// McSimulation implementation
protected override TimeGrid timeGrid()
{
Date referenceDate = process_.riskFreeRate().link.referenceDate();
DayCounter voldc = process_.blackVolatility().link.dayCounter();
List <double> fixingTimes = new InitializedList <double>(arguments_.fixingDates.Count());
for (int i = 0; i < arguments_.fixingDates.Count(); i++)
{
if (arguments_.fixingDates[i] >= referenceDate)
{
double t = voldc.yearFraction(referenceDate,
arguments_.fixingDates[i]);
fixingTimes.Add(t);
}
}
// handle here maxStepsPerYear
return(new TimeGrid(fixingTimes.Last(), fixingTimes.Count()));
}
public override void calculate()
{
/* 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");
*/
if (!(arguments_.exercise.type() == Exercise.Type.European))
{
throw new ApplicationException("not an European Option");
}
double runningLog;
int pastFixings;
if (arguments_.averageType == Average.Type.Geometric)
{
if (!(arguments_.runningAccumulator > 0.0))
{
throw new ApplicationException("positive running product required: "
+ arguments_.runningAccumulator + " not allowed");
}
runningLog =
Math.Log(arguments_.runningAccumulator.GetValueOrDefault());
pastFixings = arguments_.pastFixings.GetValueOrDefault();
}
else // it is being used as control variate
{
runningLog = 1.0;
pastFixings = 0;
}
PlainVanillaPayoff payoff = (PlainVanillaPayoff)(arguments_.payoff);
if (payoff == null)
{
throw new ApplicationException("non-plain payoff given");
}
Date referenceDate = process_.riskFreeRate().link.referenceDate();
DayCounter rfdc = process_.riskFreeRate().link.dayCounter();
DayCounter divdc = process_.dividendYield().link.dayCounter();
DayCounter voldc = process_.blackVolatility().link.dayCounter();
List <double> fixingTimes = new InitializedList <double>(arguments_.fixingDates.Count());
int i;
for (i = 0; i < arguments_.fixingDates.Count(); i++)
{
if (arguments_.fixingDates[i] >= referenceDate)
{
double t = voldc.yearFraction(referenceDate,
arguments_.fixingDates[i]);
fixingTimes.Add(t);
}
}
int remainingFixings = fixingTimes.Count();
int numberOfFixings = pastFixings + remainingFixings;
double N = numberOfFixings;
double pastWeight = pastFixings / N;
double futureWeight = 1.0 - pastWeight;
/*double timeSum = std::accumulate(fixingTimes.begin(),
* fixingTimes.end(), 0.0);*/
double timeSum = 0;
fixingTimes.ForEach((ii, vv) => timeSum += fixingTimes[ii]);
double vola = process_.blackVolatility().link.blackVol(
arguments_.exercise.lastDate(),
payoff.strike());
double temp = 0.0;
for (i = pastFixings + 1; i < numberOfFixings; i++)
{
temp += fixingTimes[i - pastFixings - 1] * (N - i);
}
double variance = vola * vola / N / N * (timeSum + 2.0 * temp);
double dsigG_dsig = Math.Sqrt((timeSum + 2.0 * temp)) / N;
double sigG = vola * dsigG_dsig;
double dmuG_dsig = -(vola * timeSum) / N;
Date exDate = arguments_.exercise.lastDate();
double dividendRate = process_.dividendYield().link.
zeroRate(exDate, divdc, Compounding.Continuous, Frequency.NoFrequency).rate();
double riskFreeRate = process_.riskFreeRate().link.
zeroRate(exDate, rfdc, Compounding.Continuous, Frequency.NoFrequency).rate();
double nu = riskFreeRate - dividendRate - 0.5 * vola * vola;
double s = process_.stateVariable().link.value();
if (!(s > 0.0))
{
throw new ApplicationException("positive underlying value required");
}
int M = (pastFixings == 0 ? 1 : pastFixings);
double muG = pastWeight * runningLog / M +
futureWeight * Math.Log(s) + nu * timeSum / N;
double forwardPrice = Math.Exp(muG + variance / 2.0);
double riskFreeDiscount = process_.riskFreeRate().link.discount(
arguments_.exercise.lastDate());
BlackCalculator black = new BlackCalculator(payoff, forwardPrice, Math.Sqrt(variance),
riskFreeDiscount);
results_.value = black.value();
results_.delta = futureWeight * black.delta(forwardPrice) * forwardPrice / s;
results_.gamma = forwardPrice * futureWeight / (s * s)
* (black.gamma(forwardPrice) * futureWeight * forwardPrice
- pastWeight * black.delta(forwardPrice));
double Nx_1, nx_1;
CumulativeNormalDistribution CND = new CumulativeNormalDistribution();
NormalDistribution ND = new NormalDistribution();
if (sigG > Const.QL_Epsilon)
{
double x_1 = (muG - Math.Log(payoff.strike()) + variance) / sigG;
Nx_1 = CND.value(x_1);
nx_1 = ND.value(x_1);
}
else
{
Nx_1 = (muG > Math.Log(payoff.strike()) ? 1.0 : 0.0);
nx_1 = 0.0;
}
results_.vega = forwardPrice * riskFreeDiscount *
((dmuG_dsig + sigG * dsigG_dsig) * Nx_1 + nx_1 * dsigG_dsig);
if (payoff.optionType() == Option.Type.Put)
{
results_.vega -= riskFreeDiscount * forwardPrice *
(dmuG_dsig + sigG * dsigG_dsig);
}
double tRho = rfdc.yearFraction(process_.riskFreeRate().link.referenceDate(),
arguments_.exercise.lastDate());
results_.rho = black.rho(tRho) * timeSum / (N * tRho)
- (tRho - timeSum / N) * results_.value;
double tDiv = divdc.yearFraction(
process_.dividendYield().link.referenceDate(),
arguments_.exercise.lastDate());
results_.dividendRho = black.dividendRho(tDiv) * timeSum / (N * tDiv);
results_.strikeSensitivity = black.strikeSensitivity();
results_.theta = Utils.blackScholesTheta(process_,
results_.value.GetValueOrDefault(),
results_.delta.GetValueOrDefault(),
results_.gamma.GetValueOrDefault());
}