Itô–Taylor expansion

E645107

The Itô–Taylor expansion is a stochastic generalization of the Taylor series that expresses solutions of stochastic differential equations as series involving iterated Itô integrals, forming the basis for higher-order numerical schemes.

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Statements (47)

Predicate Object
instanceOf generalization of Taylor series
mathematical concept
stochastic expansion
tool in stochastic analysis
accuracyCharacterization strong order of convergence
weak order of convergence
appliesTo Itô stochastic differential equations
stochastic differential equations
assumes adaptedness of coefficients to the filtration
existence and uniqueness of SDE solution
basedOn Itô calculus NERFINISHED
Itô integral NERFINISHED
component diffusion term expansion
drift term expansion
multi-index notation for iterated integrals
multiple stochastic integrals
dependsOn moments of the driving Wiener process
regularity of drift and diffusion coefficients
documentedIn Numerical Solution of Stochastic Differential Equations (Kloeden and Platen) NERFINISHED
enables high-order strong numerical methods for SDEs
high-order weak numerical methods for SDEs
systematic derivation of stochastic Runge–Kutta schemes
field numerical analysis
stochastic calculus
stochastic differential equations
generalizes Taylor series NERFINISHED
hasVariant strong Itô–Taylor expansion NERFINISHED
truncated Itô–Taylor scheme
weak Itô–Taylor expansion NERFINISHED
purpose derive higher-order numerical schemes for SDEs
express solutions of stochastic differential equations as series
obtain strong approximations of SDE solutions
obtain weak approximations of SDE solutions
relatedTo Euler–Maruyama scheme NERFINISHED
Itô’s lemma NERFINISHED
Kloeden–Platen methods NERFINISHED
Milstein scheme NERFINISHED
stochastic Runge–Kutta methods NERFINISHED
stochastic Taylor formula
typicalReference Eckhard Platen NERFINISHED
Peter E. Kloeden NERFINISHED
usedIn computational finance
engineering models with noise
numerical simulation of stochastic differential equations
stochastic modeling in biology
stochastic modeling in physics
uses iterated Itô integrals

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Milstein method relatedConcept Itô–Taylor expansion