Logo

Stochastic Differential Equations: Models and Numerics

Small book cover: Stochastic Differential Equations: Models and Numerics

Stochastic Differential Equations: Models and Numerics
by

Publisher: KTH
Number of pages: 202

Description:
The goal of this course is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and mathematical finance. Typically, these problems require numerical methods to obtain a solution and therefore the course focuses on basic understanding of stochastic and partial differential equations to construct reliable and efficient computational methods.

Home page url

Download or read it online for free here:
Download link
(2.3MB, PDF)

Similar books

Book cover: Applied Stochastic Processes in Science and EngineeringApplied Stochastic Processes in Science and Engineering
by - University of Waterloo
This book is designed as an introduction to the ideas and methods used to formulate mathematical models of physical processes in terms of random functions. A senior undergraduate course offered to students with a suitably mathematical background.
(2281 views)
Book cover: Advanced Stochastic ProcessesAdvanced Stochastic Processes
by - Bookboon
In this book, which is basically self-contained, the following topics are treated thoroughly: Brownian motion as a Gaussian process, Brownian motion as a Markov process, Brownian motion as a martingale, Markov chains, renewal theory, etc.
(2633 views)
Book cover: Introduction to Stochastic ProcessesIntroduction to Stochastic Processes
by - The University of Texas at Austin
Contents: Probability review; Mathematica in 15 minutes; Stochastic Processes; Simple random walk; Generating functions; Random walks - advanced methods; Branching processes; Markov Chains; The 'Stochastics' package; Classification of States; etc.
(2551 views)
Book cover: Stochastic Analysis - NotesStochastic Analysis - Notes
by
A gentle introduction to the mathematics of Stochastic Analysis. From the table of contents: Introduction; Conditional expectation; Martingales; Stochastic integration - informally; Wiener process; Ito's formula; Bibliography.
(9028 views)