• Title Stochastic Differential Equations: Models and Numerics
• Author(s) Jesper Carlsson, Kyoung-Sook Moon, Anders Szepessy, Ra´ul Tempone, Georgios Zouraris
• Publisher: KTH (Kungliga Tekniska Högskolan) ROYAL INSTITUTE OF TECHNOLOGY (February 12, 2019)
• Hardcover/Paperback N/A
• eBook PDF (202 pages, 2.3 MB)
• Language: English
• ISBN-10/ASIN: N/A
• ISBN-13: N/A
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Book Description

The goal of this book 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.

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• Probability, Stochastic Process, Queueing Theory, etc.
• Differential Equations and Dynamical Systems
• Numerical Analysis and Scientific Computing
• Financial Mathematics and Engineering
• Statistics, Mathematical Statistics, and SAS Programming
• Computational and Algorithmic Mathematics

• Stochastic Differential Equations: Models and Numerics (Jesper Carlsson, et al)
• 2018 Edition

• Advanced Stochastic Processes (Jan A. Van Casteren)
• Stochastic Calculus and Finance (Steven E. Shreve)
• Applied Stochastic Processes in Science and Engineering
• Stochastic Modeling and Control (Ivan Ganchev Ivanov)
• Stochastic Processes for Finance (Patrick Roger)