Mathematical and Statistical Methods for Actuarial Sciences and Finance

  • Cira Perna
  • Marilena Sibillo

Table of contents

  1. Front Matter
    Pages I-X
  2. Irene Albarrán, Pablo Alonso, Ana Arribas-Gil, Aurea Grané
    Pages 1-5
  3. Alessandra Amendola, Vincenzo Candila
    Pages 7-10
  4. Alessandra Amendola, Marialuisa Restaino
    Pages 11-15
  5. Roberto Baragona, Francesco Battaglia, Domenico Cucina
    Pages 17-20
  6. Simona Boffelli, Giovanni Urga
    Pages 35-39
  7. Stefano Bonini, Giuliana Caivano
    Pages 41-44
  8. Stefano Bonini, Giuliana Caivano
    Pages 45-48
  9. Stefania Capecchi, Domenico Piccolo
    Pages 49-52
  10. Massimiliano Caporin, Luca Corazzini, Michele Costola
    Pages 53-56
  11. Rocco Roberto Cerchiara, Vittorio Magatti
    Pages 61-64
  12. Mariarosaria Coppola, Valeria D’Amato
    Pages 65-68
  13. Valeria D’Amato, Steven Haberman, Gabriella Piscopo, Maria Russolillo
    Pages 73-76
  14. Antonio Di Crescenzo, Barbara Martinucci, Shelemyahu Zacks
    Pages 81-85

About this book


The interaction between mathematicians and statisticians working in the actuarial and financial fields is producing numerous meaningful scientific results. This volume, comprising a series of four-page papers, gathers new ideas relating to mathematical and statistical methods in the actuarial sciences and finance.

The book covers a variety of topics of interest from both theoretical and applied perspectives, including: actuarial models; alternative testing approaches; behavioral finance; clustering techniques; coherent and non-coherent risk measures; credit-scoring approaches; data envelopment analysis; dynamic stochastic programming; financial contagion models; financial ratios; intelligent financial trading systems; mixture normality approaches; Monte Carlo-based methodologies; multicriteria methods; nonlinear parameter estimation techniques; nonlinear threshold models; particle swarm optimization; performance measures; portfolio optimization; pricing methods for structured and non-structured derivatives; risk management; skewed distribution analysis; solvency analysis; stochastic actuarial valuation methods; variable selection models; and time series analysis tools.

This book will be of value for academics, PhD students, practitioners, professionals, and researchers. It will also be of interest to other readers with some quantitative background knowledge.


Insurance Mathematical Models Quantitative Finance Statistics Time series

Editors and affiliations

  • Cira Perna
    • 1
  • Marilena Sibillo
    • 2
  1. 1.Department of Economics and StatisticsUniversity of SalernoFiscianoItaly
  2. 2.Department of Economics and StatisticsUniversity of SalernoFiscianoItaly

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-05013-3
  • Online ISBN 978-3-319-05014-0
  • About this book