GrossProfitEstimator.java

package org.drip.execution.principal;

/*
 * -*- 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
 * 
 *  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>GrossProfitEstimator</i> generates the Gross Profit Distribution and the Information Ratio for a given
 * Level of Principal Discount. The References are:
 * 
 * <br><br>
 *  <ul>
 *  <li>
 *      Almgren, R., and N. Chriss (1999): Value under Liquidation <i>Risk</i> <b>12 (12)</b>
 *  </li>
 *  <li>
 *      Almgren, R., and N. Chriss (2000): Optimal Execution of Portfolio Transactions <i>Journal of Risk</i>
 *          <b>3 (2)</b> 5-39
 *  </li>
 *  <li>
 *      Almgren, R. (2003): Optimal Execution with Nonlinear Impact Functions and Trading-Enhanced Risk
 *          <i>Applied Mathematical Finance</i> <b>10 (1)</b> 1-18
 *  </li>
 *  <li>
 *      Almgren, R., and N. Chriss (2003): Bidding Principles <i>Risk</i> 97-102
 *  </li>
 *  <li>
 *      Almgren, R., C. Thum, E. Hauptmann, and H. Li (2005): Equity Market Impact <i>Risk</i> <b>18 (7)</b>
 *          57-62
 *  </li>
 *  </ul>
 *
 *  <br><br>
 *  <ul>
 *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
 *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/TransactionCostAnalyticsLibrary.md">Transaction Cost Analytics</a></li>
 *      <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/execution/README.md">Optimal Impact/Capture Based Trading Trajectories - Deterministic, Stochastic, Static, and Dynamic</a></li>
 *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/execution/principal/README.md">Information Ratio Based Principal Trades</a></li>
 *  </ul>
 * 
 * @author Lakshmi Krishnamurthy
 */

public class GrossProfitEstimator {
    private org.drip.execution.optimum.EfficientTradingTrajectory _ett = null;

    /**
     * GrossProfitEstimator Constructor
     * 
     * @param ett The efficient Trading Trajectory Instance
     * 
     * @throws java.lang.Exception Thrown if the Inputs are Invalid
     */

    public GrossProfitEstimator (
        final org.drip.execution.optimum.EfficientTradingTrajectory ett)
        throws java.lang.Exception
    {
        if (null == (_ett = ett))
            throw new java.lang.Exception ("GrossProfitEstimator Constructor => Invalid Inputs");
    }

    /**
     * Retrieve the Optimal Efficient Trajectory
     * 
     * @return The Optimal "Efficient" Trajectory
     */

    public org.drip.execution.optimum.EfficientTradingTrajectory efficientTrajectory()
    {
        return _ett;
    }

    /**
     * Generate R^1 Univariate Normal Gross Profit Distribution from the specified Principal Discount
     * 
     * @param dblPrincipalDiscount The Principal Discount
     * 
     * @return The R^1 Univariate Normal Gross Profit Distribution from the specified Principal Discount
     */

    public org.drip.measure.gaussian.R1UnivariateNormal principalMeasure (
        final double dblPrincipalDiscount)
    {
        try {
            return new org.drip.measure.gaussian.R1UnivariateNormal (dblPrincipalDiscount * _ett.tradeSize()
                - _ett.transactionCostExpectation(), java.lang.Math.sqrt (_ett.transactionCostVariance()));
        } catch (java.lang.Exception e) {
            e.printStackTrace();
        }

        return null;
    }

    /**
     * Compute the Break-even Principal Discount
     * 
     * @return The Break-even Principal Discount
     * 
     * @throws java.lang.Exception Thrown if the Inputs are Invalid
     */

    public double breakevenPrincipalDiscount()
        throws java.lang.Exception
    {
        return _ett.transactionCostExpectation() / _ett.tradeSize();
    }

    /**
     * Generate R^1 Univariate Normal Gross Profit Distribution from the specified Principal Discount
     * 
     * @param dblPrincipalDiscount The Principal Discount
     * 
     * @return The R^1 Univariate Normal Gross Profit Distribution from the specified Principal Discount
     */

    public org.drip.measure.gaussian.R1UnivariateNormal horizonPrincipalMeasure (
        final double dblPrincipalDiscount)
    {
        if (!org.drip.numerical.common.NumberUtil.IsValid (dblPrincipalDiscount)) return null;

        double dblInverseHorizon = 1. / _ett.executionTime();

        try {
            return new org.drip.measure.gaussian.R1UnivariateNormal (dblPrincipalDiscount * _ett.tradeSize()
                - _ett.transactionCostExpectation() * dblInverseHorizon, java.lang.Math.sqrt
                    (_ett.transactionCostVariance() * dblInverseHorizon));
        } catch (java.lang.Exception e) {
            e.printStackTrace();
        }

        return null;
    }

    /**
     * Compute the Information Ratio given the Principal Discount
     * 
     * @param dblPrincipalDiscount The Principal Discount
     * 
     * @return The Information Ratio
     * 
     * @throws java.lang.Exception Thrown if the Inputs cannot be calculated
     */

    public double informationRatio (
        final double dblPrincipalDiscount)
        throws java.lang.Exception
    {
        if (!org.drip.numerical.common.NumberUtil.IsValid (dblPrincipalDiscount))
            throw new java.lang.Exception ("GrossProfitEstimator::informationRatio => Invalid Inputs");

        double dblInverseHorizon = 1. / _ett.executionTime();

        return dblInverseHorizon * (dblPrincipalDiscount * _ett.tradeSize() -
            _ett.transactionCostExpectation()) / java.lang.Math.sqrt (dblInverseHorizon *
                _ett.transactionCostVariance());
    }
}