In the framework of Embedded Value new standards, namely the MCEV norms, the
latest principles published in June 2008 address the issue of market and
underwriting risks measurement by using stochastic models of projection and
valorization. Knowing that stochastic models particularly data-consuming, the
question which can arise is the treatment of insurance portfolios only
available in aggregate data or portfolios in situation of incomplete
information.
The aim of this paper is to propose an operational two-dimensional parametric
adjustment for laws of maintenance in disability. The method suggested rests on
splines in dimension 2; it is applied to a real data set, and the scale of
reserving which results from it is compared with the scale of reference of the
BCAC.
The economic equities maximization criterion (MFPE) leads to the choice of
financial portfolio, which maximizes the ratio of the expected value of the
insurance company on the capital. This criterion is presented in the framework
of a non-life insurance company and is applied within the framework of the
French legislation and in a lawful context inspired of the works in progress
about the European project Solvency 2. In the French regulation case, the
required solvency margin does not depend of the asset allocation.
The aim of this paper is to propose a realistic and operational model to
quantify the systematic risk of mortality included in an engagement of
retirement. The model presented is built on the basis of model of Lee-Carter.
The stochastic prospective tables thus built make it possible to project the
evolution of the random mortality rates in the future and to quantify the
systematic risk of mortality.
The aim of this paper is to study the construction of prospective mortality
tables from a low number of persons subjected to risk. The presented models are
the Lee-Carter and log-Poisson methods respectively. The low number of people
subjected to risk, particularly noticed for the persons who are getting on,
implies the use of an extrapolation method for the mortality rates. The
Lee-Carter and log-Poisson methods constitute twodimensional models, taking the
year and the age into account to calculate the mortality rates. The methods
suggested are applied to a real data set.
The aim of this paper is to compare two asset allocation methods for a
pension scheme during the decumulation phase in the simplified portfolio
selection between a risky asset following a geometric Brownian motion and a
riskless asset. The two asset allocation criteria are the ruin probability of
the insurance company and the optimization of the economic capital. We first
solve the asset allocation problem with deterministic pension payments then
with stochastic mortality risk. We analyze the part of mortality risk in the
global risk of the company.
Continuous time stochastic processes are useful models especially for
financial and insurance purposes. The numerical simulation of such models is
dependant of the time discrete discretization, of the parametric estimation and
of the choice of a random number generator. The aim of this paper is to provide
the tools for the practical implementation of diffusion processes simulation,
particularly for insurance contexts.
The aim of this paper is to propose a realistic and operational model to
quantify the systematic risk of mortality included in an engagement of
retirement. The model presented is built on the basis of model of Lee-Carter.
The stochastic prospective tables thus built make it possible to project the
evolution of the random mortality rates in the future and to quantify the
systematic risk of mortality.
In this paper, we present the principal components of an economic scenario
generator (ESG), both for the theoretical design and for practical
implementation. The choice of these components should be linked to the ultimate
vocation of the economic scenario generator, which can be either a tool for
pricing financial products or a tool for projection and risk management. We
then develop a study on some performance measure indicators of the ESG as an
input for the decision-making process, namely the indicators of stability and
bias absence.