RiskClassSensitivityIR.java
package org.drip.simm.product;
/*
* -*- 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>RiskClassSensitivityIR</i> holds the Risk Class Bucket Sensitivities for a single IR Class. The
* References are:
*
* <br><br>
* <ul>
* <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., S. Caenazzo, and O. Frankel (2017): Regression Sensitivities for Initial Margin
* Calculations https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2763488 <b>eSSRN</b>
* </li>
* <li>
* Anfuso, F., D. Aziz, P. Giltinan, and K. Loukopoulus (2017): A Sound Modeling and Back-testing
* Framework for Forecasting Initial Margin Requirements
* https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2716279 <b>eSSRN</b>
* </li>
* <li>
* Caspers, P., P. Giltinan, R. Lichters, and N. Nowaczyk (2017): Forecasting Initial Margin
* Requirements - A Model Evaluation https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2911167
* <b>eSSRN</b>
* </li>
* <li>
* International Swaps and Derivatives Association (2017): SIMM v2.0 Methodology
* https://www.isda.org/a/oFiDE/isda-simm-v2.pdf
* </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/MarginAnalyticsLibrary.md">Initial and Variation Margin Analytics</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/simm/README.md">Initial Margin Analytics based on ISDA SIMM and its Variants</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/simm/product/README.md">ISDA SIMM Risk Factor Sensitivities</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class RiskClassSensitivityIR
{
private org.drip.simm.product.RiskMeasureSensitivityIR _vega = null;
private org.drip.simm.product.RiskMeasureSensitivityIR _delta = null;
private org.drip.simm.product.RiskMeasureSensitivityIR _curvature = null;
/**
* RiskClassSensitivityIR Constructor
*
* @param delta The IR Delta Tenor Sensitivity
* @param vega The IR Vega Tenor Sensitivity
* @param curvature The IR Curvature Tenor Sensitivity
*
* @throws java.lang.Exception Thrown if the Inputs are Invalid
*/
public RiskClassSensitivityIR (
final org.drip.simm.product.RiskMeasureSensitivityIR delta,
final org.drip.simm.product.RiskMeasureSensitivityIR vega,
final org.drip.simm.product.RiskMeasureSensitivityIR curvature)
throws java.lang.Exception
{
if (null == (_delta = delta) ||
null == (_vega = vega) ||
null == (_curvature = curvature))
{
throw new java.lang.Exception ("RiskClassSensitivityIR Constructor => Invalid Inputs");
}
}
/**
* Retrieve the IR Delta Tenor Sensitivity
*
* @return The IR Delta Tenor Sensitivity
*/
public org.drip.simm.product.RiskMeasureSensitivityIR delta()
{
return _delta;
}
/**
* Retrieve the IR Vega Tenor Sensitivity
*
* @return The IR Vega Tenor Sensitivity
*/
public org.drip.simm.product.RiskMeasureSensitivityIR vega()
{
return _vega;
}
/**
* Retrieve the IR Curvature Tenor Sensitivity
*
* @return The IR Curvature Tenor Sensitivity
*/
public org.drip.simm.product.RiskMeasureSensitivityIR curvature()
{
return _curvature;
}
/**
* Compute the Risk Class Sensitivity Aggregate
*
* @param riskClassSensitivitySettingsIR The IR Risk Class Sensitivity Settings
* @param marginEstimationSettings Margin Estimation Settings
*
* @return The Risk Class Sensitivity Aggregate
*/
public org.drip.simm.margin.RiskClassAggregateIR aggregate (
final org.drip.simm.parameters.RiskClassSensitivitySettingsIR riskClassSensitivitySettingsIR,
final org.drip.simm.foundation.MarginEstimationSettings marginEstimationSettings)
{
if (null == riskClassSensitivitySettingsIR)
{
return null;
}
try
{
return new org.drip.simm.margin.RiskClassAggregateIR (
_delta.linearAggregate (
riskClassSensitivitySettingsIR.delta(),
marginEstimationSettings
),
_vega.linearAggregate (
riskClassSensitivitySettingsIR.vega(),
marginEstimationSettings
),
_curvature.curvatureAggregate (
riskClassSensitivitySettingsIR.curvature(),
marginEstimationSettings
)
);
}
catch (java.lang.Exception e)
{
e.printStackTrace();
}
return null;
}
}