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
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
Vincenzo Capasso
Brownian Motion Interacting Particle Systems Ito Calculus Levy Processes Stochastic Differential Equations Stochastic Processes
“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)