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This volume gathers selected peer-reviewed papers presented at the international conference "MAF 2016 - Mathematical and Statistical Methods for Actuarial Sciences and Finance", held in Paris (France) at the Université Paris-Dauphine from March 30 to April 1, 2016.
The contributions highlight new ideas on mathematical and statistical methods in actuarial sciences and finance. The cooperation between mathematicians and statisticians working in insurance and finance is a very fruitful field, one that yields unique theoretical models and practical applications, as well as new insights in the…mehr

Produktbeschreibung
This volume gathers selected peer-reviewed papers presented at the international conference "MAF 2016 - Mathematical and Statistical Methods for Actuarial Sciences and Finance", held in Paris (France) at the Université Paris-Dauphine from March 30 to April 1, 2016.

The contributions highlight new ideas on mathematical and statistical methods in actuarial sciences and finance. The cooperation between mathematicians and statisticians working in insurance and finance is a very fruitful field, one that yields unique theoretical models and practical applications, as well as new insights in the discussion of problems of national and international interest.

This volume is addressed to academicians, researchers, Ph.D. students and professionals.
Autorenporträt
Marco Corazza PhD in "Mathematics for the Analysis of Financial Markets" is an associate professor at the Department of Economics of the Ca' Foscari University of Venice (Italy). His main research interests include static and dynamic portfolio management theories; trading system models; machine learning applications in finance; bio-inspired optimization techniques; multi-criteria methods for economic decision support; port scheduling models and algorithms; non-standard probability distributions in finance. He has participated in several research projects, both at national and international level, and is the author/coauthor of about one hundred and twenty scientific publications; some of which have received national and international awards. He is also editor-in-chief of the international scientific journal "Mathematical Methods in Economics and Finance", and is a member of the scientific committees of several conferences and of some private companies. His combines his academic activities with consulting services. Prof. Cira Perna is a professor of Statistics and head of the Department of Economics and Statistics, University of Salerno (Italy). Her research work mainly focuses on non-linear time series, artificial neural network models and resampling techniques and she has published numerous papers on these topics in national and international journals. She has been a member of several scientific committees of national and international conferences. Prof. Marilena Sibillo is a professor of Mathematical Methods for Economics, Finance and Actuarial Sciences at the University of Salerno (Italy). She has several international editing engagements and is the author of over a hundred publications. Her research interests are mainly in longevity risk in life contracts, de-risking strategies, personal pension products and mortality forecasting. Prof. Florence Legros is currently dean of the ICN Business School and general delegate of the ARTEM alliance. She was previously a professor at the University of Paris Dauphine where she was director of the Insurance School, and the "magistère" Bank-Finance and Insurance as well as the E-MBA Insurance. Her research addresses ageing, pensions, social policies, savings and their effects on economic growth and financial flows. She has acted as a consultant for international administrations, served as an expert in the French prime minister's pensions advisory council and as a scientific adviser for various institutions. Between 2008 and 2011, she was chief education officer (Rector) for the Region of Burgundy (France). Between 1999 and 2004 she was deputy director of CEPII, where she actively took part in the creation of the European network Enepri.