public FDVanillaEngine(GeneralizedBlackScholesProcess process, int timeSteps, int gridPoints, bool timeDependent)
{
process_ = process;
timeSteps_ = timeSteps;
gridPoints_ = gridPoints;
timeDependent_ = timeDependent;
intrinsicValues_ = new SampledCurve(gridPoints);
BCs_ = new InitializedList <BoundaryCondition <IOperator> >(2);
}
protected void setGridLimits(double center, double t)
{
Utils.QL_REQUIRE(center > 0.0, () => "negative or null underlying given");
Utils.QL_REQUIRE(t > 0.0, () => "negative or zero residual time");
center_ = center;
int newGridPoints = safeGridPoints(gridPoints_, t);
if (newGridPoints > intrinsicValues_.size())
{
intrinsicValues_ = new SampledCurve(newGridPoints);
}
double volSqrtTime = Math.Sqrt(process_.blackVolatility().link.blackVariance(t, center_));
// the prefactor fine tunes performance at small volatilities
double prefactor = 1.0 + 0.02 / volSqrtTime;
double minMaxFactor = Math.Exp(4.0 * prefactor * volSqrtTime);
sMin_ = center_ / minMaxFactor; // underlying grid min value
sMax_ = center_ * minMaxFactor; // underlying grid max value
}
public override void calculate(IPricingEngineResults r)
{
OneAssetOption.Results results = r as OneAssetOption.Results;
setGridLimits();
initializeInitialCondition();
initializeOperator();
initializeBoundaryConditions();
initializeStepCondition();
List <IOperator> operatorSet = new List <IOperator>();
List <Vector> arraySet = new List <Vector>();
BoundaryConditionSet bcSet = new BoundaryConditionSet();
StepConditionSet <Vector> conditionSet = new StepConditionSet <Vector>();
prices_ = (SampledCurve)intrinsicValues_.Clone();
controlPrices_ = (SampledCurve)intrinsicValues_.Clone();
controlOperator_ = (TridiagonalOperator)finiteDifferenceOperator_.Clone();
controlBCs_[0] = BCs_[0];
controlBCs_[1] = BCs_[1];
operatorSet.Add(finiteDifferenceOperator_);
operatorSet.Add(controlOperator_);
arraySet.Add(prices_.values());
arraySet.Add(controlPrices_.values());
bcSet.Add(BCs_);
bcSet.Add(controlBCs_);
conditionSet.Add(stepCondition_);
conditionSet.Add(new NullCondition <Vector>());
var model = new FiniteDifferenceModel <ParallelEvolver <CrankNicolson <TridiagonalOperator> > >(operatorSet, bcSet);
object temp = arraySet;
model.rollback(ref temp, getResidualTime(), 0.0, timeSteps_, conditionSet);
arraySet = (List <Vector>)temp;
prices_.setValues(arraySet[0]);
controlPrices_.setValues(arraySet[1]);
StrikedTypePayoff striked_payoff = payoff_ as StrikedTypePayoff;
Utils.QL_REQUIRE(striked_payoff != null, () => "non-striked payoff given");
double variance = process_.blackVolatility().link.blackVariance(exerciseDate_, striked_payoff.strike());
double dividendDiscount = process_.dividendYield().link.discount(exerciseDate_);
double riskFreeDiscount = process_.riskFreeRate().link.discount(exerciseDate_);
double spot = process_.stateVariable().link.value();
double forwardPrice = spot * dividendDiscount / riskFreeDiscount;
BlackCalculator black = new BlackCalculator(striked_payoff, forwardPrice, Math.Sqrt(variance), riskFreeDiscount);
results.value = prices_.valueAtCenter()
- controlPrices_.valueAtCenter()
+ black.value();
results.delta = prices_.firstDerivativeAtCenter()
- controlPrices_.firstDerivativeAtCenter()
+ black.delta(spot);
results.gamma = prices_.secondDerivativeAtCenter()
- controlPrices_.secondDerivativeAtCenter()
+ black.gamma(spot);
results.additionalResults["priceCurve"] = prices_;
}
//public FDStepConditionEngine(GeneralizedBlackScholesProcess process, int timeSteps, int gridPoints,
// bool timeDependent = false)
public FDStepConditionEngine(GeneralizedBlackScholesProcess process, int timeSteps, int gridPoints, bool timeDependent)
: base(process, timeSteps, gridPoints, timeDependent)
{
controlBCs_ = new InitializedList <BoundaryCondition <IOperator> >(2);
controlPrices_ = new SampledCurve(gridPoints);
}
