Class MCVarianceSwapEngine

Namespace

NanoQL.PricingEngines

Assembly

NanoQL.dll

The Monte Carlo variance-swap engine: the variance the swap pays as the mean of the paths' realized variances, as described in Demeterfi, Derman, Kamal and Zou, "A Guide to Volatility and Variance Swaps" (1999).

public static class MCVarianceSwapEngine

Inheritance

object

MCVarianceSwapEngine

Inherited Members

object.GetType()

object.MemberwiseClone()

object.ToString()

object.Equals(object)

object.Equals(object, object)

object.ReferenceEquals(object, object)

object.GetHashCode()

Remarks

Stateless: each call runs its own simulation. It prices the variance from the evaluation date, whatever the swap's start date, as QuantLib documents ("does not manage seasoned variance swaps").

The path grid runs on the process's clock (Clock(GeneralizedBlackScholesProcess, FdmQuantoHelper?)), the earliest reference date of its structures, each read there accruing nothing before its own date, and the payment discounted by date (Divergences/McVarianceSwapMismatchedTimesTests.cs), where QuantLib's grid runs on the risk-free curve's time; on structures dated alike, QuantLib's.

Methods

Calculate<TRng, TStats>(VarianceSwap, EvaluationContext, GeneralizedBlackScholesProcess, int?, int?, bool, bool, int?, double?, int?, long)

Prices a variance swap by Monte Carlo.

public static VarianceSwapResults Calculate<TRng, TStats>(VarianceSwap swap, EvaluationContext context, GeneralizedBlackScholesProcess process, int? timeSteps, int? timeStepsPerYear, bool brownianBridge, bool antitheticVariate, int? requiredSamples, double? requiredTolerance, int? maxSamples, long seed) where TRng : IRngTraits where TStats : IStatistics, new()

Parameters

swap VarianceSwap

The variance swap.

context EvaluationContext

The evaluation context.

process GeneralizedBlackScholesProcess

The Black-Scholes process.

timeSteps int?

The number of time steps, or null.

timeStepsPerYear int?

The number of time steps per year, or null.

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.

seed long

The seed, in [1, 4294967295].

Returns

VarianceSwapResults

The swap's results: the NPV, the variance and, where the numbers give one, the error estimate.

Type Parameters

TRng

The random-number traits.

TStats

The statistics accumulator.

Exceptions

ArgumentNullException

The swap, the context or the process is null.

ArgumentException

The time steps are both given, neither, or not positive.

ArgumentOutOfRangeException

A number of samples is negative, or the seed is outside its range.

NanoQLException

Neither a tolerance nor a number of samples is given, or the samples can't reach the tolerance.