Analysis of Variations for Self-similar Processes

Analysis of Variations for Self-similar Processes

Author: Ciprian Tudor

Publisher: Springer Science & Business Media

Published: 2013-08-13

Total Pages: 272

ISBN-13: 3319009362

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Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades. This book presents the basic properties of these processes and focuses on the study of their variation using stochastic analysis. While self-similar processes, and especially fractional Brownian motion, have been discussed in several books, some new classes have recently emerged in the scientific literature. Some of them are extensions of fractional Brownian motion (bifractional Brownian motion, subtractional Brownian motion, Hermite processes), while others are solutions to the partial differential equations driven by fractional noises. In this monograph the author discusses the basic properties of these new classes of self-similar processes and their interrelationship. At the same time a new approach (based on stochastic calculus, especially Malliavin calculus) to studying the behavior of the variations of self-similar processes has been developed over the last decade. This work surveys these recent techniques and findings on limit theorems and Malliavin calculus.


Book Synopsis Analysis of Variations for Self-similar Processes by : Ciprian Tudor

Download or read book Analysis of Variations for Self-similar Processes written by Ciprian Tudor and published by Springer Science & Business Media. This book was released on 2013-08-13 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades. This book presents the basic properties of these processes and focuses on the study of their variation using stochastic analysis. While self-similar processes, and especially fractional Brownian motion, have been discussed in several books, some new classes have recently emerged in the scientific literature. Some of them are extensions of fractional Brownian motion (bifractional Brownian motion, subtractional Brownian motion, Hermite processes), while others are solutions to the partial differential equations driven by fractional noises. In this monograph the author discusses the basic properties of these new classes of self-similar processes and their interrelationship. At the same time a new approach (based on stochastic calculus, especially Malliavin calculus) to studying the behavior of the variations of self-similar processes has been developed over the last decade. This work surveys these recent techniques and findings on limit theorems and Malliavin calculus.

Analysis of Variations for Self-similar Processes

Analysis of Variations for Self-similar Processes

Author: Ciprian A. Tudor

Publisher: Springer

Published: 2013-08-08

Total Pages: 268

ISBN-13: 9783319009377

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Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades. This book presents the basic properties of these processes and focuses on the study of their variation using stochastic analysis. While self-similar processes, and especially fractional Brownian motion, have been discussed in several books, some new classes have recently emerged in the scientific literature. Some of them are extensions of fractional Brownian motion (bifractional Brownian motion, subtractional Brownian motion, Hermite processes), while others are solutions to the partial differential equations driven by fractional noises. In this monograph the author discusses the basic properties of these new classes of self-similar processes and their interrelationship. At the same time a new approach (based on stochastic calculus, especially Malliavin calculus) to studying the behavior of the variations of self-similar processes has been developed over the last decade. This work surveys these recent techniques and findings on limit theorems and Malliavin calculus.


Book Synopsis Analysis of Variations for Self-similar Processes by : Ciprian A. Tudor

Download or read book Analysis of Variations for Self-similar Processes written by Ciprian A. Tudor and published by Springer. This book was released on 2013-08-08 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Self-similar processes are stochastic processes that are invariant in distribution under suitable time scaling, and are a subject intensively studied in the last few decades. This book presents the basic properties of these processes and focuses on the study of their variation using stochastic analysis. While self-similar processes, and especially fractional Brownian motion, have been discussed in several books, some new classes have recently emerged in the scientific literature. Some of them are extensions of fractional Brownian motion (bifractional Brownian motion, subtractional Brownian motion, Hermite processes), while others are solutions to the partial differential equations driven by fractional noises. In this monograph the author discusses the basic properties of these new classes of self-similar processes and their interrelationship. At the same time a new approach (based on stochastic calculus, especially Malliavin calculus) to studying the behavior of the variations of self-similar processes has been developed over the last decade. This work surveys these recent techniques and findings on limit theorems and Malliavin calculus.

Stochastic Analysis and Related Topics

Stochastic Analysis and Related Topics

Author: Fabrice Baudoin

Publisher: Birkhäuser

Published: 2017-10-04

Total Pages: 221

ISBN-13: 3319596713

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The articles in this collection are a sampling of some of the research presented during the conference “Stochastic Analysis and Related Topics”, held in May of 2015 at Purdue University in honor of the 60th birthday of Rodrigo Bañuelos. A wide variety of topics in probability theory is covered in these proceedings, including heat kernel estimates, Malliavin calculus, rough paths differential equations, Lévy processes, Brownian motion on manifolds, and spin glasses, among other topics.


Book Synopsis Stochastic Analysis and Related Topics by : Fabrice Baudoin

Download or read book Stochastic Analysis and Related Topics written by Fabrice Baudoin and published by Birkhäuser. This book was released on 2017-10-04 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: The articles in this collection are a sampling of some of the research presented during the conference “Stochastic Analysis and Related Topics”, held in May of 2015 at Purdue University in honor of the 60th birthday of Rodrigo Bañuelos. A wide variety of topics in probability theory is covered in these proceedings, including heat kernel estimates, Malliavin calculus, rough paths differential equations, Lévy processes, Brownian motion on manifolds, and spin glasses, among other topics.

Long-Range Dependence and Self-Similarity

Long-Range Dependence and Self-Similarity

Author: Vladas Pipiras

Publisher: Cambridge University Press

Published: 2017-04-18

Total Pages: 693

ISBN-13: 1107039460

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A modern and rigorous introduction to long-range dependence and self-similarity, complemented by numerous more specialized up-to-date topics in this research area.


Book Synopsis Long-Range Dependence and Self-Similarity by : Vladas Pipiras

Download or read book Long-Range Dependence and Self-Similarity written by Vladas Pipiras and published by Cambridge University Press. This book was released on 2017-04-18 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: A modern and rigorous introduction to long-range dependence and self-similarity, complemented by numerous more specialized up-to-date topics in this research area.

Non-Gaussian Selfsimilar Stochastic Processes

Non-Gaussian Selfsimilar Stochastic Processes

Author: Ciprian Tudor

Publisher: Springer Nature

Published: 2023-07-04

Total Pages: 110

ISBN-13: 3031337727

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This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments live in a Wiener chaos and include the fractional Brownian motion, the only Gaussian process in this class. Using the Wiener chaos theory and multiple stochastic integrals, the book covers the main properties of Hermite processes and their multiparameter counterparts, the Hermite sheets. It delves into the probability distribution of these stochastic processes and their sample paths, while also presenting the basics of stochastic integration theory with respect to Hermite processes and sheets. The book goes beyond theory and provides a thorough analysis of physical models driven by Hermite noise, including the Hermite Ornstein-Uhlenbeck process and the solution to the stochastic heat equation driven by such a random perturbation. Moreover, it explores up-to-date topics central to current research in statistical inference for Hermite-driven models.


Book Synopsis Non-Gaussian Selfsimilar Stochastic Processes by : Ciprian Tudor

Download or read book Non-Gaussian Selfsimilar Stochastic Processes written by Ciprian Tudor and published by Springer Nature. This book was released on 2023-07-04 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an introduction to the field of stochastic analysis of Hermite processes. These selfsimilar stochastic processes with stationary increments live in a Wiener chaos and include the fractional Brownian motion, the only Gaussian process in this class. Using the Wiener chaos theory and multiple stochastic integrals, the book covers the main properties of Hermite processes and their multiparameter counterparts, the Hermite sheets. It delves into the probability distribution of these stochastic processes and their sample paths, while also presenting the basics of stochastic integration theory with respect to Hermite processes and sheets. The book goes beyond theory and provides a thorough analysis of physical models driven by Hermite noise, including the Hermite Ornstein-Uhlenbeck process and the solution to the stochastic heat equation driven by such a random perturbation. Moreover, it explores up-to-date topics central to current research in statistical inference for Hermite-driven models.

Parameter Estimation in Stochastic Volatility Models

Parameter Estimation in Stochastic Volatility Models

Author: Jaya P. N. Bishwal

Publisher: Springer Nature

Published: 2022-08-06

Total Pages: 634

ISBN-13: 3031038614

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This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.


Book Synopsis Parameter Estimation in Stochastic Volatility Models by : Jaya P. N. Bishwal

Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.

Selfsimilar Processes

Selfsimilar Processes

Author: Paul Embrechts

Publisher: Princeton University Press

Published: 2009-01-10

Total Pages: 128

ISBN-13: 1400825105

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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 the same process properly scaled in space, a simple scaling property that yields a remarkably rich theory with far-flung applications. After a short historical overview, this book describes the current state of knowledge about selfsimilar processes and their applications. Concepts, definitions and basic properties are emphasized, giving the reader a road map of the realm of selfsimilarity that allows for further exploration. Such topics as noncentral limit theory, long-range dependence, and operator selfsimilarity are covered alongside statistical estimation, simulation, sample path properties, and stochastic differential equations driven by selfsimilar processes. Numerous references point the reader to current applications. Though the text uses the mathematical language of the theory of stochastic processes, researchers and end-users from such diverse fields as mathematics, physics, biology, telecommunications, finance, econometrics, and environmental science will find it an ideal entry point for studying the already extensive theory and applications of selfsimilarity.


Book Synopsis Selfsimilar Processes by : Paul Embrechts

Download or read book Selfsimilar Processes written by Paul Embrechts and published by Princeton University Press. This book was released on 2009-01-10 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 the same process properly scaled in space, a simple scaling property that yields a remarkably rich theory with far-flung applications. After a short historical overview, this book describes the current state of knowledge about selfsimilar processes and their applications. Concepts, definitions and basic properties are emphasized, giving the reader a road map of the realm of selfsimilarity that allows for further exploration. Such topics as noncentral limit theory, long-range dependence, and operator selfsimilarity are covered alongside statistical estimation, simulation, sample path properties, and stochastic differential equations driven by selfsimilar processes. Numerous references point the reader to current applications. Though the text uses the mathematical language of the theory of stochastic processes, researchers and end-users from such diverse fields as mathematics, physics, biology, telecommunications, finance, econometrics, and environmental science will find it an ideal entry point for studying the already extensive theory and applications of selfsimilarity.

Progress in Wavelet Analysis and Applications

Progress in Wavelet Analysis and Applications

Author: Yves Meyer

Publisher: Atlantica Séguier Frontières

Published: 1993

Total Pages: 808

ISBN-13: 9782863321300

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Book Synopsis Progress in Wavelet Analysis and Applications by : Yves Meyer

Download or read book Progress in Wavelet Analysis and Applications written by Yves Meyer and published by Atlantica Séguier Frontières. This book was released on 1993 with total page 808 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Smart Spaces and Next Generation Wired/Wireless Networking

Smart Spaces and Next Generation Wired/Wireless Networking

Author: Sergey Balandin

Publisher: Springer Science & Business Media

Published: 2011-07-28

Total Pages: 650

ISBN-13: 3642228747

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This book constitutes the refereed proceedings of the 11th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking, NEW2AN 2011 and the 4th Conference on Smart Spaces, ruSMART 2011 jointly held in St. Petersburg, Russia, in August 2011. The 56 revised full papers presented were carefully reviewed and selected from numerous submissions. The ruSMART papers are organized in topical sections on role of context in smart spaces, smart spaces platforms and smart-M3, methods for studying smart spaces, and smart spaces solutions. The NEW2AN papers are organized in topical sections on wireless PHY and power control, ad hoc networks, WSN, special topics, simulation + fundamental analysis I, traffic modeling and measurement, simulation + fundamental analysis II, network performance and QoS, cooperative, P2P, overlay networks and content, applications and services, API and software, and video.


Book Synopsis Smart Spaces and Next Generation Wired/Wireless Networking by : Sergey Balandin

Download or read book Smart Spaces and Next Generation Wired/Wireless Networking written by Sergey Balandin and published by Springer Science & Business Media. This book was released on 2011-07-28 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networking, NEW2AN 2011 and the 4th Conference on Smart Spaces, ruSMART 2011 jointly held in St. Petersburg, Russia, in August 2011. The 56 revised full papers presented were carefully reviewed and selected from numerous submissions. The ruSMART papers are organized in topical sections on role of context in smart spaces, smart spaces platforms and smart-M3, methods for studying smart spaces, and smart spaces solutions. The NEW2AN papers are organized in topical sections on wireless PHY and power control, ad hoc networks, WSN, special topics, simulation + fundamental analysis I, traffic modeling and measurement, simulation + fundamental analysis II, network performance and QoS, cooperative, P2P, overlay networks and content, applications and services, API and software, and video.

Self-Similar Processes in Telecommunications

Self-Similar Processes in Telecommunications

Author: Oleg Sheluhin

Publisher: John Wiley & Sons

Published: 2007-03-13

Total Pages: 334

ISBN-13: 9780470062104

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For the first time the problems of voice services self-similarity are discussed systematically and in detail with specific examples and illustrations. Self-Similar Processes in Telecommunications considers the self-similar (fractal and multifractal) models of telecommunication traffic and efficiency based on the assumption that its traffic has fractal or multifractal properties (is self-similar). The theoretical aspects of the most well-known traffic models demonstrating self-similar properties are discussed in detail and the comparative analysis of the different models’ efficiency for self-similar traffic is presented. This book demonstrates how to use self-similar processes for designing new telecommunications systems and optimizing existing networks so as to achieve maximum efficiency and serviceability. The approach is rooted in theory, describing the algorithms (the logical arithmetical or computational procedures that define how a task is performed) for modeling these self-similar processes. However, the language and ideas are essentially accessible for those who have a general knowledge of the subject area and the advice is highly practical: all models, problems and solutions are illustrated throughout using numerous real-world examples. Adopts a detailed, theoretical, yet broad-based and practical mathematical approach for designing and operating numerous types of telecommunications systems and networks so as to achieve maximum efficiency Places the subject in context, describing the current algorithms that make up the fractal or self-similar processes while pointing to the future development of the technology Offers a comparative analysis of the different types of self-similar process usage within the context of local area networks, wide area networks and in the modeling of video traffic and mobile communications networks Describes how mathematical models are used as a basis for building numerous types of network, including voice, audio, data, video, multimedia services and IP (Internet Protocol) telephony The book will appeal to the wide range of specialists dealing with the design and exploitation of telecommunication systems. It will be useful for the post-graduate students, lecturers and researchers connected with communication networks disciplines.


Book Synopsis Self-Similar Processes in Telecommunications by : Oleg Sheluhin

Download or read book Self-Similar Processes in Telecommunications written by Oleg Sheluhin and published by John Wiley & Sons. This book was released on 2007-03-13 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the first time the problems of voice services self-similarity are discussed systematically and in detail with specific examples and illustrations. Self-Similar Processes in Telecommunications considers the self-similar (fractal and multifractal) models of telecommunication traffic and efficiency based on the assumption that its traffic has fractal or multifractal properties (is self-similar). The theoretical aspects of the most well-known traffic models demonstrating self-similar properties are discussed in detail and the comparative analysis of the different models’ efficiency for self-similar traffic is presented. This book demonstrates how to use self-similar processes for designing new telecommunications systems and optimizing existing networks so as to achieve maximum efficiency and serviceability. The approach is rooted in theory, describing the algorithms (the logical arithmetical or computational procedures that define how a task is performed) for modeling these self-similar processes. However, the language and ideas are essentially accessible for those who have a general knowledge of the subject area and the advice is highly practical: all models, problems and solutions are illustrated throughout using numerous real-world examples. Adopts a detailed, theoretical, yet broad-based and practical mathematical approach for designing and operating numerous types of telecommunications systems and networks so as to achieve maximum efficiency Places the subject in context, describing the current algorithms that make up the fractal or self-similar processes while pointing to the future development of the technology Offers a comparative analysis of the different types of self-similar process usage within the context of local area networks, wide area networks and in the modeling of video traffic and mobile communications networks Describes how mathematical models are used as a basis for building numerous types of network, including voice, audio, data, video, multimedia services and IP (Internet Protocol) telephony The book will appeal to the wide range of specialists dealing with the design and exploitation of telecommunication systems. It will be useful for the post-graduate students, lecturers and researchers connected with communication networks disciplines.