Modelling Italian mortality rates with a geometric-type fractional Ornstein-Uhlenbeck process

01/03/2019
by   Francisco Delgado-Vences, et al.
0

We propose to model mortality hazard rates for human population using the exponential of the solution of a stochastic differential equation (SDE). The noise in the SDE is a fractional Brownian motion. We will use the well-known fractional Ornstein-Uhlenbeck process. Using the Hurst parameter we showed that mortality rates exhibit long-term memory. The proposed model is a generalization of the model introduced by [6], where they used an SDE driven with a Brownian motion. We tested our model with the Italian population between the years 1950 to 2004.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/11/2018

LAN property for stochastic differential equations driven by fractional Brownian motion of Hurst parameter H∈(1/4,1/2)

In this paper, we consider the problem of estimating the drift parameter...
research
01/16/2022

Fractional SDE-Net: Generation of Time Series Data with Long-term Memory

In this paper, we focus on generation of time-series data using neural n...
research
06/27/2023

Catastrophe risk in a stochastic multi-population mortality model

This paper presents an approach to incorporate mortality shocks into mor...
research
03/02/2019

Nonparametric adaptive inference of birth and death models in a large population limit

Motivated by improving mortality tables from human demography databases,...
research
04/02/2021

Projection Estimators of the Stationary Density of a Differential Equation Driven by the Fractional Brownian Motion

The paper deals with projection estimators of the density of the station...
research
07/27/2022

Stochastic modeling using Adomian method and fractionnal differential equations

In this paper, we propose a fractional differential equation of order on...

Please sign up or login with your details

Forgot password? Click here to reset