scholarly journals A COMPARATIVE STUDY OF TWO-POPULATION MODELS FOR THE ASSESSMENT OF BASIS RISK IN LONGEVITY HEDGES

2017 ◽  
Vol 47 (3) ◽  
pp. 631-679 ◽  
Author(s):  
Andrés M. Villegas ◽  
Steven Haberman ◽  
Vladimir K. Kaishev ◽  
Pietro Millossovich

AbstractLongevity swaps have been one of the major success stories of pension scheme de-risking in recent years. However, with some few exceptions, all of the transactions to date have been bespoke longevity swaps based upon the mortality experience of a portfolio of named lives. In order for this market to start to meet its true potential, solutions will ultimately be needed that provide protection for all types of members, are cost effective for large and smaller schemes, are tradable, and enable access to the wider capital markets. Index-based solutions have the potential to meet this need; however, concerns remain with these solutions. In particular, the basis risk emerging from the potential mismatch between the underlying forces of mortality for the index reference portfolio and the pension fund/annuity book being hedged is the principal issue that has, to date, prevented many schemes progressing their consideration of index-based solutions. Two-population stochastic mortality models offer an alternative to overcome this obstacle as they allow market participants to compare and project the mortality experience for the reference and target populations and thus assess the amount of demographic basis risk involved in an index-based longevity hedge. In this paper, we systematically assess the suitability of several multi-population stochastic mortality models for assessing basis risks and provide guidelines on how to use these models in practical situations paying particular attention to the data requirements for the appropriate calibration and forecasting of such models.

2017 ◽  
Vol 47 (2) ◽  
pp. 601-629 ◽  
Author(s):  
Andrew Hunt ◽  
David Blake

AbstractFor many pension schemes, a shortage of data limits their ability to use sophisticated stochastic mortality models to assess and manage their exposure to longevity risk. In this study, we develop a mortality model designed for such pension schemes, which compares the evolution of mortality rates in a sub-population with that observed in a larger reference population. We apply this approach to data from the CMI Self-Administered Pension Scheme study, using U.K. population data as a reference. We then use the approach to investigate the potential differences in the evolution of mortality rates between these two populations and find that, in many practical situations, basis risk is much less of a problem than is commonly believed.


Author(s):  
Kevin Dowd ◽  
Andrew J. G. Cairns ◽  
David P. Blake ◽  
Guy Coughlan ◽  
David Epstein ◽  
...  

Author(s):  
Kevin Dowd ◽  
Andrew J. G. Cairns ◽  
David P. Blake ◽  
Guy Coughlan ◽  
David Epstein ◽  
...  

Author(s):  
Andrew J. G. Cairns ◽  
David P. Blake ◽  
Kevin Dowd ◽  
Guy Coughlan ◽  
David Epstein ◽  
...  

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

Author(s):  
Colin O’Hare ◽  
Youwei Li

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.


Author(s):  
Carlo Maccheroni ◽  
Samuel Nocito

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.


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