scholarly journals Mortality Density Forecasts: An Analysis of Six Stochastic Mortality Models

2008 ◽  
Author(s):  
Andrew J. G. Cairns ◽  
David P. Blake ◽  
Kevin Dowd ◽  
Guy Coughlan ◽  
David Epstein ◽  
...  
Keyword(s):  
Stochastic Mortality ◽  
Stochastic Mortality Models ◽  
Mortality Models ◽  
Density Forecasts

Backtesting Stochastic Mortality Models: An Ex-Post Evaluation of Multi-Period Ahead-Density Forecasts

2008 ◽  
Author(s):  
Kevin Dowd ◽  
Andrew J. G. Cairns ◽  
David P. Blake ◽  
Guy Coughlan ◽  
David Epstein ◽  
...  
Keyword(s):  
Stochastic Mortality ◽  
Post Evaluation ◽  
Ex Post ◽  
Stochastic Mortality Models ◽  
Mortality Models ◽  
Density Forecasts

scholarly journals Mortality density forecasts: An analysis of six stochastic mortality models

2011 ◽  
Vol 48 (3) ◽  
pp. 355-367 ◽  
Author(s):  
Andrew J.G. Cairns ◽  
David Blake ◽  
Kevin Dowd ◽  
Guy D. Coughlan ◽  
David Epstein ◽  
...  
Keyword(s):  
Stochastic Mortality ◽  
Stochastic Mortality Models ◽  
Mortality Models ◽  
Density Forecasts

Evaluating the Goodness of Fit of Stochastic Mortality Models

2009 ◽  
Author(s):  
Kevin Dowd ◽  
Andrew J. G. Cairns ◽  
David P. Blake ◽  
Guy Coughlan ◽  
David Epstein ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Stochastic Mortality ◽  
Stochastic Mortality Models ◽  
Mortality Models

Backtesting Stochastic Mortality Models

2010 ◽  
Vol 14 (3) ◽  
pp. 281-298 ◽  
Author(s):  
Kevin Dowd ◽  
Andrew J. G. Cairns ◽  
David Blake ◽  
Guy D. Coughlan ◽  
David Epstein ◽  
...  
Keyword(s):  
Stochastic Mortality ◽  
Stochastic Mortality Models ◽  
Mortality Models

scholarly journals Identifying Structural Breaks in Stochastic Mortality Models

2015 ◽  
Vol 1 (2) ◽  
Author(s):  
Colin O’Hare ◽  
Youwei Li
Keyword(s):  
Life Expectancy ◽  
Structural Breaks ◽  
Structural Break ◽  
Mortality Rates ◽  
Insurance Companies ◽  
Mortality Data ◽  
Stochastic Mortality ◽  
Stochastic Mortality Models ◽  
Mortality Models ◽  
Mortality Forecasts

In recent years, the issue of life expectancy has become of utmost importance to pension providers, insurance companies, and government bodies in the developed world. Significant and consistent improvements in mortality rates and hence life expectancy have led to unprecedented increases in the cost of providing for older ages. This has resulted in an explosion of stochastic mortality models forecasting trends in mortality data to anticipate future life expectancy and hence quantify the costs of providing for future aging populations. Many stochastic models of mortality rates identify linear trends in mortality rates by time, age, and cohort and forecast these trends into the future by using standard statistical methods. These approaches rely on the assumption that structural breaks in the trend do not exist or do not have a significant impact on the mortality forecasts. Recent literature has started to question this assumption. In this paper, we carry out a comprehensive investigation of the presence or of structural breaks in a selection of leading mortality models. We find that structural breaks are present in the majority of cases. In particular, we find that allowing for structural break, where present, improves the forecast result significantly.

scholarly journals Backtesting the Lee-Carter and the Cairns-Blake-Dowd Stochastic Mortality Models on Italian Death Rates

2017 ◽  
Author(s):  
Carlo Maccheroni ◽  
Samuel Nocito
Keyword(s):  
Real Data ◽  
Mortality Data ◽  
Male Population ◽  
Death Rates ◽  
Stochastic Mortality ◽  
National Statistics ◽  
Medium Length ◽  
Stochastic Mortality Models ◽  
Mortality Models ◽  
Short Run

The work proposes a backtesting analysis in comparison between the Lee-Carter and the Cairns-Blake-Dowd mortality models, employing Italian data. The mortality data come from the Italian National Statistics Institute (ISTAT) database and span the period 1975-2014, over which we computed back-projections evaluating the performances of the models in comparisons with real data. We propose three different backtest approaches, evaluating the goodness of short-run forecast versus medium-length ones. We find that both models were not able to capture the improving shock on the mortality observed for the male population on the analyzed period. Moreover, the results suggest that CBD forecast are reliable prevalently for ages above 75, and that LC forecast are basically more accurate for this data.

Calibrating affine stochastic mortality models using term assurance premiums

2011 ◽  
Vol 49 (1) ◽  
pp. 53-60 ◽  
Author(s):  
Vincenzo Russo ◽  
Rosella Giacometti ◽  
Sergio Ortobelli ◽  
Svetlozar Rachev ◽  
Frank J. Fabozzi
Keyword(s):  
Stochastic Mortality ◽  
Stochastic Mortality Models ◽  
Mortality Models
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