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Titlebook: Mathematical and Statistical Methods for Actuarial Sciences and Finance; MAF2024 Marco Corazza,Frédéric Gannon,Vincent Touzé Conference pro

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書目名稱Mathematical and Statistical Methods for Actuarial Sciences and Finance
副標(biāo)題MAF2024
編輯Marco Corazza,Frédéric Gannon,Vincent Touzé
視頻videohttp://file.papertrans.cn/627/626720/626720.mp4
概述Presents cooperation and contamination between mathematicians and statisticians working in actuarial sciences.Gives concise and agile presentation of research results in short articles.Covers a wide r
圖書封面Titlebook: Mathematical and Statistical Methods for Actuarial Sciences and Finance; MAF2024 Marco Corazza,Frédéric Gannon,Vincent Touzé Conference pro
描述.The book presents a collection of peer-reviewed short papers selected from those presented at the International Conference .Mathematical and Statistical Methods for Actuarial Sciences and Finance – MAF2024.. The year 2024 marks the twentieth anniversary of the first edition of this conference...The idea behind this book is that collaboration and cross-pollination between mathematicians and statisticians working in actuarial sciences and finance could enhance research in these fields. The effectiveness of this concept has been demonstrated by widespread participation across all editions, held at various locations including the University of Salerno, Italy (2004, 2006, 2010, 2014, and 2022); Ca‘ Foscari University of Venice, Italy (2008, 2012, and 2020); University Paris-Dauphine in Paris, France (2016); University Carlos III of Madrid, Madrid (2018); and University of Le Havre Normandie, Le Havre, France (2024). This effectiveness is also evident in the attention consistently shown by both the scientific community and professionals toward the volumes of peer-reviewed papers accompanying all past editions of MAF...The book is a valuable resource for academics, researchers, Ph.D. stu
出版日期Conference proceedings 2024
關(guān)鍵詞Actuarial sciences; ; Quantitative finance; ; Mathematics; ; Statistics; ; Theoretical models; ; Methodologica
版次1
doihttps://doi.org/10.1007/978-3-031-64273-9
isbn_softcover978-3-031-64275-3
isbn_ebook978-3-031-64273-9
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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,Hierarchical Clustering of?Time Series with?Wasserstein Distance,Two methods are presented in order to create a dissimilarity measure for random variables. These methods exploit some theoretical and computational advantages of the Wasserstein distance. The dissimilarity measures are hence applied to develop a hierarchical clustering procedure for time series, which are especially helpful in risk analysis.
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Giovanna Apicella,Emilia Di Lorenzo,Giulia Magni,Marilena Sibillopportunities for Cuban economists and scholars to participate in the development of the reform program. Thanks to grants from SSRC (Social Sciences Research Council, New York) and the Norwegian Ministry of Foreign Affairs, several researchers from the Cuban think tank CEEC (Center for Studies of the
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Fabio Baione,Davide Biancalana,Paolo De Angelispportunities for Cuban economists and scholars to participate in the development of the reform program. Thanks to grants from SSRC (Social Sciences Research Council, New York) and the Norwegian Ministry of Foreign Affairs, several researchers from the Cuban think tank CEEC (Center for Studies of the
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