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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.
Øksendal, Bernt K. (2003), Stochastic Differential Equations: An Introduction with Applications, Berlin: Springer, ISBN 3-540-04758-1 Protter, Philip E. (2004), Stochastic Integration and Differential Equations (2nd ed.), Springer, ISBN 3-540-00313-4
Malliavin introduced Malliavin calculus to provide a stochastic proof that Hörmander's condition implies the existence of a density for the solution of a stochastic differential equation; Hörmander's original proof was based on the theory of partial differential equations. His calculus enabled Malliavin to prove regularity bounds for the ...
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 ...
Stochastic differential equations originated in the theory of Brownian motion, in the work of Albert Einstein and Marian Smoluchowski in 1905, although Louis Bachelier was the first person credited with modeling Brownian motion in 1900, giving a very early example of a stochastic differential equation now known as Bachelier model.
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.
An important application of stochastic calculus is in mathematical finance, in which asset prices are often assumed to follow stochastic differential equations.For example, the Black–Scholes model prices options as if they follow a geometric Brownian motion, illustrating the opportunities and risks from applying stochastic calculus.
This illustrates one of the connections between stochastic analysis and the study of partial differential equations. Conversely, a given second-order linear partial differential equation of the form Λ f = 0 may be hard to solve directly, but if Λ = A ∗ for some Itô diffusion X , and an invariant measure for X is easy to compute, then that ...