Special Issue "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)

Special Issue Editors

Guest Editor
Prof. Dr. Marilena Sibillo

University of Salerno, 84084 Fisciano SA, Italy
Website | E-Mail
Guest Editor
Prof. Dr. Cira Perna

Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno, Fisciano (SA), Italy
Website | E-Mail

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)

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Open AccessArticle An Optimal Three-Way Stable and Monotonic Spectrum of Bounds on Quantiles: A Spectrum of Coherent Measures of Financial Risk and Economic Inequality
Risks 2014, 2(3), 349-392; doi:10.3390/risks2030349
Received: 15 June 2014 / Revised: 21 August 2014 / Accepted: 10 September 2014 / Published: 23 September 2014
Cited by 3 | PDF Full-text (651 KB) | HTML Full-text | XML Full-text
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
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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

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