Configuring measures using Spring Beans

The Spring Bean mechanism introduced in version 3.1.0 allows measure configuration to be customized without modifying the core application. The example below demonstrates how to add a customization using this mechanism.

Concept

Measures in Atoti Market Risk are now configured as replaceable qualified Spring Beans, with the Atoti Server post-processing chain being composed through the use of qualified parameters in the bean creation methods.

Bean annotations

All measure beans in Atoti Market Risk have custom annotations, per cube. These annotations attach a Copper context to the bean and make instantiation conditional on the cube being enabled.

Available annotations

Annotation	Condition	Cube
SensitivitiesCopperContextBean	BeanEnabledSensitivitiesCube	Sensitivity Cube
SensitivitiesSummaryCopperContextBean	BeanEnabledSensitivitiesSummaryCube	Sensitivity Summary Cube
VarCopperContextBean	BeanEnabledVaRCube	VaR-ES Cube
VarSummaryCopperContextBean	BeanEnabledVaRSummaryCube	VaR-ES Summary Cube
PnLCopperContextBean	BeanEnabledPnLCube	PLCube
PnLSummaryCopperContextBean	BeanEnabledPnLSummaryCube	PL Summary Cube
MarketDataCopperContextBean	BeanEnabledMarketDataCube	Market Data Cube

The Resolver objects

Each cube in Atoti Market Risk uses an implementation of the IMeasureResolver interface that defines the annotation to use for the measures intended for that cube.

    @Bean
    @Qualifier(SP_QUALIFIER__VAR_MEASURES_RESOLVER)
    @Conditional(BeanEnabledVaRCube.class)
    public IMeasureResolver varResolver(ICopperContextScopeManager scopeManager, ConfigurableListableBeanFactory beanFactory) {
        return new MeasureResolver(scopeManager, beanFactory, VarCopperContextBean.class);
    }

The IMeasureResolver interface performs the following actions:

Collects all annotated beans.
Groups them by @Qualifier.
Selects the @Primary bean for each individual @Qualifier.
Publishes the beans on the Copper context, ordered by dependency relationship.

Available Resolvers

Qualifier	Condition	Annotation
SP_QUALIFIER__SENSITIVITY_MEASURES_RESOLVER	BeanEnabledSensitivitiesCube	SensitivitiesCopperContextBean
SP_QUALIFIER__SENSITIVITY_SUMMARY_MEASURES_RESOLVER	BeanEnabledSensitivitiesSummaryCube	SensitivitiesSummaryCopperContextBean
SP_QUALIFIER__VAR_MEASURES_RESOLVER	BeanEnabledVaRCube	VarCopperContextBean
SP_QUALIFIER__VAR_SUMMARY_MEASURES_RESOLVER	BeanEnabledVaRSummaryCube	VarSummaryCopperContextBean
SP_QUALIFIER__PNL_MEASURES_RESOLVER	BeanEnabledPnLCube	PnLCopperContextBean
SP_QUALIFIER__PNL_SUMMARY_MEASURES_RESOLVER	BeanEnabledPnLSummaryCube	PnLSummaryCopperContextBean
SP_QUALIFIER__MARKET_DATA_MEASURES_RESOLVER	BeanEnabledMarketDataCube	MarketDataCopperContextBean

The `MeasurePublisher` beans

For each cube, a MeasurePublisher bean is created, which is responsible for calling the measure creation objects in the correct order. The possible measure creation objects are:

Object	Method	Description
`CopperCubePublisher copperCube`	`CopperCubePublisher::accept`	Optional publisher responsible for setting up Copper-defined hierarchies.
`IMeasureResolver measureResolver`	`IMeasureResolver::measures`	`IMeasureResolver` object responsible for beans defined using the mechanism described on this page.
`List<MeasurePublisher> additionalMeasures`	`MeasurePublisher::accept`	Optional `List` of publishers for additional measures.

The optional objects are not available on the Summary cubes. To replace the default copperCube and additionalMeasures publishers, the following qualifiers are available:

Qualifier	Cube
SP_QUALIFIER__SENSITIVITY_COPPER_CUBE	Sensitivity Cube
SP_QUALIFIER__ADDITIONAL_SENSITIVITY_MEASURES	Sensitivity Cube
SP_QUALIFIER__VAR_COPPER_CUBE	VaR-ES Cube
SP_QUALIFIER__ADDITIONAL_VAR_MEASURES	VaR-ES Cube
SP_QUALIFIER__PNL_COPPER_CUBE	PLCube
SP_QUALIFIER__ADDITIONAL_PNL_MEASURES	PLCube
SP_QUALIFIER__MARKET_DATA_COPPER_CUBE	Market Data Cube
SP_QUALIFIER__ADDITIONAL_MARKET_DATA_MEASURES	Market Data Cube

The MeasurePublisher beans used by the cube configuration classes use the following qualifiers:

Qualifier	Cube	Condition
SP_QUALIFIER__SENSITIVITY_MEASURES	Sensitivity Cube	BeanEnabledSensitivitiesCube
SP_QUALIFIER__SENSITIVITY_SUMMARY_MEASURES	Sensitivity Summary Cube	BeanEnabledSensitivitiesSummaryCube
SP_QUALIFIER__VAR_MEASURES	VaR-ES Cube	BeanEnabledVaRCube
SP_QUALIFIER__VAR_SUMMARY_MEASURES	VaR-ES Summary Cube	BeanEnabledVaRSummaryCube
SP_QUALIFIER__PNL_MEASURES	PLCube	BeanEnabledPnLCube
SP_QUALIFIER__PNL_SUMMARY_MEASURES	PL Summary Cube	BeanEnabledPnLSummaryCube
SP_QUALIFIER__MARKET_DATA_MEASURES	Market Data Cube	BeanEnabledMarketDataCube
SP_QUALIFIER__COMMON_MEASURES	Combined Cube	BeanEnabledCommonCube

Parameter objects

The cube-specific measure chains rely on parameter objects that contain:

Configuration properties (usually cube levels, members, formatters)
Parameters required for creating measures (e.g. formula providers, the market data retrieval service, the number of axes for a sensitivity)
Constants for use in @Qualifier annotations
Methods for naming measures

The following object types are available:

Object	Cube	Description
MarketDataMeasureParameters	Market Data Cube	Measure parameters for the Market Data cube, containing cube levels, members and formatters.
MarketDataMeasureNames	Market Data Cube	Constants and naming methods for the Market Data cube.
PnLMeasureParameters	PLCube, PL Summary Cube	Measure parameters for the PL and PL Summary cubes, containing cube levels and formatters.
PnLMeasureNames	PLCube, PL Summary Cube	Constants and naming methods for the PL and PL Summary cubes.
SensiMeasureParameters	Sensitivity Cube, Sensitivity Summary Cube	Measure parameters for the Sensitivity and Sensitivity Summary cubes, containing cube levels, members, formatters, formula providers, the number of axes for a sensitivity, the maturity converter and the market data retrieval service together with custom parameters for the service.
SensiMeasureNames	Sensitivity Cube, Sensitivity Summary Cube	Constants and naming methods for the Sensitivity and Sensitivity Summary cubes.
DividendMeasureNames	Sensitivity Cube, Sensitivity Summary Cube	Constants and naming methods specific to the Dividend measures in the Sensitivity and Sensitivity Summary cubes.
VaRMeasureParameters	VaR-ES Cube, VaR-ES Summary Cube	Measure parameters for the VaR-ES and VaR-ES Summary cubes, containing cube levels, members and formatters, as well as configurable confidence levels and risk classes.
VaRMetricParametersAndNames	VaR-ES Cube, VaR-ES Summary Cube	Constants and naming methods for the VaR-ES and VaR-ES Summary cubes, together with the postprocessor object specific to each VaR metric (VaR, Harrel-Davis VaR, VaE, ES, ETG, Weighted VaR, Weighted VaE, Weighted ES, and Weighted ETG).

The [...]MeasureParameters and VaR-ES Cube metric-specific [...]Names objects are exposed as beans. For the other cubes, the [...]Names objects are created using the parameter beans. To replace the beans, the following qualifiers are available:

Qualifier	Type	Description
SP_QUALIFIER__MARKET_DATA_MEASURE_PARAMETERS	MarketDataMeasureParameters	Measure parameters for the Market Data cube.
SP_QUALIFIER__PNL_MEASURE_PARAMETERS	PnLMeasureParameters	Measure parameters for the PL and PL Summary cubes.
SP_QUALIFIER__VAR_CUBE_MEASURE_PARAMETERS	VaRMeasureParameters	Measure parameters for the VaR-ES and VaR-ES Summary cubes.
SP_QUALIFIER__ES_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the ES metric.
SP_QUALIFIER__ETG_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the ETG metric.
SP_QUALIFIER__HD_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the Harrel-Davis VaR metric.
SP_QUALIFIER__VAE_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the VaE metric.
SP_QUALIFIER__VAR_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the VaR metric.
SP_QUALIFIER__WES_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the Weighted ES metric.
SP_QUALIFIER__WETG_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the Weighted ETG metric.
SP_QUALIFIER__WVAE_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the Weighted VaE metric.
SP_QUALIFIER__WVAR_PARAMETERS	VaRMetricParametersAndNames	The constants, naming methods, and postprocessor for the Weighted VaR metric.
SP_QUALIFIER__BASE_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the common and aggregated Sensitivity measure chains.
SP_QUALIFIER__DELTA_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Delta measure chains.
SP_QUALIFIER__GAMMA_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Gamma measure chains.
SP_QUALIFIER__VEGA_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Vega measure chains.
SP_QUALIFIER__VANNA_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Vanna measure chains.
SP_QUALIFIER__VOLGA_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Volga measure chains.
SP_QUALIFIER__THETA_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Theta measure chains.
SP_QUALIFIER__CROSS_GAMMA_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Cross Gamma measure chains.
SP_QUALIFIER__CORRELATION_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Correlation measure chains.
SP_QUALIFIER__DIVIDEND_MEASURE_PARAMETERS	SensiMeasureParameters	Required measure parameters for the Dividend measure chains.

Factories

The logic for creating Copper-based measures is contained within collections of interfaces split by logical measure sub-chain (e.g. ILadderExpansionMeasures, IRiskClassFixedConfidenceMeasures). For each cube, an abstract factory class implements the specific interfaces and stores the Parameters and Names objects required. Concrete classes extend the abstract class and define common helper methods. The methods contained within the factory interfaces are mostly of the type MeasureCreator, an interface alias for Function<CopperMeasure[], CopperMeasure>. The function takes an array of underlying measures and returns a single resulting measure. The alias also defines two additional methods:

MeasureCreator#on(CopperMeasure... measures) - an alias for Function#apply(measures) that allows the usage of varargs
MeasureCreator#noUnderlying() - an alias for Function#apply(null)

The following factory classes are available:

Cube	Factory	Abstract class	Interface	Description
Market Data Cube	MarketDataFactory	AMarketDataFactory	IMarketDataMeasures	All MeasureCreator objects used in creating measures for the Market Data cube.
PLCube, PL Summary Cube	PnLFactory	APnLFactory	IPnLMeasures	All MeasureCreator objects used in creating measures for the PL and PL Summary cubes.
Sensitivity Cube, Sensitivity Summary Cube	SensiFactory	ASensiFactory	IBaseMeasures	MeasureCreator objects for creating measures not split by sensitivity type.
			IBucketedMeasures	MeasureCreator objects for measures that can be bucketed on time pillars.
			IDayToDayMeasures	MeasureCreator objects for creating day-to-day difference measures.
			ILadderExpansionMeasures	MeasureCreator objects for creating ladder measures.
			INamedDayToDayMeasures	MeasureCreator objects for day-to-day measures.
			INativeCurrencyMeasures	MeasureCreator objects for creating sensitivity measures in the native currency.
			ISensitivityMeasures	MeasureCreator objects for creating the top-level, post-FX sensitivity measures.
			ISplitMeasures	MeasureCreator objects for creating corporate split measures.
Sensitivity Cube	PnLExplainFactory	APnLExplainFactory	IAggregateMeasures	MeasureCreator objects for creating aggregated top level measures (e.g. with a plus operation).
			IBasePnLExplainMeasures	MeasureCreator objects for creating measures not split by sensitivity type.
			IBucketedMeasures	See above.
			IFilteredMeasures	See above.
			INamedDayToDayMeasures	See above.
			IPnLExplainMeasures	MeasureCreator objects for creating PnL Explain measures, by sensitivity and aggregated.
			ISensitivityMarketDataMeasures	See above.
			ISplitMeasures	See above.
Sensitivity Cube	TaylorFactory	ATaylorFactory	IAggregateMeasures	See above.
			IBucketedMeasures	See above.
			IContextualMeasures	MeasureCreator objects for creating measures with the confidence level controlled through a context value.
			IFilteredMeasures	See above.
			IFixedConfidenceMeasures	MeasureCreator objects for creating measures per configurable confidence levels.
			IIncrementalMeasures	MeasureCreator objects for creating Incremental, LEstimator, Component VaR and Component VaR Delta measures.
			INamedDayToDayMeasures	See above.
			IShiftMeasures	MeasureCreator objects for creating market shift measures.
			ISplitMeasures	See above.
			IStatisticalMeasures	MeasureCreator for measures that perform statistical operations on vectors (e.g. min, max, mean).
			ITaylorVaRMeasures	MeasureCreator objects for creating Taylor VaR measures, by sensitivity and aggregated.
			IVaRESMeasures	MeasureCreator objects for creating measures not split by metric type.
VaR-ES Cube, VaR-ES Summary Cube	VaRFactory	AVaRFactory	IContextualMeasures	See above.
			IContextualRiskClassMeasures	MeasureCreator objects for creating measures with the confidence level controlled through a context value, split by configurable risk class.
			IFixedConfidenceMeasures	See above.
			IIncrementalMeasures	See above.
			IRiskClassFixedConfidenceMeasures	MeasureCreator objects for creating measures per configurable confidence level, split by configurable risk class.
			IVaRESMeasures	See above.

Chains

Chain classes are configuration classes that leverage measure factories to define a measure chain as a collection of beans. A typical measure definition consists of:

The cube-specific bean annotation (see Bean annotations)
A @Qualifier annotation specific to the measure.
(OPTIONAL) A @MeasureGroup annotation marking the measure to be part of a group.
(OPTIONAL) A @Conditional annotation to enable/disable creating the measure depending on the project configuration.
The type of the bean (CopperMeasure and CopperMeasure[] are currently supported).
Underlying measures as qualified parameters of the method.
The logic for creating the measure, within the method body.

Examples

A measure defined as part of the PNL_EXPLAIN_NEXT_DATE group:

    @SensitivitiesCopperContextBean
    @Qualifier(SENSI + PNL_EXPLAIN_NEXT_DATE)
    @MeasureGroup(PNL_EXPLAIN_NEXT_DATE)
    public CopperMeasure correlationPnlExplainNextDate(@Qualifier(SENSI + PNL_EXPLAIN_NATIVE_NEXT_DATE) CopperMeasure pnlExplainNativeNextDate) {
        return getFactory().pnlExplainNextDate().on(pnlExplainNativeNextDate);
    }

A measure operating on all measures part of the PNL_EXPLAIN_NEXT_DATE group:

    @SensitivitiesCopperContextBean
    @Qualifier(AGGREGATE_PNL_EXPLAIN_NATIVE_NEXT_DATE)
    public CopperMeasure pnlExplainNativeNextDate(@MeasureGroup(PNL_EXPLAIN_NATIVE_NEXT_DATE) CopperMeasure[] sensitivitiesPnlExplainNativeNextDate) {
        return getFactory().aggregateMeasures(SensiMeasureNames::getAggregatePnlExplainNativeNextDate).on(sensitivitiesPnlExplainNativeNextDate);
    }

A measure bean generating multiple measures based on project configuration:

    @VarCopperContextBean
    @Qualifier(METRIC + CONFIDENCE)
    public CopperMeasure[] esMetricConfidence(@Qualifier(VAR_FX_VECTOR) CopperMeasure varEsVarFxVector) {
        CopperMeasure[] returnArray = new CopperMeasure[getConfidenceLevels().size()];
        for (int i = 0; i < getConfidenceLevels().size(); i++) {
            returnArray[i] = getFactory().metricConfidence(getConfidenceLevels().get(i)).on(varEsVarFxVector);
        }
        return returnArray;
    }

The following packages contain [...]Chain classes implementing the relevant interfaces:

Package	Factory
`com.activeviam.mr.marketdata.measures.chains`	A single `MarketDataFactory`.
`com.activeviam.mr.pnl.measures.chains.complete`	The common `PnLFactory`.
`com.activeviam.mr.pnl.measures.chains.summary`	The common `PnLFactory`.
`com.activeviam.mr.productcontrol.measures.chains`	The common `PnLFactory`.
`com.activeviam.mr.sensi.measures.chains.complete`	A `SensiFactory` instance per sensitivity type, providing the correct Parameters and Names.
	A `PnLExplainFactory` instance per sensitivity type, providing the correct Parameters and Names.
	A `TaylorFactory` instance per sensitivity type, providing the correct Parameters and Names.
`com.activeviam.mr.sensi.measures.chains.summary`	A `SensiFactory` instance per sensitivity type, providing the correct Parameters and Names.
`com.activeviam.mr.var.measures.chains.complete`	A `VaRFactory` instance per metric type, providing the correct Parameters and Names.
`com.activeviam.mr.var.measures.chains.summary`	A `VaRFactory` instance per metric type, providing the correct Parameters and Names.

Each package contains one or more [...]Chain classes, split by logical measure sub-chain. As multiple measures can make use of the same factory MeasureCreator method, a single factory interface can result in multiple [...]Chain classes. The Sensitivity and VaR-ES measures are further duplicated by sensitivity type and VaR metric, respectively. Each sensitivity type and VaR metric has a base abstract class that defines specific Parameters objects to be used in creating the relevant Factory. Summary cubes also have a (sometimes smaller) set of [...]Chain classes, with potentially missing measures.

Customization mechanism and examples

The internal configuration described in the Concept section enables the customization of measures through standalone bean definitions anywhere in the project configuration. To customize a measure chain, you can replace individually qualified measures by defining a bean with the same annotations, marked as @Primary. Making the configuration class extend one of the A[...]Chain abstract classes gives access to the factory, names and parameters objects specific to that chain, through getFactory(), getFactory().getNames() and getParameters(). While all internally defined measures make use of the factories, this is not a requirement.

Replacing the PnLVectorExpand measure

@Configuration
public class CustomMeasuresConfig extends AVaRESChain {

    private static final int[] MULTIPLIERS = new int[]{2, 3, 5};

    @VarCopperContextBean
    @Qualifier(PNL_VECTOR_EXPAND)
    @Primary
    public CopperMeasure expandRename(@Qualifier(PNL_VECTOR_EXPAND) CopperMeasure pnlVectorExpand) {
        return pnlVectorExpand.as("PnLVectorExpandOld");
    }

    @VarCopperContextBean
    @Qualifier("MultiplePnLVectorExpand")
    @Primary
    public CopperMeasure[] multiply(@Qualifier(PNL_VECTOR_EXPAND) CopperMeasure pnlVectorExpand) {
        CopperMeasure[] returnArray = new CopperMeasure[MULTIPLIERS.length];
        for (int i = 0; i < MULTIPLIERS.length; i++) {
            returnArray[i] = pnlVectorExpand.multiply(Copper.constant(MULTIPLIERS[i])).as("PnLVectorExpand x " + MULTIPLIERS[i]);
        }
        return returnArray;
    }

    @VarCopperContextBean
    @Qualifier("Aggregate PnL Vector Expand")
    @Primary
    public CopperMeasure aggregatePnLVectorExpand(@Qualifier("MultiplePnLVectorExpand") CopperMeasure[] multipliedPnLVectorExpand) {
        return Arrays.stream(multipliedPnLVectorExpand).reduce(CopperMeasure::plus).get().as(PNL_VECTOR_EXPAND);
    }

    @VarCopperContextBean
    @Qualifier(PNL_VECTOR_EXPAND_NEIGHBOUR_VALUE)
    @Primary
    public CopperMeasure customVarEsPnlVectorExpandNeighbourValue(@Qualifier("Aggregate PnL Vector Expand") CopperMeasure varEsPnlVectorExpand) {
        return getFactory().pnlVectorExpandNeighbour().on(varEsPnlVectorExpand);
    }
}

In this example we’re renaming the initial PnLVectorExpand measure to PnLVectorExpandOld, creating PnLVectorExpand x 2, PnLVectorExpand x 3 and PnLVectorExpand x 5 measures and summing them up to replace the initial PnLVectorExpand measure. Finally, to ensure our new bean is in the correct position in the chain, we replace the PNL_VECTOR_EXPAND_NEIGHBOUR_VALUE bean and use Aggregate PnL Vector Expand instead of PNL_VECTOR_EXPAND as the underlier.

Replacing a subchain

If the use-case requires replacing a longer part of a measure chain (e.g. skipping several intermediate steps), the intermediate beans also have to be explicitly replaced. Two options are available:

Replacing the bean and returning null:

    @SensitivitiesCopperContextBean
    @Qualifier(SENSI + NATIVE_INTERMEDIATE)
    @Primary
    public CopperMeasure deltaSensiNativeIntermediate() {
        return null;
    }

Replacing the bean and returning the underlier:

    @SensitivitiesCopperContextBean
    @Qualifier(SENSI + NATIVE_VECTOR_EXPAND)
    public CopperMeasure deltaSkipVectorNativeExpand(@Qualifier(SENSI + NATIVE_SUM_TECHNICAL_FILTERED) CopperMeasure sumTechnicalFiltered) {
        return sumTechnicalFiltered;
    }

If the intermediate measures are likely to be used as underliers in other parts of the chain, return the underlier to avoid NullPointerException issues.

Custom Measures Warning

Atoti Market Risk cubes and their summary variants (for example the VaR-ES Cube and the VaR-ES Summary Cube) are created as a horizontal distribution. This enables Atoti Market Risk to show a single measure (for example VaR) with some dates coming from the full cube and other date contributions from the summary cube. This is a useful feature, but it comes with a warning. Atoti Server expects that all cubes in a horizontal distribution have exactly identical measure chains. If they do not, this can lead to errors or incorrect results when queries are executed on a query cube with both cubes. The measure chains in Atoti Market Risk are not identical between main and summary cubes, but we have taken care to avoid these failure scenarios. We strongly recommend that, if you are using summary cubes, you add any new measures both to the main and summary cubes.

Measure chain differences between main and summary cubes may lead to runtime errors or incorrect query results.

​Concept

​Bean annotations

​Available annotations

​The Resolver objects

​Available Resolvers

​The MeasurePublisher beans

​Parameter objects

​Factories

​Chains

​Examples

​Customization mechanism and examples

​Replacing the PnLVectorExpand measure

​Replacing a subchain

​Suggested Further Reading

​Custom Measures Warning

Concept

Bean annotations

Available annotations

The Resolver objects

Available Resolvers

The `MeasurePublisher` beans

Parameter objects

Factories

Chains

Examples

Customization mechanism and examples

Replacing the PnLVectorExpand measure

Replacing a subchain

Suggested Further Reading

Custom Measures Warning