Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2010

The interaction between mathematicians and statisticians reveals to be an effective approach for dealing with actuarial, insurance and financial problems, both in an academic and in an operative perspective. The international conference MAF 2008, held at the University Ca' Foscari of Venezia (Italy) in 2008, had precisely this purpose, and the collection here published gathers a selection of about the one hundred papers presented at the conference and successively referred and reviewed to this aim. They cover a wide variety of subjects in actuarial, insurance and financial fields, all treated in light of the successful cooperation between the two quantitative approaches. The subjects considered in the book are: mathematical models for actuarial sciences and insurance (namely: demographic risk, management of actuarial risks, management in insurance business, solvency-based approaches), mathematical models for finance (namely: energy markets, fund and portfolio management, methods for derivative pricing, risk and volatility models), statistical models in finance (namely: artificial neural networks, clustering techniques, kernel-based and robust estimation methods, multivariate methods for the analysis of financial markets, non-standard probabilistic models). The book is mainly addressed to academicians, practitioners, professionals and researchers.

Impact of interest rate risk on the Spanish banking sector.- Tracking error with minimum guarantee constraints.- Energy markets: crucial relationship between prices.- Tempered stable distributions and processes in finance: numerical analysis.- Transformation kernel estimation of insurance claim cost distributions.- What do distortion risk measures tell us on excess of loss reinsurance with reinstatements?.- Some classes of multivariate risk measures.- Assessing risk perception by means of ordinal models.- A financial analysis of surplus dynamics for deferred life schemes.- Checking financial markets via Benford’s law: the S&P 500 case.- Empirical likelihood based nonparametric testing for CAPM.- Lee-Carter error matrix simulation: heteroschedasticity impact on actuarial valuations.- Estimating the volatility term structure.- Exact and approximated option pricing in a stochastic volatility jump-diffusion model.- A skewed GARCH-type model for multivariate financial time series.- Financial time series and neural networks in a minority game context.- Robust estimation of style analysis coefficients.- Managing demographic risk in enhanced pensions.- Clustering mutual funds by return and risk levels.- Multivariate Variance Gamma and Gaussian Dependence: a study with copulas.- A simple dimension reduction procedure for corporate finance composite indicators.- The relation between implied and realised volatility in the DAX index options market.- Binomial algorithms for the evaluation of options on stocks with fixed per share dividends.- Nonparametric prediction in time series analysis: some empirical results.- On efficient optimisation of the CVaR and related LP computable risk measures for portfolio selection.- A pattern recognition algorithm for optimal profits in currencytrading.- Nonlinear cointegration in financial time series.- Optimal dynamic asset allocation in a non—Gaussian world.- Fair costs of guaranteed minimum death benefit contracts.- Solvency evaluation of the guaranty fund at a large financial cooperative.- A Monte Carlo approach to value exchange options using a single stochastic factor.

Effective approach between mathematicians and statisticians