Inhaltsangabe
Focusing on mathematical ideas rather than proofs, this book provides access to important fundamentals of stochastic processes. This second edition features additional material on stochastic integration, with expanded discussion of Girsanov transformation, an introduction to the Feynman-Kac formula, and an exposition on the Black-Scholes formula with applications from the field of mathematical finance. This new edition also includes new and expanded topics such as Doob's maximal inequality in the chapter on martingales and self similarity in the chapter on Brownian motion. It remains an ideal reference for professional mathematicians and statisticians as well as students.
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Über die Autorin bzw. den Autor
Greogory F. Lawler
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Hardcover. Zustand: As New. Leichte Abnutzungen. Emphasizing fundamental mathematical ideas rather than proofs, Introduction to Stochastic Processes, Second Edition provides quick access to important foundations of probability theory applicable to problems in many fields. Assuming that you have a reasonable level of computer literacy, the ability to write simple programs, and the access to software for linear algebra computations, the author approaches the problems and theorems with a focus on stochastic processes evolving with time, rather than a particular emphasis on measure theory.For those lacking in exposure to linear differential and difference equations, the author begins with a brief introduction to these concepts. He proceeds to discuss Markov chains, optimal stopping, martingales, and Brownian motion. The book concludes with a chapter on stochastic integration. The author supplies many basic, general examples and provides exercises at the end of each chapter.New to the Second. Bestandsnummer des Verkäufers b9777b72-9fb4-4a50-93b7-418ea84000bf
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Hardcover. Zustand: new. Hardcover. Emphasizing fundamental mathematical ideas rather than proofs, Introduction to Stochastic Processes, Second Edition provides quick access to important foundations of probability theory applicable to problems in many fields. Assuming that you have a reasonable level of computer literacy, the ability to write simple programs, and the access to software for linear algebra computations, the author approaches the problems and theorems with a focus on stochastic processes evolving with time, rather than a particular emphasis on measure theory.For those lacking in exposure to linear differential and difference equations, the author begins with a brief introduction to these concepts. He proceeds to discuss Markov chains, optimal stopping, martingales, and Brownian motion. The book concludes with a chapter on stochastic integration. The author supplies many basic, general examples and provides exercises at the end of each chapter.New to the Second Edition:Expanded chapter on stochastic integration that introduces modern mathematical finance Introduction of Girsanov transformation and the Feynman-Kac formula Expanded discussion of Ito's formula and the Black-Scholes formula for pricing options New topics such as Doob's maximal inequality and a discussion on self similarity in the chapter on Brownian motionApplicable to the fields of mathematics, statistics, and engineering as well as computer science, economics, business, biological science, psychology, and engineering, this concise introduction is an excellent resource both for students and professionals. Emphasizing fundamental mathematical ideas rather than proofs, this book provides access to important foundations of probability theory applicable to problems in many fields. It also discusses Markov chains, optimal stopping, martingales, and Brownian motion. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781584886518
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