MultilateralBasisCurve.java
package org.drip.state.csa;
/*
* -*- 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>MultilateralBasisCurve</i> implements the CSA Cash Rate Curve as a Basis over an Overnight Curve.
*
* <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/FixedIncomeAnalyticsLibrary.md">Fixed Income Analytics</a></li>
* <li><b>Project</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/state/README.md">Latent State Inference and Creation Utilities</a></li>
* <li><b>Package</b> = <a href = "https://github.com/lakshmiDRIP/DROP/tree/master/src/main/java/org/drip/state/csa/README.md">Credit Support Annex Latent State</a></li>
* </ul>
* <br><br>
*
* @author Lakshmi Krishnamurthy
*/
public class MultilateralBasisCurve implements org.drip.state.csa.CashFlowEstimator
{
private static final int NUM_DF_QUADRATURES = 5;
private double _dblBasis = java.lang.Double.NaN;
private org.drip.state.discount.MergedDiscountForwardCurve _mdfcOvernight = null;
/**
* Retrieve the Overnight Curve
*
* @return The Overnight Curve
*/
public org.drip.state.discount.MergedDiscountForwardCurve overnightCurve()
{
return _mdfcOvernight;
}
/**
* Retrieve the Basis to the Overnight Curve
*
* @return The Basis to the Overnight Curve
*/
public double basis()
{
return _dblBasis;
}
@Override public org.drip.analytics.date.JulianDate epoch()
{
return _mdfcOvernight.epoch();
}
@Override public double df (
final int iDate)
throws java.lang.Exception
{
int iEpochDate = epoch().julian();
if (iEpochDate >= iDate)
throw new java.lang.Exception ("MultilateralBasisCurve::df => Invalid Inputs");
return _mdfcOvernight.df (iDate) * java.lang.Math.exp (_dblBasis * (iEpochDate - iDate) / 365.25);
}
@Override public double df (
final org.drip.analytics.date.JulianDate dt)
throws java.lang.Exception
{
if (null == dt) throw new java.lang.Exception ("MultilateralBasisCurve::df => Invalid Inputs");
return df (dt.julian());
}
@Override public double df (
final java.lang.String strTenor)
throws java.lang.Exception
{
return df (epoch().addTenor (strTenor));
}
@Override public double effectiveDF (
final int iDate1,
final int iDate2)
throws java.lang.Exception
{
if (epoch().julian() > iDate1 || iDate1 >= iDate2)
throw new java.lang.Exception ("MultilateralFlatForwardCurve::effectiveDF => Invalid Inputs");
int iNumQuadratures = 0;
double dblEffectiveDF = 0.;
int iQuadratureWidth = (iDate2 - iDate1) / NUM_DF_QUADRATURES;
if (0 == iQuadratureWidth) iQuadratureWidth = 1;
for (int iDate = iDate1; iDate <= iDate2; iDate += iQuadratureWidth) {
++iNumQuadratures;
dblEffectiveDF += (df (iDate) + df (iDate + iQuadratureWidth));
}
return dblEffectiveDF / (2. * iNumQuadratures);
}
@Override public double effectiveDF (
final org.drip.analytics.date.JulianDate dt1,
final org.drip.analytics.date.JulianDate dt2)
throws java.lang.Exception
{
if (null == dt1 || null == dt2)
throw new java.lang.Exception ("MultilateralFlatForwardCurve::effectiveDF => Invalid Inputs");
return effectiveDF (
dt1.julian(),
dt2.julian()
);
}
@Override public double effectiveDF (
final java.lang.String strTenor1,
final java.lang.String strTenor2)
throws java.lang.Exception
{
org.drip.analytics.date.JulianDate dtEpoch = epoch();
return effectiveDF (
dtEpoch.addTenor (strTenor1),
dtEpoch.addTenor (strTenor2)
);
}
@Override public double rate (
final int iDate)
throws java.lang.Exception
{
int iEpochDate = epoch().julian();
if (iEpochDate >= iDate)
throw new java.lang.Exception ("MultilateralFlatForwardCurve::rate => Invalid Inputs");
return 365.25 * java.lang.Math.log (df (iEpochDate) / df (iDate)) / (iEpochDate - iDate);
}
@Override public double rate (
final org.drip.analytics.date.JulianDate dt)
throws java.lang.Exception
{
if (null == dt)
throw new java.lang.Exception ("MultilateralFlatForwardCurve::rate => Invalid Inputs");
return rate (dt.julian());
}
@Override public double rate (
final java.lang.String strTenor)
throws java.lang.Exception
{
return rate (epoch().addTenor (strTenor));
}
@Override public double rate (
final int iDate1,
final int iDate2)
throws java.lang.Exception
{
int iEpochDate = epoch().julian();
if (iEpochDate > iDate1 || iDate1 >= iDate2)
throw new java.lang.Exception ("MultilateralFlatForwardCurve::rate => Invalid Inputs");
return 365.25 * java.lang.Math.log (df (iDate1) / df (iDate2)) / (iDate2 - iDate1);
}
@Override public double rate (
final org.drip.analytics.date.JulianDate dt1,
final org.drip.analytics.date.JulianDate dt2)
throws java.lang.Exception
{
if (null == dt1 || null == dt2)
throw new java.lang.Exception ("MultilateralFlatForwardCurve::rate => Invalid Inputs");
return rate (
dt1.julian(),
dt2.julian()
);
}
@Override public double rate (
final java.lang.String strTenor1,
final java.lang.String strTenor2)
throws java.lang.Exception
{
org.drip.analytics.date.JulianDate dtEpoch = epoch();
return rate (
dtEpoch.addTenor (strTenor1),
dtEpoch.addTenor (strTenor2)
);
}
}