This class is a multivariate version of GeometricBrownianMotion. More...

Inheritance diagram for umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion:

Public Member Functions
	MultivariateGeometricBrownianMotion (int c, double[] x0, double[] mu, double[] sigma, MultivariateBrownianMotion mbm)
	Constructs a new MultivariateGeometricBrownianMotion with parameters \(\mu= \mathtt{mu}\), \(\sigma= \mathtt{sigma}\), and \(S(t_0) = \mathtt{x0}\), using mbm as the underlying.
void	setObservationTimes (double[] t, int d)
	Sets the observation times of the MultivariateGeometricBrownianMotion, but also those of the inner.
void	nextObservationVector (double[] obs)
	Generates and returns the vector of next observations.
double[]	generatePath ()
	Generates, returns, and saves the sample path.
void	resetStartProcess ()
	Same as in StochasticProcess, but also invokes resetStartProcess for the underlying BrownianMotion object.
void	setParams (int c, double[] x0, double[] mu, double[] sigma)
	Sets the parameters \(S(t_0) = \mathtt{x0}\), \(\mu= \mathtt{mu}\) and \(\sigma= \mathtt{sigma}\) of the process.
void	setStream (RandomStream stream)
	Resets the random stream for the underlying Brownian motion to stream.
RandomStream	getStream ()
	Returns the random stream for the underlying Brownian motion.
NormalGen	getGen ()
	Returns the normal random variate generator used.
MultivariateBrownianMotion	getBrownianMotion ()
	Returns a reference to the MultivariateBrownianMotion object used to generate the process.
Public Member Functions inherited from umontreal.ssj.stochprocess.MultivariateStochasticProcess
void	getSubpath (double[] subpath, int[] pathIndices)
	Returns in subpath the values of the process at a subset of the observation times, specified as the times \(t_j\) whose indices.
void	getObservation (int j, double[] obs)
	Returns \(\mathbf{X}(t_j)\) in the \(c\)-dimensional vector obs.
double	getObservation (int j, int i)
	Returns \(X_i(t_j)\) from the current sample path.
void	getCurrentObservation (double[] obs)
	Returns the value of the last generated observation.
double[]	getX0 (double[] x0)
	Returns in x0 the initial value \(\mathbf{X}(t_0)\) for this process.
int	getDimension ()
	Returns the dimension of \(\mathbf{X}\).
Public Member Functions inherited from umontreal.ssj.stochprocess.StochasticProcess
void	setObservationTimes (double delta, int d)
	Sets equidistant observation times at \(t_j = j\delta\), for.
double[]	getObservationTimes ()
	Returns a reference to the array that contains the observation times.
int	getNumObservationTimes ()
	Returns the number \(d\) of observation times, excluding the time \(t_0\).
double[]	generatePath (RandomStream stream)
	Same as generatePath(), but first resets the stream to stream.
double[]	getPath ()
	Returns a reference to the last generated sample path \(\{X(t_0), ... , X(t_d)\}\).
double	getObservation (int j)
	Returns \(X(t_j)\) from the current sample path.
boolean	hasNextObservation ()
	Returns true if \(j<d\), where \(j\) is the number of observations of the current sample path generated since the last call to resetStartProcess.
double	nextObservation ()
	Generates and returns the next observation \(X(t_j)\) of the stochastic process.
int	getCurrentObservationIndex ()
	Returns the value of the index \(j\) corresponding to the time.
double	getCurrentObservation ()
	Returns the value of the last generated observation \(X(t_j)\).
double	getX0 ()
	Returns the initial value \(X(t_0)\) for this process.
void	setX0 (double s0)
	Sets the initial value \(X(t_0)\) for this process to s0, and reinitializes.
int[]	getArrayMappingCounterToIndex ()
	Returns a reference to an array that maps an integer \(k\) to \(i_k\), the index of the observation \(S(t_{i_k})\) corresponding to the.

Detailed Description

This class is a multivariate version of GeometricBrownianMotion.

It represents a multivariate GBM process \(\{\mathbf{S}(t) = (S_1(t),…,S_c(t)), t\ge0\}\), which can be written as

\[ S_i(t) = S_i(0) \exp\left[ X_i(t) \right], \tag{GBM2} \]

where \(\mathbf{X}(t) = (X_1(t),…,X_c(t))\) is a multivariate Brownian motion. The GBM process is simulated by simulating the BM process \(\mathbf{X}\) (which is stored internally) and taking the exponential.

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Definition at line 45 of file MultivariateGeometricBrownianMotion.java.

Constructor & Destructor Documentation

◆ MultivariateGeometricBrownianMotion()

umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.MultivariateGeometricBrownianMotion	(	int	c,
		double[]	x0,
		double[]	mu,
		double[]	sigma,
		MultivariateBrownianMotion	mbm )

Constructs a new MultivariateGeometricBrownianMotion with parameters \(\mu= \mathtt{mu}\), \(\sigma= \mathtt{sigma}\), and \(S(t_0) = \mathtt{x0}\), using mbm as the underlying.

MultivariateBrownianMotion. The parameters of mbm are automatically reset to \(\mu-\sigma^2/2\) and \(\sigma\), regardless of the original parameters of mbm. The correlation structure is determined by the underlying MultivariateBrownianMotion. The observation times are the same as those of mbm. The generation method depends on that of mbm (sequential, bridge sampling, PCA, etc.).

Definition at line 65 of file MultivariateGeometricBrownianMotion.java.

Member Function Documentation

◆ generatePath()

double[] umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.generatePath ( )

Generates, returns, and saves the sample path.

\(\{\mathbf{X}(t_0), \mathbf{X}(t_1), …, \mathbf{X}(t_d)\}\), which can then be accessed via getPath, getSubpath, or getObservation. The generation method depends on the process type. If path[] denotes the returned array, then path[cj + i-1] contains \(X_i(t_j)\) for \(j=0,…,d\) and \(i=1,…,c\).

Reimplemented from umontreal.ssj.stochprocess.MultivariateStochasticProcess.

Definition at line 107 of file MultivariateGeometricBrownianMotion.java.

◆ getBrownianMotion()

MultivariateBrownianMotion umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.getBrownianMotion ( )

Returns a reference to the MultivariateBrownianMotion object used to generate the process.

Definition at line 182 of file MultivariateGeometricBrownianMotion.java.

◆ getGen()

NormalGen umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.getGen ( )

Returns the normal random variate generator used.

Definition at line 174 of file MultivariateGeometricBrownianMotion.java.

◆ getStream()

RandomStream umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.getStream ( )

Returns the random stream for the underlying Brownian motion.

Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.

Definition at line 167 of file MultivariateGeometricBrownianMotion.java.

◆ nextObservationVector()

void umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.nextObservationVector ( double[] obs )

Generates and returns the vector of next observations.

Reimplemented from umontreal.ssj.stochprocess.MultivariateStochasticProcess.

Definition at line 103 of file MultivariateGeometricBrownianMotion.java.

◆ resetStartProcess()

void umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.resetStartProcess ( )

Same as in StochasticProcess, but also invokes resetStartProcess for the underlying BrownianMotion object.

Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.

Definition at line 122 of file MultivariateGeometricBrownianMotion.java.

◆ setObservationTimes()

void umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.setObservationTimes	(	double[]	t,
		int	d )

Sets the observation times of the MultivariateGeometricBrownianMotion, but also those of the inner.

MultivariateBrownianMotion.

Reimplemented from umontreal.ssj.stochprocess.MultivariateStochasticProcess.

Definition at line 77 of file MultivariateGeometricBrownianMotion.java.

◆ setParams()

void umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.setParams	(	int	c,
		double[]	x0,
		double[]	mu,
		double[]	sigma )

Sets the parameters \(S(t_0) = \mathtt{x0}\), \(\mu= \mathtt{mu}\) and \(\sigma= \mathtt{sigma}\) of the process.

Warning: This method will recompute some quantities stored internally, which may be slow if called repeatedly.

Definition at line 133 of file MultivariateGeometricBrownianMotion.java.

◆ setStream()

void umontreal.ssj.stochprocess.MultivariateGeometricBrownianMotion.setStream ( RandomStream stream )

Resets the random stream for the underlying Brownian motion to stream.

Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.

Definition at line 160 of file MultivariateGeometricBrownianMotion.java.

The documentation for this class was generated from the following file:

src/main/java/umontreal/ssj/stochprocess/MultivariateGeometricBrownianMotion.java

SSJ API Documentation Stochastic Simulation in Java

Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ MultivariateGeometricBrownianMotion()

Member Function Documentation

◆ generatePath()

◆ getBrownianMotion()

◆ getGen()

◆ getStream()

◆ nextObservationVector()

◆ resetStartProcess()

◆ setObservationTimes()

◆ setParams()

◆ setStream()