CreditCurveRegressor.java
package org.drip.regression.curve;
/*
* -*- 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
* Copyright (C) 2012 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>CreditCurveRegressor</i> implements the regression set analysis for the Credit Curve.
* CreditCurveRegressor regresses 12 scenarios:
*
* <br><br>
* <ul>
* <li>
* #1: Create an SNAC CDS.
* </li>
* <li>
* #2: Create the credit curve from a set of CDS instruments.
* </li>
* <li>
* #3: Create the credit curve from a flat hazard rate.
* </li>
* <li>
* #4: Create the credit curve from a set of survival probabilities.
* </li>
* <li>
* #5: Create the credit curve from an array of hazard rates.
* </li>
* <li>
* #6: Extract the credit curve instruments and quotes.
* </li>
* <li>
* #7: Create a parallel hazard shifted credit curve.
* </li>
* <li>
* #8: Create a parallel quote shifted credit curve.
* </li>
* <li>
* #9: Create a node tweaked credit curve.
* </li>
* <li>
* #10: Set a specific default date on the credit curve.
* </li>
* <li>
* #11: Compute the effective survival probability between 2 dates.
* </li>
* <li>
* #12: Compute the effective hazard rate between 2 dates.
* </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/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/curve/README.md">Curve Construction/Reconciliation Regression Engine</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class CreditCurveRegressor implements org.drip.regression.core.RegressorSet {
private java.lang.String _strCurrency = "";
private org.drip.state.credit.CreditCurve _cc = null;
private org.drip.state.discount.MergedDiscountForwardCurve _dc = null;
private org.drip.analytics.date.JulianDate _dtStart = null;
private java.lang.String _strRegressionScenario = "org.drip.analytics.curve.CreditCurve";
private java.util.List<org.drip.regression.core.UnitRegressor> _setRegressors = new
java.util.ArrayList<org.drip.regression.core.UnitRegressor>();
/**
* Do Nothing CreditCurveRegressor constructor.
*/
public CreditCurveRegressor()
{
}
/*
* Set up the unit functional regressors for the credit curve regression set
*/
@Override public boolean setupRegressors()
{
try {
/*
* Testing creation of the Credit Curve from SNAC instruments - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("CreateSNAC",
_strRegressionScenario)
{
private double[] _adblQuotes = new double[5];
private java.lang.String[] _astrCalibMeasure = new java.lang.String[5];
private org.drip.product.definition.CreditDefaultSwap[] _aCDS = new
org.drip.product.definition.CreditDefaultSwap[5];
@Override public boolean preRegression()
{
_strCurrency = "USD";
if (null == (_dtStart = org.drip.analytics.date.DateUtil.CreateFromYMD (2010,
org.drip.analytics.date.DateUtil.MAY, 12)))
return false;
if (null == (_dc =
org.drip.state.creator.ScenarioDiscountCurveBuilder.ExponentiallyCompoundedFlatRate
(_dtStart, _strCurrency, 0.04)))
return false;
for (int i = 0; i < 5; ++i) {
_adblQuotes[i] = 50. * (i + 1);
_astrCalibMeasure[i] = "FairPremium";
if (null == (_aCDS[i] = org.drip.product.creator.CDSBuilder.CreateSNAC (_dtStart, (i
+ 1) + "Y", 0.01, "CORP")))
return false;
}
return true;
}
@Override public boolean execRegression()
{
return null != (_cc = org.drip.state.creator.ScenarioCreditCurveBuilder.Custom ("CORP",
_dtStart, _aCDS, _dc, _adblQuotes, _astrCalibMeasure, 0.4, false));
}
});
/*
* Testing creation of the Credit Curve from flat hazard - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("FromFlatHazard",
_strRegressionScenario)
{
private org.drip.state.credit.CreditCurve _ccFromFlatHazard = null;
@Override public boolean execRegression()
{
return null != (_ccFromFlatHazard =
org.drip.state.creator.ScenarioCreditCurveBuilder.FlatHazard (_dtStart.julian(),
"CORP", "USD", 0.02, 0.4));
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
final int NUM_DC_INSTRUMENTS = 5;
double adblHazard[] = new double[NUM_DC_INSTRUMENTS];
org.drip.analytics.date.JulianDate adt[] = new
org.drip.analytics.date.JulianDate[NUM_DC_INSTRUMENTS];
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (adblHazard[i] =
_ccFromFlatHazard.hazard (_dtStart, (adt[i] = _dtStart.addYears (i + 1)))))
return false;
rnvd.set ("HazardRateFromHazardCurve[" + adt[i] + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (adblHazard[i], 1, 4, 1));
if (!org.drip.numerical.common.NumberUtil.WithinTolerance (adblHazard[i], 0.02))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
});
/*
* Testing creation of the Credit Curve from flat survival - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("FromSurvival",
_strRegressionScenario)
{
private static final int NUM_DC_INSTRUMENTS = 5;
private int _aiDate[] = new int[NUM_DC_INSTRUMENTS];
private double _adblSurvival[] = new double[NUM_DC_INSTRUMENTS];
private org.drip.state.credit.CreditCurve _ccFromSurvival = null;
@Override public boolean preRegression()
{
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
_aiDate[i] = _dtStart.addYears (i + 1).julian();
_adblSurvival[i] = 1. - (i + 1) * 0.1;
}
return true;
}
@Override public boolean execRegression()
{
return null != (_ccFromSurvival =
org.drip.state.creator.ScenarioCreditCurveBuilder.Survival (_dtStart.julian(),
"CORP", "USD", _aiDate, _adblSurvival, 0.4));
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
double adblSurvivalCalc[] = new double[NUM_DC_INSTRUMENTS];
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (adblSurvivalCalc[i] =
_ccFromSurvival.survival (_aiDate[i])))
return false;
org.drip.analytics.date.JulianDate dt = new org.drip.analytics.date.JulianDate
(_aiDate[i]);
rnvd.set ("SurvivalFromOriginal[" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (_adblSurvival[i], 1, 4, 1));
rnvd.set ("SurvivalFromSurvival[" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (adblSurvivalCalc[i], 1, 4, 1));
if (!org.drip.numerical.common.NumberUtil.WithinTolerance (adblSurvivalCalc[i],
_adblSurvival[i]))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
});
/*
* Testing creation of the Credit Curve from hazard nodes - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("FromHazard",
_strRegressionScenario)
{
private static final int NUM_DC_INSTRUMENTS = 5;
private int _aiDate[] = new int[NUM_DC_INSTRUMENTS];
private double _adblHazard[] = new double[NUM_DC_INSTRUMENTS];
private org.drip.state.credit.CreditCurve _ccFromHazard = null;
@Override public boolean preRegression()
{
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
_aiDate[i] = _dtStart.addYears (i + 1).julian();
_adblHazard[i] = 0.01 * (1. - (i + 1) * 0.1);
}
return true;
}
@Override public boolean execRegression()
{
return null != (_ccFromHazard = org.drip.state.creator.ScenarioCreditCurveBuilder.Hazard
(_dtStart, "CORP", "USD", _aiDate, _adblHazard, 0.4));
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
org.drip.analytics.date.JulianDate dt1 = _dtStart;
double adblHazardCalc[] = new double[NUM_DC_INSTRUMENTS];
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (adblHazardCalc[i] =
_ccFromHazard.hazard (dt1, dt1.addYears (1))))
return false;
org.drip.analytics.date.JulianDate dt2 = dt1.addYears (1);
rnvd.set ("HazardFromOriginal[" + dt1 + "-" + dt2 + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (_adblHazard[i], 1, 4, 1));
rnvd.set ("HazardFromHazard[" + dt1 + "-" + dt2 + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (adblHazardCalc[i], 1, 4, 1));
if (!org.drip.numerical.common.NumberUtil.WithinTolerance (adblHazardCalc[i],
_adblHazard[i]))
return false;
dt1 = dt1.addYears (1);
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
});
/*
* Testing extraction of the credit curve components and quotes - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("CompAndQuotes",
_strRegressionScenario)
{
private org.drip.product.definition.CalibratableComponent[] _aCalibComp = null;
@Override public boolean execRegression()
{
return null != (_aCalibComp = _cc.calibComp()) && 0 != _aCalibComp.length;
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
for (int i = 0; i < _aCalibComp.length; ++i) {
org.drip.analytics.date.JulianDate dt = _aCalibComp[i].maturityDate();
java.lang.String strCode = _aCalibComp[i].primaryCode();
if (null == dt || null == strCode || strCode.isEmpty()) return false;
try {
rnvd.set ("CompQuote" + "_" + strCode + "[" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (_cc.manifestMeasure
(strCode).get ("FairPremium"), 1, 4, 1));
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
});
/*
* Testing creation of a parallel hazard shifted Credit Curve - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor
("ParallelHazardShiftedCurve", _strRegressionScenario)
{
private org.drip.state.credit.CreditCurve _ccParallelShifted = null;
@Override public boolean execRegression()
{
if (null == (_ccParallelShifted = (org.drip.state.credit.CreditCurve)
_cc.parallelShiftQuantificationMetric (0.0005)))
return false;
return true;
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
org.drip.product.definition.CalibratableComponent[] aCalibComp =
_cc.calibComp();
org.drip.analytics.date.JulianDate dt1 = _dtStart;
for (int i = 0; i < aCalibComp.length; ++i) {
org.drip.analytics.date.JulianDate dt = aCalibComp[i].maturityDate();
double dblBaseHazard = java.lang.Double.NaN;
double dblShiftedHazard = java.lang.Double.NaN;
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (dblShiftedHazard =
_ccParallelShifted.hazard (dt1, dt)) ||
!org.drip.numerical.common.NumberUtil.IsValid (dblBaseHazard = _cc.hazard
(dt1, dt)))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
rnvd.set ("BaseCurveHazard[" + dt1 + "-" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (dblBaseHazard, 1, 4, 1));
rnvd.set ("ParallelShiftedCurveHazard[" + dt1 + "-" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (dblShiftedHazard, 1, 4, 1));
dt = dt1;
if (!org.drip.numerical.common.NumberUtil.WithinTolerance (dblBaseHazard + 0.0005,
dblShiftedHazard))
return false;
}
return true;
}
});
/*
* Testing creation of the parallel quote shifted credit curve - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor
("ParallelQuoteShiftedCurve", _strRegressionScenario)
{
private org.drip.state.credit.CreditCurve _ccParallelShifted = null;
@Override public boolean execRegression()
{
return null != (_ccParallelShifted = (org.drip.state.credit.CreditCurve)
_cc.parallelShiftManifestMeasure ("FairPremium", 5.));
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
org.drip.product.definition.CalibratableComponent[] aCalibComp =
_cc.calibComp();
org.drip.analytics.date.JulianDate dt1 = _dtStart;
for (int i = 0; i < aCalibComp.length; ++i) {
org.drip.analytics.date.JulianDate dt = aCalibComp[i].maturityDate();
try {
rnvd.set ("BaseCurveQuote[" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (_cc.manifestMeasure
(aCalibComp[i].primaryCode()).get ("FairPremium"), 1, 5, 1));
rnvd.set ("ParallelShiftedCurveQuote[" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble
(_ccParallelShifted.manifestMeasure (aCalibComp[i].primaryCode()).get
("FairPremium"), 1, 5, 1));
dt = dt1;
if (!org.drip.numerical.common.NumberUtil.WithinTolerance (_cc.manifestMeasure
(aCalibComp[i].primaryCode()).get ("FairPremium") + 5.,
_ccParallelShifted.manifestMeasure (aCalibComp[i].primaryCode()).get
("FairPremium")))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
});
/*
* Testing creation of the node tweaked Credit Curve - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("NodeTweakedCurve",
_strRegressionScenario)
{
private static final int TWEAKED_NODE = 0;
private org.drip.param.definition.CreditManifestMeasureTweak _cntp = null;
private org.drip.state.credit.CreditCurve _ccTweakedCurve = null;
@Override public boolean preRegression()
{
try {
_cntp = new org.drip.param.definition.CreditManifestMeasureTweak
(org.drip.param.definition.CreditManifestMeasureTweak.CREDIT_TWEAK_NODE_PARAM_QUOTE,
org.drip.param.definition.CreditManifestMeasureTweak.CREDIT_TWEAK_NODE_MEASURE_QUOTE,
TWEAKED_NODE, true, 0.1, false);
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
return true;
}
@Override public boolean execRegression()
{
return null != (_ccTweakedCurve = (org.drip.state.credit.CreditCurve)
_cc.customTweakManifestMeasure ("FairPremium", _cntp));
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
org.drip.product.definition.CalibratableComponent[] aCalibComp =
_cc.calibComp();
org.drip.analytics.date.JulianDate dt1 = _dtStart;
for (int i = 0; i < aCalibComp.length; ++i) {
org.drip.analytics.date.JulianDate dt = aCalibComp[i].maturityDate();
double dblBaseHazard = java.lang.Double.NaN;
double dblShiftedHazard = java.lang.Double.NaN;
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (dblShiftedHazard =
_ccTweakedCurve.hazard (dt1, dt)) ||
!org.drip.numerical.common.NumberUtil.IsValid (dblBaseHazard = _cc.hazard
(dt1, dt)))
return false;
} catch (Exception e) {
e.printStackTrace();
return false;
}
rnvd.set ("UntweakedHazard[" + dt + "]",
org.drip.numerical.common.FormatUtil.FormatDouble (dblBaseHazard, 1, 5, 1));
rnvd.set ("TweakedHazard[" + dt + "]", org.drip.numerical.common.FormatUtil.FormatDouble
(dblShiftedHazard, 1, 5, 1));
dt = dt1;
}
return true;
}
});
/*
* Testing creation of the Credit Curve from flat/quoted spread - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("FlatCurve",
_strRegressionScenario)
{
private org.drip.state.credit.CreditCurve _ccFlatCurve = null;
@Override public boolean execRegression()
{
if (null == (_ccFlatCurve = _cc.flatCurve (90., false, 0.35))) return false;
return true;
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
final int NUM_DC_INSTRUMENTS = 5;
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
org.drip.analytics.date.JulianDate dt = _dtStart.addYears (i + 1);
double dblHazard = java.lang.Double.NaN;
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (dblHazard = _ccFlatCurve.hazard
(dt)))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
rnvd.set ("FlatHazard[" + dt + "]", org.drip.numerical.common.FormatUtil.FormatDouble
(dblHazard, 1, 5, 1));
}
return true;
}
});
/*
* Testing setting/removing specific default dates - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("SpecificDefault",
_strRegressionScenario)
{
private int _iSpecificDefaultDate = java.lang.Integer.MIN_VALUE;
@Override public boolean preRegression()
{
return !org.drip.numerical.common.NumberUtil.IsValid (_iSpecificDefaultDate = _dtStart.addYears
(2).julian());
}
@Override public boolean execRegression()
{
return _cc.setSpecificDefault (_iSpecificDefaultDate);
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
double dblSurvivalProb = java.lang.Double.NaN;
org.drip.analytics.date.JulianDate dtSurvival = _dtStart.addYears (3);
int iSurvivalDate = dtSurvival.julian();
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (dblSurvivalProb = _cc.survival
(iSurvivalDate)))
return false;
} catch (Exception e) {
e.printStackTrace();
return false;
}
rnvd.set ("SpecificDefaultSetSurvival[" + dtSurvival + "]", "" + dblSurvivalProb);
if (!_cc.unsetSpecificDefault()) return false;
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (dblSurvivalProb = _cc.survival
(iSurvivalDate)))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
rnvd.set ("SpecificDefaultUnsetSurvival[" + dtSurvival + "]", "" + dblSurvivalProb);
return true;
}
});
/*
* Testing calculation of effective survival between2 dates - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("EffectiveSurvival",
_strRegressionScenario)
{
private static final int NUM_DC_INSTRUMENTS = 5;
private int _aiDate[] = new int[NUM_DC_INSTRUMENTS];
private double _adblSurvival[] = new double[NUM_DC_INSTRUMENTS];
@Override public boolean preRegression()
{
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i)
_aiDate[i] = _dtStart.addYears (i + 1).julian();
return true;
}
@Override public boolean execRegression()
{
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (_adblSurvival[i] =
_cc.effectiveSurvival ((i + 1) + "Y", (i + 2) + "Y")))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
try {
rnvd.set ("EffectiveSurvival[" + new org.drip.analytics.date.JulianDate
(_aiDate[i]) + "]", org.drip.numerical.common.FormatUtil.FormatDouble
(_adblSurvival[i], 1, 4, 1));
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
});
/*
* Testing calculation of effective recovery between2 dates - implements the pre-regression, the
* post-regression, and the actual regression functionality of the UnitRegressorExecutor class.
*/
_setRegressors.add (new org.drip.regression.core.UnitRegressionExecutor ("EffectiveRecovery",
_strRegressionScenario)
{
private static final int NUM_DC_INSTRUMENTS = 5;
private double _adblEffectiveRecovery[] = new double[NUM_DC_INSTRUMENTS];
@Override public boolean execRegression()
{
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
try {
if (!org.drip.numerical.common.NumberUtil.IsValid (_adblEffectiveRecovery[i] =
_cc.effectiveRecovery ((i + 1) + "Y", (i + 2) + "Y")))
return false;
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
@Override public boolean postRegression (
final org.drip.regression.core.RegressionRunDetail rnvd)
{
for (int i = 0; i < NUM_DC_INSTRUMENTS; ++i) {
try {
rnvd.set ("EffectiveRecovery[" + (i + 1) + "Y-" + (i + 2) + "Y]",
org.drip.numerical.common.FormatUtil.FormatDouble (_adblEffectiveRecovery[i], 1,
4, 1));
rnvd.set ("CurveRecovery[" + (i + 1) + "Y-" + (i + 2) + "Y]",
org.drip.numerical.common.FormatUtil.FormatDouble (_cc.recovery ((i + 1) + "Y"),
1, 4, 1) + "-" + org.drip.numerical.common.FormatUtil.FormatDouble
(_cc.recovery ((i + 2) + "Y"), 1, 4, 1));
} catch (java.lang.Exception e) {
e.printStackTrace();
return false;
}
}
return true;
}
});
} catch (Exception e) {
e.printStackTrace();
return false;
}
return true;
}
@Override public java.util.List<org.drip.regression.core.UnitRegressor> getRegressorSet()
{
return _setRegressors;
}
@Override public java.lang.String getSetName()
{
return _strRegressionScenario;
}
}