TY  - BOOK
AU  - Capasso,Vincenzo
AU  - Bakstein,David
ED  - SpringerLink (Online service)
TI  - An Introduction to Continuous-Time Stochastic Processes: Theory, Models, and Applications to Finance, Biology, and Medicine 
T2  - Modeling and Simulation in Science, Engineering and Technology
SN  - 9780817644284
U1  - 519.2 23
PY  - 2005///
CY  - Boston, MA
PB  - Birkhäuser Boston
KW  - MATHEMATICS
KW  - BIOLOGY
KW  - FINANCE
KW  - DISTRIBUTION (PROBABILITY THEORY)
KW  - ENGINEERING MATHEMATICS
KW  - PROBABILITY THEORY AND STOCHASTIC PROCESSES
KW  - MATHEMATICAL MODELING AND INDUSTRIAL MATHEMATICS
KW  - APPLICATIONS OF MATHEMATICS
KW  - MATHEMATICAL BIOLOGY IN GENERAL
KW  - QUANTITATIVE FINANCE
KW  - APPL.MATHEMATICS/COMPUTATIONAL METHODS OF ENGINEERING
N1  - The Theory of Stochastic Processes -- Fundamentals of Probability -- Stochastic Processes -- The Itô Integral -- Stochastic Differential Equations -- The Applications of Stochastic Processes -- Applications to Finance and Insurance -- Applications to Biology and Medicine
N2  - 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
UR  - http://dx.doi.org/10.1007/b138900
ER  -