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  2. Bernt Øksendal - Wikipedia

    en.wikipedia.org/wiki/Bernt_Øksendal

    In 1982 he taught a postgraduate course in stochastic calculus at the University of Edinburgh which led to the book Øksendal, Bernt K. (1982). Stochastic Differential Equations: An Introduction with Applications. Springer, Berlin. In 2005, he taught a course in stochastic calculus at the African Institute for Mathematical Sciences in Cape Town.

  3. Malliavin calculus - Wikipedia

    en.wikipedia.org/wiki/Malliavin_calculus

    The calculus has been applied to stochastic partial differential equations as well. The calculus allows integration by parts with random variables; this operation is used in mathematical finance to compute the sensitivities of financial derivatives. The calculus has applications in, for example, stochastic filtering.

  4. Stochastic differential equation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_differential...

    A stochastic differential equation (SDE) is a differential equation in which one or more of the terms is a stochastic process, [1] resulting in a solution which is also a stochastic process. SDEs have many applications throughout pure mathematics and are used to model various behaviours of stochastic models such as stock prices , [ 2 ] random ...

  5. Itô's lemma - Wikipedia

    en.wikipedia.org/wiki/Itô's_lemma

    Stochastic Integral. Proc. Imperial Acad. Tokyo 20, 519–524. This is the paper with the Ito Formula; Online; Kiyosi Itô (1951). On stochastic differential equations. Memoirs, American Mathematical Society 4, 1–51. Online; Bernt Øksendal (2000). Stochastic Differential Equations. An Introduction with Applications, 5th edition, corrected ...

  6. Geometric Brownian motion - Wikipedia

    en.wikipedia.org/wiki/Geometric_Brownian_motion

    A stochastic process S t is said to follow a GBM if it satisfies the following stochastic differential equation (SDE): = + where is a Wiener process or Brownian motion, and ('the percentage drift') and ('the percentage volatility') are constants.

  7. Skorokhod problem - Wikipedia

    en.wikipedia.org/wiki/Skorokhod_problem

    In probability theory, the Skorokhod problem is the problem of solving a stochastic differential equation with a reflecting boundary condition. [1] The problem is named after Anatoliy Skorokhod who first published the solution to a stochastic differential equation for a reflecting Brownian motion. [2] [3] [4]

  8. Talk:Ornstein–Uhlenbeck process - Wikipedia

    en.wikipedia.org/wiki/Talk:Ornstein–Uhlenbeck...

    How about Stochastic Differential Equations by Bernt Oksendal? There O-U and mean-reverting O-U processes are distinguished. Your point above about setting \mu=0 is valid but it makes pedagogic sense to introduce the \mu=0 case first I think —Preceding unsigned comment added by 131.111.16.20 08:57, 13 April 2009 (UTC)

  9. Infinitesimal generator (stochastic processes) - Wikipedia

    en.wikipedia.org/wiki/Infinitesimal_generator...

    In mathematics — specifically, in stochastic analysis — the infinitesimal generator of a Feller process (i.e. a continuous-time Markov process satisfying certain regularity conditions) is a Fourier multiplier operator [1] that encodes a great deal of information about the process.

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