AndersenPykhtinSokolStretch.java
package org.drip.exposure.regression;
/*
* -*- 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
*
* 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>AndersenPykhtinSokolStretch</i> generates the Regression Based Path Exposures off of the Pillar
* Vertexes using the Pykhtin (2009) Scheme. Eventual Unadjusted Variation Margin Calculation follows
* Andersen, Pykhtin, and Sokol (2017). The References are:
*
* <br><br>
* <ul>
* <li>
* Andersen, L. B. G., M. Pykhtin, and A. Sokol (2017): Re-thinking Margin Period of Risk
* https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2902737 <b>eSSRN</b>
* </li>
* <li>
* Andersen, L. B. G., M. Pykhtin, and A. Sokol (2017): Credit Exposure in the Presence of
* Initial Margin https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2806156 <b>eSSRN</b>
* </li>
* <li>
* Albanese, C., and L. Andersen (2014): Accounting for OTC Derivatives: Funding Adjustments and
* the Re-Hypothecation Option https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2482955
* <b>eSSRN</b>
* </li>
* <li>
* Burgard, C., and M. Kjaer (2017): Derivatives Funding, Netting, and Accounting
* https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2534011 <b>eSSRN</b>
* </li>
* <li>
* Piterbarg, V. (2010): Funding Beyond Discounting: Collateral Agreements and Derivatives
* Pricing <i>Risk</i> <b>21 (2)</b> 97-102
* </li>
* </ul>
*
* <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/ExposureAnalyticsLibrary.md">Exposure Analytics</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/exposure/README.md">Exposure Group Level Collateralized/Uncollateralized Exposure</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/exposure/regression/README.md">Regression Based Path Exposure Generation</a></li>
* </ul>
*
* @author Lakshmi Krishnamurthy
*/
public class AndersenPykhtinSokolStretch
{
private int[] _sparseDateArray = null;
private double[] _sparseExposureArray = null;
private org.drip.exposure.mpor.TradePayment[] _denseTradePaymentArray = null;
private org.drip.function.definition.R1ToR1[] _sparseLocalVolatilityArray = null;
/**
* AndersenPykhtinSokolStretch Constructor
*
* @param sparseDateArray Array of Sparse Exposure Dates
* @param sparseExposureArray Array of Sparse Exposures
* @param sparseLocalVolatilityArray Array of Sparse Local Volatility R1 To R1 Functions
* @param denseTradePaymentArray Array of Dense Trade Payments
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public AndersenPykhtinSokolStretch (
final int[] sparseDateArray,
final double[] sparseExposureArray,
final org.drip.function.definition.R1ToR1[] sparseLocalVolatilityArray,
final org.drip.exposure.mpor.TradePayment[] denseTradePaymentArray)
throws java.lang.Exception
{
if (null == (_sparseDateArray = sparseDateArray) ||
null == (_sparseExposureArray = sparseExposureArray) ||
null == (_sparseLocalVolatilityArray = sparseLocalVolatilityArray) ||
null == (_denseTradePaymentArray = denseTradePaymentArray))
{
throw new java.lang.Exception ("AndersenPykhtinSokolStretch Constructor => Invalid Inputs");
}
int sparseExposureDateCount = _sparseDateArray.length;
int denseExposureDateCount = _denseTradePaymentArray.length;
if (0 == sparseExposureDateCount ||
sparseExposureDateCount != _sparseExposureArray.length ||
!org.drip.numerical.common.NumberUtil.IsValid (_sparseExposureArray) ||
sparseExposureDateCount != _sparseLocalVolatilityArray.length ||
sparseExposureDateCount > denseExposureDateCount)
{
throw new java.lang.Exception ("AndersenPykhtinSokolStretch Constructor => Invalid Inputs");
}
for (int sparseExposureDateIndex = 0;
sparseExposureDateIndex < sparseExposureDateCount;
++sparseExposureDateIndex)
{
if (null == _sparseLocalVolatilityArray[sparseExposureDateIndex])
{
throw new java.lang.Exception ("AndersenPykhtinSokolStretch Constructor => Invalid Inputs");
}
}
for (int denseExposureDateIndex = 0;
denseExposureDateIndex < denseExposureDateCount;
++denseExposureDateIndex)
{
if (null == _denseTradePaymentArray[denseExposureDateIndex])
{
throw new java.lang.Exception ("AndersenPykhtinSokolStretch Constructor => Invalid Inputs");
}
}
}
/**
* Retrieve the Sparse Exposure Date Array
*
* @return The Sparse Exposure Date Array
*/
public int[] sparseDateArray()
{
return _sparseDateArray;
}
/**
* Retrieve the Sparse Exposure Array
*
* @return The Sparse Exposure Array
*/
public double[] sparseExposureArray()
{
return _sparseExposureArray;
}
/**
* Retrieve the Sparse Local Volatility R1 To R1 Array
*
* @return The Sparse Local Volatility R1 To R1 Array
*/
public org.drip.function.definition.R1ToR1[] sparseLocalVolatilityArray()
{
return _sparseLocalVolatilityArray;
}
/**
* Retrieve the Dense Trade Payment Array
*
* @return The Dense Trade Payment Array
*/
public org.drip.exposure.mpor.TradePayment[] denseTradePaymentArray()
{
return _denseTradePaymentArray;
}
/**
* Generate the Dense (Complete) Segment Exposures
*
* @param wanderTrajectory The Wander Date Trajectory
*
* @return The Dense (Complete) Segment Exposures
*/
public double[] denseExposure (
final double[] wanderTrajectory)
{
int epochDate = _sparseDateArray[0];
int sparseExposureDateCount = _sparseDateArray.length;
int denseExposureDateCount = _denseTradePaymentArray.length;
double[] denseExposureTrajectory = new double[denseExposureDateCount];
for (int sparseExposureDateIndex = 1;
sparseExposureDateIndex < sparseExposureDateCount;
++sparseExposureDateIndex)
{
try
{
new AndersenPykhtinSokolSegment (
epochDate,
new org.drip.exposure.regression.PillarVertex (
_sparseDateArray[sparseExposureDateIndex - 1],
_sparseExposureArray[sparseExposureDateIndex - 1]
),
new org.drip.exposure.regression.PillarVertex (
_sparseDateArray[sparseExposureDateIndex],
_sparseExposureArray[sparseExposureDateIndex]
),
_sparseLocalVolatilityArray[sparseExposureDateIndex]
).denseExposureTrajectoryUpdate (
denseExposureTrajectory,
wanderTrajectory
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
return null;
}
}
for (int denseExposureDateIndex = 0;
denseExposureDateIndex < denseExposureDateCount;
++denseExposureDateIndex)
{
org.drip.exposure.mpor.TradePayment tradePayment =
_denseTradePaymentArray[denseExposureDateIndex];
denseExposureTrajectory[denseExposureDateIndex] = denseExposureTrajectory[denseExposureDateIndex]
+ tradePayment.dealer() - tradePayment.client();
}
return denseExposureTrajectory;
}
}