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Titlebook: Mathematical and Statistical Methods for Insurance and Finance; Cira Perna,Marilena Sibillo Conference proceedings 2008 Springer-Verlag Mi

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发表于 2025-3-21 16:29:31 | 显示全部楼层 |阅读模式
书目名称Mathematical and Statistical Methods for Insurance and Finance
编辑Cira Perna,Marilena Sibillo
视频video
图书封面Titlebook: Mathematical and Statistical Methods for Insurance and Finance;  Cira Perna,Marilena Sibillo Conference proceedings 2008 Springer-Verlag Mi
描述.The interaction between mathematicians and statisticians reveals to be an effective approach to the analysis of insurance and financial problems, in particular in an operative perspective. The Maf2006 conference, held at the University of Salerno in 2006, had precisely this purpose and the collection here published gathers some of the papers presented at the conference and successively worked out to this aim. They cover a wide variety of subjects in insurance and financial fields, all treated in light of the successful cooperation between the two quantitative methods. .
出版日期Conference proceedings 2008
关键词ARC; Analysis; Quantitative Methods; STATISTICA; Statistical Methods; Stochastic Optimization; Stochastic
版次1
doihttps://doi.org/10.1007/978-88-470-0704-8
isbn_softcover978-88-470-5601-5
isbn_ebook978-88-470-0704-8
copyrightSpringer-Verlag Milan 2008
The information of publication is updating

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Decision Making in Financial Markets Through Multivariate Ordering Procedure,ent scales and, as we will show, this can lead to undesired results. As a matter of fact, we show that, without an appropriate rescaling, variables with a large range of variation (.) are “overweighted” with respect to variables with a small one.
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blems, in particular in an operative perspective. The Maf2006 conference, held at the University of Salerno in 2006, had precisely this purpose and the collection here published gathers some of the papers presented at the conference and successively worked out to this aim. They cover a wide variety
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Scaling Laws in Stock Markets. An Analysis of Prices and Volumes,the scaling parameter heavily changes with the considered pair of time horizons. Opposite evidence is provided for the volumes, characterized by (generally low) self-similarity parameters which are somewhat uniform with respect to the pairs of time horizons.
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