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Titlebook: Introduction to Stochastic Integration; K. L. Chung,R. J. Williams Textbook 1990Latest edition Springer Science+Business Media New York 19

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Extension of the Predictable Integrands,In this chapter, we show that the definition of the stochastic integral can be extended to a larger class of integrands than the predictable ones, when either a mild condition on the Doléans measure . is satisfied or . is continuous.
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Quadratic Variation Process,For the remainder of this book, we shall only consider integrators . which are . local martingales. By Proposition 1.9 these are automatically local .-martingales. A more extensive treatment, encompassing right continuous integrators would require more elaborate considerations which are not suitable for inclusion in this short book.
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Applications of the Ito Formula,A process . is a Brownian motion in . if and only if there is a standard filtration . such that . is a continuous local martingale with quadratic variation [M] satisfying
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Stochastic Differential Equations,In this chapter, we consider . (SDE’s) of the form., or equivalently in coordinate form. where . (.., .) is an .-dimensional Brownian motion (. ≥ 1) starting from the origin, and . : . → . ⊗ . and .: . → . are Borel measurable functions. Here . ⊗ ., . ≥ 1, . ≥ 1, denotes the space of . × . real-valued matrices with the norm. for . ∈ . ⊗ ..
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https://doi.org/10.1007/978-1-4612-4480-6Brownian motion; Martingale; Probability theory; Stochastic calculus; clsmbc; local martingale; local time
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The Ito Formula,rst proved it for the special case of integration with respect to Brownian motion. The essential aspects of Itô’s formula are conveyed by the following. If . is a continuous local martingale and . is a twice continuously differentiable real-valued function on ., then the Itô formula for .(..) is
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K. L. Chung,R. J. WilliamsAffordable, softcover reprint of a classic textbook.Authors‘ exposition consistently chooses clarity over brevity.Includes an expanded collection of exercises from the first edition
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