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Selfsimilar Processes
Paul Embrechts
€ 99.73
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Description for Selfsimilar Processes
Hardback. The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. With an historical overview, this book describes the state of knowledge about selfsimilar processes and their applications. It emphasizes concepts, definitions and basic properties, giving the reader a road map of the realm of selfsimilarity. Series: Princeton Series in Applied Mathematics. Num Pages: 128 pages, 1, black & white illustrations. BIC Classification: PBWL. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 237 x 162 x 15. Weight in Grams: 350.
The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. When measured through linear correlation, many of these systems exhibit a slow correlation decay--a phenomenon often referred to as long-memory or long-range dependence. An example of this is the absolute returns of equity data in finance. Selfsimilar stochastic processes (particularly fractional Brownian motion) have long been postulated as a means to model this behavior, and the concept of selfsimilarity for a stochastic process is now proving to be extraordinarily useful. Selfsimilarity translates into the equality in distribution between the process under a linear time change and ... Read more
The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. When measured through linear correlation, many of these systems exhibit a slow correlation decay--a phenomenon often referred to as long-memory or long-range dependence. An example of this is the absolute returns of equity data in finance. Selfsimilar stochastic processes (particularly fractional Brownian motion) have long been postulated as a means to model this behavior, and the concept of selfsimilarity for a stochastic process is now proving to be extraordinarily useful. Selfsimilarity translates into the equality in distribution between the process under a linear time change and ... Read more
Product Details
Format
Hardback
Publication date
2002
Publisher
Princeton University Press United States
Number of pages
128
Condition
New
Series
Princeton Series in Applied Mathematics
Number of Pages
128
Place of Publication
New Jersey, United States
ISBN
9780691096278
SKU
V9780691096278
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Paul Embrechts
Paul Embrechts is Professor of Mathematics at the Swiss Federal Institute of Technology (ETHZ), Zurich, Switzerland. He is the author of numerous scientific papers on stochastic processes and their applications and the coauthor of the influential book on "Modelling of Extremal Events for Insurance and Finance". Makoto Maejima is Professor of Mathematics at Keio University, Yokohama, Japan. He has published ... Read more
Reviews for Selfsimilar Processes
"Authoritative and written by leading experts, this book is a significant contribution to a growing field. Selfsimilar processes crop up in a wide range of subjects from finance to physics, so this book will have a correspondingly wide readership."—Chris Rogers, Bath University "This is a timely book. Everybody is talking about scaling, and selfsimilar stochastic processes are the basic and ... Read more