:
The overall capital requirement is the sum of the individual capital requirements
Fully independent:
The overall capital requirement is less than the sum of the individual capital requirements (the difference is the diversification benefit). Under certain assumptions, the overall capital requirement can be determined as the square root of the sum of squares of the individual risk capital requirements
Partially dependent:
The overall capital requirement is less than the sum of the individual risk capital requirements. The diversification benefit depends on the degree of correlation (possibly negative) between the risks
What are some examples of likely correlations between risks?
- Inflation risk is heavily correlated with expense risk for most long-term financial products
- Traditionally equity markets have moved in the opposite direction to interest rates, but in recent years this correlation has not been so obvious
- Falling equity markets are likely to be correlated with increasing lapse rates on unit-linked savings products
- Operational risk is likely to be weakly correlated with all other risks, because if management are concentrating on some other issue they may not be concentrating on routine operational matters
- In life insurance, the longevity risk on an annuity book is strongly negatively correlated with mortality risk on a term assurance book (not perfectly negative correlation because the typical ages are different)
List 3 methods of aggregating partially dependent risks
- Stochastic model
- Correlation matrix
- Copulas
How can liability risks be measured?
Liability risks can be measured by an analysis of experience, e.g. actual deaths divided by expected deaths.
It is important to ensure consistent classification and measurement of the risk event and the exposure to risk
What are the advantages and disadvantages to the notional approach of deterministic approaches to measuring risk?
Advantages:
* Simple to implement and interpret across a diverse range of organisations
Disadvantages:
* Potential undesirable use of a “catch all” weighting for (possibly heterogeneous) undefined asset classes
* Possible distortions to the market caused by increased demand for asset classes with high weighting
* Treating short positions as if they were the exact opposite of the equivalent long position
* No allowance for concentration risk, as the risk weighthings for an asset class is the same irrespective of whether the investment in that asset class consists of a single security or a variety of different securities
* The probability of the changes considered is not quantified.
What are the advantages and disadvantages of the factor sensitivity approach?
Advantages:
* Increased understanding of the drivers of risk
Disadvantages:
* Not assessing a wider range of risks, by focusing upon a single risk factor
* Being difficult to aggregate over different risk factors
* The probability of the changes considered (in the values of assets and/or liabilities) is not quantified
What are the 4 probabilistic approaches to measuring risk?
- Deviation
- Value at Risk
- Probability of ruin
- Tail Value at Risk
Deviation
Deviation can be measured as:
- standard deviation: where deviation is measured from the mean
- Tracking error: where deviation is measured relative to a benchmark other than the mean
Value at Risk (VaR)
VaR generalises the likelihood of underperforming by providing a statistical measure of downside risk. VaR represents the maximum potential loss on a portfolio over a given future period with a given degree of confidence.
VaR can be measured either in absolute terms or relative to a benchmark.
What are the advantages and disadvantages of VaR?
Advantages:
* The simplicity of its expression
* The intelligibility of its units, i.e. money
* Its applicability to all types of risks
* Its applicability over all sources of risk - facilitating easy comparisons between products and across businesses its inherent allowance for the way in which different risks interact to cause losses
* The ease of its translation into a risk benchmark
Disadvantages:
* It gives no indication of the distribution of losses greater than the VaR
* It can under-estimate asymmetric and fat-tail risks as it does not quanitfy the size of the “tail”
* It can be very sensitive to the choices of data, parameters and assumptions
* VaR is not always sub-additive (Subadditivity means that a merger of risk situations does not increase the overall level of risk)
* If used in regulation it may encourage “herding”, thereby increasing systemic risk