NonDimensionalCostSystemic.java

  1. package org.drip.execution.hjb;

  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>NonDimensionalCostSystemic</i> contains the Level, the Gradient, and the Jacobian of the HJB Non
  82.  * Dimensional Cost Value Function to the Systemic Market State. The References are:
  83.  * 
  84.  * <br><br>
  85.  *  <ul>
  86.  *      <li>
  87.  *          Almgren, R. F., and N. Chriss (2000): Optimal Execution of Portfolio Transactions <i>Journal of
  88.  *              Risk</i> <b>3 (2)</b> 5-39
  89.  *      </li>
  90.  *      <li>
  91.  *          Almgren, R. F. (2009): Optimal Trading in a Dynamic Market
  92.  *              https://www.math.nyu.edu/financial_mathematics/content/02_financial/2009-2.pdf
  93.  *      </li>
  94.  *      <li>
  95.  *          Almgren, R. F. (2012): Optimal Trading with Stochastic Liquidity and Volatility <i>SIAM Journal
  96.  *          of Financial Mathematics</i> <b>3 (1)</b> 163-181
  97.  *      </li>
  98.  *      <li>
  99.  *          Geman, H., D. B. Madan, and M. Yor (2001): Time Changes for Levy Processes <i>Mathematical
  100.  *              Finance</i> <b>11 (1)</b> 79-96
  101.  *      </li>
  102.  *      <li>
  103.  *          Jones, C. M., G. Kaul, and M. L. Lipson (1994): Transactions, Volume, and Volatility <i>Review of
  104.  *              Financial Studies</i> <b>7 (4)</b> 631-651
  105.  *      </li>
  106.  *  </ul>
  107.  *
  108.  *  <br><br>
  109.  *  <ul>
  110.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
  111.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/TransactionCostAnalyticsLibrary.md">Transaction Cost Analytics</a></li>
  112.  *      <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>
  113.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/execution/hjb/README.md">Hamilton Jacobin Bellman Based Optimal Evolution</a></li>
  114.  *  </ul>
  115.  * 
  116.  * @author Lakshmi Krishnamurthy
  117.  */

  119. public class NonDimensionalCostSystemic extends org.drip.execution.hjb.NonDimensionalCost {
  120.     private double _dblGradient = java.lang.Double.NaN;
  121.     private double _dblJacobian = java.lang.Double.NaN;

  123.     /**
  124.      * Generate a Zero Sensitivity Systemic Non Dimensional Cost Instance
  125.      * 
  126.      * @return The Zero Sensitivity Systemic Non Dimensional Cost Instance
  127.      */

  129.     public static final NonDimensionalCostSystemic Zero()
  130.     {
  131.         try {
  132.             return new NonDimensionalCostSystemic (0., 0., 0., 0.);
  133.         } catch (java.lang.Exception e) {
  134.             e.printStackTrace();
  135.         }

  137.         return null;
  138.     }

  140.     /**
  141.      * Generate a Linear Trading Systemic Non Dimensional Cost Instance
  142.      * 
  143.      * @param dblMarketStateExponentiation The Exponentiated Market State
  144.      * @param dblNonDimensionalTime The Non Dimensional Time
  145.      * 
  146.      * @return The Linear Trading Systemic Non Dimensional Cost Instance
  147.      */

  149.     public static final NonDimensionalCostSystemic LinearThreshold (
  150.         final double dblMarketStateExponentiation,
  151.         final double dblNonDimensionalTime)
  152.     {
  153.         if (!org.drip.numerical.common.NumberUtil.IsValid (dblMarketStateExponentiation) ||
  154.             !org.drip.numerical.common.NumberUtil.IsValid (dblNonDimensionalTime) || 0. >= dblNonDimensionalTime)
  155.             return null;

  157.         double dblNonDimensionalUrgency = 1. / dblNonDimensionalTime;
  158.         double dblNonDimensionalCostThreshold = dblMarketStateExponentiation * dblNonDimensionalUrgency;

  160.         try {
  161.             return new NonDimensionalCostSystemic (dblNonDimensionalCostThreshold,
  162.                 dblNonDimensionalCostThreshold, dblNonDimensionalCostThreshold, dblNonDimensionalUrgency);
  163.         } catch (java.lang.Exception e) {
  164.             e.printStackTrace();
  165.         }

  167.         return null;
  168.     }

  170.     /**
  171.      * Generate a Euler Enhanced Linear Trading Systemic Non Dimensional Cost Instance
  172.      * 
  173.      * @param dblMarketState The Market State
  174.      * @param dblNonDimensionalCost The Non Dimensional Cost
  175.      * @param dblNonDimensionalCostCross The Non Dimensional Cost Cross Term
  176.      * 
  177.      * @return The Euler Enhanced Linear Trading Systemic Non Dimensional Cost Instance
  178.      */

  180.     public static final NonDimensionalCostSystemic EulerEnhancedLinearThreshold (
  181.         final double dblMarketState,
  182.         final double dblNonDimensionalCost,
  183.         final double dblNonDimensionalCostCross)
  184.     {
  185.         if (!org.drip.numerical.common.NumberUtil.IsValid (dblMarketState) ||
  186.             !org.drip.numerical.common.NumberUtil.IsValid (dblNonDimensionalCost) ||
  187.                 !org.drip.numerical.common.NumberUtil.IsValid (dblNonDimensionalCostCross))
  188.             return null;

  190.         try {
  191.             return new NonDimensionalCostSystemic (dblNonDimensionalCost, dblNonDimensionalCost +
  192.                 dblNonDimensionalCostCross, dblNonDimensionalCost + 2. * dblNonDimensionalCostCross,
  193.                     java.lang.Math.exp (-dblMarketState) * dblNonDimensionalCost);
  194.         } catch (java.lang.Exception e) {
  195.             e.printStackTrace();
  196.         }

  198.         return null;
  199.     }

  201.     /**
  202.      * NonDimensionalCostSystemic Constructor
  203.      * 
  204.      * @param dblRealization The Non Dimensional Cost Value Function Realization
  205.      * @param dblGradient The Non Dimensional Cost Value Function Gradient to the Systemic Market State
  206.      * @param dblJacobian The Non Dimensional Cost Value Function Jacobian to the Systemic Market State
  207.      * @param dblNonDimensionalTradeRate The Non-dimensional Trade Rate
  208.      * 
  209.      * @throws java.lang.Exception Thrown if the Inputs are Invalid
  210.      */

  212.     public NonDimensionalCostSystemic (
  213.         final double dblRealization,
  214.         final double dblGradient,
  215.         final double dblJacobian,
  216.         final double dblNonDimensionalTradeRate)
  217.         throws java.lang.Exception
  218.     {
  219.         super (dblRealization, dblNonDimensionalTradeRate);

  221.         if (!org.drip.numerical.common.NumberUtil.IsValid (_dblGradient = dblGradient) ||
  222.             !org.drip.numerical.common.NumberUtil.IsValid (_dblJacobian = dblJacobian))
  223.             throw new java.lang.Exception ("NonDimensionalCostSystemic Constructor => Invalid Inputs");
  224.     }

  226.     /**
  227.      * Retrieve the Realized Non Dimensional Cost Value Function Gradient to the Systemic Market State
  228.      * 
  229.      * @return The Realized Non Dimensional Cost Value Function Gradient to the Systemic Market State
  230.      */

  232.     public double gradient()
  233.     {
  234.         return _dblGradient;
  235.     }

  237.     /**
  238.      * Retrieve the Realized Non Dimensional Cost Value Function Jacobian to the Systemic Market State
  239.      * 
  240.      * @return The Realized Non Dimensional Cost Value Function Jacobian to the Systemic Market State
  241.      */

  243.     public double jacobian()
  244.     {
  245.         return _dblJacobian;
  246.     }
  247. }
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