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Selfsimilar Processes (Princeton Series in Applied Mathematics (21)) by Embrechts, Paul is a mathematics available to read on EtoBox.
What is Selfsimilar Processes (Princeton Series in Applied Mathematics (21)) about?
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 s
Who reads Selfsimilar Processes (Princeton Series in Applied Mathematics (21))?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Embrechts, Paul
- Publisher
- Princeton University Press
- Published
- 2009
- Language
- EN
- ISBN
- 9780691096278
- Category
- mathematics
- Subjects
- Finance, Mathematics, Stem
- Updated
- 2026-03-25
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