Search results for "Stochastic integral"

showing 9 items of 9 documents

On fractional smoothness and approximations of stochastic integrals

2009

Brownian motion processesStochastic integralsBrownin liikeintegraalilaskentastokastiset prosessit
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On the optimal approximation rate of certain stochastic integrals

2010

AbstractGiven an increasing function H:[0,1)→[0,∞) and An(H)≔infτ∈Tn(∑i=1n∫ti−1ti(ti−t)H(t)2dt)12, where Tn≔{τ=(ti)i=0n:0=t0<t1<⋯<tn=1}, we characterize the property An(H)≤cn, and give conditions for An(H)≤cnβ and An(H)≥1cnβ for β∈(0,1), both in terms of integrability properties of H. These results are applied to the approximation of stochastic integrals.

Discrete mathematicsMathematics(all)Numerical AnalysisRegular sequencesGeneral MathematicsApplied MathematicsStochastic integralsNon linear approximationFunction (mathematics)CombinatoricsNon-linear approximationFunction compositionAnalysisMathematicsJournal of Approximation Theory
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Martingale Convergence Theorems and Their Applications

2020

We became familiar with martingales X=(X n ) n∈N0 as fair games and found that under certain transformations (optional stopping, discrete stochastic integral) martingales turn into martingales. In this chapter, we will see that under weak conditions (non-negativity or uniform integrability) martingales converge almost surely. Furthermore, the martingale structure implies L p -convergence under assumptions that are (formally) weaker than those of Chapter 7. The basic ideas of this chapter are Doob’s inequality (Theorem 11.4) and the upcrossing inequality (Lemma 11.3).

Doob's martingale inequalityUniform integrabilityPure mathematicsDoob's martingale convergence theoremsLocal martingaleAlmost surelyMartingale (probability theory)Stock priceStochastic integralMathematics
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Response Correlations of Linear Systems with White Noise Linearly Parametric Inputs

1996

Relationships between moments and correlations of the response of linear systems subjected to linearly parametric normal white noise inputs are here reported. They are obtained by extensively using the properties of the stochastic integral calculus.

Linear systemApplied mathematicsWhite noiseStochastic integralParametric statisticsMathematics
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On fractional smoothness and Lp-approximation on the Wiener space

2015

Real interpolationBesov spacesStochastic analysis on a Gaussian spaceApproximation of stochastic integralsRiemann-Liouville operators
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On an approximation problem for stochastic integrals where random time nets do not help

2006

Abstract Given a geometric Brownian motion S = ( S t ) t ∈ [ 0 , T ] and a Borel measurable function g : ( 0 , ∞ ) → R such that g ( S T ) ∈ L 2 , we approximate g ( S T ) - E g ( S T ) by ∑ i = 1 n v i - 1 ( S τ i - S τ i - 1 ) where 0 = τ 0 ⩽ ⋯ ⩽ τ n = T is an increasing sequence of stopping times and the v i - 1 are F τ i - 1 -measurable random variables such that E v i - 1 2 ( S τ i - S τ i - 1 ) 2 ∞ ( ( F t ) t ∈ [ 0 , T ] is the augmentation of the natural filtration of the underlying Brownian motion). In case that g is not almost surely linear, we show that one gets a lower bound for the L 2 -approximation rate of 1 / n if one optimizes over all nets consisting of n + 1 stopping time…

Statistics and ProbabilityRandom time netsMeasurable functionStochastic processStochastic integralsApplied MathematicsUpper and lower boundsNatural filtrationCombinatoricsModeling and SimulationStopping timeModelling and SimulationAlmost surelyApproximationBorel measureBrownian motionMathematicsStochastic Processes and their Applications
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A stochastic integral of operator-valued functions.

2009

A stochastic integral of operator-valued functions.

Stochastic integral operator-valued functions.
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On Malliavin calculus and approximation of stochastic integrals for Lévy processes

2012

Stochastic integralsApproximation theoryMalliavian calculusStochastic analysisapproksimointiLévy processStochastic processstokastiset prosessit
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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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