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finmath lib is a Mathematical Finance Library in Java.
It provides algorithms and methodologies related to mathematical finance.
/*
* (c) Copyright Christian P. Fries, Germany. Contact: [email protected].
*
* Created on 20.05.2005
*/
package net.finmath.montecarlo;
import java.time.LocalDateTime;
import java.util.Map;
import net.finmath.exception.CalculationException;
import net.finmath.modelling.Model;
import net.finmath.stochastic.RandomVariable;
import net.finmath.time.TimeDiscretization;
/**
* The interface implemented by a simulation of an SDE.
* Provides the dimension of the SDE and the the time discretization of the
* simulation.
*
* @author Christian Fries
* @version 1.0
*/
public interface MonteCarloSimulationModel extends Model {
/**
* Returns the numberOfPaths.
*
* @return Returns the numberOfPaths.
*/
int getNumberOfPaths();
/**
* Returns the model's date corresponding to the time discretization's \( t = 0 \).
*
* @return The model's date corresponding to the time discretization's \( t = 0 \).
*/
default LocalDateTime getReferenceDate() {
// TODO remove default value in 4.0.0 - this is only for backward compatiblity.
return null;
}
/**
* Returns the timeDiscretizationFromArray.
*
* @return Returns the timeDiscretizationFromArray.
*/
TimeDiscretization getTimeDiscretization();
/**
* Returns the time for a given time index.
*
* @param timeIndex Time index
* @return Returns the time for a given time index.
*/
double getTime(int timeIndex);
/**
* Returns the time index for a given time.
*
* @param time The time.
* @return Returns the time index for a given time.
*/
int getTimeIndex(double time);
/**
* Returns a random variable which is initialized to a constant,
* but has exactly the same number of paths or discretization points as the ones used by this MonteCarloSimulationModel.
*
* @param value The constant value to be used for initialized the random variable.
* @return A new random variable.
*/
RandomVariable getRandomVariableForConstant(double value);
/**
* This method returns the weights of a weighted Monte Carlo method (the probability density).
*
* @param timeIndex Time index at which the process should be observed
* @return A vector of positive weights which sums up to one
* @throws net.finmath.exception.CalculationException Thrown if the valuation fails, specific cause may be available via the cause() method.
*/
RandomVariable getMonteCarloWeights(int timeIndex) throws CalculationException;
/**
* This method returns the weights of a weighted Monte Carlo method (the probability density).
*
* @param time Time at which the process should be observed
* @return A vector of positive weights which sums up to one
* @throws net.finmath.exception.CalculationException Thrown if the valuation fails, specific cause may be available via the cause() method.
*/
RandomVariable getMonteCarloWeights(double time) throws CalculationException;
/**
* Create a clone of this simulation modifying some of its properties (if any).
*
* The properties that should be modified correspond to arguments of constructors. A constructor is then called
* with where all arguments that are not found in the key value map are being set to this objects values.
*
* @param dataModified The data which should be changed in the new model. This is a key value may, where the key corresponds to the name of a property in one of the objects constructors.
* @return Returns a clone of this object, with some data modified (then it is no longer a clone :-)
* @throws net.finmath.exception.CalculationException Thrown if the valuation fails, specific cause may be available via the cause() method.
*/
MonteCarloSimulationModel getCloneWithModifiedData(Map dataModified) throws CalculationException;
}