Search results for "Malliavin Calculus"

showing 10 items of 21 documents

Bismut's Way of the Malliavin Calculus for Elliptic Pseudodifferential Operators on a Lie Group

2018

We give an adaptation of the Malliavin Calculus of Bismut type for a semi-group generated by a right-invariant elliptic pseudodifferential operator on a Lie group.

Pure mathematicsOperator (computer programming)Mathematics::ProbabilityMathematics::K-Theory and HomologyPseudodifferential operatorsLie group[MATH]Mathematics [math]Type (model theory)Malliavin calculusComputingMilieux_MISCELLANEOUSMathematicsSSRN Electronic Journal
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SOME RELATIONS BETWEEN BOUNDED BELOW ELLIPTIC OPERATORS AND STOCHASTIC ANALYSIS

2019

International audience; We apply Malliavin Calculus tools to the case of a bounded below elliptic rightinvariant Pseudodifferential operators on a Lie group. We give examples of bounded below pseudodifferential elliptic operators on R d by using the theory of Poisson process and the Garding inequality. In the two cases, there is no stochastic processes besides because the considered semi-groups do not preserve positivity.

Pure mathematicsStochastic process010102 general mathematicsLie groupPoisson processMalliavin calculus01 natural sciences[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]010104 statistics & probabilityElliptic operatorsymbols.namesakeBounded functionsymbols0101 mathematics[MATH]Mathematics [math]Mathematics
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$L_2$-variation of L\'{e}vy driven BSDEs with non-smooth terminal conditions

2016

We consider the $L_2$-regularity of solutions to backward stochastic differential equations (BSDEs) with Lipschitz generators driven by a Brownian motion and a Poisson random measure associated with a L\'{e}vy process $(X_t)_{t\in[0,T]}$. The terminal condition may be a Borel function of finitely many increments of the L\'{e}vy process which is not necessarily Lipschitz but only satisfies a fractional smoothness condition. The results are obtained by investigating how the special structure appearing in the chaos expansion of the terminal condition is inherited by the solution to the BSDE.

Statistics and Probability$L_{2}$-regularityPure mathematicsSmoothness (probability theory)Malliavin calculus010102 general mathematicsChaos expansionPoisson random measureFunction (mathematics)Lipschitz continuityMalliavin calculus01 natural sciencesLévy process010104 statistics & probabilityStochastic differential equationMathematics::ProbabilityLévy processesbackward stochastic differential equations0101 mathematicsL 2 -regularityBrownian motionMathematics - ProbabilityMathematics
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Mean square rate of convergence for random walk approximation of forward-backward SDEs

2020

AbstractLet (Y,Z) denote the solution to a forward-backward stochastic differential equation (FBSDE). If one constructs a random walk$B^n$from the underlying Brownian motionBby Skorokhod embedding, one can show$L_2$-convergence of the corresponding solutions$(Y^n,Z^n)$to$(Y, Z).$We estimate the rate of convergence based on smoothness properties, especially for a terminal condition function in$C^{2,\alpha}$. The proof relies on an approximative representation of$Z^n$and uses the concept of discretized Malliavin calculus. Moreover, we use growth and smoothness properties of the partial differential equation associated to the FBSDE, as well as of the finite difference equations associated to t…

Statistics and ProbabilityDiscretizationapproximation schemeMalliavin calculus01 natural sciences010104 statistics & probabilityconvergence rateMathematics::ProbabilityConvergence (routing)random walk approximation 2010 Mathematics Subject Classification: Primary 60H10FOS: MathematicsApplied mathematics0101 mathematicsBrownian motionrandom walk approximationMathematicsstokastiset prosessitSmoothness (probability theory)konvergenssiApplied Mathematics010102 general mathematicsProbability (math.PR)Backward stochastic differential equationsFunction (mathematics)Random walkfinite difference equation[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Rate of convergencebackward stochastic differential equations60G50 Secondary 60H3060H35approksimointidifferentiaaliyhtälötMathematics - Probability
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Malliavin Calculus and Skorohod Integration for Quantum Stochastic Processes

2000

A derivation operator and a divergence operator are defined on the algebra of bounded operators on the symmetric Fock space over the complexification of a real Hilbert space $\eufrak{h}$ and it is shown that they satisfy similar properties as the derivation and divergence operator on the Wiener space over $\eufrak{h}$. The derivation operator is then used to give sufficient conditions for the existence of smooth Wigner densities for pairs of operators satisfying the canonical commutation relations. For $\eufrak{h}=L^2(\mathbb{R}_+)$, the divergence operator is shown to coincide with the Hudson-Parthasarathy quantum stochastic integral for adapted integrable processes and with the non-causal…

Statistics and ProbabilityPure mathematics[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Integrable systemComplexificationSpace (mathematics)Malliavin calculus01 natural sciences81S25Fock space81S25; 60H07; 60G15010104 statistics & probabilitysymbols.namesakeOperator (computer programming)60H07FOS: Mathematics0101 mathematicsMathematical PhysicsMathematicsApplied Mathematics010102 general mathematicsProbability (math.PR)Hilbert spaceStatistical and Nonlinear Physics[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Bounded function60G15symbols[ MATH.MATH-PR ] Mathematics [math]/Probability [math.PR]Mathematics - Probability
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A note on Malliavin smoothness on the Lévy space

2017

We consider Malliavin calculus based on the Itô chaos decomposition of square integrable random variables on the Lévy space. We show that when a random variable satisfies a certain measurability condition, its differentiability and fractional differentiability can be determined by weighted Lebesgue spaces. The measurability condition is satisfied for all random variables if the underlying Lévy process is a compound Poisson process on a finite time interval. peerReviewed

Statistics and ProbabilitySmoothness (probability theory)matematiikkaLévy processMalliavin calculus010102 general mathematicsMalliavin calculus01 natural sciencesLévy processinterpolation010104 statistics & probability60H07Mathematics::ProbabilitySquare-integrable functionCompound Poisson processApplied mathematicsinterpolointiDifferentiable functiontila0101 mathematicsStatistics Probability and UncertaintyLp spaceRandom variable60G51MathematicsElectronic Communications in Probability
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Malliavin calculus of Bismut type without probability

2007

We translate in semigroup theory Bismut's way of the Malliavin calculus.

Statistics::TheoryH-derivativeMathematics::Operator AlgebrasProbability (math.PR)General ChemistryType (model theory)Malliavin calculusMalliavin derivativeMathematics::ProbabilityMathematics::K-Theory and HomologyFOS: MathematicsCalculusMathematics::Differential GeometryMathematics - ProbabilityMathematicsProceedings of the Indian Academy of Sciences - Section A
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What is Differential Stochastic Calculus?

1999

Some well known concepts of stochastic differential calculus of non linear systems corrupted by parametric normal white noise are here outlined. Ito and Stratonovich integrals concepts as well as Ito differential rule are discussed. Applications to the statistics of the response of some linear and non linear systems is also presented.

Stochastic differential equationMathematics::ProbabilityQuantum stochastic calculusMultivariable calculusStochastic calculusApplied mathematicsDifferential calculusTime-scale calculusMalliavin calculusDifferential (mathematics)Mathematics
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Stochastic Differential Calculus

1993

In many cases of engineering interest it has become quite common to use stochastic processes to model loadings resulting from earthquake, turbulent winds or ocean waves. In these circumstances the structural response needs to be adequately described in a probabilistic sense, by evaluating the cumulants or the moments of any order of the response (see e.g. [1, 2]). In particular, for linear systems excited by normal input, the response process is normal too and the moments or the cumulants up to the second order fully characterize the probability density function of both input and output processes. Many practical problems involve processes which are approximately normal and the effect of the…

Stochastic differential equationQuantum stochastic calculusStochastic processComputer scienceLinear systemStochastic calculusTime-scale calculusStatistical physicsMalliavin calculusCumulant
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Stochastic Differential Equations

2020

Stochastic differential equations describe the time evolution of certain continuous n-dimensional Markov processes. In contrast with classical differential equations, in addition to the derivative of the function, there is a term that describes the random fluctuations that are coded as an Ito integral with respect to a Brownian motion. Depending on how seriously we take the concrete Brownian motion as the driving force of the noise, we speak of strong and weak solutions. In the first section, we develop the theory of strong solutions under Lipschitz conditions for the coefficients. In the second section, we develop the so-called (local) martingale problem as a method of establishing weak so…

Stochastic partial differential equationExamples of differential equationsStochastic differential equationWeak solutionApplied mathematicsMartingale (probability theory)Malliavin calculusNumerical partial differential equationsIntegrating factorMathematics
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