Isbn: 9783030642525 - counting statistics for dependent random events: with a focus on finance (15 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2022

    3030642526 / 9783030642525

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  • Lingua: Inglese

    Editore: Springer, 2022

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  • Lingua: Inglese

    Editore: Springer, 2022

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  • Lingua: Inglese

    Editore: Springer, 2022

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    Condizione: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

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    Lingua: Inglese

    Editore: Springer, 2022

    3030642526 / 9783030642525

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    Taschenbuch. Condizione: Neu. Counting Statistics for Dependent Random Events | With a Focus on Finance | Enrico Bernardi (u. a.) | Taschenbuch | xiii | Englisch | 2022 | Springer | EAN 9783030642525 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030642526 / 9783030642525

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030642526 / 9783030642525

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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    Condizione: new. Questo è un articolo print on demand.

  • Lingua: Inglese

    Editore: Springer International Publishing Mrz 2022, 2022

    3030642526 / 9783030642525

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    Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 220 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer International Publishing, 2022

    3030642526 / 9783030642525

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    Da: moluna, Greven, Germaniamoluna

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Proposes a novel approach to counting dependent random events, combining clustering, copulas and combinatoricsIncludes examples and real-world data applications to demonstrate the new techniquesReduces the complexity of problems arising fro.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030642526 / 9783030642525

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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    EUR 176,03

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    Condizione: New. Print on Demand.

  • Lingua: Inglese

    Editore: Springer, 2022

    3030642526 / 9783030642525

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    Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios

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  • Lingua: Inglese

    Editore: Springer, Springer Mär 2022, 2022

    3030642526 / 9783030642525

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    Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 220 pp. Englisch.