An Introduction to Continuous-Time Stochastic Processes: Theory, Models, and Applications to Finance, Biology, and Medicine: Modeling and Simulation in Science, Engineering and Technology
Autor Vincenzo Capasso, David Baksteinen Limba Engleză Paperback – 9 oct 2016
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Specificații
ISBN-13: 9781493938360
ISBN-10: 1493938363
Pagini: 498
Ilustrații: XVI, 482 p. 14 illus.
Dimensiuni: 155 x 235 x 26 mm
Greutate: 0.69 kg
Ediția:Softcover reprint of the original 3rd ed. 2015
Editura: Springer
Colecția Birkhäuser
Seria Modeling and Simulation in Science, Engineering and Technology
Locul publicării:New York, NY, United States
ISBN-10: 1493938363
Pagini: 498
Ilustrații: XVI, 482 p. 14 illus.
Dimensiuni: 155 x 235 x 26 mm
Greutate: 0.69 kg
Ediția:Softcover reprint of the original 3rd ed. 2015
Editura: Springer
Colecția Birkhäuser
Seria Modeling and Simulation in Science, Engineering and Technology
Locul publicării:New York, NY, United States
Cuprins
Part I: Theory of Stochastic Processes.- Fundamentals of Probability.- Stochastic Processes.- The Itô Integral.- Stochastic Differential Equations.- Stability, Stationary, Ergodicity.- Part II: Applications of Stochastic Processes.- Applications to Finance and Insurance.- Applications to Biology and Medicine.- Measure and Integration.- Convergence of Probability Measures on Metric Spaces.- Appendices.
Recenzii
“This is indeed a very well written book on stochastic processes and their numerous applications. … The reader will definitely benefit from the exercises given at the end of each of the chapters. … The book is strongly recommended to students following any graduate program in mathematics and mathematical modeling. University teachers can easily use this book as a possible reference book for special intermediate and advanced courses in stochastics and its applications.” (Jordan M. Stoyanov, zbMATH 1333.60002, 2016)
Notă biografică
Vincenzo Capasso is a Professor of Probability and Mathematical Statistics at the University of Milan. His research interests include spatially structured stochastic processes, stochastic geometry, reaction-diffusion systems, and statistics of structured stochastic processes. David Bakstein is a professor at the University of Milan, in ADAMSS (Interdisciplinary Center for Advanced Applied Mathematical and Statistical Sciences).
Textul de pe ultima copertă
This textbook, now in its third edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations. Expertly balancing theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required.
Key topics include:
* Markov processes
* Stochastic differential equations
* Arbitrage-free markets and financial derivatives
* Insurance risk
* Population dynamics, and epidemics
* Agent-based models
New to the Third Edition:
* Infinitely divisible distributions
* Random measures
* Levy processes
* Fractional Brownian motion
* Ergodic theory
* Karhunen-Loeve expansion
* Additional applications
* Additional exercises
* Smoluchowski approximation of Langevin systems
An Introduction to Continuous-Time Stochastic Processes, Third Edition will be of interest to a broad audience of students, pure and applied mathematicians, and researchers and practitioners in mathematical finance, biomathematics, biotechnology, and engineering. Suitable as a textbook for graduate or undergraduate courses, as well as European Masters courses (according to the two-year-long second cycle of the “Bologna Scheme”), 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.
From reviews of previous editions:
"The book 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
Key topics include:
* Markov processes
* Stochastic differential equations
* Arbitrage-free markets and financial derivatives
* Insurance risk
* Population dynamics, and epidemics
* Agent-based models
New to the Third Edition:
* Infinitely divisible distributions
* Random measures
* Levy processes
* Fractional Brownian motion
* Ergodic theory
* Karhunen-Loeve expansion
* Additional applications
* Additional exercises
* Smoluchowski approximation of Langevin systems
An Introduction to Continuous-Time Stochastic Processes, Third Edition will be of interest to a broad audience of students, pure and applied mathematicians, and researchers and practitioners in mathematical finance, biomathematics, biotechnology, and engineering. Suitable as a textbook for graduate or undergraduate courses, as well as European Masters courses (according to the two-year-long second cycle of the “Bologna Scheme”), 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.
From reviews of previous editions:
"The book 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
Caracteristici
Provides a good balance between a rigorous mathematical approach and easy access to methods in applied research Revised and expanded edition includes new exercises, updated methodologies, and a new chapter on ergodic theory Minimal background knowledge of stochastic processes required Includes models of real world problems