Counting statistics for dependent random events : with a focus on finance / Enrico Bernardi, Silvia Romagnoli.
2021
QA273.6
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Title
Counting statistics for dependent random events : with a focus on finance / Enrico Bernardi, Silvia Romagnoli.
Author
ISBN
9783030642501 (electronic book)
303064250X (electronic book)
3030642496
9783030642495
303064250X (electronic book)
3030642496
9783030642495
Published
Cham, Switzerland : Springer, [2021]
Language
English
Description
1 online resource (xiii, 206 pages) : illustrations
Item Number
10.1007/978-3-030-64250-1 doi
Call Number
QA273.6
Dewey Decimal Classification
519.5/35
Summary
This book on counting statistics presents a novel copula-based approach to counting dependent random events. It combines clustering, combinatorics-based algorithms and dependence structure in order to tackle and simplify complex problems, without disregarding the hierarchy of or interconnections between the relevant variables. These problems typically arise in real-world applications and computations involving big data in finance, insurance and banking, where experts are confronted with counting variables in monitoring random events. In this new approach, combinatorial distributions of random events are the core element. In order to deal with the high-dimensional features of the problem, the combinatorial techniques are used together with a clustering approach, where groups of variables sharing common characteristics and similarities are identified and the dependence structure within groups is taken into account. The original problems can then be modeled using new classes of copulas, referred to here as clusterized copulas, which are essentially based on preliminary groupings of variables depending on suitable characteristics and hierarchical aspects. The book includes examples and real-world data applications, with a special focus on financial applications, where the new algorithms performance is compared to alternative approaches and further analyzed. Given its scope, the book will be of interest to master students, PhD students and researchers whose work involves or can benefit from the innovative methodologies put forward here. It will also stimulate the empirical use of new approaches among professionals and practitioners in finance, insurance and banking.
Bibliography, etc. Note
Includes bibliographical references.
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Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed April 7, 2021).
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Available in Other Form
Print version: 9783030642495
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Table of Contents
Clustering
Copula function and C-volume
Combinatorics and random matrices : a brief review
Counting a random event : traditional approaches and new perspectives
A new copula-based approach for counting : the distorted and the limiting case
Real data empirical applications.
Copula function and C-volume
Combinatorics and random matrices : a brief review
Counting a random event : traditional approaches and new perspectives
A new copula-based approach for counting : the distorted and the limiting case
Real data empirical applications.