Heavy-Tailed Time Series

This book aims to present a comprehensive, self-contained, and concise overview of extreme value theory for time series, incorporating the latest research trends alongside classical methodology. Appropriate for graduate coursework or professional reference, the book requires a background in extreme...

Full description

Bibliographic Details
Main Authors: Kulik, Rafal, Soulier, Philippe (Author)
Format: eBook
Language:English
Published: New York, NY Springer New York 2020, 2020
Edition:1st ed. 2020
Series:Springer Series in Operations Research and Financial Engineering
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary:This book aims to present a comprehensive, self-contained, and concise overview of extreme value theory for time series, incorporating the latest research trends alongside classical methodology. Appropriate for graduate coursework or professional reference, the book requires a background in extreme value theory for i.i.d. data and basics of time series. Following a brief review of foundational concepts, it progresses linearly through topics in limit theorems and time series models while including historical insights at each chapter’s conclusion. Additionally, the book incorporates complete proofs and exercises with solutions as well as substantive reference lists and appendices, featuring a novel commentary on the theory of vague convergence
Physical Description:XIX, 681 p. 7 illus., 5 illus. in color online resource
ISBN:9781071607374