Package org.jquantlib.instruments

Examples of org.jquantlib.instruments.StrikedTypePayoff

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                             d.addAssign(new Period(6, TimeUnit.Months))) {
                      dividendDates.add(d.clone());
                      dividends.add(5.0);
                  }

                  final StrikedTypePayoff payoff = new PlainVanillaPayoff(type, strike);
                  final BlackScholesMertonProcess stochProcess = new BlackScholesMertonProcess(new Handle<Quote>(spot), qTS, rTS, volTS);
                  final PricingEngine engine = new FDDividendEuropeanEngine(stochProcess, timeSteps, gridPoints);
                  final PricingEngine ref_engine = new AnalyticDividendEuropeanEngine(stochProcess);

                  final DividendVanillaOption option = new DividendVanillaOption(payoff, exercise, dividendDates, dividends);
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                    final Constructor<T> baseConstructor = engineClass.getConstructor(GeneralizedBlackScholesProcess.class);
                    engine = baseConstructor.newInstance(stochProcess);
                } catch (final Exception e) {
                    throw new LibraryException(e);
                }
                final StrikedTypePayoff payoff = new PlainVanillaPayoff(type, strike);

                final DividendVanillaOption option = new DividendVanillaOption(payoff, exercise, dividendDates, dividends);
                option.setPricingEngine(engine);

                for (final double u : underlyings)
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            engine = baseConstructor.newInstance(process, timeSteps, gridPoints);
        } catch (final Exception e) {
            throw new LibraryException(e);
        }

        final StrikedTypePayoff payoff = new PlainVanillaPayoff(Option.Type.Call, 55.0);
        final /* @Real */ double tolerance = 3.0e-3;

        final List<Date> dividendDates = new ArrayList<Date>();
        final List</* @Real */ Double> dividends = new ArrayList<Double>();

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    //

    @Override
    public void calculate() /* @ReadOnly */ {
        QL.require(a.exercise.type() == Exercise.Type.European , NOT_AN_EUROPEAN_OPTION); // TODO: message
        final StrikedTypePayoff payoff = (StrikedTypePayoff) a.payoff;
        QL.require(payoff != null , NON_STRIKED_PAYOFF_GIVEN); // TODO: message

        /* @Variance */final double variance = process.blackVolatility().currentLink().blackVariance(a.exercise.lastDate(), payoff.strike());
        /* @DiscountFactor */final double dividendDiscount = process.dividendYield().currentLink().discount(a.exercise.lastDate());
        /* @DiscountFactor */final double riskFreeDiscount = process.riskFreeRate().currentLink().discount(a.exercise.lastDate());
        /* @Real */final double spot = process.stateVariable().currentLink().value();
        QL.require(spot > 0.0, "negative or null underlying given"); // TODO: message
        /* @Real */final double forwardPrice = spot * dividendDiscount / riskFreeDiscount;
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    // TODO: define tolerance for calculate()
    @Override
    public void calculate() {
        QL.require(a.exercise.type()==Exercise.Type.European , NOT_AN_AMERICAN_OPTION); // TODO: message
        QL.require(a.payoff instanceof StrikedTypePayoff , NON_STRIKED_PAYOFF_GIVEN); // TODO: message
        final StrikedTypePayoff payoff = (StrikedTypePayoff) a.payoff;

        final double variance = process.blackVolatility().currentLink().blackVariance(a.exercise.lastDate(), payoff.strike());
        final double /* @DiscountFactor */dividendDiscount = process.dividendYield().currentLink().discount(a.exercise.lastDate());
        final double /* @DiscountFactor */riskFreeDiscount = process.riskFreeRate().currentLink().discount(a.exercise.lastDate());
        final double /* @Rate */drift = Math.log(dividendDiscount / riskFreeDiscount) - 0.5 * variance;

        final Integrand f = new Integrand(a.payoff, process.stateVariable().currentLink().value(), drift, variance);
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    //

    @Override
    public void calculate() /*@ReadOnly*/{
        QL.require(a.exercise.type()==Exercise.Type.European , NOT_AN_EUROPEAN_OPTION); // TODO: message
        final StrikedTypePayoff payoff = (StrikedTypePayoff) a.payoff;
        QL.require(a.payoff instanceof StrikedTypePayoff , NON_STRIKED_PAYOFF_GIVEN); // TODO: message

        /*
         * This engine cannot really check for the averageType==Geometric
         * since it can be used as control variate for the Arithmetic version
         *
         * QL_REQUIRE(arguments_.averageType == Average::Geometric, "not a geometric average option");
         */

        double runningLog;
        int pastFixings;
        if (a.averageType == AverageType.Geometric) {
            if (!(a.runningAccumulator>0.0))
                throw new IllegalArgumentException(
                        "positive running product required: "
                        + a.runningAccumulator + " not allowed");
            runningLog = Math.log(a.runningAccumulator);
            pastFixings = a.pastFixings;
        } else {  // it is being used as control variate
            runningLog = 1.0;
            pastFixings = 0;
        }

        final Date referenceDate = process.riskFreeRate().currentLink().referenceDate();
        final DayCounter rfdc  = process.riskFreeRate().currentLink().dayCounter();
        final DayCounter divdc = process.dividendYield().currentLink().dayCounter();
        final DayCounter voldc = process.blackVolatility().currentLink().dayCounter();

        // TODO: consider double[] instead
        final List<Double> fixingTimes = new ArrayList<Double>();
        /*@Size*/ int i;
        for (i=0; i<a.fixingDates.size(); i++) {
            if (a.fixingDates.get(i).ge(referenceDate)) {
                /*@Time*/ final double t = voldc.yearFraction(referenceDate,
                        a.fixingDates.get(i));
                fixingTimes.add(Double.valueOf(t));
            }
        }

        /*@Size*/ final int remainingFixings = fixingTimes.size();
        /*@Size*/ final int numberOfFixings = pastFixings + remainingFixings;
        /*@Real*/ final double N = numberOfFixings;

        /*@Real*/ final double pastWeight = pastFixings/N;
        /*@Real*/ final double futureWeight = 1.0-pastWeight;

        double timeSum = 0.0;
        for (int k=0; k<fixingTimes.size(); k++) {
            timeSum += fixingTimes.get(k);
        }

        /*@Volatility*/ final double vola = process.blackVolatility().currentLink().blackVol(a.exercise.lastDate(), payoff.strike());

        /*@Real*/ double temp = 0.0;
        for (i=pastFixings+1; i<numberOfFixings; i++) {
            temp += fixingTimes.get(i-pastFixings-1)*(N-i);
        }

        /*@Real*/ final double variance = vola*vola /N/N * (timeSum+ 2.0*temp);
        /*@Real*/ final double dsigG_dsig = Math.sqrt((timeSum + 2.0*temp))/N;
        /*@Real*/ final double sigG = vola * dsigG_dsig;
        /*@Real*/ final double dmuG_dsig = -(vola * timeSum)/N;

        final Date exDate = a.exercise.lastDate();
        /*@Rate*/ final double dividendRate = process.dividendYield().currentLink().
        zeroRate(exDate, divdc, Compounding.Continuous, Frequency.NoFrequency).rate();
        /*@Rate*/ final double riskFreeRate = process.riskFreeRate().currentLink().
        zeroRate(exDate, rfdc, Compounding.Continuous, Frequency.NoFrequency).rate();
        /*@Rate*/ final double nu = riskFreeRate - dividendRate - 0.5*vola*vola;

        /*@Real*/ final double  s = process.stateVariable().currentLink().value();

        /*@Real*/ final double muG = pastWeight * runningLog +
        futureWeight * Math.log(s) + nu*timeSum/N;
        /*@Real*/ final double forwardPrice = Math.exp(muG + variance / 2.0);

        /*@DiscountFactor*/ final double riskFreeDiscount = process.riskFreeRate().currentLink().
        discount(a.exercise.lastDate());

        final BlackCalculator black = new BlackCalculator(payoff, forwardPrice, Math.sqrt(variance), riskFreeDiscount);

        r.value = black.value();
        greeks.delta = futureWeight*black.delta(forwardPrice)*forwardPrice/s;
        greeks.gamma = forwardPrice*futureWeight/(s*s)*(black.gamma(forwardPrice)*futureWeight*forwardPrice
                - pastWeight*black.delta(forwardPrice) );

        /*@Real*/ double Nx_1, nx_1;
        final CumulativeNormalDistribution CND = new CumulativeNormalDistribution();
        final NormalDistribution ND = new NormalDistribution();

        if (sigG > Constants.QL_EPSILON) {
            /*@Real*/ final double x_1  = (muG-Math.log(payoff.strike())+variance)/sigG;
            Nx_1 = CND.op(x_1);
            nx_1 = ND.op(x_1);
        } else {
            Nx_1 = (muG > Math.log(payoff.strike()) ? 1.0 : 0.0);
            nx_1 = 0.0;
        }
        greeks.vega = forwardPrice * riskFreeDiscount * ( (dmuG_dsig + sigG * dsigG_dsig)*Nx_1 + nx_1*dsigG_dsig );

        if (payoff.optionType() == Option.Type.Put) {
            greeks.vega -= riskFreeDiscount * forwardPrice * (dmuG_dsig + sigG * dsigG_dsig);
        }

        /*@Time*/ final double tRho = rfdc.yearFraction(process.riskFreeRate().currentLink().referenceDate(), a.exercise.lastDate());
        greeks.rho = black.rho(tRho)*timeSum/(N*tRho) - (tRho-timeSum/N) * r.value;
 
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        QL.require(a.exercise.type()==Exercise.Type.American , NOT_AN_AMERICAN_OPTION); // QA:[RG]::verified
        QL.require(a.exercise instanceof AmericanExercise , NON_AMERICAN_EXERCISE_GIVEN); // QA:[RG]::verified
        final AmericanExercise ex = (AmericanExercise)a.exercise;
        QL.require(!ex.payoffAtExpiry() , PAYOFF_AT_EXPIRY_NOT_HANDLED); // QA:[RG]::verified
        QL.require(a.payoff instanceof StrikedTypePayoff , NON_STRIKE_PAYOFF_GIVEN); // QA:[RG]::verified
        final StrikedTypePayoff payoff = (StrikedTypePayoff)a.payoff;

        final double /* @Real */variance = process.blackVolatility().currentLink().blackVariance(ex.lastDate(), payoff.strike());
        final double /* @DiscountFactor */dividendDiscount = process.dividendYield().currentLink().discount(ex.lastDate());
        final double /* @DiscountFactor */riskFreeDiscount = process.riskFreeRate().currentLink().discount(ex.lastDate());
        final double /* @Real */spot = process.stateVariable().currentLink().value();
        QL.require(spot > 0.0, "negative or null underlying given"); // TODO: message
        final double /* @Real */forwardPrice = spot * dividendDiscount / riskFreeDiscount;
        final BlackCalculator black = new BlackCalculator(payoff, forwardPrice, Math.sqrt(variance), riskFreeDiscount);

        if (dividendDiscount>=1.0 && payoff.optionType()==Option.Type.Call) {
            // early exercise never optimal
            r.value           = black.value();
            greeks.delta            = black.delta(spot);
            moreGreeks.deltaForward = black.deltaForward();
            moreGreeks.elasticity   = black.elasticity(spot);
            greeks.gamma            = black.gamma(spot);

            final DayCounter rfdc  = process.riskFreeRate().currentLink().dayCounter();
            final DayCounter divdc = process.dividendYield().currentLink().dayCounter();
            final DayCounter voldc = process.blackVolatility().currentLink().dayCounter();
            double /*@Time*/ t = rfdc.yearFraction(process.riskFreeRate().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.rho = black.rho(t);

            t = divdc.yearFraction(process.dividendYield().currentLink().referenceDate(), a.exercise.lastDate());
            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
            final CumulativeNormalDistribution cumNormalDist = new CumulativeNormalDistribution();
            final NormalDistribution normalDist = new NormalDistribution();

            final double /*@Real*/ tolerance = 1e-6;
            final double /*@Real*/ Sk = BaroneAdesiWhaleyApproximationEngine.criticalPrice(payoff, riskFreeDiscount, dividendDiscount, variance, tolerance);

            final double /*@Real*/ forwardSk = Sk * dividendDiscount / riskFreeDiscount;

            final double /*@Real*/ alpha = -2.0*Math.log(riskFreeDiscount)/(variance);
            final double /*@Real*/ beta = 2.0*Math.log(dividendDiscount/riskFreeDiscount)/
            (variance);
            final double /*@Real*/ h = 1 - riskFreeDiscount;
            double /*@Real*/ phi;

            switch (payoff.optionType()) {
            case Call:
                phi = 1;
                break;
            case Put:
                phi = -1;
                break;
            default:
                throw new LibraryException(UNKNOWN_OPTION_TYPE); // QA:[RG]::verified
            }

            // TODO: study how zero interest rate could be handled
            QL.ensure(h != 0.0 , DIVIDING_BY_ZERO_INTEREST_RATE); // QA:[RG]::verified

            final double /* @Real */temp_root = Math.sqrt((beta - 1) * (beta - 1) + (4 * alpha) / h);
            final double /* @Real */lambda = (-(beta - 1) + phi * temp_root) / 2;
            final double /* @Real */lambda_prime = -phi * alpha / (h * h * temp_root);

            final double /* @Real */black_Sk = BlackFormula.blackFormula(payoff.optionType(), payoff.strike(), forwardSk, Math.sqrt(variance)) * riskFreeDiscount;
            final double /* @Real */hA = phi * (Sk - payoff.strike()) - black_Sk;

            final double /* @Real */d1_Sk = (Math.log(forwardSk / payoff.strike()) + 0.5 * variance) / Math.sqrt(variance);
            final double /* @Real */d2_Sk = d1_Sk - Math.sqrt(variance);
            final double /* @Real */part1 = forwardSk * normalDist.op(d1_Sk) / (alpha * Math.sqrt(variance));
            final double /* @Real */part2 = -phi * forwardSk * cumNormalDist.op(phi * d1_Sk) * Math.log(dividendDiscount) / Math.log(riskFreeDiscount);
            final double /* @Real */part3 = +phi * payoff.strike() * cumNormalDist.op(phi * d2_Sk);
            final double /* @Real */V_E_h = part1 + part2 + part3;

            final double /* @Real */b = (1 - h) * alpha * lambda_prime / (2 * (2 * lambda + beta - 1));
            final double /* @Real */c = -((1 - h) * alpha / (2 * lambda + beta - 1)) * (V_E_h / (hA) + 1 / h + lambda_prime / (2 * lambda + beta - 1));
            final double /* @Real */temp_spot_ratio = Math.log(spot / Sk);
            final double /* @Real */chi = temp_spot_ratio * (b * temp_spot_ratio + c);

            if (phi * (Sk - spot) > 0) {
                r.value = black.value() + hA * Math.pow((spot / Sk), lambda) / (1 - chi);
            } else {
                r.value = phi * (spot - payoff.strike());
            }

            final double /* @Real */temp_chi_prime = (2 * b / spot) * Math.log(spot / Sk);
            final double /* @Real */chi_prime = temp_chi_prime + c / spot;
            final double /* @Real */chi_double_prime = 2 * b / (spot * spot) - temp_chi_prime / spot - c / (spot * spot);
            greeks.delta = phi * dividendDiscount * cumNormalDist.op(phi * d1_Sk)
            + (lambda / (spot * (1 - chi)) + chi_prime / ((1 - chi)*(1 - chi))) *
            (phi * (Sk - payoff.strike()) - black_Sk) * Math.pow((spot/Sk), lambda);

            greeks.gamma = phi * dividendDiscount * normalDist.op(phi*d1_Sk) /
            (spot * Math.sqrt(variance))
            + (2 * lambda * chi_prime / (spot * (1 - chi) * (1 - chi))
                    + 2 * chi_prime * chi_prime / ((1 - chi) * (1 - chi) * (1 - chi))
                    + chi_double_prime / ((1 - chi) * (1 - chi))
                    + lambda * (1 - lambda) / (spot * spot * (1 - chi)))
                    * (phi * (Sk - payoff.strike()) - black_Sk)
                    * Math.pow((spot/Sk), lambda);
        }

    } // end of "early exercise can be optimal"
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    @Override
    public void calculate() /* @ReadOnly */ {

        QL.require(a.exercise.type() == Exercise.Type.European, "not an European option"); // TODO: message

        final StrikedTypePayoff payoff = (StrikedTypePayoff) a.payoff;
        QL.require(payoff!=null, "non-striked payoff given"); // TODO: message

        final Date settlementDate = process.riskFreeRate().currentLink().referenceDate();
        double riskless = 0.0;
        for (int i=0; i<a.cashFlow.size(); i++) {
            final CashFlow cashflow = a.cashFlow.get(i);
            if (cashflow.date().gt(settlementDate)) {
                riskless += cashflow.amount() * process.riskFreeRate().currentLink().discount(cashflow.date());
            }
        }

        final double spot = process.stateVariable().currentLink().value() - riskless;
        QL.require(spot > 0.0, "negative or null underlying after subtracting dividends"); // TODO: message

        final /*@DiscountFactor*/ double dividendDiscount = process.dividendYield().currentLink().discount(a.exercise.lastDate());
        final /*@DiscountFactor*/ double riskFreeDiscount = process.riskFreeRate().currentLink().discount(a.exercise.lastDate());
        final double forwardPrice = spot * dividendDiscount / riskFreeDiscount;

        final double variance = process.blackVolatility().currentLink().blackVariance(a.exercise.lastDate(), payoff.strike());
        final BlackCalculator black = new BlackCalculator(payoff, forwardPrice, Math.sqrt(variance), riskFreeDiscount);

        r.value = black.value();
        greeks.delta = black.delta(spot);
        greeks.gamma = black.gamma(spot);
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        QL.require(a.exercise.type()==Exercise.Type.American , NOT_AN_AMERICAN_OPTION); // QA:[RG]::verified
        QL.require(a.exercise instanceof AmericanExercise , NON_AMERICAN_EXERCISE_GIVEN); // QA:[RG]::verified
        final AmericanExercise ex = (AmericanExercise)a.exercise;
        QL.require(!ex.payoffAtExpiry() , PAYOFF_AT_EXPIRY_NOT_HANDLED); // QA:[RG]::verified
        QL.require(a.payoff instanceof StrikedTypePayoff , NON_STRIKE_PAYOFF_GIVEN); // QA:[RG]::verified
        final StrikedTypePayoff payoff = (StrikedTypePayoff)a.payoff;

        final double /*@Real*/ variance = process.blackVolatility().currentLink().blackVariance(ex.lastDate(), payoff.strike());
        final double /*@DiscountFactor*/ dividendDiscount = process.dividendYield().currentLink().discount(ex.lastDate());
        final double /*@DiscountFactor*/ riskFreeDiscount = process.riskFreeRate().currentLink().discount(ex.lastDate());
        final double /*@Real*/ spot = process.stateVariable().currentLink().value();
        QL.require(spot > 0.0, "negative or null underlying given"); // TODO: message
        final double /*@Real*/ forwardPrice = spot * dividendDiscount / riskFreeDiscount;
        final BlackCalculator black = new BlackCalculator(payoff, forwardPrice, Math.sqrt(variance), riskFreeDiscount);

        if (dividendDiscount>=1.0 && payoff.optionType()==Option.Type.Call) {
            // early exercise never optimal
            r.value                     = black.value();
            greeks.delta            = black.delta(spot);
            moreGreeks.deltaForward = black.deltaForward();
            moreGreeks.elasticity   = black.elasticity(spot);
            greeks.gamma            = black.gamma(spot);

            final DayCounter rfdc  = process.riskFreeRate().currentLink().dayCounter();
            final DayCounter divdc = process.dividendYield().currentLink().dayCounter();
            final DayCounter voldc = process.blackVolatility().currentLink().dayCounter();

            double /*@Time*/ t = rfdc.yearFraction(process.riskFreeRate().currentLink().referenceDate(), a.exercise.lastDate());
            greeks.rho = black.rho(t);

            t = divdc.yearFraction(process.dividendYield().currentLink().referenceDate(), a.exercise.lastDate());
            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
            final CumulativeNormalDistribution cumNormalDist = new CumulativeNormalDistribution();
            final double /*@Real*/ tolerance = 1e-6;
            final double /*@Real*/ Sk = criticalPrice(payoff, riskFreeDiscount, dividendDiscount, variance, tolerance);
            final double /*@Real*/ forwardSk = Sk * dividendDiscount / riskFreeDiscount;
            final double /*@Real*/ d1 = (Math.log(forwardSk/payoff.strike()) + 0.5*variance)/Math.sqrt(variance);
            final double /*@Real*/ n = 2.0*Math.log(dividendDiscount/riskFreeDiscount)/variance;
            final double /*@Real*/ K = -2.0*Math.log(riskFreeDiscount)/(variance*(1.0-riskFreeDiscount));
            double /*@Real*/ Q, a;
            switch (payoff.optionType()) {
            case Call:
                Q = (-(n-1.0) + Math.sqrt(((n-1.0)*(n-1.0))+4.0*K))/2.0;
                a =  (Sk/Q) * (1.0 - dividendDiscount * cumNormalDist.op(d1));
                if (spot<Sk)
                    r.value = black.value() + a * Math.pow((spot/Sk), Q);
                else
                    r.value = spot - payoff.strike();
                break;
            case Put:
                Q = (-(n-1.0) - Math.sqrt(((n-1.0)*(n-1.0))+4.0*K))/2.0;
                a = -(Sk/Q) * (1.0 - dividendDiscount * cumNormalDist.op(-d1));
                if (spot>Sk)
                    r.value = black.value() + a * Math.pow((spot/Sk), Q);
                else
                    r.value = payoff.strike() - spot;
                break;
            default:
                throw new LibraryException(UNKNOWN_OPTION_TYPE); // QA:[RG]::verified
            }
        } // end of "early exercise can be optimal"
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        sMax = center * minMaxFactor; // underlying grid max value
    }

    protected void ensureStrikeInGrid() {
        // ensure strike is included in the grid
        final StrikedTypePayoff striked_payoff = (StrikedTypePayoff) (payoff);
        if (striked_payoff == null)
            return;
        /* Real */final double requiredGridValue = striked_payoff.strike();

        if (sMin > requiredGridValue / safetyZoneFactor) {
            sMin = requiredGridValue / safetyZoneFactor;
            // enforce central placement of the underlying
            sMax = center / (sMin / center);
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