EquityVegaMargin20.java

package org.drip.sample.simmeq;

import java.util.Map;
import java.util.TreeMap;

import org.drip.analytics.support.CaseInsensitiveHashMap;
import org.drip.numerical.common.FormatUtil;
import org.drip.service.env.EnvManager;
import org.drip.simm.foundation.MarginEstimationSettings;
import org.drip.simm.margin.BucketAggregate;
import org.drip.simm.margin.RiskMeasureAggregate;
import org.drip.simm.parameters.RiskMeasureSensitivitySettings;
import org.drip.simm.product.BucketSensitivity;
import org.drip.simm.product.RiskMeasureSensitivity;

/*
 * -*- 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.
 */

/**
 * EquityVegaMargin20 illustrates the Computation of the SIMM 2.0 Vega Margin across a Group of Equity Bucket
 *  Exposure Sensitivities. 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 EquityVegaMargin20
{

	private static final void AddBucketRiskFactorSensitivity (
		final Map<String, Map<String, Double>> bucketRiskFactorSensitivityMap,
		final int bucketIndex,
		final double notional,
		final String[] equityArray)
	{
		Map<String, Double> riskFactorSensitivityMap = new CaseInsensitiveHashMap<Double>();

		for (String equity : equityArray)
		{
			riskFactorSensitivityMap.put (
				equity,
				notional * (Math.random() - 0.5)
			);
		}

		bucketRiskFactorSensitivityMap.put (
			"" + bucketIndex,
			riskFactorSensitivityMap
		);
	}

	private static final Map<String, Map<String, Double>> BucketRiskFactorSensitivityMap (
		final double notional)
		throws Exception
	{
		Map<String, Map<String, Double>> bucketRiskFactorSensitivityMap =
			new TreeMap<String, Map<String, Double>>();

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			-1,
			notional,
			new String[]
			{
				"BOEING  ",
				"LOCKHEED",
				"RAND    ",
				"RAYTHEON",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			1,
			notional,
			new String[]
			{
				"ADP     ",
				"PSEANDG ",
				"STAPLES ",
				"U-HAUL  ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			2,
			notional,
			new String[]
			{
				"CISCO   ",
				"DEERE   ",
				"HALIBTN ",
				"VERIZON ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			3,
			notional,
			new String[]
			{
				"DUKE    ",
				"MONSANTO",
				"MMM     ",
				"VEDANTA ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			4,
			notional,
			new String[]
			{
				"AMAZON  ",
				"GOLDMAN ",
				"MORGAN  ",
				"REMAX   ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			5,
			notional,
			new String[]
			{
				"ALDI    ",
				"INFOSYS ",
				"OLLA    ",
				"RELIANCE",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			6,
			notional,
			new String[]
			{
				"GCC     ",
				"NOKIA   ",
				"SIEMENS ",
				"VODAFONE",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			7,
			notional,
			new String[]
			{
				"ADIDAS  ",
				"BAYER   ",
				"BILLERTN",
				"DE BEER ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			8,
			notional,
			new String[]
			{
				"NOKIA   ",
				"NOMURA  ",
				"QATARSOV",
				"SOTHEBY ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			9,
			notional,
			new String[]
			{
				"AUTODESK",
				"CALYPSO ",
				"NUMERIX ",
				"WEBLOGIC",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			10,
			notional,
			new String[]
			{
				"COGNIZAN",
				"TATAMOTO",
				"TOBLERON",
				"TVS     ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			11,
			notional,
			new String[]
			{
				"DJIA    ",
				"LEHMAN  ",
				"RUSSELL ",
				"SANDP   ",
			}
		);

		AddBucketRiskFactorSensitivity (
			bucketRiskFactorSensitivityMap,
			12,
			notional,
			new String[]
			{
				"CBOE    ",
				"CITI    ",
				"RUSSELL ",
				"VIX     ",
			}
		);

		return bucketRiskFactorSensitivityMap;
	}

	private static final void DisplayBucketRiskFactorSensitivity (
		final Map<String, Map<String, Double>> bucketRiskFactorSensitivityMap)
		throws Exception
	{
		System.out.println ("\t|--------------------------||");

		System.out.println ("\t|     RISK FACTOR VEGA     ||");

		System.out.println ("\t|--------------------------||");

		System.out.println ("\t|  L -> R:                 ||");

		System.out.println ("\t|    - Ticker              ||");

		System.out.println ("\t|    - Bucket              ||");

		System.out.println ("\t|    - Vega                ||");

		System.out.println ("\t|--------------------------||");

		for (Map.Entry<String, Map<String, Double>> bucketSensitivityMapEntry :
			bucketRiskFactorSensitivityMap.entrySet())
		{
			String bucketIndex = bucketSensitivityMapEntry.getKey();

			Map<String, Double> riskFactorSensitivityMap = bucketSensitivityMapEntry.getValue();

			for (Map.Entry<String, Double> riskFactorSensitivityMapEntry :
				riskFactorSensitivityMap.entrySet())
			{
				String currency = riskFactorSensitivityMapEntry.getKey();

				double riskFactorSensitivity = riskFactorSensitivityMapEntry.getValue();

				System.out.println (
					"\t| " +
					currency + " => " +
					FormatUtil.FormatDouble (Integer.parseInt (bucketIndex), 2, 0, 1.) + " | " +
					FormatUtil.FormatDouble (riskFactorSensitivity, 2, 2, 1.) + " ||"
				);
			}
		}

		System.out.println ("\t|--------------------------||");

		System.out.println();
	}

	public static void main (
		final String[] argumentArray)
		throws Exception
	{
		EnvManager.InitEnv ("");

		double notional = 100.;

		MarginEstimationSettings marginEstimationSettings = MarginEstimationSettings.CornishFischer
			(MarginEstimationSettings.POSITION_PRINCIPAL_COMPONENT_COVARIANCE_ESTIMATOR_ISDA);

		RiskMeasureSensitivitySettings riskMeasureSensitivitySettings =
			RiskMeasureSensitivitySettings.ISDA_EQ_VEGA_20();

		Map<String, Map<String, Double>> bucketRiskFactorSensitivityMap = BucketRiskFactorSensitivityMap
			(notional);

		DisplayBucketRiskFactorSensitivity (bucketRiskFactorSensitivityMap);

		Map<String, BucketSensitivity> bucketSensitivityMap = new TreeMap<String, BucketSensitivity>();

		System.out.println ("\t|------------------------||");

		System.out.println ("\t|    BUCKET AGGREGATE    ||");

		System.out.println ("\t|------------------------||");

		System.out.println ("\t|  L -> R:               ||");

		System.out.println ("\t|    - Bucket Index      ||");

		System.out.println ("\t|    - Bucket Margin     ||");

		System.out.println ("\t|    - Bucket Vega       ||");

		System.out.println ("\t|------------------------||");

		for (Map.Entry<String, Map<String, Double>> bucketSensitivityMapEntry :
			bucketRiskFactorSensitivityMap.entrySet())
		{
			String bucketIndex = bucketSensitivityMapEntry.getKey();

			BucketSensitivity bucketSensitivity = new BucketSensitivity
				(bucketSensitivityMapEntry.getValue());

			bucketSensitivityMap.put (
				"" + bucketIndex,
				bucketSensitivity
			);

			BucketAggregate bucketAggregate = bucketSensitivity.aggregate
				(riskMeasureSensitivitySettings.bucketSettingsMap().get (bucketIndex));

			System.out.println ("\t| " +
				FormatUtil.FormatDouble (Integer.parseInt (bucketIndex), 2, 0, 1.) + " => " +
				FormatUtil.FormatDouble (Math.sqrt (bucketAggregate.sensitivityMarginVariance()), 5, 0, 1.) + " | " +
				FormatUtil.FormatDouble (bucketAggregate.cumulativeSensitivityMargin(), 5, 0, 1.) + " ||"
			);
		}

		System.out.println ("\t|------------------------||");

		System.out.println();

		RiskMeasureAggregate riskMeasureAggregate =
			new RiskMeasureSensitivity (bucketSensitivityMap).linearAggregate (
				riskMeasureSensitivitySettings,
				marginEstimationSettings
			);

		System.out.println ("\t|-----------------------------------------------------||");

		System.out.println ("\t|               SBA BASED VEGA MARGIN                 ||");

		System.out.println ("\t|-----------------------------------------------------||");

		System.out.println ("\t|                                                     ||");

		System.out.println ("\t|    L -> R:                                          ||");

		System.out.println ("\t|                                                     ||");

		System.out.println ("\t|            - Core Vega SBA Margin                   ||");

		System.out.println ("\t|            - Residual Vega SBA Margin               ||");

		System.out.println ("\t|            - SBA Vega Margin                        ||");

		System.out.println ("\t|-----------------------------------------------------||");

		System.out.println ("\t| VEGA MARGIN COMPONENTS  => " +
			FormatUtil.FormatDouble (Math.sqrt (riskMeasureAggregate.coreSBAVariance()), 5, 0, 1.) +
				" | " +
			FormatUtil.FormatDouble (Math.sqrt (riskMeasureAggregate.residualSBAVariance()), 5, 0, 1.) +
				" | " +
			FormatUtil.FormatDouble (riskMeasureAggregate.sba(), 5, 0, 1.) + " ||"
		);

		System.out.println ("\t|-----------------------------------------------------||");

		EnvManager.TerminateEnv();
	}
}