The Fair Valuation of Defined Contribution Pension Funds in a Stochastic Mortality Environment

This paper analyses the role of the term structure of interest and mortality rates for Defined Contribution Pension Schemes. In particular, the model suggested allows the actuary to determine the fair valuation of such a scheme by modelling both mortality and financial risk by means of diffusion processes. A numerical example illustrates the fair value accounting impact on reserve evaluations by comparing a traditional deterministic approach and a stochastic one for interest and mortality rates

Pension funds risk analysis: stochastic solvency in a management perspective

The aim of the paper is to deal with the solvency requirements for Defined Contributions Pension funds. The probability of underfunding is investigated in a stochastic framework by means of the funding ratio, which is the ratio of the market value of the assets to the market value of the liabilities. Demographic and investment risks are modelled by means of diffusion processes. Their impact on the total riskiness of the fund is analyzed via a quantile approach

Distribution of Exonic Variants in Glycogen Synthesis and Catabolism Genes in Late Onset Pompe Disease (LOPD)

Pompe disease (PD) is a monogenic autosomal recessive disorder caused by biallelic pathogenic variants of the GAA gene encoding lysosomal alpha-glucosidase; its loss causes glycogen storage in lysosomes, mainly in the muscular tissue. The genotype-phenotype correlation has been extensively discussed, and caution is recommended when interpreting the clinical significance of any mutation in a single patient. As there is no evidence that environmental factors can modulate the phenotype, the observed clinical variability in PD suggests that genetic variants other than pathogenic GAA mutations influence the mechanisms of muscle damage/repair and the overall clinical picture. Genes encoding proteins involved in glycogen synthesis and catabolism may represent excellent candidates as phenotypic modifiers of PD. The genes analyzed for glycogen synthesis included UGP2, glycogenin (GYG1-muscle, GYG2, and other tissues), glycogen synthase (GYS1-muscle and GYS2-liver), GBE1, EPM2A, NHLRC1, GSK3A, and GSK3B. The only enzyme involved in glycogen catabolism in lysosomes is alpha-glucosidase, which is encoded by GAA, while two cytoplasmic enzymes, phosphorylase (PYGB-brain, PGL-liver, and PYGM-muscle) and glycogen debranching (AGL) are needed to obtain glucose 1-phosphate or free glucose. Here, we report the potentially relevant variants in genes related to glycogen synthesis and catabolism, identified by whole exome sequencing in a group of 30 patients with late-onset Pompe disease (LOPD). In our exploratory analysis, we observed a reduced number of variants in the genes expressed in muscles versus the genes expressed in other tissues, but we did not find a single variant that strongly affected the phenotype. From our work, it also appears that the current clinical scores used in LOPD do not describe muscle impairment with enough qualitative/quantitative details to correlate it with genes that, even with a slightly reduced function due to genetic variants, impact the phenotype

BOOK OF SHORT PAPERS: IES 2023

Abstract This study proposes an alternative approach to measuring excess mortality due to COVID19 pandemics compared to the CEMC method. It investigates changes in biometric dynamics since the COVID-19 outbreak in 2019 by comparing empirical data from Italian mortality tables between 2011 and 2021 to counterfactual death probabilities derived from two commonly used statistical models, Lee- Carter and Renshaw-Haberman. Estimates are provided for 2019, 2020, and 2021, with an additional estimate for 2020 to 2021. The findings are presented to observe the dynamics of expected deaths over time

Investigation on life expectation at birth process nature.

This framework consists in an application of an ARIMAX model in order to analyze the impact of COVID19 pandemic on the life expectancy Malia (2021) at birth process with a Impulse Response Function. More pre- cisely we model the process, then we emulate the shock observed on this process to check if it is stable and trend reverting. In this way we decompose the time series of the life expectancy at birth in a deterministic trend compo- nent and a residual part where we will model with an ARIMAX model with order 1 in auto-regressive component and with order 1 for the integration component. We will show that residual could be considered as white noise and, then, that the process is estimated to be stable and trend reverting in few years. Finally we compare forecast of the model without shock with the one with shock. Then, we complete the comparison looking at the observed life expectancy at birth in order to see if the realty is following the theoretical framework