An Introduction to Continuous-Time Stochastic Processes
Theory, Models, and Applications to Finance, Biology, and Medicine
(Sprache: Englisch)
This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. Balancing theory and applications, the authors use stochastic methods and concrete examples to model real-world problems from...
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Produktinformationen zu „An Introduction to Continuous-Time Stochastic Processes “
This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. Balancing theory and applications, the authors use stochastic methods and concrete examples to model real-world problems from engineering, biomathematics, biotechnology, and finance. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. The book will be of interest to students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, physics, and engineering.
Klappentext zu „An Introduction to Continuous-Time Stochastic Processes “
This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. A balance of theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required.Key topics covered include:Interacting particles and agent-based models (ant colonies)Population dynamics: from birth and death processes to epidemicsFinancial market models: the non-arbitrage principleContingent claim valuation modelsRisk analysis in insuranceAn Introduction to Continuous-Time Stochastic Processes will be of interest to a broad audience of students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, biotechnology, physics, and engineering. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. Prerequisites include knowledge of calculus and some analysis; exposure to probability would be helpful but not required since the necessary fundamentals of measure and integration are provided.
This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. A balance of theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required.
Key topics covered include:
- Interacting particles and agent-based models (ant colonies)
- Population dynamics: from birth and death processes to epidemics
- Financial market models: the non-arbitrage principle
- Contingent claim valuation models
- Risk analysis in insurance
An Introduction to Continuous-Time Stochastic Processes will be of interest to a broad audience of students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, biotechnology, physics, and engineering. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. Prerequisites include knowledge of calculus and some analysis; exposure to probability would be helpful but not required since the necessary fundamentals of measure and integration are provided.
Key topics covered include:
- Interacting particles and agent-based models (ant colonies)
- Population dynamics: from birth and death processes to epidemics
- Financial market models: the non-arbitrage principle
- Contingent claim valuation models
- Risk analysis in insurance
An Introduction to Continuous-Time Stochastic Processes will be of interest to a broad audience of students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, biotechnology, physics, and engineering. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. Prerequisites include knowledge of calculus and some analysis; exposure to probability would be helpful but not required since the necessary fundamentals of measure and integration are provided.
Inhaltsverzeichnis zu „An Introduction to Continuous-Time Stochastic Processes “
Preface- Part I: The Theory of Stochastic Processes
- Fundamentals of Probability
- Stochastic Processes
- The Ito Integral
- Stochastic Differential Equations
- Part II: The Applications of Stochastic Processes
- Applications to Finance and Insurance
- Applications to Biology and Medicine
- Part III: Appendices
- A. Measure and Integration
- B. Convergence of Probability Measures on Metric Spaces
- C. Maximum Principles of Elliptic and Parabolic Operators
- D. Stability of Ordinary Differential Equations
- References
- Nomenclature
- Index.
Bibliographische Angaben
- Autoren: Vincenzo Capasso , David Bakstein
- 2005, XI, 343 Seiten, mit Abbildungen, Maße: 15,8 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer
- ISBN-10: 0817632344
- ISBN-13: 9780817632342
Sprache:
Englisch
Rezension zu „An Introduction to Continuous-Time Stochastic Processes “
"This is an introductory text on continuous time stochastic processes and their applications to finance and biology. The first part of the book reviews basic probability and then covers the basic continuous time processes such as Brownian motion, point processes, etc.... The book will be useful for applied mathematicians who are not probabilists to get a quick flavour of the techniques of stochastic calculus, and for professional probabilists to get a quick flavour of the applications." -Mathematical Reviews"The book is a systematic, rigorous, and self-contained introduction to the theory of continuous-time stochastic processes. It is an account of fundamental concepts as they appear in relevant modern applications and literature.... The book addresses three main groups: first, mathematicians working in a different field; second, other scientists and professionals from a business or academic background; third, graduate or advanced undergraduate students of a quantitative subject related to stochastic theory and/or applications." -Zentralblatt MATH"This book provides a mathematical overview of the theory of continuous-time stochastic processes, with emphasis on stochastic differential equations (SDEs). Applications in finance and population modelling are also briefly reviewed.... The primary audience for this book will be mathematicians (both pure and applied) active in other areas who require an introduction to stochastic theory. Scientists already working in the applications of SDEs will also benefit from this mathematically rigorous reference text. The core of the text on Ito calculus...would be suitable supplementary reading for graduate or advanced undergraduate students of stochastic theory.... The style of the text...is concise and rigorous.... Each chapter concludes with a set of exercises inviting readers to prove supplementary results and review particular aspects of the theory.... In summary, I have found this to be a useful reference text, and would
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recommend it to those wishing to delve into the mathematical theory of stochastic processes." -UK Nonlinear News"This book covers an extensive part of probability theory, the theory for time-continuous stochastic processes, and also gives a lot of examples from finance, biology, and medicine.... Most of the contents of the book have been used as lecture material for several years, which is evident by the fact that there are very few misprints, and the text is well-structured also having a good labelling system.... [T]he book is quite compact covering the fundamentals in probability theory and stochastic processes in 200 pages.... The chapter on applications towards finance covers many classical models such as arbitrage-free markets, [the] Black-Scholes model, and models for interest and ruin probabilities. This chapter is probably the best in the book.... The chapter on applications towards biology and medicine...contains models for epidemics, individual-based models, and a model for neural activity.... After each chapter there are several exercises illustrating and extending the theory presented in the text. Many of these exercises are interesting and rewarding to solve." -Mathematical Biosciences"The book is written in a systematic and self-contained way where omitted details are compensated by references to a commonly accessible literature. The book is [geared] to students or professionals who want to get acquainted with the role of stochastic processes in modeling random phenomena in economics, biology, or medicine." -Applications of Mathematics
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