Class MCLDBarrierEngine

Namespace: NanoQL.PricingEngines

Assembly: NanoQL.dll

MCBarrierEngine on low-discrepancy draws with QuantLib's default statistics: QuantLib-Python's MCLDBarrierEngine, QuantLib's MCBarrierEngine<LowDiscrepancy>, its calculations closed at LowDiscrepancy and GeneralStatistics.

public static class MCLDBarrierEngine

Inheritance: object

MCLDBarrierEngine

Inherited Members: object.GetType()

object.MemberwiseClone()

object.ToString()

object.Equals(object)

object.Equals(object, object)

object.ReferenceEquals(object, object)

object.GetHashCode()

Methods

Calculate(BarrierOption, EvaluationContext, GeneralizedBlackScholesProcess, int?, int?, bool, bool, int?, double?, int?, bool, long)

Prices a barrier option by Monte Carlo.

public static OneAssetOptionResults Calculate(BarrierOption option, EvaluationContext context, GeneralizedBlackScholesProcess process, int? timeSteps, int? timeStepsPerYear, bool brownianBridge, bool antitheticVariate, int? requiredSamples, double? requiredTolerance, int? maxSamples, bool isBiased, long seed)

Parameters

option BarrierOption: The option.
context EvaluationContext: The evaluation context.
process GeneralizedBlackScholesProcess: The Black-Scholes process.
timeSteps int?: The number of time steps, or null for steps per year.
timeStepsPerYear int?: The number of time steps per year, or null for a number of steps.
brownianBridge bool: Whether the draws are ordered by a Brownian bridge.
antitheticVariate bool: Whether antithetic variates are used.
requiredSamples int?: The number of samples, or null.
requiredTolerance double?: The absolute tolerance, or null; it takes precedence.
maxSamples int?: The most samples for a tolerance, or null for no limit.
isBiased bool: Whether the barrier is checked at the path's points only.
seed long: The seed, in [1, 4294967295].

Returns

OneAssetOptionResults: The option's results, the NPV and the error estimate; the expired results when it has expired.

Exceptions

ArgumentNullException: The option, the context or the process is null.
ArgumentException: The time steps are given neither or both ways, or aren't positive.
ArgumentOutOfRangeException: A number of samples is negative, or the seed is outside its range.
NanoQLException: The exercise isn't European, the spot isn't positive or lies beyond the barrier ("barrier touched"), the payoff isn't plain vanilla, neither a tolerance nor a number of samples is given, or the samples can't reach the tolerance.