VarianceTerm.java

package org.drip.portfolioconstruction.objective;

/*
 * -*- 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 Krishnamurthy0
 * 
 *  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>VarianceTerm</i> holds the Details of the Portfolio Risk (Variance) Objective Term. Variance can be
 * Absolute or in relation to a Benchmark.
 *
 *	<br><br>
 *  <ul>
 *		<li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/PortfolioCore.md">Portfolio Core Module</a></li>
 *		<li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/AssetAllocationAnalyticsLibrary.md">Asset Allocation Analytics</a></li>
 *		<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>
 *		<li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/portfolioconstruction/objective/README.md">Portfolio Construction Objective Term Suite</a></li>
 *  </ul>
 * <br><br>
 *
 * @author Lakshmi Krishnamurthy
 */

public class VarianceTerm
	extends org.drip.portfolioconstruction.objective.RiskTerm
{

	/**
	 * VarianceTerm Constructor
	 * 
	 * @param name Name of the Objective Function
	 * @param initialHoldingsArray The Initial Holdings
	 * @param assetCovarianceMatrix The Asset Covariance
	 * @param benchmarkConstrictedHoldingsArray The Constricted Benchmark Holdings
	 * 
	 * @throws java.lang.Exception Thrown if the Inputs are Invalid
	 */

	public VarianceTerm (
		final java.lang.String name,
		final double[] initialHoldingsArray,
		final double[][] assetCovarianceMatrix,
		final double[] benchmarkConstrictedHoldingsArray)
		throws java.lang.Exception
	{
		super (
			name,
			"OT_VARIANCE",
			"Variance Objective Term",
			initialHoldingsArray,
			assetCovarianceMatrix,
			benchmarkConstrictedHoldingsArray
		);
	}

	@Override public org.drip.function.definition.RdToR1 rdtoR1()
	{
		return new org.drip.function.definition.RdToR1 (null)
		{
			@Override public int dimension()
			{
				return initialHoldingsArray().length;
			}

			@Override public double evaluate (
				final double[] variateArray)
				throws java.lang.Exception
			{
				if (null == variateArray ||
					!org.drip.numerical.common.NumberUtil.IsValid (variateArray))
				{
					throw new java.lang.Exception ("VarianceTerm::rdToR1::evaluate => Invalid Input");
				}

				double[] benchmarkConstrictedHoldingsArray = benchmarkConstrictedHoldings();

				double[][] assetCovarianceMatrix = assetCovariance();

				int assetCount = assetCovarianceMatrix.length;
				double covariance = 0.;

				if (variateArray.length != assetCount)
				{
					throw new java.lang.Exception
						("VarianceTerm::rdToR1::evaluate => Invalid Variate Dimension");
				}

				for (int assetIndexI = 0; assetIndexI < assetCount; ++assetIndexI)
				{
					double outerAdjustedVariate = null == benchmarkConstrictedHoldingsArray ?
						variateArray[assetIndexI] :
						variateArray[assetIndexI] - benchmarkConstrictedHoldingsArray[assetIndexI];

					for (int assetIndexJ = 0; assetIndexJ < assetCount; ++assetIndexJ)
					{
						covariance += assetCovarianceMatrix[assetIndexI][assetIndexJ] * outerAdjustedVariate *
						(
							null == benchmarkConstrictedHoldingsArray ?
								variateArray[assetIndexJ] :
								variateArray[assetIndexJ] - benchmarkConstrictedHoldingsArray[assetIndexJ]
						);
					}
				}

				return covariance;
			}
		};
	}
}