Introduction to Stochastic Analysis

This book PDF is perfect for those who love Mathematics genre, written by Vigirdas Mackevicius and published by John Wiley & Sons which was released on 07 February 2013 with total hardcover pages 220. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Introduction to Stochastic Analysis books below.

Introduction to Stochastic Analysis
Introduction to Stochastic Analysis
Author : Vigirdas Mackevicius
File Size : 46,6 Mb
Publisher : John Wiley & Sons
Language : English
Release Date : 07 February 2013
ISBN : 9781118603246
Pages : 220 pages
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Introduction to Stochastic Analysis by Vigirdas Mackevicius Book PDF Summary

This is an introduction to stochastic integration and stochastic differential equations written in an understandable way for a wide audience, from students of mathematics to practitioners in biology, chemistry, physics, and finances. The presentation is based on the naïve stochastic integration, rather than on abstract theories of measure and stochastic processes. The proofs are rather simple for practitioners and, at the same time, rather rigorous for mathematicians. Detailed application examples in natural sciences and finance are presented. Much attention is paid to simulation diffusion processes. The topics covered include Brownian motion; motivation of stochastic models with Brownian motion; Itô and Stratonovich stochastic integrals, Itô’s formula; stochastic differential equations (SDEs); solutions of SDEs as Markov processes; application examples in physical sciences and finance; simulation of solutions of SDEs (strong and weak approximations). Exercises with hints and/or solutions are also provided.

Introduction to Stochastic Analysis

Introduction to Stochastic Analysis by Vigirdas Mackevicius

This is an introduction to stochastic integration and stochastic differential equations written in an understandable way for a wide audience, from students of mathematics to practitioners in biology, chemistry, physics, and finances. The presentation is based on the naïve stochastic integration, rather than on abstract theories of measure and

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