IRFoundationMarginComparison.java
package org.drip.sample.simmcurvature;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import org.drip.numerical.common.FormatUtil;
import org.drip.service.env.EnvManager;
import org.drip.simm.foundation.MarginEstimationSettings;
import org.drip.simm.margin.RiskClassAggregateIR;
import org.drip.simm.margin.RiskMeasureAggregateIR;
import org.drip.simm.parameters.RiskClassSensitivitySettingsIR;
import org.drip.simm.product.BucketSensitivityIR;
import org.drip.simm.product.RiskClassSensitivityIR;
import org.drip.simm.product.RiskFactorTenorSensitivity;
import org.drip.simm.product.RiskMeasureSensitivityIR;
/*
* -*- mode: java; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*-
*/
/*!
* Copyright (C) 2018 Lakshmi Krishnamurthy
*
* This file is part of DRIP, a free-software/open-source library for buy/side financial/trading model
* libraries targeting analysts and developers
* https://lakshmidrip.github.io/DRIP/
*
* DRIP is composed of four main libraries:
*
* - DRIP Fixed Income - https://lakshmidrip.github.io/DRIP-Fixed-Income/
* - DRIP Asset Allocation - https://lakshmidrip.github.io/DRIP-Asset-Allocation/
* - DRIP Numerical Optimizer - https://lakshmidrip.github.io/DRIP-Numerical-Optimizer/
* - DRIP Statistical Learning - https://lakshmidrip.github.io/DRIP-Statistical-Learning/
*
* - DRIP Fixed Income: Library for Instrument/Trading Conventions, Treasury Futures/Options,
* Funding/Forward/Overnight Curves, Multi-Curve Construction/Valuation, Collateral Valuation and XVA
* Metric Generation, Calibration and Hedge Attributions, Statistical Curve Construction, Bond RV
* Metrics, Stochastic Evolution and Option Pricing, Interest Rate Dynamics and Option Pricing, LMM
* Extensions/Calibrations/Greeks, Algorithmic Differentiation, and Asset Backed Models and Analytics.
*
* - DRIP Asset Allocation: Library for model libraries for MPT framework, Black Litterman Strategy
* Incorporator, Holdings Constraint, and Transaction Costs.
*
* - DRIP Numerical Optimizer: Library for Numerical Optimization and Spline Functionality.
*
* - DRIP Statistical Learning: Library for Statistical Evaluation and Machine Learning.
*
* 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.
*/
/**
* IRFoundationMarginComparison illustrates the Comparison of the IR Margin Estimates using different Schemes
* for Calculating the Position-Bucket Curvature Margin. The References are:
*
* - 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, eSSRN.
*
* - Albanese, C., S. Caenazzo, and O. Frankel (2017): Regression Sensitivities for Initial Margin
* Calculations, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2763488, eSSRN.
*
* - 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, eSSRN.
*
* - 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, eSSRN.
*
* - International Swaps and Derivatives Association (2017): SIMM v2.0 Methodology,
* https://www.isda.org/a/oFiDE/isda-simm-v2.pdf.
*
* @author Lakshmi Krishnamurthy
*/
public class IRFoundationMarginComparison
{
private static final RiskFactorTenorSensitivity CurveTenorSensitivityMap (
final double notional)
throws Exception
{
Map<String, Double> tenorSensitivityMap = new HashMap<String, Double>();
tenorSensitivityMap.put (
"2W",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"1M",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"3M",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"6M",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"1Y",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"2Y",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"3Y",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"5Y",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"10Y",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"15Y",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"20Y",
notional * (Math.random() - 0.5)
);
tenorSensitivityMap.put (
"30Y",
notional * (Math.random() - 0.5)
);
return new RiskFactorTenorSensitivity (tenorSensitivityMap);
}
private static final BucketSensitivityIR CurrencyBucketSensitivity (
final String currency,
final double notional)
throws Exception
{
return new BucketSensitivityIR (
CurveTenorSensitivityMap (notional),
CurveTenorSensitivityMap (notional),
CurveTenorSensitivityMap (notional),
CurveTenorSensitivityMap (notional),
CurveTenorSensitivityMap (notional),
CurveTenorSensitivityMap (notional),
CurveTenorSensitivityMap (notional)
);
}
private static final void ISDABucketCovarianceMargin (
final String positionBucketCovarianceScheme,
final Map<String, BucketSensitivityIR> bucketDeltaSensitivityMap,
final Map<String, BucketSensitivityIR> bucketVegaSensitivityMap,
final RiskClassSensitivitySettingsIR riskClassSensitivitySettings,
final MarginEstimationSettings marginEstimationSettings)
throws Exception
{
RiskClassAggregateIR riskClassAggregate = new RiskClassSensitivityIR (
new RiskMeasureSensitivityIR (bucketDeltaSensitivityMap),
new RiskMeasureSensitivityIR (bucketVegaSensitivityMap),
new RiskMeasureSensitivityIR (bucketVegaSensitivityMap)
).aggregate (
riskClassSensitivitySettings,
marginEstimationSettings
);
RiskMeasureAggregateIR deltaRiskMeasureAggregate = riskClassAggregate.deltaMargin();
RiskMeasureAggregateIR vegaRiskMeasureAggregate = riskClassAggregate.vegaMargin();
RiskMeasureAggregateIR curvatureRiskMeasureAggregate = riskClassAggregate.curvatureMargin();
System.out.println ("\t|----------------------------------------||");
System.out.println ("\t| " + positionBucketCovarianceScheme + " SBA MARGIN ||");
System.out.println ("\t|----------------------------------------||");
System.out.println ("\t| MEASURE => CORE | RESIDUAL | TOTAL ||");
System.out.println ("\t|----------------------------------------||");
System.out.println ("\t| DELTA => " +
FormatUtil.FormatDouble (Math.sqrt (deltaRiskMeasureAggregate.coreSBAVariance()), 5, 0, 1.) +
" | " +
FormatUtil.FormatDouble (Math.sqrt (deltaRiskMeasureAggregate.residualSBAVariance()), 5, 0, 1.) +
" |" +
FormatUtil.FormatDouble (deltaRiskMeasureAggregate.sba(), 5, 0, 1.) + " ||"
);
System.out.println ("\t| VEGA => " +
FormatUtil.FormatDouble (Math.sqrt (vegaRiskMeasureAggregate.coreSBAVariance()), 5, 0, 1.) +
" | " +
FormatUtil.FormatDouble (Math.sqrt (vegaRiskMeasureAggregate.residualSBAVariance()), 5, 0, 1.) +
" |" +
FormatUtil.FormatDouble (vegaRiskMeasureAggregate.sba(), 5, 0, 1.) + " ||"
);
System.out.println ("\t| CURVATURE => " +
FormatUtil.FormatDouble (Math.sqrt (curvatureRiskMeasureAggregate.coreSBAVariance()), 5, 0, 1.) +
" | " +
FormatUtil.FormatDouble (Math.sqrt (curvatureRiskMeasureAggregate.residualSBAVariance()), 5, 0, 1.) +
" |" +
FormatUtil.FormatDouble (curvatureRiskMeasureAggregate.sba(), 5, 0, 1.) + " ||"
);
System.out.println ("\t|----------------------------------------||");
System.out.println();
}
public static final void main (
final String[] inputs)
throws Exception
{
EnvManager.InitEnv ("");
String[] currencyArray = {
"USD",
"EUR",
"CNY",
"INR",
"JPY"
};
double[] notionalArray = {
100.,
108.,
119.,
49.,
28.
};
Map<String, BucketSensitivityIR> bucketDeltaSensitivityMap = new HashMap<String, BucketSensitivityIR>();
Map<String, BucketSensitivityIR> bucketVegaSensitivityMap = new HashMap<String, BucketSensitivityIR>();
for (int currencyIndex = 0; currencyIndex < currencyArray.length; ++currencyIndex)
{
bucketDeltaSensitivityMap.put (
currencyArray[currencyIndex],
CurrencyBucketSensitivity (
currencyArray[currencyIndex],
notionalArray[currencyIndex]
)
);
bucketVegaSensitivityMap.put (
currencyArray[currencyIndex],
CurrencyBucketSensitivity (
currencyArray[currencyIndex],
notionalArray[currencyIndex]
)
);
}
List<String> currencyList = new ArrayList<String>();
for (String currency : currencyArray)
{
currencyList.add (currency);
}
RiskClassSensitivitySettingsIR riskClassSensitivitySettings =
RiskClassSensitivitySettingsIR.ISDA_20 (currencyList);
ISDABucketCovarianceMargin (
" FRTB",
bucketDeltaSensitivityMap,
bucketVegaSensitivityMap,
riskClassSensitivitySettings,
MarginEstimationSettings.FRTB
(MarginEstimationSettings.POSITION_PRINCIPAL_COMPONENT_COVARIANCE_ESTIMATOR_ISDA)
);
ISDABucketCovarianceMargin (
" ISDA DELTA",
bucketDeltaSensitivityMap,
bucketVegaSensitivityMap,
riskClassSensitivitySettings,
MarginEstimationSettings.ISDADelta
(MarginEstimationSettings.POSITION_PRINCIPAL_COMPONENT_COVARIANCE_ESTIMATOR_ISDA)
);
ISDABucketCovarianceMargin (
"CORNISH FISCHER",
bucketDeltaSensitivityMap,
bucketVegaSensitivityMap,
riskClassSensitivitySettings,
MarginEstimationSettings.CornishFischer
(MarginEstimationSettings.POSITION_PRINCIPAL_COMPONENT_COVARIANCE_ESTIMATOR_FRTB)
);
EnvManager.TerminateEnv();
}
}