/**
* Copyright (C) 2012 - present by OpenGamma Inc. and the OpenGamma group of companies
*
* Please see distribution for license.
*/
package com.opengamma.analytics.financial.provider.curve.hullwhite;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.LinkedHashMap;
import java.util.List;
import org.apache.commons.lang.ArrayUtils;
import com.opengamma.analytics.financial.curve.interestrate.generator.GeneratorYDCurve;
import com.opengamma.analytics.financial.instrument.index.IborIndex;
import com.opengamma.analytics.financial.instrument.index.IndexON;
import com.opengamma.analytics.financial.interestrate.InstrumentDerivative;
import com.opengamma.analytics.financial.interestrate.InstrumentDerivativeVisitor;
import com.opengamma.analytics.financial.provider.curve.CurveBuildingBlock;
import com.opengamma.analytics.financial.provider.curve.CurveBuildingBlockBundle;
import com.opengamma.analytics.financial.provider.curve.MultiCurveBundle;
import com.opengamma.analytics.financial.provider.curve.SingleCurveBundle;
import com.opengamma.analytics.financial.provider.description.interestrate.HullWhiteOneFactorProviderDiscount;
import com.opengamma.analytics.financial.provider.description.interestrate.HullWhiteOneFactorProviderInterface;
import com.opengamma.analytics.financial.provider.sensitivity.hullwhite.ParameterSensitivityHullWhiteMatrixCalculator;
import com.opengamma.analytics.financial.provider.sensitivity.multicurve.MulticurveSensitivity;
import com.opengamma.analytics.math.function.Function1D;
import com.opengamma.analytics.math.linearalgebra.DecompositionFactory;
import com.opengamma.analytics.math.matrix.CommonsMatrixAlgebra;
import com.opengamma.analytics.math.matrix.DoubleMatrix1D;
import com.opengamma.analytics.math.matrix.DoubleMatrix2D;
import com.opengamma.analytics.math.matrix.MatrixAlgebra;
import com.opengamma.analytics.math.rootfinding.newton.BroydenVectorRootFinder;
import com.opengamma.util.ArgumentChecker;
import com.opengamma.util.money.Currency;
import com.opengamma.util.tuple.ObjectsPair;
import com.opengamma.util.tuple.Pair;
/**
* Functions to build curves.
*/
// TODO: REVIEW: Embed in a better object.
// TODO: This class should be re-factored with ProviderDiscountBuildingRepository.
public class HullWhiteProviderDiscountBuildingRepository {
/**
* The absolute tolerance for the root finder.
*/
private final double _toleranceAbs;
/**
* The relative tolerance for the root finder.
*/
private final double _toleranceRel;
/**
* The relative tolerance for the root finder.
*/
private final int _stepMaximum;
/**
* The root finder used for curve calibration.
*/
private final BroydenVectorRootFinder _rootFinder;
/**
* The matrix algebra used for matrix inversion.
*/
private static final MatrixAlgebra MATRIX_ALGEBRA = new CommonsMatrixAlgebra();
/**
* Constructor.
* @param toleranceAbs The absolute tolerance for the root finder.
* @param toleranceRel The relative tolerance for the root finder.
* @param stepMaximum The maximum number of step for the root finder.
*/
public HullWhiteProviderDiscountBuildingRepository(final double toleranceAbs, final double toleranceRel, final int stepMaximum) {
_toleranceAbs = toleranceAbs;
_toleranceRel = toleranceRel;
_stepMaximum = stepMaximum;
_rootFinder = new BroydenVectorRootFinder(_toleranceAbs, _toleranceRel, _stepMaximum, DecompositionFactory.getDecomposition(DecompositionFactory.SV_COLT_NAME));
// TODO: make the root finder flexible.
}
/**
* Build a unit of curves.
* @param instruments The instruments used for the unit calibration.
* @param initGuess The initial parameters guess.
* @param knownData The known data (fx rates, other curves, model parameters, ...)
* @param discountingMap The discounting curves names map.
* @param forwardIborMap The forward curves names map.
* @param forwardONMap The forward curves names map.
* @param generatorsMap The generators map.
* @param calculator The calculator of the value on which the calibration is done (usually ParSpreadMarketQuoteCalculator (recommended) or converted present value).
* @param sensitivityCalculator The parameter sensitivity calculator.
* @return The new curves and the calibrated parameters.
*/
private Pair<HullWhiteOneFactorProviderDiscount, Double[]> makeUnit(final InstrumentDerivative[] instruments, final double[] initGuess, final HullWhiteOneFactorProviderDiscount knownData,
final LinkedHashMap<String, Currency> discountingMap, final LinkedHashMap<String, IborIndex[]> forwardIborMap, final LinkedHashMap<String, IndexON[]> forwardONMap,
final LinkedHashMap<String, GeneratorYDCurve> generatorsMap, final InstrumentDerivativeVisitor<HullWhiteOneFactorProviderInterface, Double> calculator,
final InstrumentDerivativeVisitor<HullWhiteOneFactorProviderInterface, MulticurveSensitivity> sensitivityCalculator) {
final GeneratorHullWhiteProviderDiscount generator = new GeneratorHullWhiteProviderDiscount(knownData, discountingMap, forwardIborMap, forwardONMap, generatorsMap);
final HullWhiteProviderDiscountBuildingData data = new HullWhiteProviderDiscountBuildingData(instruments, generator);
final Function1D<DoubleMatrix1D, DoubleMatrix1D> curveCalculator = new HullWhiteProviderDiscountFinderFunction(calculator, data);
final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianCalculator = new HullWhiteProviderDiscountFinderJacobian(new ParameterSensitivityHullWhiteMatrixCalculator(sensitivityCalculator), data);
final double[] parameters = _rootFinder.getRoot(curveCalculator, jacobianCalculator, new DoubleMatrix1D(initGuess)).getData();
final HullWhiteOneFactorProviderDiscount newCurves = data.getGeneratorMarket().evaluate(new DoubleMatrix1D(parameters));
return new ObjectsPair<>(newCurves, ArrayUtils.toObject(parameters));
}
/**
* Build the Jacobian matrixes associated to a unit of curves.
* @param instruments The instruments used for the block calibration.
* @param startBlock The index of the first parameter of the unit in the block.
* @param nbParameters The number of parameters for each curve in the unit.
* @param parameters The parameters used to build each curve in the block.
* @param knownData The known data (FX rates, other curves, model parameters, ...) for the block calibration.
* @param discountingMap The discounting curves names map.
* @param forwardIborMap The forward curves names map.
* @param forwardONMap The forward curves names map.
* @param generatorsMap The generators map.
* @param sensitivityCalculator The parameter sensitivity calculator for the value on which the calibration is done
(usually ParSpreadMarketQuoteDiscountingProviderCalculator (recommended) or converted present value).
* @return The part of the inverse Jacobian matrix associated to each curve.
* The Jacobian matrix is the transition matrix between the curve parameters and the par spread.
*/
// TODO: Currently only for the ParSpreadMarketQuoteDiscountingProviderCalculator.
private DoubleMatrix2D[] makeCurveMatrix(final InstrumentDerivative[] instruments, final int startBlock, final int[] nbParameters, final Double[] parameters,
final HullWhiteOneFactorProviderDiscount knownData, final LinkedHashMap<String, Currency> discountingMap, final LinkedHashMap<String, IborIndex[]> forwardIborMap,
final LinkedHashMap<String, IndexON[]> forwardONMap, final LinkedHashMap<String, GeneratorYDCurve> generatorsMap,
final InstrumentDerivativeVisitor<HullWhiteOneFactorProviderInterface, MulticurveSensitivity> sensitivityCalculator) {
final GeneratorHullWhiteProviderDiscount generator = new GeneratorHullWhiteProviderDiscount(knownData, discountingMap, forwardIborMap, forwardONMap, generatorsMap);
final HullWhiteProviderDiscountBuildingData data = new HullWhiteProviderDiscountBuildingData(instruments, generator);
final Function1D<DoubleMatrix1D, DoubleMatrix2D> jacobianCalculator = new HullWhiteProviderDiscountFinderJacobian(new ParameterSensitivityHullWhiteMatrixCalculator(sensitivityCalculator), data);
final DoubleMatrix2D jacobian = jacobianCalculator.evaluate(new DoubleMatrix1D(parameters));
final DoubleMatrix2D inverseJacobian = MATRIX_ALGEBRA.getInverse(jacobian);
final double[][] matrixTotal = inverseJacobian.getData();
final DoubleMatrix2D[] result = new DoubleMatrix2D[nbParameters.length];
int startCurve = 0;
for (int loopmat = 0; loopmat < nbParameters.length; loopmat++) {
final double[][] matrixCurve = new double[nbParameters[loopmat]][matrixTotal.length];
for (int loopparam = 0; loopparam < nbParameters[loopmat]; loopparam++) {
matrixCurve[loopparam] = matrixTotal[startBlock + startCurve + loopparam].clone();
}
result[loopmat] = new DoubleMatrix2D(matrixCurve);
startCurve += nbParameters[loopmat];
}
return result;
}
/**
* Build a block of curves.
* @param curveBundles The curve bundles, not null
* @param knownData The known data (fx rates, other curves, model parameters, ...)
* @param discountingMap The discounting curves names map.
* @param forwardIborMap The forward curves names map.
* @param forwardONMap The forward curves names map.
* @param calculator The calculator of the value on which the calibration is done (usually ParSpreadMarketQuoteCalculator (recommended) or converted present value).
* @param sensitivityCalculator The parameter sensitivity calculator.
* @return A pair with the calibrated yield curve bundle (including the known data) and the CurveBuildingBlckBundle with the relevant inverse Jacobian Matrix.
*/
public Pair<HullWhiteOneFactorProviderDiscount, CurveBuildingBlockBundle> makeCurvesFromDerivatives(final MultiCurveBundle<GeneratorYDCurve>[] curveBundles,
final HullWhiteOneFactorProviderDiscount knownData, final LinkedHashMap<String, Currency> discountingMap,
final LinkedHashMap<String, IborIndex[]> forwardIborMap, final LinkedHashMap<String, IndexON[]> forwardONMap,
final InstrumentDerivativeVisitor<HullWhiteOneFactorProviderInterface, Double> calculator,
final InstrumentDerivativeVisitor<HullWhiteOneFactorProviderInterface, MulticurveSensitivity> sensitivityCalculator) {
ArgumentChecker.notNull(curveBundles, "curve bundles");
ArgumentChecker.notNull(knownData, "known data");
ArgumentChecker.notNull(discountingMap, "discounting map");
ArgumentChecker.notNull(forwardIborMap, "forward ibor map");
ArgumentChecker.notNull(forwardONMap, "forward overnight map");
ArgumentChecker.notNull(calculator, "calculator");
ArgumentChecker.notNull(sensitivityCalculator, "sensitivity calculator");
final int nbUnits = curveBundles.length;
final HullWhiteOneFactorProviderDiscount knownSoFarData = knownData.copy();
final List<InstrumentDerivative> instrumentsSoFar = new ArrayList<>();
final LinkedHashMap<String, GeneratorYDCurve> generatorsSoFar = new LinkedHashMap<>();
final LinkedHashMap<String, Pair<CurveBuildingBlock, DoubleMatrix2D>> unitBundleSoFar = new LinkedHashMap<>();
final List<Double> parametersSoFar = new ArrayList<>();
final LinkedHashMap<String, Pair<Integer, Integer>> unitMap = new LinkedHashMap<>();
int startUnit = 0;
for (int iUnits = 0; iUnits < nbUnits; iUnits++) {
final MultiCurveBundle<GeneratorYDCurve> curveBundle = curveBundles[iUnits];
final int nbCurve = curveBundle.size();
final int[] startCurve = new int[nbCurve]; // First parameter index of the curve in the unit.
final LinkedHashMap<String, GeneratorYDCurve> gen = new LinkedHashMap<>();
final int[] nbIns = new int[curveBundle.getNumberOfInstruments()];
int nbInsUnit = 0; // Number of instruments in the unit.
for (int iCurve = 0; iCurve < nbCurve; iCurve++) {
final SingleCurveBundle<GeneratorYDCurve> singleCurve = curveBundle.getCurveBundle(iCurve);
startCurve[iCurve] = nbInsUnit;
nbIns[iCurve] = singleCurve.size();
nbInsUnit += nbIns[iCurve];
instrumentsSoFar.addAll(Arrays.asList(singleCurve.getDerivatives()));
}
final InstrumentDerivative[] instrumentsUnit = new InstrumentDerivative[nbInsUnit];
final double[] parametersGuess = new double[nbInsUnit];
final InstrumentDerivative[] instrumentsSoFarArray = instrumentsSoFar.toArray(new InstrumentDerivative[instrumentsSoFar.size()]);
for (int iCurve = 0; iCurve < nbCurve; iCurve++) {
final SingleCurveBundle<GeneratorYDCurve> singleCurve = curveBundle.getCurveBundle(iCurve);
final InstrumentDerivative[] derivatives = singleCurve.getDerivatives();
System.arraycopy(derivatives, 0, instrumentsUnit, startCurve[iCurve], nbIns[iCurve]);
System.arraycopy(singleCurve.getStartingPoint(), 0, parametersGuess, startCurve[iCurve], nbIns[iCurve]);
final GeneratorYDCurve tmp = singleCurve.getCurveGenerator().finalGenerator(derivatives);
final String curveName = singleCurve.getCurveName();
gen.put(curveName, tmp);
generatorsSoFar.put(curveName, tmp);
unitMap.put(curveName, new ObjectsPair<>(startUnit + startCurve[iCurve], nbIns[iCurve]));
}
final Pair<HullWhiteOneFactorProviderDiscount, Double[]> unitCal = makeUnit(instrumentsUnit, parametersGuess, knownSoFarData,
discountingMap, forwardIborMap, forwardONMap, gen, calculator, sensitivityCalculator);
parametersSoFar.addAll(Arrays.asList(unitCal.getSecond()));
final DoubleMatrix2D[] mat = makeCurveMatrix(instrumentsSoFarArray, startUnit, nbIns, parametersSoFar.toArray(new Double[parametersSoFar.size()]), knownData, discountingMap,
forwardIborMap, forwardONMap, generatorsSoFar, sensitivityCalculator);
// TODO: should curve matrix be computed only once at the end? To save time
for (int iCurve = 0; iCurve < nbCurve; iCurve++) {
final SingleCurveBundle<GeneratorYDCurve> singleCurve = curveBundle.getCurveBundle(iCurve);
unitBundleSoFar.put(singleCurve.getCurveName(), new ObjectsPair<>(new CurveBuildingBlock(unitMap), mat[iCurve]));
}
knownSoFarData.setAll(unitCal.getFirst());
startUnit = startUnit + nbInsUnit;
}
return new ObjectsPair<>(knownSoFarData, new CurveBuildingBlockBundle(unitBundleSoFar));
}
}