Mathematical and Statistical Methods for Actuarial Sciences and Finance (eBook)

MAF 2022

Marco Corazza, Cira Perna, Claudio Pizzi, Marilena Sibillo (Herausgeber)

eBook Download: PDF

2022 | 1st ed. 2022
XIV, 443 Seiten
Springer International Publishing (Verlag)
978-3-030-99638-3 (ISBN)

Infos

The cooperation and contamination among mathematicians, statisticians and econometricians working in actuarial sciences and finance are improving the research on these topics and producing numerous meaningful scientific results. This volume presents new ideas in the form of four- to six-page papers presented at the International Conference MAF2022 - Mathematical and Statistical Methods for Actuarial Sciences and Finance. Due to the COVID-19 pandemic, the conference, to which this book is related, was organized in a hybrid form by the Department of Economics and Statistics of the University of Salerno, with the partnership of the Department of Economics of Cà Foscari University of Venice, and was held from 20 to 22 April 2022 in Salerno (Italy) 

MAF2022 is the tenth edition of an international biennial series of scientific meetings, started in 2004 on the initiative of the Department of Economics and Statistics of the University of Salerno. It has established itself internationally with gradual and continuous growth and scientific enrichment. The effectiveness of this idea has been proven by the wide participation in all the editions, which have been held in Salerno (2004, 2006, 2010, 2014, 2022), Venice (2008, 2012 and 2020 online), Paris (2016) and Madrid (2018).

This book covers a wide variety of subjects: artificial intelligence and machine learning in finance and insurance, behavioural finance, credit risk methods and models, dynamic optimization in finance, financial data analytics, forecasting dynamics of actuarial and financial phenomena, foreign exchange markets, insurance models, interest rate models, longevity risk, models and methods for financial time series analysis, multivariate techniques for financial markets analysis, pension systems, portfolio selection and management, real-world finance, risk analysis and management, trading systems, and others.

This volume is a valuable resource for academics, PhD students, practitioners, professionals and researchers. Moreover, it is also of interest to other readers with quantitative background knowledge.

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. Among his main research interests are static and dynamic portfolio management theories, trading system models, machine learning applications in finance, bioinspired metaheuristics for optimization, multicriteria methods for economic decision support, nonstandard probability distributions in finance, port scheduling models and algorithms. He participated and participates in several research projects, both at the national and international levels. He is the author/coauthor of approximately one hundred forty scientific publications; some of them have received national and international awards. He is further editor-in-chief of the international scientific journal 'Mathematical Methods in Economics and Finance', review editor of the international scientific journal 'Frontiers in Applied Mathematics and Statistics', and editor of Springer books. He has been and is a member of the scientific committees of several conferences and of the technical ones of some private companies. He combines academic activity with consulting services

Cira Perna is a full professor of Statistics at the Department of Economics and Statistics of the University of Salerno (Italy). Since 2018, she is an elected member of the Steering Committee of the Italian Statistical Society, and a member of the Board of Directors of the University of Salerno. Since the first edition of the Conference, in 2004, she is the chair of the international conference MAF and guest editor of the associated international journals, and  Editor of the Springer books MAF. Her research work mainly focuses on nonlinear time series, artificial neural network models and resampling techniques. On these topics, she has published numerous papers in national and international journals. She has participated in several research projects, both at the national and international levels, and she has been a member of several scientific committees of national and international conferences.

Claudio Pizzi is an associate professor at the Department of Economics of the Ca' Foscari University of Venice, where he teaches statistical methods for financial and monetary markets and business statistics. His research interests mainly focus on statistical analysis of financial time series, linear and nonlinear models for time series, technical analysis, trading system models, bioinspired meta-heuristics for optimization, and systemic risk. He has participated in both national and international research projects. He is the editor of some Springer books MAF, and he is a member of the editorial board of 'Statistical Method and Applications'.

Marilena Sibillo is a full professor of Mathematical Methods for Economics, Finance and Actuarial Sciences at the University of Salerno and at present an adjunct professor of Financial Mathematics at Luiss University in Rome. In 2012, she was an Emerald Highly Commended Award Winner, and since 2013, she is a Paul Harris Fellow. She has had national and international awards related to teaching. Since 2006 she is Editor of the Springer books MAF, and guest editor of international journals. She is the author of more than 100 papers mostly published in international journals and books. Her scientific activity mainly addresses Actuarial Mathematics. She has a degree in piano from the Conservatorio San Pietro a Majella in Naples.

Produkt-Details

• Erscheint lt. Verlag: 11.4.2022
• Zusatzinfo: XIV, 443 p. 83 illus., 54 illus. in color.
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Schlagworte: insurance • Mathematical Models • Quantitative Finance • Statistics • Time Series
• ISBN-10: 3-030-99638-7 / 3030996387
• ISBN-13: 978-3-030-99638-3 / 9783030996383