Search results for "Reflected Brownian motion"

showing 6 items of 6 documents

Hard-wall interactions in soft matter systems: Exact numerical treatment

2011

An algorithm for handling hard-wall interactions in simulations of driven diffusive particle motion is proposed. It exploits an exact expression for the one-dimensional transition probability in the presence of a hard (reflecting) wall and therefore is numerically exact in the sense that it does not introduce any additional approximation beyond the usual discretization procedures. Studying two standard situations from soft matter systems, its performance is compared to the heuristic approaches used in the literature.

Fractional Brownian motionFrictionComputer simulationDiscretizationStochastic processHeuristic (computer science)Models TheoreticalBrownian bridgeDiffusionPhysical PhenomenaStable processReflected Brownian motionStatistical physicsMathematicsPhysical Review E
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Mean Escape Time in a System with Stochastic Volatility

2007

We study the mean escape time in a market model with stochastic volatility. The process followed by the volatility is the Cox Ingersoll and Ross process which is widely used to model stock price fluctuations. The market model can be considered as a generalization of the Heston model, where the geometric Brownian motion is replaced by a random walk in the presence of a cubic nonlinearity. We investigate the statistical properties of the escape time of the returns, from a given interval, as a function of the three parameters of the model. We find that the noise can have a stabilizing effect on the system, as long as the global noise is not too high with respect to the effective potential barr…

Physics - Physics and SocietyMean escape timeFOS: Physical sciencesPhysics and Society (physics.soc-ph)Heston modelFOS: Economics and businessEconometricsEconophysics; Mean escape time; Heston model; Stochastic modelStatistical physicsCondensed Matter - Statistical MechanicsMathematicsGeometric Brownian motionStatistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Stochastic volatilityStochastic processEconophysicQuantitative Finance - Statistical FinanceDisordered Systems and Neural Networks (cond-mat.dis-nn)Brownian excursionCondensed Matter - Disordered Systems and Neural NetworksSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Heston modelStochastic modelReflected Brownian motionVolatility (finance)Rendleman–Bartter model
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Dissipation and decoherence in Brownian motion

2007

We consider the evolution of a Brownian particle described by a measurement-based master equation. We derive the solution to this equation for general initial conditions and apply it to a Gaussian initial state. We analyse the effects of the diffusive terms, present in the master equation, and describe how these modify uncertainties and coherence length. This allows us to model dissipation and decoherence in quantum Brownian motion.

PhysicsHistoryGeometric Brownian motionFractional Brownian motionBrownian excursionHeavy traffic approximationComputer Science ApplicationsEducationClassical mechanicsReflected Brownian motionDiffusion processMaster equationFokker–Planck equationStatistical physicsJournal of Physics: Conference Series
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Fractional Brownian motion and Martingale-differences

2004

Abstract We generalize a result of Sottinen (Finance Stochastics 5 (2001) 343) by proving an approximation theorem for the fractional Brownian motion, with H> 1 2 , using martingale-differences.

Statistics and ProbabilityGeometric Brownian motionFractional Brownian motionMathematics::ProbabilityDiffusion processReflected Brownian motionMathematical analysisBrownian excursionStatistics Probability and UncertaintyHeavy traffic approximationMartingale (probability theory)Martingale representation theoremMathematicsStatistics & Probability Letters
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Erratum to “Simulation of BSDEs with jumps by Wiener Chaos expansion” [Stochastic Process. Appl. 126 (2016) 2123–2162]

2017

Abstract We correct Proposition 2.9 from “Simulation of BSDEs with jumps by Wiener Chaos expansion” published in Stochastic Processes and their Applications, 126 (2016) 2123–2162. The proposition which provides an expression for the expectation of products of multiple integrals (w.r.t. Brownian motion and compensated Poisson process) requires a stronger integrability assumption on the kernels than previously stated. This does not affect the remaining results of the article.

Statistics and ProbabilityPolynomial chaosStochastic processApplied MathematicsMultiple integral010102 general mathematicsMathematical analysisMotion (geometry)Poisson processExpression (computer science)01 natural sciences010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityReflected Brownian motionModeling and SimulationsymbolsApplied mathematics0101 mathematicsMathematicsStochastic Processes and their Applications
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BROWNIAN DYNAMICS SIMULATIONS WITHOUT GAUSSIAN RANDOM NUMBERS

1991

We point out that in a Brownian dynamics simulation it is justified to use arbitrary distribution functions of random numbers if the moments exhibit the correct limiting behavior prescribed by the Fokker-Planck equation. Our argument is supported by a simple analytical consideration and some numerical examples: We simulate the Wiener process, the Ornstein-Uhlenbeck process and the diffusion in a Φ4 potential, using both Gaussian and uniform random numbers. In these examples, the rate of convergence of the mean first exit time is found to be nearly identical for both types of random numbers.

Stochastic processMathematical analysisGeneral Physics and AstronomyStatistical and Nonlinear PhysicsOrnstein–Uhlenbeck processBrownian excursionBrownian bridgeComputer Science Applicationssymbols.namesakeComputational Theory and MathematicsWiener processReflected Brownian motionStochastic simulationsymbolsStatistical physicsGaussian processMathematical PhysicsMathematicsInternational Journal of Modern Physics C
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