PathVertexExerciseMetrics.java

  1. package org.drip.sample.govviemc;

  3. import org.drip.analytics.date.*;
  4. import org.drip.measure.crng.RandomNumberGenerator;
  5. import org.drip.measure.discrete.CorrelatedPathVertexDimension;
  6. import org.drip.measure.dynamics.DiffusionEvaluatorLogarithmic;
  7. import org.drip.measure.process.DiffusionEvolver;
  8. import org.drip.measure.statistics.UnivariateDiscreteThin;
  9. import org.drip.numerical.common.FormatUtil;
  10. import org.drip.param.creator.MarketParamsBuilder;
  11. import org.drip.param.market.CurveSurfaceQuoteContainer;
  12. import org.drip.param.valuation.ValuationParams;
  13. import org.drip.product.creator.BondBuilder;
  14. import org.drip.product.credit.BondComponent;
  15. import org.drip.product.params.EmbeddedOptionSchedule;
  16. import org.drip.service.env.EnvManager;
  17. import org.drip.service.template.LatentMarketStateBuilder;
  18. import org.drip.state.discount.MergedDiscountForwardCurve;
  19. import org.drip.state.govvie.GovvieCurve;
  20. import org.drip.state.sequence.*;

  22. /*
  23.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  24.  */

  26. /*!
  27.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  28.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  29.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  30.  * 
  31.  *  This file is part of DROP, an open-source library targeting risk, transaction costs, exposure, margin
  32.  *      calculations, valuation adjustment, and portfolio construction within and across fixed income,
  33.  *      credit, commodity, equity, FX, and structured products.
  34.  *  
  35.  *      https://lakshmidrip.github.io/DROP/
  36.  *  
  37.  *  DROP is composed of three modules:
  38.  *  
  39.  *  - DROP Analytics Core - https://lakshmidrip.github.io/DROP-Analytics-Core/
  40.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  41.  *  - DROP Numerical Core - https://lakshmidrip.github.io/DROP-Numerical-Core/
  42.  * 
  43.  *  DROP Analytics Core implements libraries for the following:
  44.  *  - Fixed Income Analytics
  45.  *  - Asset Backed Analytics
  46.  *  - XVA Analytics
  47.  *  - Exposure and Margin Analytics
  48.  * 
  49.  *  DROP Portfolio Core implements libraries for the following:
  50.  *  - Asset Allocation Analytics
  51.  *  - Transaction Cost Analytics
  52.  * 
  53.  *  DROP Numerical Core implements libraries for the following:
  54.  *  - Statistical Learning
  55.  *  - Numerical Optimizer
  56.  *  - Spline Builder
  57.  *  - Algorithm Support
  58.  * 
  59.  *  Documentation for DROP is Spread Over:
  60.  * 
  61.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  62.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  63.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  64.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  65.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  66.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  67.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  68.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  69.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  70.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  71.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  72.  * 
  73.  *  Licensed under the Apache License, Version 2.0 (the "License");
  74.  *      you may not use this file except in compliance with the License.
  75.  *   
  76.  *  You may obtain a copy of the License at
  77.  *      http://www.apache.org/licenses/LICENSE-2.0
  78.  *  
  79.  *  Unless required by applicable law or agreed to in writing, software
  80.  *      distributed under the License is distributed on an "AS IS" BASIS,
  81.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  82.  *  
  83.  *  See the License for the specific language governing permissions and
  84.  *      limitations under the License.
  85.  */

  87. /**
  88.  * <i>PathVertexExerciseMetrics</i> demonstrates the Simulations of the Per-Path Callable Bond OAS Based
  89.  * Exercise Metrics.
  90.  *  
  91.  * <br><br>
  92.  *  <ul>
  93.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/AnalyticsCore.md">Analytics Core Module</a></li>
  94.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/FixedIncomeAnalyticsLibrary.md">Fixed Income Analytics Library</a></li>
  95.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/README.md">Sample</a></li>
  96.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/sample/govviemc/README.md">Govvie Curve Monte Carlo Runs</a></li>
  97.  *  </ul>
  98.  * <br><br>
  99.  * 
  100.  * @author Lakshmi Krishnamurthy
  101.  */

  103. public class PathVertexExerciseMetrics {

  105.     private static final MergedDiscountForwardCurve FundingCurve (
  106.         final JulianDate dtSpot,
  107.         final String strCurrency,
  108.         final double dblBump)
  109.         throws Exception
  110.     {
  111.         String[] astrDepositMaturityTenor = new String[] {
  112.             "2D"
  113.         };

  115.         double[] adblDepositQuote = new double[] {
  116.             0.0111956 + dblBump // 2D
  117.         };

  119.         double[] adblFuturesQuote = new double[] {
  120.             0.011375 + dblBump, // 98.8625
  121.             0.013350 + dblBump, // 98.6650
  122.             0.014800 + dblBump, // 98.5200
  123.             0.016450 + dblBump, // 98.3550
  124.             0.017850 + dblBump, // 98.2150
  125.             0.019300 + dblBump  // 98.0700
  126.         };

  128.         String[] astrFixFloatMaturityTenor = new String[] {
  129.             "02Y",
  130.             "03Y",
  131.             "04Y",
  132.             "05Y",
  133.             "06Y",
  134.             "07Y",
  135.             "08Y",
  136.             "09Y",
  137.             "10Y",
  138.             "11Y",
  139.             "12Y",
  140.             "15Y",
  141.             "20Y",
  142.             "25Y",
  143.             "30Y",
  144.             "40Y",
  145.             "50Y"
  146.         };

  148.         double[] adblFixFloatQuote = new double[] {
  149.             0.017029 + dblBump, //  2Y
  150.             0.019354 + dblBump, //  3Y
  151.             0.021044 + dblBump, //  4Y
  152.             0.022291 + dblBump, //  5Y
  153.             0.023240 + dblBump, //  6Y
  154.             0.024025 + dblBump, //  7Y
  155.             0.024683 + dblBump, //  8Y
  156.             0.025243 + dblBump, //  9Y
  157.             0.025720 + dblBump, // 10Y
  158.             0.026130 + dblBump, // 11Y
  159.             0.026495 + dblBump, // 12Y
  160.             0.027230 + dblBump, // 15Y
  161.             0.027855 + dblBump, // 20Y
  162.             0.028025 + dblBump, // 25Y
  163.             0.028028 + dblBump, // 30Y
  164.             0.027902 + dblBump, // 40Y
  165.             0.027655 + dblBump  // 50Y
  166.         };

  168.         return LatentMarketStateBuilder.SmoothFundingCurve (
  169.             dtSpot,
  170.             strCurrency,
  171.             astrDepositMaturityTenor,
  172.             adblDepositQuote,
  173.             "ForwardRate",
  174.             adblFuturesQuote,
  175.             "ForwardRate",
  176.             astrFixFloatMaturityTenor,
  177.             adblFixFloatQuote,
  178.             "SwapRate"
  179.         );
  180.     }

  182.     private static final PathVertexGovvie ScenarioGovvieCurves (
  183.         final JulianDate dtSpot,
  184.         final int iNumPath,
  185.         final int iNumVertex)
  186.         throws Exception
  187.     {
  188.         double dblVolatility = 0.10;
  189.         String strTreasuryCode = "UST";

  191.         String[] astrTenor = new String[] {
  192.             "01Y",
  193.             "02Y",
  194.             "03Y",
  195.             "05Y",
  196.             "07Y",
  197.             "10Y",
  198.             "20Y",
  199.             "30Y"
  200.         };

  202.         double[] adblTreasuryCoupon = new double[] {
  203.             0.0100,
  204.             0.0100,
  205.             0.0125,
  206.             0.0150,
  207.             0.0200,
  208.             0.0225,
  209.             0.0250,
  210.             0.0300
  211.         };

  213.         double[] adblTreasuryYield = new double[] {
  214.             0.0083, //  1Y
  215.             0.0122, //  2Y
  216.             0.0149, //  3Y
  217.             0.0193, //  5Y
  218.             0.0227, //  7Y
  219.             0.0248, // 10Y
  220.             0.0280, // 20Y
  221.             0.0308  // 30Y
  222.         };

  224.         int iNumDimension = astrTenor.length;
  225.         double[][] aadblCorrelation = new double[iNumDimension][iNumDimension];

  227.         for (int i = 0; i < iNumDimension; ++i) {
  228.             for (int j = 0; j < iNumDimension; ++j)
  229.                 aadblCorrelation[i][j] = i == j ? 1. : 0.;
  230.         }

  232.         GovvieBuilderSettings gbs = new GovvieBuilderSettings (
  233.             dtSpot,
  234.             strTreasuryCode,
  235.             astrTenor,
  236.             adblTreasuryCoupon,
  237.             adblTreasuryYield
  238.         );

  240.         return PathVertexGovvie.Standard (
  241.             gbs,
  242.             new CorrelatedPathVertexDimension (
  243.                 new RandomNumberGenerator(),
  244.                 aadblCorrelation,
  245.                 iNumVertex,
  246.                 iNumPath,
  247.                 false,
  248.                 null
  249.             ),
  250.             new DiffusionEvolver (
  251.                 DiffusionEvaluatorLogarithmic.Standard (
  252.                     0.,
  253.                     dblVolatility
  254.                 )
  255.             )
  256.         );
  257.     }

  259.     private static final BondComponent Callable (
  260.         final EmbeddedOptionSchedule eos)
  261.         throws Exception
  262.     {
  263.         JulianDate dtEffective = DateUtil.CreateFromYMD (
  264.             2009,
  265.             12,
  266.             3
  267.         );

  269.         JulianDate dtMaturity  = DateUtil.CreateFromYMD (
  270.             2039,
  271.             12,
  272.             1
  273.         );

  275.         double dblCoupon = 0.06558;
  276.         int iFreq = 2;
  277.         String strCUSIP = "033177XV3";
  278.         String strDayCount = "30/360";

  280.         BondComponent bond = BondBuilder.CreateSimpleFixed (
  281.             strCUSIP,
  282.             "USD",
  283.             "",
  284.             dblCoupon,
  285.             iFreq,
  286.             strDayCount,
  287.             dtEffective,
  288.             dtMaturity,
  289.             null,
  290.             null
  291.         );

  293.         bond.setEmbeddedCallSchedule (eos);

  295.         return bond;
  296.     }

  298.     public static final void main (
  299.         final String[] astrArgs)
  300.         throws Exception
  301.     {
  302.         EnvManager.InitEnv ("");

  304.         JulianDate dtSpot = DateUtil.CreateFromYMD (
  305.             2017,
  306.             DateUtil.MARCH,
  307.             24
  308.         );

  310.         int iNumPath = 50;
  311.         double dblCleanPrice = 1.08641;
  312.         int[] aiExerciseDate = new int[] {
  313.             DateUtil.CreateFromYMD (2019, 12,  1).julian(),
  314.             DateUtil.CreateFromYMD (2020, 12,  1).julian(),
  315.             DateUtil.CreateFromYMD (2021, 12,  1).julian(),
  316.             DateUtil.CreateFromYMD (2022, 12,  1).julian(),
  317.             DateUtil.CreateFromYMD (2023, 12,  1).julian(),
  318.             DateUtil.CreateFromYMD (2024, 12,  1).julian(),
  319.             DateUtil.CreateFromYMD (2025, 12,  1).julian(),
  320.             DateUtil.CreateFromYMD (2026, 12,  1).julian(),
  321.             DateUtil.CreateFromYMD (2027, 12,  1).julian(),
  322.             DateUtil.CreateFromYMD (2028, 12,  1).julian(),
  323.             DateUtil.CreateFromYMD (2029, 12,  1).julian(),
  324.             DateUtil.CreateFromYMD (2030, 12,  1).julian(),
  325.             DateUtil.CreateFromYMD (2031, 12,  1).julian(),
  326.             DateUtil.CreateFromYMD (2032, 12,  1).julian(),
  327.             DateUtil.CreateFromYMD (2033, 12,  1).julian(),
  328.             DateUtil.CreateFromYMD (2034, 12,  1).julian(),
  329.             DateUtil.CreateFromYMD (2035, 12,  1).julian(),
  330.             DateUtil.CreateFromYMD (2036, 12,  1).julian(),
  331.             DateUtil.CreateFromYMD (2037, 12,  1).julian(),
  332.             DateUtil.CreateFromYMD (2038, 12,  1).julian(),
  333.         };
  334.         double[] adblExercisePrice = new double[] {
  335.             1.,
  336.             1.,
  337.             1.,
  338.             1.,
  339.             1.,
  340.             1.,
  341.             1.,
  342.             1.,
  343.             1.,
  344.             1.,
  345.             1.,
  346.             1.,
  347.             1.,
  348.             1.,
  349.             1.,
  350.             1.,
  351.             1.,
  352.             1.,
  353.             1.,
  354.             1.,
  355.         };

  357.         int iNumVertex = aiExerciseDate.length;
  358.         double[] adblOptimalExercisePV = new double[iNumPath];
  359.         int[] aiOptimalExerciseVertexIndex = new int[iNumPath];
  360.         double[] adblOptimalExerciseOAS = new double[iNumPath];
  361.         double[] adblOptimalExercisePrice = new double[iNumPath];
  362.         double[] adblOptimalExerciseOASGap = new double[iNumPath];
  363.         double[] adblOptimalExerciseDuration = new double[iNumPath];
  364.         double[] adblOptimalExerciseConvexity = new double[iNumPath];
  365.         JulianDate[] adtOptimalExerciseDate = new JulianDate[iNumPath];
  366.         double[][] aadblForwardPrice = new double[iNumPath][iNumVertex];
  367.         ValuationParams[] aValParamsEvent = new ValuationParams[iNumVertex];

  369.         BondComponent bond = Callable (
  370.             new EmbeddedOptionSchedule (
  371.                 aiExerciseDate,
  372.                 adblExercisePrice,
  373.                 false,
  374.                 30,
  375.                 false,
  376.                 Double.NaN,
  377.                 "",
  378.                 Double.NaN
  379.             )
  380.         );

  382.         PathVertexGovvie mcrg = ScenarioGovvieCurves (
  383.             dtSpot,
  384.             iNumPath,
  385.             iNumVertex
  386.         );

  388.         GovvieCurve[][] aaGCPathEvent = mcrg.pathVertex (aiExerciseDate);

  390.         MergedDiscountForwardCurve mdfc = FundingCurve (
  391.             dtSpot,
  392.             "USD",
  393.             0.
  394.         );

  396.         CurveSurfaceQuoteContainer csqcSpot = MarketParamsBuilder.Create (
  397.             mdfc,
  398.             mcrg.govvieBuilderSettings().groundState(),
  399.             null,
  400.             null,
  401.             null,
  402.             null,
  403.             null
  404.         );

  406.         ValuationParams valParamsSpot = ValuationParams.Spot (dtSpot.julian());

  408.         double dblOASSpot = bond.oasFromPrice (
  409.             valParamsSpot,
  410.             csqcSpot,
  411.             null,
  412.             dblCleanPrice
  413.         );

  415.         for (int iVertex = 0; iVertex < iNumVertex; ++iVertex)
  416.             aValParamsEvent[iVertex] = ValuationParams.Spot (aiExerciseDate[iVertex]);

  418.         for (int iPath = 0; iPath < iNumPath; ++iPath) {
  419.             for (int iVertex = 0; iVertex < iNumVertex; ++iVertex) {
  420.                 CurveSurfaceQuoteContainer csqcEvent = MarketParamsBuilder.Create (
  421.                     mdfc,
  422.                     aaGCPathEvent[iPath][iVertex],
  423.                     null,
  424.                     null,
  425.                     null,
  426.                     null,
  427.                     null
  428.                 );

  430.                 aadblForwardPrice[iPath][iVertex] = bond.priceFromOAS (
  431.                     aValParamsEvent[iVertex],
  432.                     csqcEvent,
  433.                     null,
  434.                     dblOASSpot
  435.                 );
  436.             }
  437.         }

  439.         for (int iPath = 0; iPath < iNumPath; ++iPath) {
  440.             adblOptimalExercisePV[iPath] = 0.;
  441.             adblOptimalExercisePrice[iPath] = 1.;
  442.             aiOptimalExerciseVertexIndex[0] = iNumVertex - 1;

  444.             adtOptimalExerciseDate[iPath] = bond.maturityDate();

  446.             for (int iVertex = 0; iVertex < iNumVertex; ++iVertex) {
  447.                 double dblExercisePV = (aadblForwardPrice[iPath][iVertex] - adblExercisePrice[iVertex])
  448.                     * mdfc.df (aiExerciseDate[iVertex]);

  450.                 if (dblExercisePV > adblOptimalExercisePV[iPath]) {
  451.                     adtOptimalExerciseDate[iPath] = new JulianDate (aiExerciseDate[iVertex]);

  453.                     adblOptimalExercisePrice[iPath] = adblExercisePrice[iVertex];
  454.                     aiOptimalExerciseVertexIndex[iPath] = iVertex;
  455.                     adblOptimalExercisePV[iPath] = dblExercisePV;
  456.                 }
  457.             }
  458.         }

  460.         System.out.println ("\n");

  462.         System.out.println ("\t||---------------------------------------------------------------------------||");

  464.         System.out.println ("\t||                        PATH-WISE EXERCISE METRICS                         ||");

  466.         System.out.println ("\t||---------------------------------------------------------------------------||");

  468.         System.out.println ("\t||    L -> R:                                                                ||");

  470.         System.out.println ("\t||        Path Number                                                        ||");

  472.         System.out.println ("\t||        Optimal Exercise Index                                             ||");

  474.         System.out.println ("\t||        Optimal Exercise Date                                              ||");

  476.         System.out.println ("\t||        Optimal Exercise Price                                             ||");

  478.         System.out.println ("\t||        Optimal Exercise Value                                             ||");

  480.         System.out.println ("\t||        Optimal Exercise OAS                                               ||");

  482.         System.out.println ("\t||        Optimal Exercise OAS Gap                                           ||");

  484.         System.out.println ("\t||        Optimal Exercise Duration                                          ||");

  486.         System.out.println ("\t||        Optimal Exercise Convexity                                         ||");

  488.         System.out.println ("\t||---------------------------------------------------------------------------||");

  490.         for (int iPath = 0; iPath < iNumPath; ++iPath) {
  491.             int iOptimalExerciseDate = adtOptimalExerciseDate[iPath].julian();

  493.             adblOptimalExerciseOAS[iPath] = bond.oasFromPrice (
  494.                 valParamsSpot,
  495.                 csqcSpot,
  496.                 null,
  497.                 iOptimalExerciseDate,
  498.                 adblOptimalExercisePrice[iPath],
  499.                 dblCleanPrice
  500.             );

  502.             adblOptimalExerciseDuration[iPath] = bond.modifiedDurationFromPrice (
  503.                 valParamsSpot,
  504.                 csqcSpot,
  505.                 null,
  506.                 iOptimalExerciseDate,
  507.                 adblOptimalExercisePrice[iPath],
  508.                 dblCleanPrice
  509.             );

  511.             adblOptimalExerciseConvexity[iPath] = bond.convexityFromPrice (
  512.                 valParamsSpot,
  513.                 csqcSpot,
  514.                 null,
  515.                 iOptimalExerciseDate,
  516.                 adblOptimalExercisePrice[iPath],
  517.                 dblCleanPrice
  518.             );

  520.             adblOptimalExerciseOASGap[iPath] = adblOptimalExerciseOAS[iPath] - dblOASSpot;

  522.             System.out.println (
  523.                 "\t|| " +
  524.                 FormatUtil.FormatDouble (iPath, 2, 0, 1.) + " => " +
  525.                 FormatUtil.FormatDouble (aiOptimalExerciseVertexIndex[iPath], 2, 0, 1.) + " | " +
  526.                 adtOptimalExerciseDate[iPath] + " | " +
  527.                 FormatUtil.FormatDouble (adblOptimalExercisePrice[iPath], 3, 2, 100.) + " | " +
  528.                 FormatUtil.FormatDouble (adblOptimalExercisePV[iPath], 2, 1, 100.) + " | " +
  529.                 FormatUtil.FormatDouble (adblOptimalExerciseOAS[iPath], 3, 0, 10000.) + " | " +
  530.                 FormatUtil.FormatDouble (adblOptimalExerciseOASGap[iPath], 3, 0, 10000.) + " | " +
  531.                 FormatUtil.FormatDouble (adblOptimalExerciseDuration[iPath], 2, 2, 10000.)  + " | " +
  532.                 FormatUtil.FormatDouble (adblOptimalExerciseConvexity[iPath], 1, 2, 1000000.) + " ||"
  533.             );
  534.         }

  536.         System.out.println ("\t||---------------------------------------------------------------------------||");

  538.         System.out.println();

  540.         UnivariateDiscreteThin udtOptimalExercisePrice = new UnivariateDiscreteThin (adblOptimalExercisePrice);

  542.         UnivariateDiscreteThin udtOptimalExercisePV = new UnivariateDiscreteThin (adblOptimalExercisePV);

  544.         UnivariateDiscreteThin udtOptimalExerciseOAS = new UnivariateDiscreteThin (adblOptimalExerciseOAS);

  546.         UnivariateDiscreteThin udtOptimalExerciseOASGap = new UnivariateDiscreteThin (adblOptimalExerciseOASGap);

  548.         UnivariateDiscreteThin udtOptimalExerciseDuration = new UnivariateDiscreteThin (adblOptimalExerciseDuration);

  550.         UnivariateDiscreteThin udtOptimalExerciseConvexity = new UnivariateDiscreteThin (adblOptimalExerciseConvexity);

  552.         System.out.println ("\t||-------------------------------------------------------------||");

  554.         System.out.println ("\t||        Optimal Exercise Price                               ||");

  556.         System.out.println ("\t||        Optimal Exercise Value                               ||");

  558.         System.out.println ("\t||        Optimal Exercise OAS                                 ||");

  560.         System.out.println ("\t||        Optimal Exercise OAS Gap                             ||");

  562.         System.out.println ("\t||        Optimal Exercise Duration                            ||");

  564.         System.out.println ("\t||        Optimal Exercise Convexity                           ||");

  566.         System.out.println ("\t||-------------------------------------------------------------||");

  568.         System.out.println ("\t|| AVERAGE => " +
  569.             FormatUtil.FormatDouble (udtOptimalExercisePrice.average(), 3, 2, 100.) + " | " +
  570.             FormatUtil.FormatDouble (udtOptimalExercisePV.average(), 2, 1, 100.) + " | " +
  571.             FormatUtil.FormatDouble (udtOptimalExerciseOAS.average(), 3, 1, 10000.) + " | " +
  572.             FormatUtil.FormatDouble (udtOptimalExerciseOASGap.average(), 3, 0, 10000.) + " | " +
  573.             FormatUtil.FormatDouble (udtOptimalExerciseDuration.average(), 2, 2, 10000.) + " | " +
  574.             FormatUtil.FormatDouble (udtOptimalExerciseConvexity.average(), 1, 2, 1000000.) + " ||"
  575.         );

  577.         System.out.println ("\t||  ERROR  => " +
  578.             FormatUtil.FormatDouble (udtOptimalExercisePrice.error(), 3, 2, 100.) + " | " +
  579.             FormatUtil.FormatDouble (udtOptimalExercisePV.error(), 2, 1, 100.) + " | " +
  580.             FormatUtil.FormatDouble (udtOptimalExerciseOAS.error(), 3, 1, 10000.) + " | " +
  581.             FormatUtil.FormatDouble (udtOptimalExerciseOASGap.error(), 3, 0, 10000.) + " | " +
  582.             FormatUtil.FormatDouble (udtOptimalExerciseDuration.error(), 2, 2, 10000.) + " | " +
  583.             FormatUtil.FormatDouble (udtOptimalExerciseConvexity.error(), 1, 2, 1000000.) + " ||"
  584.         );

  586.         System.out.println ("\t|| MAXIMUM => " +
  587.             FormatUtil.FormatDouble (udtOptimalExercisePrice.maximum(), 3, 2, 100.) + " | " +
  588.             FormatUtil.FormatDouble (udtOptimalExercisePV.maximum(), 2, 1, 100.) + " | " +
  589.             FormatUtil.FormatDouble (udtOptimalExerciseOAS.maximum(), 3, 1, 10000.) + " | " +
  590.             FormatUtil.FormatDouble (udtOptimalExerciseOASGap.maximum(), 3, 0, 10000.) + " | " +
  591.             FormatUtil.FormatDouble (udtOptimalExerciseDuration.maximum(), 2, 2, 10000.) + " | " +
  592.             FormatUtil.FormatDouble (udtOptimalExerciseConvexity.maximum(), 1, 2, 1000000.) + " ||"
  593.         );

  595.         System.out.println ("\t|| MINIMUM => " +
  596.             FormatUtil.FormatDouble (udtOptimalExercisePrice.minimum(), 3, 2, 100.) + " | " +
  597.             FormatUtil.FormatDouble (udtOptimalExercisePV.minimum(), 2, 1, 100.) + " | " +
  598.             FormatUtil.FormatDouble (udtOptimalExerciseOAS.minimum(), 3, 1, 10000.) + " | " +
  599.             FormatUtil.FormatDouble (udtOptimalExerciseOASGap.minimum(), 3, 0, 10000.) + " | " +
  600.             FormatUtil.FormatDouble (udtOptimalExerciseDuration.minimum(), 2, 2, 10000.) + " | " +
  601.             FormatUtil.FormatDouble (udtOptimalExerciseConvexity.minimum(), 1, 2, 1000000.) + " ||"
  602.         );

  604.         System.out.println ("\t||-------------------------------------------------------------||");

  606.         System.out.println();

  608.         EnvManager.TerminateEnv();
  609.     }
  610. }
Created with JaCoCo 0.7.9.201702052155