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Itô calculus, named after Kiyosi Itô, extends the methods of calculus to stochastic processes such as Brownian motion (see Wiener process). It has important applications in mathematical finance, in stochastic differential equations, and more recently even in machine learning.
Standards, Overview & Integration with respect to Brownian motion
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integral stochastic itô process displaystyle processes martingale predictable adapted calculus brownian motion time int used bounded integrable respect defined local
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Brownian motion | instance of | extends the methods of calculus to stochastic processes | 0.80 | text |
| Brownian motion or | instance of | The prices of stocks and other traded financial assets can be modeled by stochastic processes | 0.80 | text |
| more often | instance of | The prices of stocks and other traded financial assets can be modeled by stochastic processes | 0.80 | text |
| geometric Brownian motion | instance of | The prices of stocks and other traded financial assets can be modeled by stochastic processes | 0.80 | text |
| martingale representation theorems | instance of | it is inadequate for other important topics | 0.80 | text |
| local times.The integral extends to all predictable | instance of | it is inadequate for other important topics | 0.80 | text |
| locally bounded integrands | instance of | it is inadequate for other important topics | 0.80 | text |
| in a unique way | instance of | it is inadequate for other important topics | 0.80 | text |
| such that the dominated convergence theorem holds | instance of | it is inadequate for other important topics | 0.80 | text |
| Itô's lemma | instance of | This is general enough to be able to apply techniques | 0.80 | text |
| Itô calculus | related to Differentiation in Itô calculus | The Itô | 0.60 | section |
| Itô calculus | related to Differentiation in Itô calculus | However | 0.60 | section |
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