TrajectoryShortfallRealization.java
package org.drip.execution.capture;
/*
* -*- 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>TrajectoryShortfallRealization</i> holds Execution Cost Realization across each Interval in the Trade
* during a Single Simulation Run. 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>
* Bertsimas, D., and A. W. Lo (1998): Optimal Control of Execution Costs <i>Journal of Financial
* Markets</i> <b>1</b> 1-50
* </li>
* <li>
* Chan, L. K. C., and J. Lakonishak (1995): The Behavior of Stock Prices around Institutional
* Trades <i>Journal of Finance</i> <b>50</b> 1147-1174
* </li>
* <li>
* Keim, D. B., and A. Madhavan (1997): Transaction Costs and Investment Style: An Inter-exchange
* Analysis of Institutional Equity Trades <i>Journal of Financial Economics</i> <b>46</b>
* 265-292
* </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/capture/README.md">Execution Trajectory Transaction Cost Capture</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class TrajectoryShortfallRealization {
private java.util.List<org.drip.execution.discrete.ShortfallIncrement> _lsSI = null;
/**
* TrajectoryShortfallRealization Constructor
*
* @param lsSI List of the Composite Slice Short-fall Increments
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public TrajectoryShortfallRealization (
final java.util.List<org.drip.execution.discrete.ShortfallIncrement> lsSI)
throws java.lang.Exception
{
if (null == (_lsSI = lsSI))
throw new java.lang.Exception ("TrajectoryShortfallRealization Constructor => Invalid Inputs");
int iNumSlice = _lsSI.size();
if (0 == iNumSlice)
throw new java.lang.Exception ("TrajectoryShortfallRealization Constructor => Invalid Inputs");
for (org.drip.execution.discrete.ShortfallIncrement si : _lsSI) {
if (null == si)
throw new java.lang.Exception
("TrajectoryShortfallRealization Constructor => Invalid Inputs");
}
}
/**
* Retrieve the List of the Realized Composite Cost Increments
*
* @return The List of the Realized Composite Cost Increments
*/
public java.util.List<org.drip.execution.discrete.ShortfallIncrement> list()
{
return _lsSI;
}
/**
* Generate the Array of Incremental Market Dynamic Cost Drift
*
* @return The Array of Incremental Market Dynamic Cost Drift
*/
public double[] incrementalMarketDynamicDrift()
{
int iNumInterval = _lsSI.size();
double[] adblIncrementalMarketDynamicDrift = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblIncrementalMarketDynamicDrift[i] = _lsSI.get (i).marketDynamicDrift();
return adblIncrementalMarketDynamicDrift;
}
/**
* Generate the Array of Cumulative Market Dynamic Cost Drift
*
* @return The Array of Cumulative Market Dynamic Cost Drift
*/
public double[] cumulativeMarketDynamicDrift()
{
int iNumInterval = _lsSI.size();
double[] adblCumulativeMarketDynamicDrift = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblCumulativeMarketDynamicDrift[i] = 0 == i ? _lsSI.get (i).marketDynamicDrift() : _lsSI.get
(i).marketDynamicDrift() + adblCumulativeMarketDynamicDrift[i - 1];
return adblCumulativeMarketDynamicDrift;
}
/**
* Generate the Total Market Dynamic Cost Drift
*
* @return The Total Market Dynamic Cost Drift
*/
public double totalMarketDynamicDrift()
{
int iNumInterval = _lsSI.size();
double dblTotalMarketDynamicDrift = 0.;
for (int i = 0; i < iNumInterval; ++i)
dblTotalMarketDynamicDrift = dblTotalMarketDynamicDrift + _lsSI.get (i).marketDynamicDrift();
return dblTotalMarketDynamicDrift;
}
/**
* Generate the Array of Incremental Market Dynamic Cost Wander
*
* @return The Array of Incremental Market Dynamic Cost Wander
*/
public double[] incrementalMarketDynamicWander()
{
int iNumInterval = _lsSI.size();
double[] adblIncrementalMarketDynamicWander = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblIncrementalMarketDynamicWander[i] = _lsSI.get (i).marketDynamicWander();
return adblIncrementalMarketDynamicWander;
}
/**
* Generate the Array of Cumulative Market Dynamic Cost Wander
*
* @return The Array of Cumulative Market Dynamic Cost Wander
*/
public double[] cumulativeMarketDynamicWander()
{
int iNumInterval = _lsSI.size();
double[] adblCumulativeMarketDynamicWander = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblCumulativeMarketDynamicWander[i] = 0 == i ? _lsSI.get (i).marketDynamicWander() : _lsSI.get
(i).marketDynamicWander() + adblCumulativeMarketDynamicWander[i - 1];
return adblCumulativeMarketDynamicWander;
}
/**
* Generate the Total Market Dynamic Cost Wander
*
* @return The Total Market Dynamic Cost Wander
*/
public double totalMarketDynamicWander()
{
int iNumInterval = _lsSI.size();
double dblTotalMarketDynamicWander = 0.;
for (int i = 0; i < iNumInterval; ++i)
dblTotalMarketDynamicWander = dblTotalMarketDynamicWander + _lsSI.get (i).marketDynamicWander();
return dblTotalMarketDynamicWander;
}
/**
* Generate the Array of Incremental Permanent Cost Drift
*
* @return The Array of Incremental Permanent Cost Drift
*/
public double[] incrementalPermanentDrift()
{
int iNumInterval = _lsSI.size();
double[] adblIncrementalPermanentDrift = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblIncrementalPermanentDrift[i] = _lsSI.get (i).permanentImpactDrift();
return adblIncrementalPermanentDrift;
}
/**
* Generate the Array of Cumulative Permanent Cost Drift
*
* @return The Array of Cumulative Permanent Cost Drift
*/
public double[] cumulativePermanentDrift()
{
int iNumInterval = _lsSI.size();
double[] adblCumulativePermanentDrift = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblCumulativePermanentDrift[i] = 0 == i ? _lsSI.get (i).permanentImpactDrift() : _lsSI.get
(i).permanentImpactDrift() + adblCumulativePermanentDrift[i - 1];
return adblCumulativePermanentDrift;
}
/**
* Generate the Total Permanent Cost Drift
*
* @return The Total Permanent Cost Drift
*/
public double totalPermanentDrift()
{
int iNumInterval = _lsSI.size();
double dblTotalPermanentDrift = 0.;
for (int i = 0; i < iNumInterval; ++i)
dblTotalPermanentDrift = dblTotalPermanentDrift + _lsSI.get (i).permanentImpactDrift();
return dblTotalPermanentDrift;
}
/**
* Generate the Array of Incremental Permanent Cost Wander
*
* @return The Array of Incremental Permanent Cost Wander
*/
public double[] incrementalPermanentWander()
{
int iNumInterval = _lsSI.size();
double[] adblIncrementalPermanentWander = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblIncrementalPermanentWander[i] = _lsSI.get (i).permanentImpactWander();
return adblIncrementalPermanentWander;
}
/**
* Generate the Array of Cumulative Permanent Cost Wander
*
* @return The Array of Cumulative Permanent Cost Wander
*/
public double[] cumulativePermanentWander()
{
int iNumInterval = _lsSI.size();
double[] adblCumulativePermanentWander = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblCumulativePermanentWander[i] = 0 == i ? _lsSI.get (i).permanentImpactWander() : _lsSI.get
(i).permanentImpactWander() + adblCumulativePermanentWander[i - 1];
return adblCumulativePermanentWander;
}
/**
* Generate the Total Permanent Cost Wander
*
* @return The Total Permanent Cost Wander
*/
public double totalPermanentWander()
{
int iNumInterval = _lsSI.size();
double dblTotalPermanentWander = 0.;
for (int i = 0; i < iNumInterval; ++i)
dblTotalPermanentWander = dblTotalPermanentWander + _lsSI.get (i).permanentImpactWander();
return dblTotalPermanentWander;
}
/**
* Generate the Array of Incremental Temporary Cost Drift
*
* @return The Array of Incremental Temporary Cost Drift
*/
public double[] incrementalTemporaryDrift()
{
int iNumInterval = _lsSI.size();
double[] adblIncrementalTemporaryDrift = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblIncrementalTemporaryDrift[i] = _lsSI.get (i).temporaryImpactDrift();
return adblIncrementalTemporaryDrift;
}
/**
* Generate the Array of Cumulative Temporary Cost Drift
*
* @return The Array of Cumulative Temporary Cost Drift
*/
public double[] cumulativeTemporaryDrift()
{
int iNumInterval = _lsSI.size();
double[] adblCumulativeTemporaryDrift = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblCumulativeTemporaryDrift[i] = 0 == i ? _lsSI.get (i).temporaryImpactDrift() : _lsSI.get
(i).temporaryImpactDrift() + adblCumulativeTemporaryDrift[i - 1];
return adblCumulativeTemporaryDrift;
}
/**
* Generate the Total Temporary Cost Drift
*
* @return The Total Temporary Cost Drift
*/
public double totalTemporaryDrift()
{
int iNumInterval = _lsSI.size();
double dblTotalTemporaryDrift = 0.;
for (int i = 0; i < iNumInterval; ++i)
dblTotalTemporaryDrift = dblTotalTemporaryDrift + _lsSI.get (i).temporaryImpactDrift();
return dblTotalTemporaryDrift;
}
/**
* Generate the Array of Incremental Temporary Cost Wander
*
* @return The Array of Incremental Temporary Cost Wander
*/
public double[] incrementalTemporaryWander()
{
int iNumInterval = _lsSI.size();
double[] adblIncrementalTemporaryWander = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblIncrementalTemporaryWander[i] = _lsSI.get (i).temporaryImpactWander();
return adblIncrementalTemporaryWander;
}
/**
* Generate the Array of Cumulative Temporary Cost Wander
*
* @return The Array of Cumulative Temporary Cost Wander
*/
public double[] cumulativeTemporaryWander()
{
int iNumInterval = _lsSI.size();
double[] adblCumulativeTemporaryWander = new double[iNumInterval];
for (int i = 0; i < iNumInterval; ++i)
adblCumulativeTemporaryWander[i] = 0 == i ? _lsSI.get (i).temporaryImpactWander() : _lsSI.get
(i).temporaryImpactWander() + adblCumulativeTemporaryWander[i - 1];
return adblCumulativeTemporaryWander;
}
/**
* Generate the Total Temporary Cost Wander
*
* @return The Total Temporary Cost Wander
*/
public double totalTemporaryWander()
{
int iNumInterval = _lsSI.size();
double dblTotalTemporaryWander = 0.;
for (int i = 0; i < iNumInterval; ++i)
dblTotalTemporaryWander = dblTotalTemporaryWander + _lsSI.get (i).temporaryImpactWander();
return dblTotalTemporaryWander;
}
}