Marilena Sibillo

Prof. Marilena Sibillo

Università degli Studi di Salerno, Italy
+1
orcid

Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 April 2011 in North American Actuarial Journal
Verified
Journal Article
Closed access
VDValeria D’AMato
Valeria D’AMato
Emilia Di LorenzoEmilia Di Lorenzo
Emilia Di Lorenzo
SHSteven Haberman
Steven Haberman
Maria RUSSOLILLOMaria RUSSOLILLO
Maria RUSSOLILLO
Marilena SibilloMarilena Sibillo
Marilena Sibillo
Life insurance companies deal with two fundamental types of risks when issuing annuity contracts: financial risk and demographic risk. Recent work on the latter has focused on modeling the trend in mortality as a stochastic process. A popular method for modeling death rates is the Lee-Carter model. This methodology has become widely used, and various extensions and modifications have been proposed to obtain a broader interpretation and to capture the main features of the dynamics of mortality rates. In order to improve the measurement of uncertainty in survival probability estimates, in particular for older ages, the paper proposes an extension based on simulation procedures and on the bootstrap methodology. It aims to obtain more reliable and accurate mortality projections, based on the idea of obtaining an acceptable accuracy of the estimate by means of variance reducing techniques. In this way the forecasting procedure becomes more efficient. The longevity question constitutes a critical element in the solvency appraisal of pension annuities. The demographic models used for the cash flow distributions in a portfolio impact on the mathematical reserve and surplus calculations and affect the risk management choices for a pension plan. The paper extends the investigation of the impact of survival uncertainty for life annuity portfolios and for a guaranteed annuity option in the case where interest rates are stochastic. In a framework in which insurance companies need to use internal models for risk management purposes and for determining their solvency capital requirement, the authors consider the surplus value, calculated as the ratio between the market value of the projected assets to that of the liabilities, as a meaningful measure of the company’s financial position, expressing the degree to which the liabilities are covered by the assets.

1 January 2019 in Research in International Business and Finance
Verified
Journal Article
Closed access
ESElisabetta Scognamiglio
Elisabetta Scognamiglio
Emilia Di LorenzoEmilia Di Lorenzo
Emilia Di Lorenzo
Marilena SibilloMarilena Sibillo
Marilena Sibillo
ATAnnarita Trotta
Annarita Trotta

10 May 2019 in Annals of Operations Research
Verified
Journal Article
Closed access
PDF file
VDV. D’aMato
V. D’aMato
Emilia Di LorenzoEmilia Di Lorenzo
Emilia Di Lorenzo
Steven HabermanSteven Haberman
Steven Haberman
Marilena SibilloMarilena Sibillo
Marilena Sibillo
RTR. Tizzano
R. Tizzano

22 February 2020 in Decisions in Economics and Finance
Verified
Journal Article
Closed access
PDF file
Emilia Di LorenzoEmilia Di Lorenzo
Emilia Di Lorenzo
GPGabriella Piscopo
Gabriella Piscopo
Marilena SibilloMarilena Sibillo
Marilena Sibillo
RTRoberto Tizzano
Roberto Tizzano

1 March 2018 in Insurance: Mathematics and Economics
Verified
Journal Article
Open access
VDValeria D’amato
Valeria D’amato
Emilia Di LorenzoEmilia Di Lorenzo
Emilia Di Lorenzo
SHSteven Haberman
Steven Haberman
PSPretty Sagoo
Pretty Sagoo
Marilena SibilloMarilena Sibillo
Marilena Sibillo
The paper proposes a demographic de-risking strategy for a pension provider, to deal with the future uncertainty in longevity over a long time horizon. The innovative idea of a longevity spread buy-in is presented. The formulae for calculating the buy-in premium are proposed in the case of pension plans. The proposal directly impacts the pension provider’s risk management systems and hence can be an important part of the overall approach to risk management. The numerical results, developed under specified stochastic hypotheses for the dynamics of the underlying financial and demographic processes, show how the proposal of the paper can be practically implemented

2 April 2024 in Socio-Economic Planning Sciences
Verified
Journal Article
Open access
VDValeria D'Amato
Valeria D'Amato
ELEmilia Di Lorenzo
Emilia Di Lorenzo
GPGabriella Piscopo
Gabriella Piscopo
Marilena SibilloMarilena Sibillo
Marilena Sibillo
Annarita TrottaAnnarita Trotta
Annarita Trotta