Package org.jquantlib.pricingengines

Examples of org.jquantlib.pricingengines.BlackCalculator.thetaPerDay()

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            t = voldc.yearFraction(process.blackVolatility().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.vega        = black.vega(t);
            greeks.theta       = black.theta(spot, t);

            moreGreeks.thetaPerDay        = black.thetaPerDay(spot, t);
            moreGreeks.strikeSensitivity  = black.strikeSensitivity();
            moreGreeks.itmCashProbability = black.itmCashProbability();
        } else {
            // early exercise can be optimal
            final CumulativeNormalDistribution cumNormalDist = new CumulativeNormalDistribution();
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            greeks.dividendRho = black.dividendRho(t);

            t = voldc.yearFraction(process.blackVolatility().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.vega            = black.vega(t);
            greeks.theta           = black.theta(spot, t);
            moreGreeks.thetaPerDay = black.thetaPerDay(spot, t);

            moreGreeks.strikeSensitivity  = black.strikeSensitivity();
            moreGreeks.itmCashProbability = black.itmCashProbability();
        } else {
            // early exercise can be optimal
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            greeks.dividendRho = black.dividendRho(t);

            t = voldc.yearFraction(process.blackVolatility().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.vega            = black.vega(t);
            greeks.theta           = black.theta(spot, t);
            moreGreeks.thetaPerDay = black.thetaPerDay(spot, t);

            moreGreeks.strikeSensitivity  = black.strikeSensitivity();
            moreGreeks.itmCashProbability = black.itmCashProbability();
        } else {
            // early exercise can be optimal - use approximation
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            greeks.dividendRho = black.dividendRho(t);

            t = voldc.yearFraction(process.blackVolatility().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.vega            = black.vega(t);
            greeks.theta           = black.theta(spot, t);
            moreGreeks.thetaPerDay = black.thetaPerDay(spot, t);

            moreGreeks.strikeSensitivity  = black.strikeSensitivity();
            moreGreeks.itmCashProbability = black.itmCashProbability();
        } else {
            // early exercise can be optimal - use approximation
View Full Code Here
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            greeks.dividendRho = black.dividendRho(t);

            t = voldc.yearFraction(process.blackVolatility().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.vega            = black.vega(t);
            greeks.theta           = black.theta(spot, t);
            moreGreeks.thetaPerDay = black.thetaPerDay(spot, t);

            moreGreeks.strikeSensitivity  = black.strikeSensitivity();
            moreGreeks.itmCashProbability = black.itmCashProbability();
        } else {
            // early exercise can be optimal
View Full Code Here
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            t = voldc.yearFraction(process.blackVolatility().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.vega        = black.vega(t);
            greeks.theta       = black.theta(spot, t);

            moreGreeks.thetaPerDay        = black.thetaPerDay(spot, t);
            moreGreeks.strikeSensitivity  = black.strikeSensitivity();
            moreGreeks.itmCashProbability = black.itmCashProbability();
        } else {
            // early exercise can be optimal
            final CumulativeNormalDistribution cumNormalDist = new CumulativeNormalDistribution();
View Full Code Here
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