Linear aggregation of risk. More...
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Linear aggregation of risk.
[in] | ds_in_configuration_table | Input configuration table. It provides information about risk sources to be aggregated and information about the corresponding scenarios. |
[in] | ds_in_correlation_table | Input correlation table. It contains information about the correlation matrix to be used for the linear aggregation |
[in] | working_libname | Working LIBNAME. By default, it is set to work. This option is typically used to facilitate debugging. |
[out] | ds_out_risk_analysis_table | Output table. It contains results about the linear aggregation.. |
Given an input configuration table (DS_IN_CONFIGURATION_TABLE) and an input correlation matrix (DS_IN_CORRELATION_TABLE), this macro will linearly aggregate the risk sources defined in the configuration table (DS_IN_CONFIGURATION_TABLE). Notice that the aggregation can be performed with respect to different scenarios: the configuration table (DS_IN_CONFIGURATION_TABLE) and the (DS_IN_CORRELATION_TABLE) need to contain a properly specified scenario variable (<SCENARIO_ID>).
The structure of the DS_IN_CONFIGURATION_TABLE table is as follows:
Variable | Type | Description |
---|---|---|
<REPORTING_DT> | NUMERIC | SAS Date value. |
<SCENARIO_ID> | CHARACTER/NUMERIC | Scenario identifier variable. |
<NAME> | CHARACTER | Name of the risk source. |
<EXPECTEDLOSS> | NUMERIC | Expected Loss |
<VALUEATRISK> | NUMERIC | Value-at-Risk |
<ECONOMIC_CAPITAL> | NUMERIC | Economic Capital |
The structure of the DS_IN_CORRELATION_TABLE table is as follows:
Variable | Type | Description |
---|---|---|
<SCENARIO_ID> | CHARACTER/NUMERIC | Scenario identifier variable. |
<NAME> | CHARACTER | Name of the risk source. |
<RISK_MEASURE> | CHARACTER | Type of risk measure: VaR, EC, etc.... |
<TYPE> | CHARACTER | Type of dependence matrix. Currently it only supports "corr" |
NAME variables | NUMERIC | The list of variables specified in <NAME>. These specify the values of the dependence matrix. |
Definition in file irmst_riskagg_linear.sas.