DiscriminatoryPowerAnalyzerAggregate.java
package org.drip.validation.riskfactorsingle;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2020 Lakshmi Krishnamurthy
* Copyright (C) 2019 Lakshmi Krishnamurthy
*
* This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
* asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
* analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
* equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
* numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
* and computational support.
*
* https://lakshmidrip.github.io/DROP/
*
* DROP is composed of three modules:
*
* - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
* - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
* - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
*
* DROP Product Core implements libraries for the following:
* - Fixed Income Analytics
* - Loan Analytics
* - Transaction Cost Analytics
*
* DROP Portfolio Core implements libraries for the following:
* - Asset Allocation Analytics
* - Asset Liability Management Analytics
* - Capital Estimation Analytics
* - Exposure Analytics
* - Margin Analytics
* - XVA Analytics
*
* DROP Computational Core implements libraries for the following:
* - Algorithm Support
* - Computation Support
* - Function Analysis
* - Model Validation
* - Numerical Analysis
* - Numerical Optimizer
* - Spline Builder
* - Statistical Learning
*
* Documentation for DROP is Spread Over:
*
* - Main => https://lakshmidrip.github.io/DROP/
* - Wiki => https://github.com/lakshmiDRIP/DROP/wiki
* - GitHub => https://github.com/lakshmiDRIP/DROP
* - Repo Layout Taxonomy => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
* - Javadoc => https://lakshmidrip.github.io/DROP/Javadoc/index.html
* - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
* - Release Versions => https://lakshmidrip.github.io/DROP/version.html
* - Community Credits => https://lakshmidrip.github.io/DROP/credits.html
* - Issues Catalog => https://github.com/lakshmiDRIP/DROP/issues
* - JUnit => https://lakshmidrip.github.io/DROP/junit/index.html
* - Jacoco => https://lakshmidrip.github.io/DROP/jacoco/index.html
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
*
* You may obtain a copy of the License at
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
*
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/**
* <i>DiscriminatoryPowerAnalyzerAggregate</i> implements the Discriminatory Power Analyzer for the given
* Sample across the One/More Hypothesis and Multiple Events.
*
* <br><br>
* <ul>
* <li>
* Anfuso, F., D. Karyampas, and A. Nawroth (2017): A Sound Basel III Compliant Framework for
* Back-testing Credit Exposure Models
* https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2264620 <b>eSSRN</b>
* </li>
* <li>
* Diebold, F. X., T. A. Gunther, and A. S. Tay (1998): Evaluating Density Forecasts with
* Applications to Financial Risk Management <i>International Economic Review</i> <b>39 (4)</b>
* 863-883
* </li>
* <li>
* Kenyon, C., and R. Stamm (2012): <i>Discounting, LIBOR, CVA, and Funding: Interest Rate and
* Credit Pricing</i> <b>Palgrave Macmillan</b>
* </li>
* <li>
* Wikipedia (2018): Probability Integral Transform
* https://en.wikipedia.org/wiki/Probability_integral_transform
* </li>
* <li>
* Wikipedia (2019): p-value https://en.wikipedia.org/wiki/P-value
* </li>
* </ul>
*
* <br><br>
* <ul>
* <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ComputationalCore.md">Computational Core Module</a></li>
* <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ModelValidationAnalyticsLibrary.md">Model Validation Analytics Library</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation/README.md">Risk Factor and Hypothesis Validation, Evidence Processing, and Model Testing</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/validation/riskfactorsingle/README.md">Single Risk Factor Aggregate Tests</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class DiscriminatoryPowerAnalyzerAggregate
{
private org.drip.validation.distance.GapTestSetting _gapTestSetting = null;
private org.drip.validation.riskfactorsingle.EventAggregationWeightFunction _eventAggregationWeightFunction =
null;
private java.util.Map<java.lang.String, org.drip.validation.hypothesis.ProbabilityIntegralTransform>
_eventSamplePITMap = new
org.drip.analytics.support.CaseInsensitiveHashMap<org.drip.validation.hypothesis.ProbabilityIntegralTransform>();
/**
* DiscriminatoryPowerAnalyzerAggregate Constructor
*
* @param eventSamplePITMap Event Sample PIT Map
* @param gapTestSetting The Distance Gap Test Setting
* @param eventAggregationWeightFunction Event Aggregation Weight Function
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public DiscriminatoryPowerAnalyzerAggregate (
final java.util.Map<java.lang.String, org.drip.validation.hypothesis.ProbabilityIntegralTransform>
eventSamplePITMap,
final org.drip.validation.distance.GapTestSetting gapTestSetting,
final org.drip.validation.riskfactorsingle.EventAggregationWeightFunction eventAggregationWeightFunction)
throws java.lang.Exception
{
if (null == (_eventSamplePITMap = eventSamplePITMap) || 0 == _eventSamplePITMap.size() ||
null == (_gapTestSetting = gapTestSetting) ||
null == (_eventAggregationWeightFunction = eventAggregationWeightFunction))
{
throw new java.lang.Exception
("DiscriminatoryPowerAnalyzerAggregate Constructor => Invalid Inputs");
}
}
/**
* Retrieve the Gap Test Setting
*
* @return The Gap Test Setting
*/
public org.drip.validation.distance.GapTestSetting gapTestSetting()
{
return _gapTestSetting;
}
/**
* Retrieve the Event Aggregation Weight Function
*
* @return The Event Aggregation Weight Function
*/
public org.drip.validation.riskfactorsingle.EventAggregationWeightFunction eventAggregationWeightFunction()
{
return _eventAggregationWeightFunction;
}
/**
* Retrieve the Event Sample PIT Map
*
* @return The Event Sample PIT Map
*/
public java.util.Map<java.lang.String, org.drip.validation.hypothesis.ProbabilityIntegralTransform>
eventSamplePITMap()
{
return _eventSamplePITMap;
}
private org.drip.validation.riskfactorsingle.GapTestOutcomeAggregate eventOutcomeAggregate (
final java.lang.String hypothesisID,
final java.util.Map<java.lang.String, org.drip.validation.evidence.Ensemble> eventEnsembleMap)
{
double distanceAggregate = 0.;
java.util.Map<java.lang.String, org.drip.validation.distance.GapTestOutcome> eventOutcomeMap = new
org.drip.analytics.support.CaseInsensitiveHashMap<org.drip.validation.distance.GapTestOutcome>();
try
{
for (java.util.Map.Entry<java.lang.String, org.drip.validation.evidence.Ensemble> eventEnsemble :
eventEnsembleMap.entrySet())
{
java.lang.String eventID = eventEnsemble.getKey();
if (!_eventSamplePITMap.containsKey (eventID))
{
return null;
}
DiscriminatoryPowerAnalyzer discriminatoryPowerAnalyzer = new DiscriminatoryPowerAnalyzer
(
_eventSamplePITMap.get (eventID),
_gapTestSetting
);
org.drip.validation.distance.GapTestOutcome gapTestOutcome =
discriminatoryPowerAnalyzer.gapTest (eventEnsemble.getValue());
if (null == gapTestOutcome)
{
return null;
}
distanceAggregate = distanceAggregate + gapTestOutcome.distance() *
_eventAggregationWeightFunction.loading (eventID);
eventOutcomeMap.put (
eventID,
gapTestOutcome
);
}
return new org.drip.validation.riskfactorsingle.GapTestOutcomeAggregate (
eventOutcomeMap,
distanceAggregate
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
return null;
}
}
/**
* Generate the Hypotheses Outcome Suite Aggregate for the specified Hypothesis Suite Aggregate
*
* @param hypothesisSuiteAggregate The Hypothesis Suite Aggregate
*
* @return The Suite of Gap Test Outcomes
*/
public org.drip.validation.riskfactorsingle.HypothesisOutcomeSuiteAggregate hypothesisGapTest (
final org.drip.validation.riskfactorsingle.HypothesisSuiteAggregate hypothesisSuiteAggregate)
{
if (null == hypothesisSuiteAggregate)
{
return null;
}
java.util.Map<java.lang.String, java.util.Map<java.lang.String,
org.drip.validation.evidence.Ensemble>> hypothesisEventMap =
hypothesisSuiteAggregate.hypothesisEventMap();
if (0 == hypothesisEventMap.size())
{
return null;
}
org.drip.validation.riskfactorsingle.HypothesisOutcomeSuiteAggregate hypothesisOutcomeSuiteAggregate = new
org.drip.validation.riskfactorsingle.HypothesisOutcomeSuiteAggregate();
for (java.util.Map.Entry<java.lang.String, java.util.Map<java.lang.String,
org.drip.validation.evidence.Ensemble>> hypothesisEvent : hypothesisEventMap.entrySet())
{
java.lang.String hypothesisID = hypothesisEvent.getKey();
if (!hypothesisOutcomeSuiteAggregate.add (
hypothesisID,
eventOutcomeAggregate (
hypothesisID,
hypothesisEvent.getValue()
)
))
{
return null;
}
}
return hypothesisOutcomeSuiteAggregate;
}
}