Search results for "fractional Brownian motion"

showing 9 items of 9 documents

Parameter Estimation for α-Fractional Bridges

2013

Let α, T > 0. We study the asymptotic properties of a least squares estimator for the parameter α of a fractional bridge defined as \(\mathrm{d}X_{t} = -\alpha \, \frac{X_{t}} {T-t}\,\mathrm{d}t + \mathrm{d}B_{t}\), 0 ≤ t \frac{1} {2}\). Depending on the value of α, we prove that we may have strong consistency or not as t → T. When we have consistency, we obtain the rate of this convergence as well. Also, we compare our results to the (known) case where B is replaced by a standard Brownian motion W.

CombinatoricsPhysicssymbols.namesakeFractional Brownian motionWiener processEstimation theoryConsistency (statistics)symbolsStrong consistencyBrownian motion
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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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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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Acceleration of diffusion in randomly switching potential with supersymmetry

2004

We investigate the overdamped Brownian motion in a supersymmetric periodic potential switched by Markovian dichotomous noise between two configurations. The two configurations differ from each other by a shift of one-half period. The calculation of the effective diffusion coefficient is reduced to the mean first passage time problem. We derive general equations to calculate the effective diffusion coefficient of Brownian particles moving in arbitrary supersymmetric potential. For the sawtooth potential, we obtain the exact expression for the effective diffusion coefficient, which is valid for the arbitrary mean rate of potential switchings and arbitrary intensity of white Gaussian noise. We…

PhysicsStochastic differential equationRandomly Switching PotentialFractional Brownian motionDiffusion processAnomalous diffusionQuantum mechanicsMathematical analysisEffective diffusion coefficientDiffusion (business)First-hitting-time modelBrownian motionPhysical Review E
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Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion

2021

In this article, we propose a test of the dynamics of stock market indexes typical of the US and EU capital markets in order to determine which of the two fundamental hypotheses, efficient market hypothesis (EMH) or fractal market hypothesis (FMH), best describes market behavior. The article’s major goal is to show how to appropriately model return distributions for financial market indexes, specifically which geometric Brownian motion (GBM) and geometric fractional Brownian motion (GFBM) dynamic equations best define the evolution of the S&P 500 and Stoxx Europe 600 stock indexes. Daily stock index data were acquired from the Thomson Reuters Eikon database during a ten-year period, fro…

Rescaled rangeHurst exponentefficient market hypothesisGeometric Brownian motionFractional Brownian motionGeneral MathematicsFinancial marketgeometric fractional Brownian motionStock market indexFractalgeometric Brownian motion; geometric fractional Brownian motion; efficient market hypothesis; fractal market hypothesisfractal market hypothesisOrder (exchange)QA1-939Computer Science (miscellaneous)Econometricsgeometric Brownian motionEngineering (miscellaneous)MathematicsMathematicsMathematics
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Rough linear PDE's with discontinuous coefficients - existence of solutions via regularization by fractional Brownian motion

2020

We consider two related linear PDE's perturbed by a fractional Brownian motion. We allow the drift to be discontinuous, in which case the corresponding deterministic equation is ill-posed. However, the noise will be shown to have a regularizing effect on the equations in the sense that we can prove existence of solutions for almost all paths of the fractional Brownian motion.

Statistics and ProbabilityFractional Brownian motion010102 general mathematicsMathematical analysisProbability (math.PR)fractional Brownian motionlocal times01 natural sciencesRegularization (mathematics)VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410010104 statistics & probabilityDeterministic equation60H05FOS: Mathematics60H1560J5560H1060G220101 mathematicsStatistics Probability and Uncertaintystochastic PDEsrough pathsregularization by noiseMathematics - ProbabilityMathematics
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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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Statistical mechanics characterization of spatio-compositional inhomogeneity

2009

On the basis of a model system of pillars built of unit cubes, a two-component entropic measure for the multiscale analysis of spatio-compositional inhomogeneity is proposed. It quantifies the statistical dissimilarity per cell of the actual configurational macrostate and the theoretical reference one that maximizes entropy. Two kinds of disorder compete: i) the spatial one connected with possible positions of pillars inside a cell (the first component of the measure), ii) the compositional one linked to compositions of each local sum of their integer heights into a number of pillars occupying the cell (the second component). As both the number of pillars and sum of their heights are conser…

Statistics and ProbabilityPhysicsFractional Brownian motionStatistical Mechanics (cond-mat.stat-mech)Entropy (statistical thermodynamics)PillarTime evolutionFOS: Physical sciencesModel systemStatistical mechanicsCondensed Matter PhysicsCombinatoricsUnit cubeStatistical physicsCondensed Matter - Statistical Mechanics
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Bayesian semiparametric long memory models for discretized event data

2020

We introduce a new class of semiparametric latent variable models for long memory discretized event data. The proposed methodology is motivated by a study of bird vocalizations in the Amazon rain forest; the timings of vocalizations exhibit self-similarity and long range dependence. This rules out Poisson process based models where the rate function itself is not long range dependent. The proposed class of FRActional Probit (FRAP) models is based on thresholding, a latent process. This latent process is modeled by a smooth Gaussian process and a fractional Brownian motion by assuming an additive structure. We develop a Bayesian approach to inference using Markov chain Monte Carlo and show g…

mallintaminenFOS: Computer and information sciencesStatistics and Probabilitylong range dependenceaikasarjatMarkovin ketjutfractional Brownian motionsademetsätekologinen mallinnusStatistics - ApplicationsArticleMethodology (stat.ME)fractalApplications (stat.AP)AmazonStatistics - Methodologylatent Gaussian process modelstodennäköisyyslaskentanonparametric Bayesbayesilainen menetelmägaussiset prosessitmatemaattinen tilastotiedeluonnonäänetlinnut -- äänetluonnon monimuotoisuusMonte Carlo -menetelmätComputer Science::SoundModeling and Simulationprobitfraktaalittime seriesStatistics Probability and UncertaintyThe Annals of Applied Statistics
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