Mathematical and Statistical Methods for Actuarial Sciences and Finance

The interaction between mathematicians, statisticians and econometricians working in actuarial sciences and finance is producing numerous meaningful scientific results. This volume introduces new ideas, in the form of four-page papers, presented at the international conference Mathematical and Statistical Methods for Actuarial Sciences and Finance (MAF), held at Universidad Carlos III de Madrid (Spain), 4th-6th April 2018.

The book covers a wide variety of subjects in actuarial science and financial fields, all discussed in the context of the cooperation between the three quantitative approaches. The topics include: actuarial models; analysis of high frequency financial data; behavioural finance; carbon and green finance; credit risk methods and models; dynamic optimization in finance; financial econometrics; forecasting of dynamical actuarial and financial phenomena; fund performance evaluation; insurance portfolio risk analysis; interest rate models; longevity risk; machine learning and soft-computing in finance; management in insurance business; models and methods for financial time series analysis, models for financial derivatives; multivariate techniques for financial markets analysis; optimization in insurance; pricing; probability in actuarial sciences, insurance and finance; real world finance; risk management; solvency analysis; sovereign risk; static and dynamic portfolio selection and management; trading systems.

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

Offers selected peer-reviewed papers Focuses on mathematical and statistical methods in actuarial sciences and finance Intended for academicians, researchers, Ph.D. students and professionals

Auteur

Marco Corazza has a PhD in "Mathematics for the Analysis of Financial Markets" and 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; and non-standard probability distributions in finance. He has participated in several research projects, at both the national and international level, and is the author/coauthor of 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.

María Durbán is a professor of Statistics at Universidad Carlos III de Madrid (Spain). Her main areas of research are non-parametric regression, smooth mixed models and regression models for spatio-temporal data. She has numerous publications in these topics and their application in areas such as epidemiology, economics, and environmental sciences. She has been part of many scientific committees of international conferences.

Aurea Grané is a professor of Statistics at Universidad Carlos III de Madrid (Spain). Her research interests are mainly in goodness-of-fit, multivariate techniques for mixed-type data, functional data analysis and she has published numerous papers on these topics in international journals. She has been a member of several scientific committees of international conferences, and was co-director of the Master in Quantitative Techniques for the Insurance Sector and vice-director of the Department of Statistics at Universidad Carlos III de Madrid.

Cira Perna is a professor of Statistics and head of the Department of Economics and Statistics, University of Salerno (Italy). Her research 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.

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.

Contenu
1 M. Caporin, G. Bonaccolto and S. Paterlini, Conditional Autoregressive Quantile-Located Value-at-Risk.- 2 M. Galeotti, G. Rabitti and E. Vannucci, The Rearrangement algorithm of Puccetti and Rüschendorf: proving the convergence.- 3 R. Cesari and V. Mosco, Optimal Management of Immunized Portfolios.- 4 E. Russo, M. Costabile and I. Massabo, Evaluating variable annuities with GMWB when exogenous factors influence the policy-holder withdrawals.- 5 A. Jokiel-Rokita and R. Magiera, Estimation and prediction for the modulated power law process.- 6 M. De La O González and F. Jareño, Extensions of Fama and French models.- 7 A. Hitaj, L. Mercuri and E. Rroji, Stochastic mortality modelling: some extensions based on Lévy CARMA models.- 8 L. Ballester, R. Fernández and A. González-Urteaga, An empirical analysis of the lead lag relationship between the CDS and stock market: Evidence in Europe and US.- 9 I.L. Amerise, Automatic detection and imputation of outliers in electricity price time series.- 10 F. Giordano, M. Niglio and M. Restaino, Variable selection in estimating bank default.- 11 F. Jareño, M.Á. Medina, M. Tolentino and M. De La O González, European Insurers: Interest Rate Risk Management.- 12 M. Corazza and C. Nardelli, Comparing possibilistic portfolios to probabilistic ones.- 13 M. Maggi and P. Uberti, Google searches for portfolio management: a risk and return analysis.- 14 M.C. Schisani, M.P. Vitale and G. Ragozini, Financial Networks and Mechanisms of Business Capture in Southern Italy over the First Global Wave (1812-1913). A Network Approach.- 15 H. Gzyl, S. Mayoral and E. P. Gomes, Loss data analysis with maximum entropy.- 16 I.D.Fabián, P. Devolder, J. A. Herce and F. Del Olmo, A two-steps mixed pension system: An aggregate analysis.- 17 D. Atance and E. Navarro, A Single Factor Model for Constructing Dynamic Life Tables.- 18 L. Sanchis, J.M. Montero and G. Fernández-Avilés, Downside risk co-movement in commodity markets during distress periods. A Multidimensional scaling approach.- 19 G. Caivano and S. Bonini, Probability of Default Modeling: A Machine Learning Approach.- 20 S. Corsaro, V. De Simone, Z. Marino and F. Perla, Numerical solution of the regularized portfolio selection problem.- 21 N. Ahlgren and P. Catani, Practical Problems with Tests of Cointegration Rank with Strong Persistence and Heavy-Tailed Errors.- 22 M. De La O Gonzalez, F. Jareño and C. El Haddouti Ben Ali, The Islamic Financial Industry. Performance of Islamic vs. conventional sector portfolios.- 23 L. Invernizzi and V. Magatti, Could Machine Learning predict the Conversion in Motor Business?.- 24 S. Albosaily and S. Pergamenshchikov, The optimal investment and consumption for financial markets generated by the spread of risky assets for the power utility.- 25 M.E. De Giuli, M. Neffelli and M. Resta, An Integrated Approach to Explore the Complexity of Interest Rates Network Structure.- 26 I. Fuente, E. Navarro and G. Serna, Estimating regulatory capital requirements for reverse mortgages. An international comparison .- 27 L. Gómez-Valle and J. Martínez-Rodríguez, Real-world versus neutral risk measures in the estimation of an interest rate model with stochastic volatility.- 28 G. Apicella, M. Daco…