Class MCSSolution

java.lang.Object
  Solution
      SamplingSolution
          MCSSolution

Direct Known Subclasses:

MCSDrawSolution

public class MCSSolution

extends SamplingSolution

MCSSolution -- contains the Monte Carlo Sampling solution

Version:

$Revision: 1.13 $

See Also:

ParticleSolution, Solution

Field Summary

protected double[][]	currentState A vector with the current realisation(s) evolved from initial price(s)
protected double	kappa The exponent in the random walk
protected double[][]	mark A vector with the current markers keeping track of price history
protected int	numberOfRealisations The number of independent realisations to evolve
protected ShapeFunction	option The terminal payoff
protected java.util.Random	random Random number generator
protected double	rate The interest rate
protected boolean	solutionUpToDate Whether the expected solution is up to date
protected double	strike The default initial / terminal condition

Fields inherited from class Solution

df, dfm, dfp, dg, dgm, dgp, dx, f, f0, fm, fp, g, gm, gp, ic, initialMoments, mesh, method, scheme, time, topic, x, x_0, x_1, xOffset, xSize, y_0, y_1, yOffset, ySize

Constructor Summary

MCSSolution(RunData runData)
Creates a MCSSolution object.

Method Summary

void	discretize(ShapeFunction function) Discretize the initial Shape function and initialize the moments Initializes a new set of particles, the number being determined by the numerical scheme parameter.
protected void	expectedValue() Generates a probability distribution and an expectation from the set of sampled values.
double	getValue(double arg) Linear interpolation of the solution.
double	getValue(int index) Gives the value of the function for an index
boolean	hasOption(java.lang.String option) Tells whether the solution implements a option
double[]	limits() Calculates the limits of the solution.
double	momentsDeviation(int m) Calculates the deviation from the m:th initial moment.
boolean	next(RunData runData) Advance the solution forward one step in time.
void	plot(java.awt.Canvas plotArea, java.awt.Image offScrImage, boolean headers) Plots the solution
boolean	previous(RunData runData) Take the solution backward one step to initialize schemes with 3 time levels; not really appropriate in this context.

Methods inherited from class Solution

calculateMoments, getTime, getWinSize, incTime, limits, measure, output, rescale, setIC, setMethod, setScheme, setTime, setTopic, updateHeaders

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

option

protected ShapeFunction option

The terminal payoff

numberOfRealisations

protected int numberOfRealisations

The number of independent realisations to evolve

currentState

protected double[][] currentState

A vector with the current realisation(s) evolved from initial price(s)

mark

protected double[][] mark

A vector with the current markers keeping track of price history

kappa

protected double kappa

The exponent in the random walk

rate

protected double rate

The interest rate

strike

protected double strike

The default initial / terminal condition

solutionUpToDate

protected boolean solutionUpToDate

Whether the expected solution is up to date

random

protected java.util.Random random

Random number generator

Constructor Detail

MCSSolution

public MCSSolution(RunData runData)

Creates a MCSSolution object. discretize must be called before next is called for the first time.

Parameters:

runData - The run time parameters

See Also:

Solution.next(RunData), Solution.discretize(ShapeFunction)

Method Detail

next

public boolean next(RunData runData)

Advance the solution forward one step in time. The equation is set by the internal variable method and the numerical scheme by the internal variable scheme

Specified by:

next in class Solution

Parameters:

runData - List of run parameters

Returns:

True if a scheme is implemented for that equation

See Also:

RunData

hasOption

public boolean hasOption(java.lang.String option)

Tells whether the solution implements a option

Specified by:

hasOption in class Solution

Parameters:

option - The the option to implement

Returns:

True if the option is implemented

See Also:

vmarket.topicNames, vmarket.schemeNames

plot

public void plot(java.awt.Canvas plotArea,
                 java.awt.Image offScrImage,
                 boolean headers)

Plots the solution

Overrides:

plot in class Solution

Parameters:

plotArea - The plot area

offScrImage - The off screen image to draw on

headers - Whether to draw headers

previous

public boolean previous(RunData runData)

Take the solution backward one step to initialize schemes with 3 time levels; not really appropriate in this context.

Specified by:

previous in class Solution

Parameters:

runData - List of run parameters

Returns:

False since it is not used here

See Also:

RunData

discretize

public void discretize(ShapeFunction function)

Discretize the initial Shape function and initialize the moments Initializes a new set of particles, the number being determined by the numerical scheme parameter.

Specified by:

discretize in class Solution

Parameters:

function - The initial shape to be approximated

See Also:

Solution.setScheme(java.lang.String)

momentsDeviation

public double momentsDeviation(int m)

Calculates the deviation from the m:th initial moment.

Overrides:

momentsDeviation in class Solution

Parameters:

m - The order of the moment

Returns:

The deviation of the m:th moment from the beginning

limits

public double[] limits()

Calculates the limits of the solution.

Returns:

A vector consisting of {min(solution), max(solution)}

getValue

public double getValue(int index)

Gives the value of the function for an index

Overrides:

getValue in class Solution

Parameters:

index - The index for which to get the value

Returns:

The value of the distribution function at a given index

getValue

public double getValue(double arg)

Linear interpolation of the solution. Assumes a uniform mesh.

Overrides:

getValue in class Solution

Parameters:

arg - Argument

Returns:

A linear interpolation of the function for a given argument

expectedValue

protected void expectedValue()

Generates a probability distribution and an expectation from the set of sampled values. Assumes a uniform mesh.