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  2. Stochastic oscillator - Wikipedia

    en.wikipedia.org/wiki/Stochastic_oscillator

    Stochastic oscillator is a momentum indicator within technical analysis that uses support and resistance levels as an oscillator. George Lane developed this indicator in the late 1950s. [ 1 ] The term stochastic refers to the point of a current price in relation to its price range over a period of time. [ 2 ]

  3. Malliavin calculus - Wikipedia

    en.wikipedia.org/wiki/Malliavin_calculus

    In probability theory and related fields, Malliavin calculus is a set of mathematical techniques and ideas that extend the mathematical field of calculus of variations from deterministic functions to stochastic processes. In particular, it allows the computation of derivatives of random variables.

  4. Continuous-time stochastic process - Wikipedia

    en.wikipedia.org/wiki/Continuous-time_stochastic...

    In probability theory and statistics, a continuous-time stochastic process, or a continuous-space-time stochastic process is a stochastic process for which the index variable takes a continuous set of values, as contrasted with a discrete-time process for which the index variable takes only distinct values.

  5. Stochastic process - Wikipedia

    en.wikipedia.org/wiki/Stochastic_process

    When interpreted as time, if the index set of a stochastic process has a finite or countable number of elements, such as a finite set of numbers, the set of integers, or the natural numbers, then the stochastic process is said to be in discrete time. [54] [55] If the index set is some interval of the real line, then time is said to be continuous.

  6. Stochastic approximation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_approximation

    Stochastic approximation methods are a family of iterative methods typically used for root-finding problems or for optimization problems. The recursive update rules of stochastic approximation methods can be used, among other things, for solving linear systems when the collected data is corrupted by noise, or for approximating extreme values of functions which cannot be computed directly, but ...

  7. Stochastic simulation - Wikipedia

    en.wikipedia.org/wiki/Stochastic_simulation

    A stochastic simulation is a simulation of a system that has variables that can change stochastically (randomly) with individual probabilities. [ 1 ] Realizations of these random variables are generated and inserted into a model of the system.

  8. Progressively measurable process - Wikipedia

    en.wikipedia.org/wiki/Progressively_measurable...

    It can be shown [1] that (), the space of stochastic processes : [,] for which the Itô integral ∫ 0 T X t d B t {\displaystyle \int _{0}^{T}X_{t}\,\mathrm {d} B_{t}} with respect to Brownian motion B {\displaystyle B} is defined, is the set of equivalence classes of P r o g {\displaystyle \mathrm {Prog} } -measurable processes in L 2 ( [ 0 ...

  9. Probability management - Wikipedia

    en.wikipedia.org/wiki/Probability_management

    The simplest approach is to use vector arrays of simulated or historical realizations and metadata called Stochastic Information Packets (SIPs). A set of SIPs, which preserve statistical relationships between variables, is said to be coherent and is referred to as a Stochastic Library Unit with Relationships Preserved (SLURP). SIPs and SLURPs ...