MeanVarianceOptimizer.java

  1. package org.drip.portfolioconstruction.allocator;

  3. /*
  4.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  5.  */

  7. /*!
  8.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  10.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  11.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  12.  * Copyright (C) 2016 Lakshmi Krishnamurthy
  13.  * 
  14.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  15.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  16.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  17.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  18.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  19.  *      and computational support.
  20.  *  
  21.  *      https://lakshmidrip.github.io/DROP/
  22.  *  
  23.  *  DROP is composed of three modules:
  24.  *  
  25.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  26.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  27.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  28.  * 
  29.  *  DROP Product Core implements libraries for the following:
  30.  *  - Fixed Income Analytics
  31.  *  - Loan Analytics
  32.  *  - Transaction Cost Analytics
  33.  * 
  34.  *  DROP Portfolio Core implements libraries for the following:
  35.  *  - Asset Allocation Analytics
  36.  *  - Asset Liability Management Analytics
  37.  *  - Capital Estimation Analytics
  38.  *  - Exposure Analytics
  39.  *  - Margin Analytics
  40.  *  - XVA Analytics
  41.  * 
  42.  *  DROP Computational Core implements libraries for the following:
  43.  *  - Algorithm Support
  44.  *  - Computation Support
  45.  *  - Function Analysis
  46.  *  - Model Validation
  47.  *  - Numerical Analysis
  48.  *  - Numerical Optimizer
  49.  *  - Spline Builder
  50.  *  - Statistical Learning
  51.  * 
  52.  *  Documentation for DROP is Spread Over:
  53.  * 
  54.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  55.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  56.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  57.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  58.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  59.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  60.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  61.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  62.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  63.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  64.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  65.  * 
  66.  *  Licensed under the Apache License, Version 2.0 (the "License");
  67.  *      you may not use this file except in compliance with the License.
  68.  *   
  69.  *  You may obtain a copy of the License at
  70.  *      http://www.apache.org/licenses/LICENSE-2.0
  71.  *  
  72.  *  Unless required by applicable law or agreed to in writing, software
  73.  *      distributed under the License is distributed on an "AS IS" BASIS,
  74.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  75.  *  
  76.  *  See the License for the specific language governing permissions and
  77.  *      limitations under the License.
  78.  */

  80. /**
  81.  * <i>MeanVarianceOptimizer</i> exposes Portfolio Construction using Mean Variance Optimization Techniques.
  82.  *
  83.  *  <br><br>
  84.  *  <ul>
  85.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/PortfolioCore.md">Portfolio Core Module</a></li>
  86.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/AssetAllocationAnalyticsLibrary.md">Asset Allocation Analytics</a></li>
  87.  *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/portfolioconstruction/README.md">Portfolio Construction under Allocation Constraints</a></li>
  88.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/portfolioconstruction/allocator/README.md">MVO Based Portfolio Allocation Construction</a></li>
  89.  *  </ul>
  90.  *
  91.  * @author Lakshmi Krishnamurthy
  92.  */

  94. public abstract class MeanVarianceOptimizer
  95. {

  97.     protected abstract org.drip.portfolioconstruction.allocator.HoldingsAllocationControl
  98.         constrainedPCP (
  99.             final org.drip.portfolioconstruction.allocator.HoldingsAllocationControl
  100.                 designPortfolioConstructionParameters,
  101.             final double returnsConstraint);

  103.     /**
  104.      * Allocate the Long-Only Maximum Returns Portfolio
  105.      * 
  106.      * @param portfolioConstructionParameters The Portfolio Construction Parameters
  107.      * @param assetUniverseStatisticalProperties The Asset Universe Statistical Properties Instance
  108.      * 
  109.      * @return The Long-Only Maximum Returns Portfolio
  110.      */

  112.     public abstract org.drip.portfolioconstruction.allocator.HoldingsAllocation
  113.         longOnlyMaximumReturnsAllocate (
  114.             final org.drip.portfolioconstruction.allocator.HoldingsAllocationControl
  115.                 portfolioConstructionParameters,
  116.             final org.drip.portfolioconstruction.params.AssetUniverseStatisticalProperties
  117.                 assetUniverseStatisticalProperties);

  119.     /**
  120.      * Allocate the Global Minimum Variance Portfolio without any Returns Constraints in the Parameters
  121.      * 
  122.      * @param portfolioConstructionParameters The Portfolio Construction Parameters
  123.      * @param assetUniverseStatisticalProperties The Asset Universe Statistical Properties Instance
  124.      * 
  125.      * @return The Global Minimum Variance Portfolio
  126.      */

  128.     public abstract org.drip.portfolioconstruction.allocator.HoldingsAllocation
  129.         globalMinimumVarianceAllocate (
  130.             final org.drip.portfolioconstruction.allocator.HoldingsAllocationControl
  131.                 portfolioConstructionParameters,
  132.             final org.drip.portfolioconstruction.params.AssetUniverseStatisticalProperties
  133.                 assetUniverseStatisticalProperties);

  135.     /**
  136.      * Allocate the Optimal Portfolio Weights given the Portfolio Construction Parameters
  137.      * 
  138.      * @param portfolioConstructionParameters The Portfolio Construction Parameters
  139.      * @param assetUniverseStatisticalProperties The Asset Universe Statistical Properties Instance
  140.      * 
  141.      * @return The Optimal Portfolio
  142.      */

  144.     public abstract org.drip.portfolioconstruction.allocator.HoldingsAllocation allocate (
  145.         final org.drip.portfolioconstruction.allocator.HoldingsAllocationControl
  146.             portfolioConstructionParameters,
  147.         final org.drip.portfolioconstruction.params.AssetUniverseStatisticalProperties
  148.             assetUniverseStatisticalProperties);

  150.     /**
  151.      * Generate the Efficient Frontier given the Portfolio Construction Parameters
  152.      * 
  153.      * @param portfolioConstructionParameters The Portfolio Construction Parameters
  154.      * @param assetUniverseStatisticalProperties The Asset Universe Statistical Properties Instance
  155.      * @param frontierSampleUnits The Number of Frontier Sample Units
  156.      * 
  157.      * @return The Efficient Frontier
  158.      */

  160.     public org.drip.portfolioconstruction.mpt.MarkovitzBullet efficientFrontier (
  161.         final org.drip.portfolioconstruction.allocator.HoldingsAllocationControl
  162.             portfolioConstructionParameters,
  163.         final org.drip.portfolioconstruction.params.AssetUniverseStatisticalProperties
  164.             assetUniverseStatisticalProperties,
  165.         final int frontierSampleUnits)
  166.     {
  167.         if (0 >= frontierSampleUnits)
  168.         {
  169.             return null;
  170.         }

  172.         org.drip.portfolioconstruction.allocator.HoldingsAllocation globalMinimumVarianceOptimizationOutput =
  173.             globalMinimumVarianceAllocate (
  174.                 portfolioConstructionParameters,
  175.                 assetUniverseStatisticalProperties
  176.             );

  178.         if (null == globalMinimumVarianceOptimizationOutput)
  179.         {
  180.             return null;
  181.         }

  183.         org.drip.portfolioconstruction.allocator.HoldingsAllocation longOnlyMaximumReturnsOptimizationOutput
  184.             = longOnlyMaximumReturnsAllocate (
  185.                 portfolioConstructionParameters,
  186.                 assetUniverseStatisticalProperties
  187.             );

  189.         if (null == longOnlyMaximumReturnsOptimizationOutput)
  190.         {
  191.             return null;
  192.         }

  194.         double globalMinimumVarianceReturns =
  195.             globalMinimumVarianceOptimizationOutput.optimalMetrics().excessReturnsMean();

  197.         double longOnlyMaximumReturns =
  198.             longOnlyMaximumReturnsOptimizationOutput.optimalMetrics().excessReturnsMean();

  200.         double returnsConstraintGridWidth = (longOnlyMaximumReturns - globalMinimumVarianceReturns) /
  201.             frontierSampleUnits;
  202.         double returnsConstraint = globalMinimumVarianceReturns + returnsConstraintGridWidth;
  203.         org.drip.portfolioconstruction.mpt.MarkovitzBullet markovitzBullet = null;

  205.         try
  206.         {
  207.             markovitzBullet = new org.drip.portfolioconstruction.mpt.MarkovitzBullet (
  208.                 globalMinimumVarianceOptimizationOutput,
  209.                 longOnlyMaximumReturnsOptimizationOutput
  210.             );
  211.         }
  212.         catch (java.lang.Exception e)
  213.         {
  214.             e.printStackTrace();

  216.             return null;
  217.         }

  219.         while (returnsConstraint <= longOnlyMaximumReturns)
  220.         {
  221.             try
  222.             {
  223.                 markovitzBullet.addOptimalPortfolio (
  224.                     allocate (
  225.                         constrainedPCP (
  226.                             portfolioConstructionParameters,
  227.                             returnsConstraint
  228.                         ),
  229.                         assetUniverseStatisticalProperties
  230.                     )
  231.                 );
  232.             }
  233.             catch (java.lang.Exception e)
  234.             {
  235.                 e.printStackTrace();

  237.                 return null;
  238.             }

  240.             returnsConstraint += returnsConstraintGridWidth;
  241.         }

  243.         return markovitzBullet;
  244.     }
  245. }
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