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Stochastic analysis is analysis based on Ito's calculus. This calculus
was developed to cope with questions arising in probability theory in
which processes are modelled by motion along paths which typically are
not differentiable. The development of this calculus now rests on linear
analysis and measure theory.
Stochastic analysis is a basic tool in much of modern probability
theory and is used in many applied areas from biology (Burroughs ) to
physics (Zaboronski),
especially statistical mechanics. It has become particularly well known
via the Black-Scholes formula as a way of modelling financial markets
and strategies (Jacka
*). This is one of the topics in the MSc course in Financial Mathematics offered by the department.
As a branch of pure mathematics it has a rich intrinsic interest (Jacka
*,
Warren*). Riemannian geometry (and
degenerate versions of it) is bound up with the study of solutions of
stochastic ordinary differential equations which can be considered as a
model for dynamical systems with noise (Elworthy, J. Robinson).
These equations are also used in the study of partial
differential equations, for example those arising in geometric
problems (Elworthy, Kendall
a>*).
Numerical methods are needed for computation
(Stuart)
of solutions for stochastic ordinary, and partial, differential
equations.
There is currently especial interest in questions relating to
stochastic calculus for motion on singular spaces (such as on the
branches of a tree) and on fractals: foundational, dynamical, and
geometric aspects all appear here. Stochastic analysis is also a tool
for the development of analysis on infinite dimensional spaces (Elworthy, Jones).
Stochastic partial differential equations are partial differential
equations with some noise term. The noise may be due to intrinsic
randomness in the system (eg from quantum effects) or from unknown
random disturbances to the dynamics being modelled. Non-random partial
differential equations form a special case and the questions, techniques
and applications of stocahstic pdes are at least as wide as they are for
classical pdes. Questions include the existence and properties of
attractors for evolution equations (J. Robinson, Stuart ),
travelling wave solutions (Elworthy, Tribe),
intermittency, fractal properties and the relationships with turbulence
(Tribe, Zaboronsky),
ergodic behaviour (Stuart , Tribe), and
control theory of stochastic p.d.e (Jacka
*, Tribe).
See also the SE & SEEQ web page.
*Member of Statistics
Dept.
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