/// <overloads>
/// Initialize a new SinglePathGenerator.
/// </overloads>
/// <summary>
/// Initialize a new SinglePathGenerator with constant drift and variance,
/// sampled at the given number of equal time steps.
/// </summary>
/// <param name="generator">The generator.</param>
/// <param name="drift">
/// Constant drift of the Brownian random walks.
/// </param>
/// <param name="variance">
/// Constant variance.
/// </param>
/// <param name="time">
/// Time span which is sampled in <paramref name="timeSteps"/> equal time steps.
/// </param>
/// <param name="timeSteps">
/// Number of equal time steps at which the path will be sampled.
/// </param>
public SinglePathGenerator(IContinuousRng generator,
double drift, double variance, double time, int timeSteps)
: base(new SparseVector(1, drift), time, timeSteps)
{
if (variance < 0.0)
{
throw new ArgumentException("TODO: Variance can not be negative.");
}
ArrayGenerator = new RandomArrayGenerator(generator,
new SparseVector(TimeSteps, variance * time / TimeSteps));
}
/// <summary>
/// Initialize a new SinglePathGenerator with constant drift and variance.
/// </summary>
/// <remarks>
/// The initial time is assumed to be zero and must
/// <b>not</b> be included in the passed SparseVector.
/// </remarks>
/// <param name="generator">The generator.</param>
/// <param name="drift">
/// Constant drift of the Brownian random walks.
/// </param>
/// <param name="variance">
/// Constant variance.
/// </param>
/// <param name="times">
/// A <see cref="SparseVector"/> of explicitly specified times at which the
/// path will be sampled.
/// The initial time is assumed to be zero and must
/// <b>not</b> be included in the passed SparseVector.
/// </param>
public SinglePathGenerator(IContinuousRng generator,
double drift, double variance, SparseVector times)
: base(new SparseVector(1, drift), times)
{
if (variance < 0.0)
{
throw new ArgumentException("TODO: Variance can not be negative.");
}
ArrayGenerator = new RandomArrayGenerator(generator,
TimeDelays * variance);
}
private void InitializeGenerator(IContinuousRng generator, Matrix covariance)
{
SparseVector diagonal = covariance.Diagonal;
if (Count != diagonal.Length)
{
throw new ArgumentException("TODO: Covariance matrix does not match number of assets");
}
if (diagonal.Min() < 0.0)
{
throw new ArgumentException("TODO: Covariance matrix contains negative variance.");
}
ArrayGenerator = new RandomArrayGenerator(generator, covariance);
}
/// <summary>
/// different averages, different variances, covariance
/// </summary>
/// <param name="generator"></param>
/// <param name="covariance"></param>
public RandomArrayGenerator(
IContinuousRng generator, Matrix covariance)
{
if (covariance.RowCount != covariance.ColumnCount)
{
throw new ArgumentException("TODO: Covariance matrix must be square.");
}
if (covariance.RowCount == 0)
{
throw new ArgumentException("TODO: Null covariance matrix given.");
}
Count = covariance.RowCount;
_generator = generator;
_sqrtCovariance = Matrix.Sqrt(covariance);
}
/// <summary>
/// equal average, different variances, no covariance
/// </summary>
/// <param name="generator"></param>
/// <param name="variance"></param>
public RandomArrayGenerator(
IContinuousRng generator, SparseVector variance)
{
Count = variance.Length;
_generator = generator;
// TODO: replace by VML equiv. and check return
// status for exceptions
_sqrtVariance = SparseVector.Sqrt(variance);
for (int i = 0; i < _sqrtVariance.Length; i++)
{
if (variance[i] < 0.0)
{
throw new ArgumentOutOfRangeException(nameof(generator));
}
}
}
/// <summary>
/// Initialize a new SinglePathGenerator with a zero drift and time dependent path.
/// </summary>
/// <remarks>
/// The initial time is assumed to be zero and must
/// <b>not</b> be included in the passed SparseVector.
/// </remarks>
/// <param name="generator">The generator.</param>
/// <param name="variance">
/// A <see cref="SparseVector"/> of time-dependent variances.
/// </param>
/// <param name="times">
/// A <see cref="SparseVector"/> of explicitly specified times at which the
/// path will be sampled.
/// The initial time is assumed to be zero and must
/// <b>not</b> be included in the passed SparseVector.
/// </param>
public SinglePathGenerator(IContinuousRng generator,
SparseVector variance, SparseVector times)
: base(1, times.Length)
{
if (times[0] < 0.0)
{
throw new ArgumentException("TODO: First time can not be negative (times[0] must be >= 0.0).");
}
if (variance.Length != TimeSteps)
{
throw new ArgumentException("TODO: Size mismatch between variance and time SparseVectors.");
}
Times = times;
TimeDelays = AdjacentDifference(times);
Drift[0] = new SparseVector(times.Length);
ArrayGenerator = new RandomArrayGenerator(generator,
TimeDelays * variance);
}
/// <summary>
/// Initialize a new MultiPathGenerator with constant drifts and variances.
/// </summary>
/// <summary>
/// Initialize a new MultiPathGenerator which samples at explicitly specified times.
/// </summary>
/// <remarks>
/// The initial time is assumed to be zero and must
/// <b>not</b> be included in the passed SparseVector.
/// </remarks>
/// <param name="generator"></param>
/// <param name="drifts">
/// A <see cref="SparseVector"/> of constant drifts - one for each single asset.
/// </param>
/// <param name="covariance">
/// A covariance <see cref="Matrix"/> which encapsulates the relations between
/// the diffusion components of the single assets.
/// </param>
/// <param name="times">
/// A <see cref="SparseVector"/> of explicitly specified times at which the
/// path will be sampled.
/// The initial time is assumed to be zero and must
/// <b>not</b> be included in the passed SparseVector.
/// </param>
public MultiPathGenerator(IContinuousRng generator,
SparseVector drifts, Matrix covariance, SparseVector times)
: base(drifts, times)
{
InitializeGenerator(generator, covariance);
}
