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Dive into the research topics where Raimondo Manca is active.

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Featured researches published by Raimondo Manca.


Archive | 2007

Semi-markov risk models for finance, insurance and reliability

Jacques Janssen; Raimondo Manca

Probability Tools For Stochastic Modelling.- Renewal Theory and Markov Chains.- Markov Renewal Processes, Semi-Markov Processes and Markov Random Walks.- Discrete Time and Reward Smp and their Numerical Treatment.- Semi-Markov Extensions of the Black-Scholes Model.- Other Semi-Markov Models in Finance and Insurance.- Insurance Risk Models.- Reliability and Credit Risk Models.- Generalised Non-Homogeneous Models for Pension Funds and Manpower Management.


Methodology and Computing in Applied Probability | 2004

Numerical Treatment of Homogeneous Semi-Markov Processes in Transient Case–a Straightforward Approach

Gianfranco Corradi; Jacques Janssen; Raimondo Manca

This paper presents the numerical solution of the process evolution equation of a homogeneous semi-Markov process (HSMP) with a general quadrature method. Furthermore, results that justify this approach proving that the numerical solution tends to the evolution equation of the continuous time HSMP are given. The results obtained generalize classical results on integral equation numerical solutions applying them to particular kinds of integral equation systems. A method for obtaining the discrete time HSMP is shown by applying a very particular quadrature formula for the discretization. Following that, the problem of obtaining the continuous time HSMP from the discrete one is considered. In addition, the discrete time HSMP in matrix form is presented and the fact that the solution of the evolution equation of this process always exists is proved. Afterwards, an algorithm for solving the discrete time HSMP is given. Finally, a simple application of the HSMP is given for a real data social security example.


Archive | 2012

Discrete Time Non-Homogeneous Semi-Markov Processes Applied to Models for Disability Insurance

Guglielmo D’Amico; Montserrat Guillén; Raimondo Manca

In this paper, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non-homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.


Methodology and Computing in Applied Probability | 2001

Numerical Solution of non-Homogeneous Semi-Markov Processes in Transient Case*

Jacques Janssen; Raimondo Manca

In this article a numerical solution for the evolution equation of a continuous time non-homogeneous semi-Markov process (NHSMP) is obtained using a quadrature method. The paper, after a short introduction to continuous time NHSMP, presents the numerical solution of the process evolution equation with a general quadrature method. Furthermore, the paper gives results that justify this approach, proving that the numerical solution tends to the evolution equation of the continuous time NHSMP. Moreover, the formulae related to some specific quadrature methods are given and a method for obtaining the discrete time NHSMP by applying a very particular quadrature formula for the discretization is shown. In this way the relation between the continuous and discrete time NHSMP is proved. Then, the problem of obtaining the continuous time NHSMP from the discrete one is considered. This problem is solved showing that the discrete process converges in law to the continuous one if the discretized time interval tends to zero. In addition, the discrete time NHSMP in matrix form is presented, and the fact that the solution to this process always exists is proved. Finally, an algorithm for solving the discrete time NHSMP is given. To illustrate the use of this algorithm for a discrete NHSMP, an example in the area of finance is presented.


Communications in Statistics-theory and Methods | 2004

Numerical Treatment of Homogeneous and Non-homogeneous Semi-Markov Reliability Models

A. Blasi; Jacques Janssen; Raimondo Manca

Abstract In this paper, we extend to our knowledge, for the first case, some reliability results using homogeneous semi-Markov processes to the case of homogeneous modeling semi-Markov processes. Moreover, we apply some of our preceding results to give the numerical solutions and so the possibility to treat real life problems for which non-homogeneity in time is important.


Communications in Statistics - Simulation and Computation | 1984

An algorithmic approach to non-homogeneous semi-markov processes

Rodolfo De Dominicis; Raimondo Manca

De Dominicis 1979 suggested a generalization of the notion of semi-Markov process by introducing a suitable definition of the transition kernel of the process and proved a theorm on the existence and uniqueness of the solution of integral equation describing the process evolution. In this paper a quite general algorithm useful for the resolution of the evolution equation is performed; in addition an application to an actuarial problem is presented.


Communications in Statistics-theory and Methods | 2013

Semi-Markov Disability Insurance Models

Guglielmo D'Amico; Montserrat Guillén; Raimondo Manca

In this article, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.


Mathematical Problems in Engineering | 2007

A Stochastic Model for the HIV/AIDS Dynamic Evolution

Giuseppe Di Biase; Guglielmo D'Amico; Arturo Di Girolamo; Jacques Janssen; Stefano Iacobelli; Nicola Tinari; Raimondo Manca

This paper analyses the HIV/AIDS dynamic evolution as defined by CD4 levels, from a macroscopic point of view, by means of homogeneous semi-Markov stochastic processes. A large number of results have been obtained including the following conditional probabilities: an infected patient will be in state j after a time t given that she/he entered at time 0 (starting time) in state i; that she/he will survive up to a time t, given the starting state; that she/he will continue to remain in the starting state up to time t; that she/he reach stage j of the disease in the next transition, if the previous state was i and no state change occurred up to time t. The immunological states considered are based on CD4 counts and our data refer to patients selected from a series of 766 HIV-positive intravenous drug users.


Journal of Applied Mathematics and Decision Sciences | 2009

Semi-Markov Reliability Models with Recurrence Times and Credit Rating Applications

Guglielmo D'Amico; Jacques Janssen; Raimondo Manca

We show how it is possible to construct efficient duration dependent semi-Markov reliability models by considering recurrence time processes. We define generalized reliability indexes and we show how it is possible to compute them. Finally, we describe a possible application in the study of credit rating dynamics by considering the credit rating migration as a reliability problem.


Stochastic Models | 2002

Salary cost evaluation by means of non-homogeneous semi-Markov processes

Jacques Janssen; Raimondo Manca

A useful model for forecasting the future development of salary costs in a firm is presented in this paper. This problem is relevant in the field of pension funds and also when a company decides to change the structure of its workforce. In the latter case, it might be necessary to forecast future salary costs in the new organizational hierarchy. The problem is solved by means of a special kind of stochastic process. To be more precise, this paper presents a generalization of discrete time non-homogeneous semi-Markov processes and of the related reward process. This new stochastic process is able to take in account all the aspects of the problem.

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Jacques Janssen

Université libre de Bruxelles

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Guglielmo D'Amico

University of Chieti-Pescara

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Guglielmo D’Amico

University of Chieti-Pescara

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Giuseppe Di Biase

University of Chieti-Pescara

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Pierre Devolder

Université catholique de Louvain

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Fredrik Stenberg

Mälardalen University College

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G. Salvi

Sapienza University of Rome

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