DiscreteAlmgrenChriss.java

  1. package org.drip.execution.nonadaptive;

  2. /*
  3.  * -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
  4.  */

  5. /*!
  6.  * Copyright (C) 2020 Lakshmi Krishnamurthy
  7.  * Copyright (C) 2019 Lakshmi Krishnamurthy
  8.  * Copyright (C) 2018 Lakshmi Krishnamurthy
  9.  * Copyright (C) 2017 Lakshmi Krishnamurthy
  10.  * Copyright (C) 2016 Lakshmi Krishnamurthy
  11.  *
  12.  *  This file is part of DROP, an open-source library targeting analytics/risk, transaction cost analytics,
  13.  *      asset liability management analytics, capital, exposure, and margin analytics, valuation adjustment
  14.  *      analytics, and portfolio construction analytics within and across fixed income, credit, commodity,
  15.  *      equity, FX, and structured products. It also includes auxiliary libraries for algorithm support,
  16.  *      numerical analysis, numerical optimization, spline builder, model validation, statistical learning,
  17.  *      and computational support.
  18.  *  
  19.  *      https://lakshmidrip.github.io/DROP/
  20.  *  
  21.  *  DROP is composed of three modules:
  22.  *  
  23.  *  - DROP Product Core - https://lakshmidrip.github.io/DROP-Product-Core/
  24.  *  - DROP Portfolio Core - https://lakshmidrip.github.io/DROP-Portfolio-Core/
  25.  *  - DROP Computational Core - https://lakshmidrip.github.io/DROP-Computational-Core/
  26.  *
  27.  *  DROP Product Core implements libraries for the following:
  28.  *  - Fixed Income Analytics
  29.  *  - Loan Analytics
  30.  *  - Transaction Cost Analytics
  31.  *
  32.  *  DROP Portfolio Core implements libraries for the following:
  33.  *  - Asset Allocation Analytics
  34.  *  - Asset Liability Management Analytics
  35.  *  - Capital Estimation Analytics
  36.  *  - Exposure Analytics
  37.  *  - Margin Analytics
  38.  *  - XVA Analytics
  39.  *
  40.  *  DROP Computational Core implements libraries for the following:
  41.  *  - Algorithm Support
  42.  *  - Computation Support
  43.  *  - Function Analysis
  44.  *  - Model Validation
  45.  *  - Numerical Analysis
  46.  *  - Numerical Optimizer
  47.  *  - Spline Builder
  48.  *  - Statistical Learning
  49.  *
  50.  *  Documentation for DROP is Spread Over:
  51.  *
  52.  *  - Main                     => https://lakshmidrip.github.io/DROP/
  53.  *  - Wiki                     => https://github.com/lakshmiDRIP/DROP/wiki
  54.  *  - GitHub                   => https://github.com/lakshmiDRIP/DROP
  55.  *  - Repo Layout Taxonomy     => https://github.com/lakshmiDRIP/DROP/blob/master/Taxonomy.md
  56.  *  - Javadoc                  => https://lakshmidrip.github.io/DROP/Javadoc/index.html
  57.  *  - Technical Specifications => https://github.com/lakshmiDRIP/DROP/tree/master/Docs/Internal
  58.  *  - Release Versions         => https://lakshmidrip.github.io/DROP/version.html
  59.  *  - Community Credits        => https://lakshmidrip.github.io/DROP/credits.html
  60.  *  - Issues Catalog           => https://github.com/lakshmiDRIP/DROP/issues
  61.  *  - JUnit                    => https://lakshmidrip.github.io/DROP/junit/index.html
  62.  *  - Jacoco                   => https://lakshmidrip.github.io/DROP/jacoco/index.html
  63.  *
  64.  *  Licensed under the Apache License, Version 2.0 (the "License");
  65.  *      you may not use this file except in compliance with the License.
  66.  *  
  67.  *  You may obtain a copy of the License at
  68.  *      http://www.apache.org/licenses/LICENSE-2.0
  69.  *  
  70.  *  Unless required by applicable law or agreed to in writing, software
  71.  *      distributed under the License is distributed on an "AS IS" BASIS,
  72.  *      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  73.  *  
  74.  *  See the License for the specific language governing permissions and
  75.  *      limitations under the License.
  76.  */

  77. /**
  78.  * <i>DiscreteAlmgrenChriss</i> generates the Trade/Holdings List of Optimal Execution Schedule for the
  79.  * Equally Spaced Trading Intervals based on the No-Drift Linear Impact Evolution Walk Parameters specified.
  80.  * The References are:
  81.  *
  82.  * <br><br>
  83.  *  <ul>
  84.  *      <li>
  85.  *          Almgren, R., and N. Chriss (1999): Value under Liquidation <i>Risk</i> <b>12 (12)</b>
  86.  *      </li>
  87.  *      <li>
  88.  *          Almgren, R., and N. Chriss (2000): Optimal Execution of Portfolio Transactions <i>Journal of
  89.  *              Risk</i> <b>3 (2)</b> 5-39
  90.  *      </li>
  91.  *      <li>
  92.  *          Bertsimas, D., and A. W. Lo (1998): Optimal Control of Execution Costs <i>Journal of Financial
  93.  *              Markets</i> <b>1</b> 1-50
  94.  *      </li>
  95.  *      <li>
  96.  *          Chan, L. K. C., and J. Lakonishak (1995): The Behavior of Stock Prices around Institutional
  97.  *              Trades <i>Journal of Finance</i> <b>50</b> 1147-1174
  98.  *      </li>
  99.  *      <li>
  100.  *          Keim, D. B., and A. Madhavan (1997): Transaction Costs and Investment Style: An Inter-exchange
  101.  *              Analysis of Institutional Equity Trades <i>Journal of Financial Economics</i> <b>46</b>
  102.  *              265-292
  103.  *      </li>
  104.  *  </ul>
  105.  *
  106.  *  <br><br>
  107.  *  <ul>
  108.  *      <li><b>Module </b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/ProductCore.md">Product Core Module</a></li>
  109.  *      <li><b>Library</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/TransactionCostAnalyticsLibrary.md">Transaction Cost Analytics</a></li>
  110.  *      <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>
  111.  *      <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/execution/nonadaptive/README.md">Almgren-Chriss Static Optimal Trajectory</a></li>
  112.  *  </ul>
  113.  *
  114.  * @author Lakshmi Krishnamurthy
  115.  */

  116. public class DiscreteAlmgrenChriss extends org.drip.execution.nonadaptive.StaticOptimalSchemeDiscrete {

  117.     private double KappaTau (
  118.         final double dblKappaTildaSquared,
  119.         final double dblTau)
  120.     {
  121.         double dblKappaTildaSquaredTauSquared = dblKappaTildaSquared * dblTau * dblTau;

  122.         return java.lang.Math.log (0.5 * (2. + dblKappaTildaSquaredTauSquared + dblTau * java.lang.Math.sqrt
  123.             (dblKappaTildaSquared * (dblKappaTildaSquaredTauSquared + 4.))));
  124.     }

  125.     /**
  126.      * Create the Standard DiscreteAlmgrenChriss Instance
  127.      *
  128.      * @param dblStartHoldings Trajectory Start Holdings
  129.      * @param dblFinishTime Trajectory Finish Time
  130.      * @param iNumInterval The Number of Fixed Intervals
  131.      * @param lpep Linear Impact Price Walk Parameters
  132.      * @param dblRiskAversion The Risk Aversion Parameter
  133.      *
  134.      * @return The DiscreteAlmgrenChriss Instance
  135.      */

  136.     public static final DiscreteAlmgrenChriss Standard (
  137.         final double dblStartHoldings,
  138.         final double dblFinishTime,
  139.         final int iNumInterval,
  140.         final org.drip.execution.dynamics.LinearPermanentExpectationParameters lpep,
  141.         final double dblRiskAversion)
  142.     {
  143.         try {
  144.             return new DiscreteAlmgrenChriss
  145.                 (org.drip.execution.strategy.DiscreteTradingTrajectoryControl.FixedInterval (new
  146.                     org.drip.execution.strategy.OrderSpecification (dblStartHoldings, dblFinishTime),
  147.                         iNumInterval), lpep, new org.drip.execution.risk.MeanVarianceObjectiveUtility
  148.                             (dblRiskAversion));
  149.         } catch (java.lang.Exception e) {
  150.             e.printStackTrace();
  151.         }

  152.         return null;
  153.     }

  154.     private DiscreteAlmgrenChriss (
  155.         final org.drip.execution.strategy.DiscreteTradingTrajectoryControl dttc,
  156.         final org.drip.execution.dynamics.LinearPermanentExpectationParameters lpep,
  157.         final org.drip.execution.risk.MeanVarianceObjectiveUtility mvou)
  158.         throws java.lang.Exception
  159.     {
  160.         super (dttc, lpep, mvou);
  161.     }

  162.     @Override public org.drip.execution.optimum.EfficientTradingTrajectoryDiscrete generate()
  163.     {
  164.         org.drip.execution.strategy.DiscreteTradingTrajectoryControl dttc = control();

  165.         double[] adblTNode = dttc.executionTimeNodes();

  166.         org.drip.execution.dynamics.LinearPermanentExpectationParameters lpep =
  167.             (org.drip.execution.dynamics.LinearPermanentExpectationParameters) priceEvolutionParameters();

  168.         org.drip.execution.impact.TransactionFunction tfTemporaryExpectation =
  169.             lpep.temporaryExpectation().epochImpactFunction();

  170.         if (!(tfTemporaryExpectation instanceof org.drip.execution.impact.TransactionFunctionLinear))
  171.             return null;

  172.         double dblEpochVolatility = java.lang.Double.NaN;
  173.         org.drip.execution.impact.TransactionFunctionLinear tflTemporaryExpectation =
  174.             (org.drip.execution.impact.TransactionFunctionLinear) tfTemporaryExpectation;

  175.         try {
  176.             dblEpochVolatility = lpep.arithmeticPriceDynamicsSettings().epochVolatility();
  177.         } catch (java.lang.Exception e) {
  178.             e.printStackTrace();

  179.             return null;
  180.         }

  181.         double dblGamma = lpep.linearPermanentExpectation().epochLiquidityFunction().slope();

  182.         double dblEta = tflTemporaryExpectation.slope();

  183.         double dblX = dttc.startHoldings();

  184.         int iNumNode = adblTNode.length;
  185.         double dblXSquared = dblX * dblX;
  186.         final double dblSigma = dblEpochVolatility;
  187.         double dblTau = adblTNode[1] - adblTNode[0];
  188.         double dblSigmaSquared = dblSigma * dblSigma;
  189.         double[] adblHoldings = new double[iNumNode];
  190.         double[] adblTradeList = new double[iNumNode - 1];
  191.         double dblT = adblTNode[iNumNode - 1] - adblTNode[0];
  192.         double dblEtaTilda = dblEta - 0.5 * dblGamma * dblTau;

  193.         double dblKappaTildaSquared = ((org.drip.execution.risk.MeanVarianceObjectiveUtility)
  194.             objectiveUtility()).riskAversion() * dblSigmaSquared / dblEtaTilda;

  195.         double dblKappaTau = KappaTau (dblKappaTildaSquared, dblTau);

  196.         double dblHalfKappaTau = 0.5 * dblKappaTau;
  197.         double dblKappa = dblKappaTau / dblTau;
  198.         double dblKappaT = dblKappa * dblT;

  199.         double dblSinhKappaT = java.lang.Math.sinh (dblKappaT);

  200.         double dblSinhKappaTau = java.lang.Math.sinh (dblKappaTau);

  201.         double dblSinhHalfKappaTau = java.lang.Math.sinh (dblHalfKappaTau);

  202.         double dblTSinhKappaTau = dblT * dblSinhKappaTau;
  203.         double dblInverseSinhKappaT = 1. / dblSinhKappaT;
  204.         double dblTrajectoryScaler = dblInverseSinhKappaT * dblX;
  205.         double dblTradeListScaler = 2. * dblSinhHalfKappaTau * dblTrajectoryScaler;
  206.         double dblReciprocalSinhKappaTSquared = dblInverseSinhKappaT * dblInverseSinhKappaT;

  207.         for (int i = 0; i < iNumNode; ++i) {
  208.             adblHoldings[i] = dblTrajectoryScaler * java.lang.Math.sinh (dblKappa * (dblT - adblTNode[i]));

  209.             if (i < iNumNode - 1)
  210.                 adblTradeList[i] = -1. * dblTradeListScaler * java.lang.Math.cosh (dblKappa * (dblT - dblTau
  211.                     * (0.5 + i)));
  212.         }

  213.         try {
  214.             return new org.drip.execution.optimum.AlmgrenChrissDiscrete (adblTNode, adblHoldings,
  215.                 adblTradeList, java.lang.Math.sqrt (dblKappaTildaSquared), dblKappa, 0.5 * dblGamma *
  216.                     dblXSquared + tflTemporaryExpectation.offset() * dblX + dblEtaTilda * dblXSquared *
  217.                         dblReciprocalSinhKappaTSquared * java.lang.Math.tanh (dblHalfKappaTau) * (dblTau *
  218.                             java.lang.Math.sinh (2. * dblKappaT) + 2. * dblTSinhKappaTau) / (2. * dblTau *
  219.                                 dblTau), 0.5 * dblSigmaSquared * dblXSquared * dblReciprocalSinhKappaTSquared
  220.                                     * (dblTau * dblSinhKappaT * java.lang.Math.cosh (dblKappa * (dblT -
  221.                                         dblTau)) - dblTSinhKappaTau) / dblSinhKappaTau, dblEpochVolatility *
  222.                                             dblX / (dblT * dblEpochVolatility * java.lang.Math.sqrt (dblT)));
  223.         } catch (java.lang.Exception e) {
  224.             e.printStackTrace();
  225.         }

  226.         return null;
  227.     }
  228. }