Package com.opengamma.analytics.financial.model.option.pricing.analytic.formula

Examples of com.opengamma.analytics.financial.model.option.pricing.analytic.formula.BlackFunctionData

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     */
    double bs(final double strike) {
      final EuropeanVanillaOption option = new EuropeanVanillaOption(strike, _timeToExpiry, _isCall);
      final Function1D<SABRFormulaData, Double> funcSabr = _sabrFunction.getVolatilityFunction(option, _forward);
      final double volatility = funcSabr.evaluate(_sabrData);
      final BlackFunctionData dataBlack = new BlackFunctionData(_forward, 1.0, volatility);
      final Function1D<BlackFunctionData, Double> func = _blackFunction.getPriceFunction(option);
      return func.evaluate(dataBlack);
    }
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    for (int i = 0; i < n; i++) {
      final double k = strikeNprice[i][0];
      final double price = strikeNprice[i][1];

      final double impVol = BLACK_IMPLIED_VOL.getImpliedVolatility(new BlackFunctionData(FORWARD, DF, 0.0), new EuropeanVanillaOption(k, T, true), price);
      //System.out.println(k + "\t" + impVol);
      assertEquals(sigma, impVol, 1e-3);
    }
  }
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    final double forward = 1.0;
    final double t = 1 / 12.0;

    final MartingaleCharacteristicExponent heston = new HestonCharacteristicExponent(kappa, theta, vol0, omega, rho);
    final BlackFunctionData data = new BlackFunctionData(forward, 1, 0.2);

    boolean isCall = true;
   
   //this contains strike, price then the derivatives of price wrt the parameters
    double[][] res = modelGreekFFT.getGreeks(forward, 1.0, t, isCall,heston,0.3,2.0,50,0.2,alpha,1e-16);
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    final double pvbp = METHOD_SWAP.getAnnuityCash(swaption.getUnderlyingSwap(), forward);
    // Implementation comment: cash-settled swaptions make sense only for constant strike, the computation of coupon equivalent is not required.
    final BlackPriceFunction blackFunction = new BlackPriceFunction();
    final double volatility = curveBlack.getBlackParameters().getVolatility(swaption.getTimeToExpiry(), tenor);
    final double discountFactorSettle = curveBlack.getMulticurveProvider().getDiscountFactor(swaption.getCurrency(), swaption.getSettlementTime());
    final BlackFunctionData dataBlack = new BlackFunctionData(forward, discountFactorSettle * pvbp, volatility);
    final Function1D<BlackFunctionData, Double> func = blackFunction.getPriceFunction(swaption);
    final double price = func.evaluate(dataBlack) * (swaption.isLong() ? 1.0 : -1.0);
    return MultipleCurrencyAmount.of(swaption.getCurrency(), price);
  }
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    final double pvbpDf = METHOD_SWAP.getAnnuityCashDerivative(swaption.getUnderlyingSwap(), forward);
    // Implementation note: strictly speaking, the strike equivalent is curve dependent; that dependency is ignored.
    final BlackPriceFunction blackFunction = new BlackPriceFunction();
    final double volatility = curveBlack.getBlackParameters().getVolatility(swaption.getTimeToExpiry(), tenor);
    final double discountFactorSettle = curveBlack.getMulticurveProvider().getDiscountFactor(swaption.getCurrency(), swaption.getSettlementTime());
    final BlackFunctionData dataBlack = new BlackFunctionData(forward, 1.0, volatility);
    final double[] bsAdjoint = blackFunction.getPriceAdjoint(swaption, dataBlack);
    final double sensiDF = -swaption.getSettlementTime() * discountFactorSettle * pvbp * bsAdjoint[0];
    final List<DoublesPair> list = new ArrayList<>();
    list.add(new DoublesPair(swaption.getSettlementTime(), sensiDF));
    MulticurveSensitivity result = forwardDr.multipliedBy(discountFactorSettle * (pvbpDf * bsAdjoint[0] + pvbp * bsAdjoint[1]));
 
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    final double pvbp = METHOD_SWAP.getAnnuityCash(swaption.getUnderlyingSwap(), forward);
    final double discountFactorSettle = curveBlack.getMulticurveProvider().getDiscountFactor(swaption.getCurrency(), swaption.getSettlementTime());
    final DoublesPair point = new DoublesPair(swaption.getTimeToExpiry(), swaption.getMaturityTime());
    final BlackPriceFunction blackFunction = new BlackPriceFunction();
    final double volatility = curveBlack.getBlackParameters().getVolatility(point);
    final BlackFunctionData dataBlack = new BlackFunctionData(forward, 1.0, volatility);
    final double[] bsAdjoint = blackFunction.getPriceAdjoint(swaption, dataBlack);
    final Map<DoublesPair, Double> sensitivity = new HashMap<>();
    sensitivity.put(point, bsAdjoint[2] * pvbp * discountFactorSettle * (swaption.isLong() ? 1.0 : -1.0));
    return new PresentValueBlackSwaptionSensitivity(sensitivity, curveBlack.getBlackParameters().getGeneratorSwap());
  }
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    final FourierPricer pricer = new FourierPricer();

    for (int i = 0; i < 21; i++) {
      final double k = 0.2 + 3.0 * i / 20.0;
      final EuropeanVanillaOption option = new EuropeanVanillaOption(k * FORWARD, T, true);
      final BlackFunctionData data = new BlackFunctionData(FORWARD, DF, 0);
      final double price = pricer.price(data, option, heston, -0.5, 1e-6);
      final double impVol = BLACK_IMPLIED_VOL.getImpliedVolatility(data, option, price);
      assertEquals(sigma, impVol, 1e-3);
    }
  }
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    final double omega = 2; // vol-of-vol
    final double rho = -0.8; // correlation
    final double t = 1.0;// / 52.0;
    final MartingaleCharacteristicExponent heston = new HestonCharacteristicExponent(kappa, theta, vol0, omega, rho);
    final EuropeanPriceIntegrand integrand = new EuropeanPriceIntegrand(heston, alpha, true);
    final BlackFunctionData data = new BlackFunctionData(1, 1, 0.5);
    for (int i = 0; i < 201; i++) {
      final double x = -0. + i * 80. / 200.0;
      final EuropeanVanillaOption option = new EuropeanVanillaOption(2, t, true);
      final Double res = integrand.getFunction(data, option).evaluate(x);
      System.out.println(x + "\t" + res);
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    final double t = 1 / 12.0;

    final MartingaleCharacteristicExponent heston = new HestonCharacteristicExponent(kappa, theta, vol0, omega, rho);
    final FourierPricer pricer = new FourierPricer();
    final BlackFunctionData data = new BlackFunctionData(1, 1, 0);
    for (int i = 0; i < 11; i++) {
      final double k = 0.5 + 1.0 * i / 10.0;

      final EuropeanVanillaOption option = new EuropeanVanillaOption(k, t, true);
      final double price = pricer.price(data, option, heston, alpha, 1e-8);
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    final double forward = 1.0;
    final double t = 1 / 12.0;

    final MartingaleCharacteristicExponent heston = new HestonCharacteristicExponent(kappa, theta, vol0, omega, rho);
    final FourierPricer pricer = new FourierPricer();
    final BlackFunctionData data = new BlackFunctionData(forward, 1, 0);

    boolean isCall;
    for (int i = 0; i < 11; i++) {
      final double k = 0.7 + 0.6 * i / 10.0;
      isCall = k >= forward;
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Related Classes of com.opengamma.analytics.financial.model.option.pricing.analytic.formula.BlackFunctionData

  • com.opengamma.analytics.financial.forex.method.ForexNonDeliverableOptionBlackMethod
  • com.opengamma.analytics.financial.forex.method.ForexOptionVanillaBlackSmileMethod
  • com.opengamma.analytics.financial.forex.method.ForexOptionVanillaBlackSmileMethodTest
  • com.opengamma.analytics.financial.forex.method.ForexOptionVanillaBlackTermStructureMethod
  • com.opengamma.analytics.financial.forex.method.ForexOptionVanillaVannaVolgaMethod
  • com.opengamma.analytics.financial.forex.method.ForexOptionVanillaVannaVolgaMethodTest
  • com.opengamma.analytics.financial.forex.provider.ForexNonDeliverableOptionBlackSmileMethod
  • com.opengamma.analytics.financial.forex.provider.ForexOptionVanillaBlackFlatMethod
  • com.opengamma.analytics.financial.forex.provider.ForexOptionVanillaBlackSmileMethod
  • com.opengamma.analytics.financial.forex.provider.ForexOptionVanillaBlackSmileMethodTest
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