- Table showing you the fields included in each row of a Vega Sensitivity CSV Input Data file, indicating which stores these fields are copied to during the ETL process.
- Key fields for vector creation and the fields that have the potential to be populated with vectors, as opposed to always containing scalar values.
Vectorization
The following table provides information about the vectors employed within the Vega CSV Input files for each risk class:Un-Vectorization
Vectors within the input are split into several scalar lines by the RiskClassTuplePublisher. For each OptionMaturity in the vectorized input, the corresponding index of VegaSensitivities is used to create scalar tuples under the scalar risk factor. The scalar risk factor is the concatenation of the input riskFactor and the OptionMaturity, using a space as a delimiter. If OptionMaturity is not provided, a default of “6M”, “1Y”, “3Y”, “5Y”, “10Y” is used in that order. In the case of GIRR Yield curves, UnderlyingMaturity is the second dimension of the vectorized input. The scalar risk factor is the concatenation of the input riskFactor, the OptionMaturity, and the UnderlyingMaturity using a space as a delimiter. If UnderlyingMaturity is not provided, a default of “1Y” is used.Normalization
Vega-relevant stores
The stores that are relevant for Vega are:Mapping of SBM Vega CSV file fields onto the stores that they populate
Column Calculators and Tuple Publishers
RiskFactorColumnCalculator
If Risk Factor is not provided,RiskFactorColumnCalculator will create one based on risk class the table below explains how Risk Factors are derived.
If
sbm.risk-factor.always-append-tenor is set to true, then tenor will also be added to Risk Factor.