What is Risk Aggregation?
Risk aggregation is one of the most difficult components of building an economic capital framework. Most banks use either an equally-weighted sum of individual risk components (i.e., assuming no diversification or a fixed percentage of diversification gains across all components) or a weighted sum of individual risk components based on an estimated variance-covariance matrix that represents risk co-movement. Few banks try more technically advanced aggregation methods like copulas or even bottom-up approaches that create broad economic estimations from the common relationship between specific risk components and underlying factors.
Example of Risk Aggregation:
Before risk types can be aggregated into a single measure, they must be expressed in comparable units. There are three items to consider: risk metric, confidence level, and time horizon.
- Risk metric: This relies on the metrics used in the quantification of different risk types. Must consider whether the metric satisfies the subadditivity condition.
- Confidence level: Loss distributions for different types of risk are assumed to have different shapes, which implies differences in confidence intervals. The lack of consistency in choosing confidence levels creates additional complexity in the aggregation process.
- Time horizon: Choosing the risk measurement time horizon is one of the most challenging tasks in risk measurement. For example, combining risk measures that have been determined using different time horizons creates problems irrespective of the actual measurement methods used. Specifically, there will be inaccurate comparisons between risk types.
Why is risk aggregation important?
In order to determine the total enterprise risk for a financial institution, all risks must be aggregated and analyzed. Banks are now required to aggregate their risk forecasts across the entire organization for the purposes of enterprise risk management and capital planning.