An Introduction to Continuous-Time Stochastic Processes

Capasso V Capasso Vincenzo

ISBN 10: 0817632344 / ISBN 13: 9780817632342

Published by Springer, 2004

About this Item

pp. xi + 343 Illus.

Seller Inventory # 7547314

Bibliographic Details

• Title: An Introduction to Continuous-Time Stochastic Processes
• Publisher: Springer
• Publication Date: 2004
• Language: English
• ISBN 10: 0817632344
• ISBN 13: 9780817632342
• Binding: Hardcover
• Condition: New

About this title

Synopsis

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.

From the Back Cover

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, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required.Key topics covered include:* Interacting particles and agent-based models: from polymers to ants * Population dynamics: from birth and death processes to epidemics * Financial market models: the non-arbitrage principle * Contingent claim valuation models: the risk-neutral valuation theory * 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, 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.