Selected Papers from the Sixth International Conference on Mathematical and Statistical Methods for Actuarial Sciences and Finance

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (25 July 2014) | Viewed by 5373

Special Issue Editors


E-Mail Website
Guest Editor
Department of Economics and Statistics, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy
Interests: stochastic processes; stochastic models; financial and insurance risk; risk management
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Economics and Statistics, University of Salerno, Via Giovanni Paolo II, 132, 84084 Fisciano, SA, Italy
Interests: non-linear time series; artificial neural networks; resampling techniques
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

The International Conference MAF-Mathematical and Statistical Methods for Actuarial Sciences and Finance was born at the University of Salerno (Italy) in 2004. Its main aim is to promote the interaction between mathematicians and statisticians, in order to provide new theoretical and methodological results together with significant applications in actuarial sciences and finance, by the capabilities of the interdisciplinary mathematical-and-statistical approach.

The conference covers a wide variety of subjects in actuarial science and financial fields, all treated in light of the cooperation between the two quantitative approaches. It is open to both academicians and professionals.

It is biennial and, starting from 2008, avails itself of the collaboration of the University of Venice; the preceding conferences were organized in Salerno (2004, 2006, 2010) and in Venice (2008, 2012).

The 2014 edition, April 22-24, will take place in Vietri sul Mare (Costa di Amalfi). Five invited speakers will attend the conference: Erricos Kontoghiorghes (Cyprus University of Technology), Teemu Pennanen (King’s College London), Dimitris Politis (University of California, San Diego), Daniel Ryan (Swiss Re Services LtD, London), Lucio Sarno (Cass Business School, City University, London).

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

651 KiB  
Article
An Optimal Three-Way Stable and Monotonic Spectrum of Bounds on Quantiles: A Spectrum of Coherent Measures of Financial Risk and Economic Inequality
by Iosif Pinelis
Risks 2014, 2(3), 349-392; https://doi.org/10.3390/risks2030349 - 23 Sep 2014
Cited by 23 | Viewed by 4913
Abstract
A spectrum of upper bounds (Qα(X ; p) αε[0,∞] on the (largest) (1-p)-quantile Q(X;p) of an arbitrary random variable X is introduced and shown to be stable and monotonic in α [...] Read more.
A spectrum of upper bounds (Qα(X ; p) αε[0,∞] on the (largest) (1-p)-quantile Q(X;p) of an arbitrary random variable X is introduced and shown to be stable and monotonic in α, p, and X , with Q0(X ;p) = Q(X;p). If p is small enough and the distribution of X is regular enough, then Qα(X ; p) is rather close to Q(X ; p). Moreover, these quantile bounds are coherent measures of risk. Furthermore, Qα(X ; p) is the optimal value in a certain minimization problem, the minimizers in which are described in detail. This allows of a comparatively easy incorporation of these bounds into more specialized optimization problems. In finance, Q0(X;p) and Q1(X ; p) are known as the value at risk (VaR) and the conditional value at risk (CVaR). The bounds Qα(X ; p) can also be used as measures of economic inequality. The spectrum parameter α plays the role of an index of sensitivity to risk. The problems of the effective computation of the bounds are considered. Various other related results are obtained. Full article
Show Figures

Graphical abstract

Back to TopTop