enow.com Web Search

  1. Ad

    related to: what is stochastic differential equation explained in terms of k and t chart

Search results

  1. Results from the WOW.Com Content Network
  2. 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 ...

  3. Feynman–Kac formula - Wikipedia

    en.wikipedia.org/wiki/Feynman–Kac_formula

    The Feynman–Kac formula, named after Richard Feynman and Mark Kac, establishes a link between parabolic partial differential equations and stochastic processes.In 1947, when Kac and Feynman were both faculty members at Cornell University, Kac attended a presentation of Feynman's and remarked that the two of them were working on the same thing from different directions. [1]

  4. Vasicek model - Wikipedia

    en.wikipedia.org/wiki/Vasicek_model

    The model specifies that the instantaneous interest rate follows the stochastic differential equation: d r t = a ( b − r t ) d t + σ d W t {\displaystyle dr_{t}=a(b-r_{t})\,dt+\sigma \,dW_{t}} where W t is a Wiener process under the risk neutral framework modelling the random market risk factor, in that it models the continuous inflow of ...

  5. Runge–Kutta method (SDE) - Wikipedia

    en.wikipedia.org/wiki/Runge–Kutta_method_(SDE)

    In mathematics of stochastic systems, the Runge–Kutta method is a technique for the approximate numerical solution of a stochastic differential equation. It is a generalisation of the Runge–Kutta method for ordinary differential equations to stochastic differential equations (SDEs). Importantly, the method does not involve knowing ...

  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. Stochastic quantum mechanics - Wikipedia

    en.wikipedia.org/wiki/Stochastic_quantum_mechanics

    Stochastic mechanics is a framework for describing the dynamics of particles that are subjected to an intrinsic random processes as well as various external forces. The framework provides a derivation of the diffusion equations associated to these stochastic particles.

  8. Stochastic processes and boundary value problems - Wikipedia

    en.wikipedia.org/wiki/Stochastic_processes_and...

    Let be a domain (an open and connected set) in .Let be the Laplace operator, let be a bounded function on the boundary, and consider the problem: {() =, = (),It can be shown that if a solution exists, then () is the expected value of () at the (random) first exit point from for a canonical Brownian motion starting at .

  9. Differential equation - Wikipedia

    en.wikipedia.org/wiki/Differential_equation

    A stochastic differential equation (SDE) is an equation in which the unknown quantity is a stochastic process and the equation involves some known stochastic processes, for example, the Wiener process in the case of diffusion equations. A stochastic partial differential equation (SPDE) is an equation that generalizes SDEs to include space-time ...

  1. Ad

    related to: what is stochastic differential equation explained in terms of k and t chart