Self Normalized Processes
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Self Normalized Processes
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Author : Victor H. Peña
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-25
Self Normalized Processes written by Victor H. Peña and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-25 with Mathematics categories.
Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is on the front cover. Due to the highly non-linear nature of these processes, the theory experienced a long period of slow development. In recent years there have been a number of important advances in the theory and applications of self-normalized processes. Some of these developments are closely linked to the study of central limit theorems, which imply that self-normalized processes are approximate pivots for statistical inference. The present volume covers recent developments in the area, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales. This is the first book that systematically treats the theory and applications of self-normalization.
Probability Finance And Insurance
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Author : T. L. Lai
language : en
Publisher: World Scientific
Release Date : 2004
Probability Finance And Insurance written by T. L. Lai and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Business & Economics categories.
This workshop was the first of its kind in bringing together researchers in probability theory, stochastic processes, insurance and finance from mainland China, Taiwan, Hong Kong, Singapore, Australia and the United States. In particular, as China has joined the WTO, there is a growing demand for expertise in actuarial sciences and quantitative finance. The strong probability research and graduate education programs in many of China's universities can be enriched by their outreach in fields that are of growing importance to the country's expanding economy, and the workshop and its proceedings can be regarded as the first step in this direction. This book presents the most recent developments in probability, finance and actuarial sciences, especially in Chinese probability research. It focuses on the integration of probability theory with applications in finance and insurance. It also brings together academic researchers and those in industry and government. With contributions by leading authorities on probability theory OCo particularly limit theory and large derivations, valuation of credit derivatives, portfolio selection, dynamic protection and ruin theory OCo it is an essential source of ideas and information for graduate students and researchers in probability theory, mathematical finance and actuarial sciences, and thus every university should acquire a copy. The proceedings have been selected for coverage in: . OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings). OCo Index to Social Sciences & Humanities Proceedings- (ISSHP- / ISI Proceedings). OCo Index to Social Sciences & Humanities Proceedings (ISSHP CDROM version / ISI Proceedings). OCo CC Proceedings OCo Engineering & Physical Sciences. Contents: Limit Theorems for Moving Averages (T L Lai); On Large Deviations for Moving Average Processes (L Wu); Recent Progress on Self-Normalized Limit Theorems (Q-M Shao); Limit Theorems for Independent Self-Normalized Sums (B-Y Jing); Phase Changes in Random Recursive Structures and Algorithms (H-K Hwang); JohnsonOCoMehl Tessellations: Asymptotics and Inferences (S N Chiu); Rapid Simulation of Correlated Defaults and the Valuation of Basket Default Swaps (Z Zhang et al.); Dynamic Protection with Optimal Withdrawal (H U Gerber & E S W Shiu); Ruin Probability for a Model Under Markovian Switching Regime (H Yang & G Yin); and other papers. Readership: Researchers and graduate students in probability and statistics."
Sharp Martingale And Semimartingale Inequalities
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Author : Adam Osękowski
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-08-14
Sharp Martingale And Semimartingale Inequalities written by Adam Osękowski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-14 with Mathematics categories.
This monograph is a presentation of a unified approach to a certain class of semimartingale inequalities, which can be regarded as probabilistic extensions of classical estimates for conjugate harmonic functions on the unit disc. The approach, which has its roots in the seminal works of Burkholder in the 80s, enables to deduce a given inequality for semimartingales from the existence of a certain special function with some convex-type properties. Remarkably, an appropriate application of the method leads to the sharp version of the estimate under investigation, which is particularly important for applications. These include the theory of quasiregular mappings (with deep implications to the geometric function theory); the boundedness of two-dimensional Hilbert transform and a more general class of Fourier multipliers; the theory of rank-one convex and quasiconvex functions; and more. The book is divided into a few separate parts. In the introductory chapter we present motivation for the results and relate them to some classical problems in harmonic analysis. The next part contains a general description of the method, which is applied in subsequent chapters to the study of sharp estimates for discrete-time martingales; discrete-time sub- and supermartingales; continuous time processes; the square and maximal functions. Each chapter contains additional bibliographical notes included for reference.
Long Range Dependence And Self Similarity
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Author : Vladas Pipiras
language : en
Publisher: Cambridge University Press
Release Date : 2017-04-18
Long Range Dependence And Self Similarity written by Vladas Pipiras and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-18 with Business & Economics categories.
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.
Issues In Statistics Decision Making And Stochastics 2013 Edition
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Author :
language : en
Publisher: ScholarlyEditions
Release Date : 2013-05-01
Issues In Statistics Decision Making And Stochastics 2013 Edition written by and has been published by ScholarlyEditions this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-01 with Mathematics categories.
Issues in Statistics, Decision Making, and Stochastics: 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Regular and Chaotic Dynamics. The editors have built Issues in Statistics, Decision Making, and Stochastics: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Regular and Chaotic Dynamics in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Statistics, Decision Making, and Stochastics: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Parameter Estimation In Stochastic Volatility Models
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Author : Jaya P. N. Bishwal
language : en
Publisher: Springer Nature
Release Date : 2022-08-06
Parameter Estimation In Stochastic Volatility Models written by Jaya P. N. Bishwal and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-06 with Mathematics categories.
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
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Author : Paul Embrechts
language : en
Publisher: Princeton University Press
Release Date : 2009-01-10
Selfsimilar Processes written by Paul Embrechts and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-10 with Mathematics categories.
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.
Asymptotic Laws And Methods In Stochastics
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Author : Donald Dawson
language : en
Publisher: Springer
Release Date : 2015-11-12
Asymptotic Laws And Methods In Stochastics written by Donald Dawson and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-12 with Mathematics categories.
This book contains articles arising from a conference in honour of mathematician-statistician Miklόs Csörgő on the occasion of his 80th birthday, held in Ottawa in July 2012. It comprises research papers and overview articles, which provide a substantial glimpse of the history and state-of-the-art of the field of asymptotic methods in probability and statistics, written by leading experts. The volume consists of twenty articles on topics on limit theorems for self-normalized processes, planar processes, the central limit theorem and laws of large numbers, change-point problems, short and long range dependent time series, applied probability and stochastic processes, and the theory and methods of statistics. It also includes Csörgő’s list of publications during more than 50 years, since 1962.
The Poisson Dirichlet Distribution And Related Topics
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Author : Shui Feng
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-05-27
The Poisson Dirichlet Distribution And Related Topics written by Shui Feng and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-27 with Mathematics categories.
Presenting a comprehensive study of the Poisson-Dirichlet distribution, this volume emphasizes recent progress in evolutionary dynamics and asymptotic behaviors. The self-contained text presents methods and techniques that appeal to researchers in a wide variety of subjects.
Statistics For Long Memory Processes
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Author : Jan Beran
language : en
Publisher: CRC Press
Release Date : 1994-10-01
Statistics For Long Memory Processes written by Jan Beran and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-10-01 with Mathematics categories.
Statistical Methods for Long Term Memory Processes covers the diverse statistical methods and applications for data with long-range dependence. Presenting material that previously appeared only in journals, the author provides a concise and effective overview of probabilistic foundations, statistical methods, and applications. The material emphasizes basic principles and practical applications and provides an integrated perspective of both theory and practice. This book explores data sets from a wide range of disciplines, such as hydrology, climatology, telecommunications engineering, and high-precision physical measurement. The data sets are conveniently compiled in the index, and this allows readers to view statistical approaches in a practical context. Statistical Methods for Long Term Memory Processes also supplies S-PLUS programs for the major methods discussed. This feature allows the practitioner to apply long memory processes in daily data analysis. For newcomers to the area, the first three chapters provide the basic knowledge necessary for understanding the remainder of the material. To promote selective reading, the author presents the chapters independently. Combining essential methodologies with real-life applications, this outstanding volume is and indispensable reference for statisticians and scientists who analyze data with long-range dependence.