EDFJacobianRegressorSet.java
package org.drip.regression.curvejacobian;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2020 Lakshmi Krishnamurthy
* Copyright (C) 2019 Lakshmi Krishnamurthy
* Copyright (C) 2018 Lakshmi Krishnamurthy
* Copyright (C) 2017 Lakshmi Krishnamurthy
* Copyright (C) 2016 Lakshmi Krishnamurthy
* Copyright (C) 2015 Lakshmi Krishnamurthy
* Copyright (C) 2014 Lakshmi Krishnamurthy
* Copyright (C) 2013 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>EDFJacobianRegressorSet</i> implements the regression analysis set for the EDF product related
* Sensitivity Jacobians. Specifically, it computes the PVDF micro-Jack.
*
* <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/ComputationSupportLibrary.md">Computation Support</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/README.md">Regression Engine Core and the Unit Regressors</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/regression/curvejacobian/README.md">Curve Jacobian Reconciliation Regression Engine</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class EDFJacobianRegressorSet implements org.drip.regression.core.RegressorSet {
private java.lang.String _strRegressionScenario =
"org.drip.analytics.definition.EDFDiscountCurve.CompPVDFJacobian";
private java.util.List<org.drip.regression.core.UnitRegressor> _setRegressors = new
java.util.ArrayList<org.drip.regression.core.UnitRegressor>();
@Override public java.util.List<org.drip.regression.core.UnitRegressor> getRegressorSet()
{
return _setRegressors;
}
@Override public boolean setupRegressors()
{
try {
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("EDFJacobian",
_strRegressionScenario) {
org.drip.analytics.date.JulianDate dtStart = null;
org.drip.state.discount.MergedDiscountForwardCurve dcEDF = null;
org.drip.numerical.differentiation.WengertJacobian wjPVDF = null;
org.drip.numerical.differentiation.WengertJacobian aWJComp[] = null;
org.drip.product.definition.CalibratableComponent aCompCalib[] = null;
@Override public boolean preRegression()
{
int NUM_DC_INSTR = 8;
int aiDate[] = new int[NUM_DC_INSTR];
double adblRate[] = new double[NUM_DC_INSTR];
double adblCompCalibValue[] = new double[NUM_DC_INSTR];
aWJComp = new org.drip.numerical.differentiation.WengertJacobian[NUM_DC_INSTR];
java.lang.String astrCalibMeasure[] = new java.lang.String[NUM_DC_INSTR];
aCompCalib = new
org.drip.product.definition.CalibratableComponent[NUM_DC_INSTR];
dtStart = org.drip.analytics.date.DateUtil.CreateFromYMD (2011, 4, 6);
adblCompCalibValue[0] = .0027;
adblCompCalibValue[1] = .0032;
adblCompCalibValue[2] = .0041;
adblCompCalibValue[3] = .0054;
adblCompCalibValue[4] = .0077;
adblCompCalibValue[5] = .0104;
adblCompCalibValue[6] = .0134;
adblCompCalibValue[7] = .0160;
org.drip.analytics.date.JulianDate dtEDFStart = dtStart;
org.drip.product.definition.CalibratableComponent[] aEDF =
org.drip.product.creator.SingleStreamComponentBuilder.ForwardRateFuturesPack
(dtStart, 8, "USD");
for (int i = 0; i < NUM_DC_INSTR; ++i) {
adblRate[i] = 0.01;
aCompCalib[i] = aEDF[i];
astrCalibMeasure[i] = "Rate";
aiDate[i] = dtEDFStart.addDays ((i + 1) * 91).julian();
}
return null != (dcEDF =
org.drip.state.creator.ScenarioDiscountCurveBuilder.NonlinearBuild (dtStart, "USD",
aCompCalib, adblCompCalibValue, astrCalibMeasure, null));
}
@Override public boolean execRegression()
{
for (int i = 0; i < aCompCalib.length; ++i) {
try {
if (null == (aWJComp[i] = aCompCalib[i].jackDDirtyPVDManifestMeasure (new
org.drip.param.valuation.ValuationParams (dtStart, dtStart, "USD"), null,
org.drip.param.creator.MarketParamsBuilder.Create (dcEDF, null,
null, null, null, null, null), null)))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return null != (wjPVDF = dcEDF.compJackDPVDManifestMeasure (dtStart));
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
for (int i = 0; i < aCompCalib.length; ++i) {
if (!rnvd.set ("PVDFMicroJack_" + aCompCalib[i].name(), aWJComp[i].displayString()))
return false;
}
return rnvd.set ("CompPVDFJacobian", "" + wjPVDF.displayString());
}
});
} catch (java.lang.Exception e) {
e.printStackTrace();
}
return true;
}
@Override public java.lang.String getSetName()
{
return _strRegressionScenario;
}
}