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 growth models[3] or physical systems that are subjected to thermal fluctuations.
SDEs have a random differential that is in the most basic case random white noise calculated as the derivative of a Brownian motion or more generally a semimartingale. However, other types of random behaviour are possible, such as jump processes like Lévy processes[4] or semimartingales with jumps. Random differential equations are conjugate to stochastic differential equations. Stochastic differential equations can also be extended to differential manifolds.[5][6][7][8]
^Rogers, L.C.G.; Williams, David (2000). Diffusions, Markov Processes and Martingales, Vol 2: Ito Calculus (2nd ed., Cambridge Mathematical Library ed.). Cambridge University Press. doi:10.1017/CBO9780511805141. ISBN 0-521-77594-9. OCLC 42874839.
^Musiela, M., and Rutkowski, M. (2004), Martingale Methods in Financial Modelling, 2nd Edition, Springer Verlag, Berlin.
^Cite error: The named reference oksendal was invoked but never defined (see the help page).
^Kunita, H. (2004). Stochastic Differential Equations Based on Lévy Processes and Stochastic Flows of Diffeomorphisms. In: Rao, M.M. (eds) Real and Stochastic Analysis. Trends in Mathematics. Birkhäuser Boston. https://doi.org/10.1007/978-1-4612-2054-1_6
^Imkeller, Peter; Schmalfuss, Björn (2001). "The Conjugacy of Stochastic and Random Differential Equations and the Existence of Global Attractors". Journal of Dynamics and Differential Equations. 13 (2): 215–249. doi:10.1023/a:1016673307045. ISSN 1040-7294. S2CID 3120200.
^Michel Emery (1989). Stochastic calculus in manifolds. Springer Berlin, Heidelberg. Doi https://doi.org/10.1007/978-3-642-75051-9
^Zdzisław Brzeźniak and K. D. Elworthy, Stochastic differential equations on Banach manifolds, Methods Funct. Anal. Topology 6 (2000), no. 1, 43-84.
^Armstrong J. and Brigo D. (2018). Intrinsic stochastic differential equations as jets. Proc. R. Soc. A., 474: 20170559,
http://doi.org/10.1098/rspa.2017.0559
and 19 Related for: Stochastic differential equation information
Stochastic partial differentialequations (SPDEs) generalize partial differentialequations via random force terms and coefficients, in the same way ordinary...
partial differentialequations (PDEs) which may be with respect to more than one independent variable, and, less commonly, in contrast with stochastic differential...
In mathematics, a differentialequation is an equation that relates one or more unknown functions and their derivatives. In applications, the functions...
In physics, a Langevin equation (named after Paul Langevin) is a stochasticdifferentialequation describing how a system evolves when subjected to a combination...
stochastic differentialequations (QSDE) that are analogous to classical Langevin equations. For the remainder of this article stochastic calculus will...
In mathematics, stochastic analysis on manifolds or stochasticdifferential geometry is the study of stochastic analysis over smooth manifolds. It is...
dynamical system and differentialequation topics, by Wikipedia page. See also list of partial differentialequation topics, list of equations. Deterministic...
with drift. It is an important example of stochastic processes satisfying a stochasticdifferentialequation (SDE); in particular, it is used in mathematical...
In mathematics, a partial differentialequation (PDE) is an equation which computes a function between various partial derivatives of a multivariable function...
papers developing the field of stochastic calculus, which involves stochastic integrals and stochasticdifferentialequations based on the Wiener or Brownian...
for ordinary differentialequations are methods used to find numerical approximations to the solutions of ordinary differentialequations (ODEs). Their...
of assets—are stochastic. Backward stochasticdifferentialequationStochastic process Control theory Multiplier uncertainty Stochastic scheduling Definition...
case, the aforementioned controlled differentialequation can be interpreted as a stochasticdifferentialequation and integration against " d X t j {\displaystyle...
the solution of a stochasticdifferentialequation; Hörmander's original proof was based on the theory of partial differentialequations. The calculus has...
probabilistic models, noise conditioned score networks, and stochasticdifferentialequations. Diffusion models were introduced in 2015 as a method to learn...
application of stochastic calculus is in mathematical finance, in which asset prices are often assumed to follow stochasticdifferentialequations. For example...