Module net.finmath.lib
Package net.finmath.montecarlo
Provides basic interfaces and classes used in MonteCarlo models (like LIBOR market model or MonteCarlo simulation
of a BlackScholes model), e.g., the MonteCarlo random variable and the Brownian motion.
 Author:
 Christian Fries

Interface Summary Interface Description BrownianMotion Interface description of a timediscrete ndimensional Brownian motion W = (W_{1},...,W_{n}) where W_{i} is a Brownian motion.IndependentIncrements Interface description of a timediscrete ndimensional stochastic process \( X = (X_{1},\ldots,X_{n}) \) provided by independent increments \( \Delta X(t_{i}) = X(t_{i+1})X(t_{i}) \).MonteCarloProduct Interface for products requiring an MonteCarloSimulationModel for valuation.MonteCarloSimulationModel The interface implemented by a simulation of an SDE.RandomVariableFactory A factory for creating objects implementingnet.finmath.stochastic.RandomVariable
. 
Class Summary Class Description AbstractMonteCarloProduct Base class for products requiring an MonteCarloSimulationModel for valuation.AbstractRandomVariableFactory BrownianBridge This class implements a Brownian bridge, i.e., samples of realizations of a Brownian motion conditional to a given start and end value.BrownianMotionFromMersenneRandomNumbers Implementation of a timediscrete ndimensional Brownian motion W = (W_{1},...,W_{n}) where W_{i} is a Brownian motion and W_{i}, W_{j} are independent for i not equal j.BrownianMotionFromRandomNumberGenerator Implementation of a timediscrete ndimensional Brownian motion W = (W_{1},...,W_{n}) where W_{i} is a Brownian motion and W_{i}, W_{j} are independent for i not equal j.BrownianMotionLazyInit Deprecated. Refactor rename.BrownianMotionView A Brownian motion which is defined by some factors of a given Brownian motion, i.e., for a given multifactorial Brownian motion W, this Brownian motion is given by ( W(i[0]), W(i[1]) W(i[2]), ..., W(i[n1]) ) where i is a given array of integers.BrownianMotionWithControlVariate Provides a Brownian motion from given (independent) increments and performs a control of the expectation and the standard deviation.CorrelatedBrownianMotion Provides a correlated Brownian motion from given (independent) increments and a given matrix of factor loadings.GammaProcess Implementation of a timediscrete ndimensional Gamma process \( \Gamma = (\Gamma_{1},\ldots,\Gamma_{n}) \), where \( \Gamma_{i} \) is a Gamma process and \( \Gamma_{i} \), \( \Gamma_{j} \) are independent for i not equal j.IndependentIncrementsFromICDF Implementation of a timediscrete ndimensional sequence of independent increments W = (W_{1},...,W_{n}) form a given set of inverse cumulative distribution functions.JumpProcessIncrements Implementation of a timediscrete ndimensional jump process J = (J_{1},...,J_{n}) where J_{i} is a Poisson jump process and J_{i}, J_{j} are independent for i not equal j.MertonJumpProcess Implementation of the compound Poisson process for the Merton jump diffusion model.RandomVariableFloatFactory RandomVariableFromArrayFactory A factory (helper class) to create random variables.RandomVariableFromDoubleArray The class RandomVariableFromDoubleArray represents a random variable being the evaluation of a stochastic process at a certain time within a MonteCarlo simulation.RandomVariableFromFloatArray The class RandomVariableFromFloatArray represents a random variable being the evaluation of a stochastic process at a certain time within a MonteCarlo simulation.RandomVariableLazyEvaluation Implements a MonteCarlo random variable (likeRandomVariableFromDoubleArray
using late evaluation of Java 8 streams Accesses performed exclusively through the interfaceRandomVariable
is thread safe (and does not mutate the class).RandomVariableLazyEvaluationFactory VarianceGammaProcess Implementation of a timediscrete ndimensional Variance Gamma process via Brownian subordination through a Gamma Process.