Search results for "Martingale"

showing 10 items of 30 documents

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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On decoupling in Banach spaces

2021

AbstractWe consider decoupling inequalities for random variables taking values in a Banach space X. We restrict the class of distributions that appear as conditional distributions while decoupling and show that each adapted process can be approximated by a Haar-type expansion in which only the pre-specified conditional distributions appear. Moreover, we show that in our framework a progressive enlargement of the underlying filtration does not affect the decoupling properties (in particular, it does not affect the constants involved). As a special case, we deal with one-sided moment inequalities for decoupled dyadic (i.e., Paley–Walsh) martingales and show that Burkholder–Davis–Gundy-type in…

Statistics and ProbabilityPure mathematicsGeneral MathematicsBanach space01 natural sciences010104 statistics & probabilityFOS: MathematicsFiltration (mathematics)decoupling in Banach spaces0101 mathematicsSpecial casestokastiset prosessitMathematicsMathematics::Functional Analysisdyadic martingalesProbability (math.PR)010102 general mathematicsDecoupling (cosmology)Conditional probability distributionBanachin avaruudetAdapted processMoment (mathematics)regular conditional probabilities60E15 60H05 46B09stochastic integrationStatistics Probability and UncertaintyfunktionaalianalyysiRandom variableMathematics - Probability
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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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Set-valued and fuzzy stochastic differential equations driven by semimartingales

2013

Abstract In the paper we present set-valued and fuzzy stochastic integrals with respect to semimartingale integrators as well as their main properties. Then we study the existence of solutions to set-valued and fuzzy-set-valued stochastic differential equations driven by semimartingales. The stability of solutions is also established.

Stratonovich integralApplied MathematicsMathematical analysisStochastic calculusStability (learning theory)Fuzzy logicSet (abstract data type)Stochastic partial differential equationStochastic differential equationSemimartingaleMathematics::ProbabilityApplied mathematicsAnalysisMathematicsNonlinear Analysis-Theory Methods & Applications
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The Itô Integral

2014

The Ito integral allows us to integrate stochastic processes with respect to the increments of a Brownian motion or a somewhat more general stochastic process. We develop the Ito integral first for Brownian motion and then for generalized diffusion processes (so called Ito processes). In the third section, we derive the celebrated Ito formula. This is the chain rule for the Ito integral that enables us to do explicit calculations with the Ito integral. In the fourth section, we use the Ito formula to obtain a stochastic solution of the classical Dirichlet problem. This in turn is used in the fifth section in order to show that like symmetric simple random walk, Brownian motion is recurrent …

Stratonovich integralDirichlet problemSection (fiber bundle)Mathematics::ProbabilityStochastic processMathematical analysisLocal martingaleChain ruleDiffusion (business)Brownian motionMathematics
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Fuzzy Stochastic Integral Equations Driven by Martingales

2011

Exploiting the properties of set-valued stochastic trajectory integrals we consider a notion of fuzzy stochastic Lebesgue–Stieltjes trajectory integral and a notion of fuzzy stochastic trajectory integral with respect to martingale. Then we use these integrals in a formulation of fuzzy stochastic integral equations. We investigate the existence and uniqueness of solution to such the equations.

Stratonovich integralMathematical analysisMathematicsofComputing_NUMERICALANALYSISApplied mathematicsUniquenessMartingale (probability theory)Fuzzy logicStochastic integralMathematics
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Operator martingale decomposition and the Radon-Nikodym property in Banach spaces

2010

Abstract We consider submartingales and uniform amarts of maps acting between a Banach lattice and a Banach lattice or a Banach space. In this measure-free setting of martingale theory, it is known that a Banach space Y has the Radon–Nikodým property if and only if every uniformly norm bounded martingale defined on the Chaney–Schaefer l-tensor product E ⊗ ˜ l Y , where E is a suitable Banach lattice, is norm convergent. We present applications of this result. Firstly, an analogues characterization for Banach lattices Y with the Radon–Nikodým property is given in terms of a suitable set of submartingales (supermartingales) on E ⊗ ˜ l Y . Secondly, we derive a Riesz decomposition for uniform …

Uniform amartPure mathematicsDinculeanu operatorApproximation propertyEberlein–Šmulian theoremBanach spaceRadon–Nikodým propertyFinite-rank operatorBanach manifoldBanach lattice Banach space Bochner norm Cone absolutely summing operator Convergent martingale Convergent submartingale Dinculeanu operator Radon–Nikodým propertySettore MAT/05 - Analisi MatematicaLp spaceC0-semigroupBanach lattice Banach space Bochner norm Cone absolutely summing operator Convergent martingale Convergent submartingale Dinculeanu operator Radon–Nikodým property Uniform amartMathematicsDiscrete mathematicsMathematics::Functional AnalysisBanach spaceApplied MathematicsConvergent martingaleConvergent submartingaleBanach latticeBochner normCone absolutely summing operatorBounded functionAnalysis
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Recursion at the crossroads of sequence modeling, random trees, stochastic algorithms and martingales

2013

This monograph synthesizes several studies spanning from dynamical systems in the statistical analysis of sequences, to analysis of algorithms in random trees and discrete stochastic processes. These works find applications in various fields ranging from biological sequences to linear regression models, branching processes, through functional statistics and estimates of risk indicators for insurances. All the established results use, in one way or another, the recursive property of the structure under study, by highlighting invariants such as martingales, which are at the heart of this monograph, as tools as well as objects of study.

modèles auto-régressifs[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]estimation and prediction errorstochastic gradient algorithmschaîne de Markov à mémoire variable[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]Digital search treesvariable length Markov chainstrong laws for discrete martingalessuffix trietemps d'occurrences de motifsoptimisation stochastique.dynamical systemtrie des suffixesstochastic optimization.erreur d'estimation et de prédictionArbres digitaux de rechercheauto-regressive modelssystème dynamiquelois fortes de martingales discrètesalgorithmes de gradient stochastiques[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]occurrences time
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MR2407444 (2009e:60101) Labuschagne, Coenraad C. A. Join-semilattices of integrable set-valued martingales. Thai J. Math. 5 (2007), no. 1, 53--69. (R…

2009

Join-semilattices of integrable set-valued martingales

set-valued martingales
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MR2541232 (2010j:60101) Yong, Jiao; Lihua, Peng; Peide, Liu Atomic decompositions of Lorentz martingale spaces and applications. J. Funct. Spaces App…

2010

In this paper atomic decomposition theorems of martingales are considered. In particular, three atomic decomposition theorems for Lorentz martingale spacesHs p,q, Qp,q andDp,q, where 0 < p < 1, and 0 < q 1, are proved. As a consequence of these decompositions, the authors obtain a sufficient condition for a sublinear operator T, defined on the previous Lorentz martingale spaces Hs p,q, Qp,q and Dp,q and taking values in Lorentz spaces Lr, to be bounded. Also, a restricted weak-type interpolation theorem is established.

weak Orlicz space maximal function martingale space martingale inequality
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