INTRODUCTION TO STOCHASTIC CALCULUS WITH APPLICATIONS (3RD EDITION)

随机计算导论及应用 第3版

数学史

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作      者
出  版 社
出版时间
2012年03月22日
装      帧
平装
ISBN
9781848168329
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页      码
452
语      种
英文
版      次
3rd ed.
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图书简介
This book presents a concise and rigorous treatment of stochastic calculus. It also gives its main applications in finance, biology and engineering. In finance, the stochastic calculus is applied to pricing options by no arbitrage. In biology, it is applied to populations’ models, and in engineering it is applied to filter signal from noise. Not everything is proved, but enough proofs are given to make it a mathematically rigorous exposition. This book aims to present the theory of stochastic calculus and its applications to an audience which possesses only a basic knowledge of calculus and probability. It may be used as a textbook by graduate and advanced undergraduate students in stochastic processes, financial mathematics and engineering. It is also suitable for researchers to gain working knowledge of the subject. It contains many solved examples and exercises making it suitable for self study. In the book many of the concepts are introduced through worked-out examples, eventually leading to a complete, rigorous statement of the general result, and either a complete proof, a partial proof or a reference. Using such structure, the text will provide a mathematically literate reader with rapid introduction to the subject and its advanced applications. The book covers models in mathematical finance, biology and engineering. For mathematicians, this book can be used as a first text on stochastic calculus or as a companion to more rigorous texts by a way of examples and exercises. Key Feature: • The emphasis of the book is on methods and applications. By sacrificing some foundational issues the book achieves advanced topics much quicker than a strictly rigorous conventional text. It brings the techniques of stochastic calculus to wider audiences without deep knowledge of analysis and probability. It is hard to find books on stochastic analysis which present such a wide spectrum of results with relatively modest prerequisites. The book covers many important models in Finance, Biology and Engineering
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