public FDEuropeanEngine(GeneralizedBlackScholesProcess process, int timeSteps, int gridPoints, bool timeDependent)
: base(process, timeSteps, gridPoints, timeDependent)
{
prices_ = new SampledCurve(gridPoints);
process.registerWith(update);
}
public FDEuropeanEngine(GeneralizedBlackScholesProcess process, int timeSteps, int gridPoints, bool timeDependent)
: base(process, timeSteps, gridPoints, timeDependent)
{
prices_ = new SampledCurve(gridPoints);
process.registerWith(update);
}
public StulzEngine(GeneralizedBlackScholesProcess process1, GeneralizedBlackScholesProcess process2, double correlation)
{
process1_ = process1;
process2_ = process2;
rho_ = correlation;
process1_.registerWith(update);
process2_.registerWith(update);
}
public AnalyticDoubleBarrierEngine(GeneralizedBlackScholesProcess process, int series = 5)
{
process_ = process;
series_ = series;
f_ = new CumulativeNormalDistribution();
process_.registerWith(update);
}
public BinomialVanillaEngine(GeneralizedBlackScholesProcess process, int timeSteps)
{
process_ = process;
timeSteps_ = timeSteps;
Utils.QL_REQUIRE(timeSteps > 0, () => "timeSteps must be positive, " + timeSteps + " not allowed");
process_.registerWith(update);
}
public AnalyticBSMHullWhiteEngine(double equityShortRateCorrelation,
GeneralizedBlackScholesProcess process,
HullWhite model)
: base(model)
{
rho_ = equityShortRateCorrelation;
process_ = process;
process_.registerWith(update);
}
public BinomialVanillaEngine(GeneralizedBlackScholesProcess process, int timeSteps)
{
process_ = process;
timeSteps_ = timeSteps;
if (!(timeSteps > 0))
{
throw new ApplicationException("timeSteps must be positive, " + timeSteps + " not allowed");
}
process_.registerWith(update);
}
// Constructor
public FdBlackScholesRebateEngine(
GeneralizedBlackScholesProcess process,
int tGrid = 100, int xGrid = 100, int dampingSteps = 0,
FdmSchemeDesc schemeDesc = null,
bool localVol = false,
double?illegalLocalVolOverwrite = null)
{
process_ = process;
tGrid_ = tGrid;
xGrid_ = xGrid;
dampingSteps_ = dampingSteps;
schemeDesc_ = schemeDesc == null ? new FdmSchemeDesc().Douglas() : schemeDesc;
localVol_ = localVol;
illegalLocalVolOverwrite_ = illegalLocalVolOverwrite;
process_.registerWith(update);
}
/*! \param maxTimeSteps is used to limit timeSteps when using Boyle-Lau
* optimization. If zero (the default) the maximum number of
* steps is calculated by an heuristic: anything when < 1000,
* otherwise no more than 5*timeSteps.
* If maxTimeSteps is equal to timeSteps Boyle-Lau is disabled.
* Likewise if the lattice is not CoxRossRubinstein Boyle-Lau is
* disabled and maxTimeSteps ignored.
*/
public BinomialBarrierEngine(GetTree getTree, GetAsset getAsset,
GeneralizedBlackScholesProcess process, int timeSteps, int maxTimeSteps = 0)
{
process_ = process;
timeSteps_ = timeSteps;
maxTimeSteps_ = maxTimeSteps;
getTree_ = getTree;
getAsset_ = getAsset;
Utils.QL_REQUIRE(timeSteps > 0, () =>
"timeSteps must be positive, " + timeSteps + " not allowed");
Utils.QL_REQUIRE(maxTimeSteps == 0 || maxTimeSteps >= timeSteps, () =>
"maxTimeSteps must be zero or greater than or equal to timeSteps, " + maxTimeSteps + " not allowed");
if (maxTimeSteps_ == 0)
{
maxTimeSteps_ = Math.Max(1000, timeSteps_ * 5);
}
process_.registerWith(update);
}
// constructor
public MCDiscreteAveragingAsianEngine(
GeneralizedBlackScholesProcess process,
int maxTimeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
bool controlVariate,
int requiredSamples,
double requiredTolerance,
int maxSamples,
ulong seed) : base(antitheticVariate, controlVariate)
{
process_ = process;
maxTimeStepsPerYear_ = maxTimeStepsPerYear;
requiredSamples_ = requiredSamples;
maxSamples_ = maxSamples;
requiredTolerance_ = requiredTolerance;
brownianBridge_ = brownianBridge;
seed_ = seed;
process_.registerWith(update);
}
public FdBlackScholesVanillaEngine(
GeneralizedBlackScholesProcess process,
FdmQuantoHelper quantoHelper = null,
int tGrid = 100, int xGrid = 100, int dampingSteps = 0,
FdmSchemeDesc schemeDesc = null,
bool localVol = false,
double?illegalLocalVolOverwrite = null,
CashDividendModel cashDividendModel = CashDividendModel.Spot)
{
process_ = process;
tGrid_ = tGrid;
xGrid_ = xGrid;
dampingSteps_ = dampingSteps;
schemeDesc_ = schemeDesc == null ? new FdmSchemeDesc().Douglas() : schemeDesc;
localVol_ = localVol;
illegalLocalVolOverwrite_ = illegalLocalVolOverwrite;
quantoHelper_ = quantoHelper;
process_.registerWith(update);
}
public MCBarrierEngine(GeneralizedBlackScholesProcess process,
int?timeSteps,
int?timeStepsPerYear,
bool brownianBridge,
bool antitheticVariate,
int?requiredSamples,
double?requiredTolerance,
int?maxSamples,
bool isBiased,
ulong seed)
: base(antitheticVariate, false)
{
process_ = process;
timeSteps_ = timeSteps;
timeStepsPerYear_ = timeStepsPerYear;
requiredSamples_ = requiredSamples;
maxSamples_ = maxSamples;
requiredTolerance_ = requiredTolerance;
isBiased_ = isBiased;
brownianBridge_ = brownianBridge;
seed_ = seed;
Utils.QL_REQUIRE(timeSteps != null || timeStepsPerYear != null, () => "no time steps provided");
Utils.QL_REQUIRE(timeSteps == null || timeStepsPerYear == null, () => "both time steps and time steps per year were provided");
if (timeSteps != null)
{
Utils.QL_REQUIRE(timeSteps > 0, () => "timeSteps must be positive, " + timeSteps + " not allowed");
}
if (timeStepsPerYear != null)
{
Utils.QL_REQUIRE(timeStepsPerYear > 0, () => "timeStepsPerYear must be positive, " + timeStepsPerYear + " not allowed");
}
process_.registerWith(update);
}
public AnalyticDiscreteGeometricAveragePriceAsianEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public AnalyticBarrierWithPartiRateEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
//registerWith(process_);
process_.registerWith(update);
}
public BaroneAdesiWhaleyApproximationEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
//public FDEngineAdapter(GeneralizedBlackScholesProcess process, Size timeSteps=100, Size gridPoints=100, bool timeDependent = false)
public FDEngineAdapter(GeneralizedBlackScholesProcess process, int timeSteps, int gridPoints, bool timeDependent)
{
optionBase = (Base) new Base().factory(process, timeSteps, gridPoints, timeDependent);
process.registerWith(update);
}
public AnalyticPerformanceEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public JuQuadraticApproximationEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
//registerWith(process_);
process_.registerWith(update);
}
public AnalyticBarrierEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
//registerWith(process_);
process_.registerWith(update);
}
public JuQuadraticApproximationEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public BaroneAdesiWhaleyApproximationEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public IntegralEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public ForwardVanillaEngine(GeneralizedBlackScholesProcess process, GetOriginalEngine getEngine)
{
process_ = process;
process_.registerWith(update);
getOriginalEngine_ = getEngine;
}
public AnalyticBinaryBarrierEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public AnalyticContinuousGeometricAveragePriceAsianEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public AnalyticContinuousPartialFixedLookbackEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public BjerksundStenslandApproximationEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public AnalyticEuropeanEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public AnalyticDividendEuropeanEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}
public BjerksundStenslandApproximationEngine(GeneralizedBlackScholesProcess process) {
process_ = process;
process_.registerWith(update);
}
public IntegralEngine(GeneralizedBlackScholesProcess process)
{
process_ = process;
process_.registerWith(update);
}