Mathematical and statistical methods for actuarial sciences and finance : [electronic resource] MAF 2018 / Edited by Marco Corazza and 4 others.

Intro; Preface; Contents; About the Editors; The Effect of Rating Contingent Guidelines and Regulation Around Credit Rating News; 1 Introduction; 2 Rating-Based Investment Guidelines; 3 Data and Analysis Implementation; 4 Results; 5 Concluding Remarks; References; Practical Problems with Tests of Cointegration Rank with Strong Persistence and Heavy-Tailed Errors; 1 Introduction; 2 Power of Tests in the Heteroskedastic VAR Model with Heavy-Tailed Errors; 3 Empirical Results; 4 Conclusions; References; Inference in a Non-Homogeneous Vasicek Type Model; 1 Introduction and Background; 2 The Model 3 Fitting the Model4 A Simulation Study; References; Small Sample Analysis in Diffusion Processes: A Simulation Study; 1 Introduction; 2 ML Estimation and Bootstrap Correction; 3 Simulation Experiment and Results; References; Using Deepest Dependency Paths to Enhance Life ExpectancyEstimation; 1 Introduction; 2 Methodology; 3 Results; References; The Optimal Investment and Consumption for Financial Markets Generated by the Spread of Risky Assets for the Power Utility; 1 Market Model; 2 Stochastic Programming Method; 3 Main Results; References; Combining Multivariate Volatility Models 1 Introduction2 MCS Combination Strategy; 3 Empirical Analysis; References; Automatic Detection and Imputation of Outliers in Electricity Price Time Series; 1 Introduction; 2 Time Series Outlier Detection and Imputation; 3 Results and Discussion; References; Bayesian Factorization Machines for Risk Management and Robust Decision Making; 1 Introduction; 2 Prediction; 3 Multiobjective Optimization; References; Improving Lee-Carter Forecasting: Methodology and Some Results; 1 Introduction and Literature; 2 Mathematical Framework and Empirical Methodology 3 Graphical Assessment of the Predictive Accuracy of the ``mLC'' Model4 Concluding Remarks; References; The Bank Tailored Integrated Rating; 1 Motivation and Methodology; 2 Stylized Mathematical Approach; 3 Summaries and Future Developments; Appendix; References; A Single Factor Model for Constructing Dynamic Life Tables; 1 Single Factor Model; 1.1 Adjusting a Sensitivity Function to bx, x*; 1.2 Forecasting Mortality Rates; 2 Lee-Carter (1992) Model; 3 Comparison Between the Single Factor Model and the Lee-Carter Model; References; Variable Annuities with State-Dependent Fees; 1 Introduction 2 The Structure of the Contract3 Valuation Framework; 3.1 The Static Approach; 3.2 The Mixed Approach; 4 Numerical Implementation; References; Dynamic Policyholder Behavior and Surrender Option Evaluation for Life Insurance; 1 Introduction; 2 A Model for the Lapse Rate Estimation According to Policyholder Behavior; 2.1 Step 1; 2.2 Step 2; 3 Some Numerical Results; References; Classification Ratemaking via Quantile Regression and a Comparison with Generalized Linear Models; 1 Introduction; 2 A Quantile Premium Principle Based on a Two-Part Model

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.