"This book is an 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. An Introduction to Continuous-Time S
An introduction to continuous-time stochastic processes: theory, models, and applications to finance, biology, and medicine
✍ Scribed by Vincenzo Capasso, David Bakstein
- Book ID
- 127426128
- Publisher
- Birkhäuser
- Year
- 2005
- Tongue
- English
- Weight
- 2 MB
- Series
- Modeling and simulation in science, engineering and technology
- Edition
- 1
- Category
- Library
- City
- Boston
- ISBN-13
- 9780817632342
No coin nor oath required. For personal study only.
✦ Synopsis
Here is an 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 engineering, biomathematics, industrial mathematics, and finance using stochastic methods. Key topics include:
• Interacting particles, from polymers to ants
• Population dynamics: birth and death processes
• Financial market models: the non-arbitrage principle
• Option pricing: the risk-neutral valuation theory
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, 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.
📜 SIMILAR VOLUMES
This is an introductory textbook on probability theory and its applications. Basic concepts such as probability measure, random variable, distribution, and expectation are fully treated without technical complications. Both the discrete and continuous cases are covered, the elements of calculus bein
This is an introductory textbook on probability theory and its applications. Basic concepts such as probability measure, random variable, distribution, and expectation are fully treated without technical complications. Both the discrete and continuous cases are covered, the elements of calculus bein
When the student of engineering or applied science is first exposed to stochastic processes, or noise theory, he is usually content to manipulate random variables formally as if they were ordinary functions. Sometime later the serious student becomes concerned about such problems as the validity of