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Stochastic modeling of financing longevity risk in pension insurance

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  • Ronkainen , Vesa

    ()
    (Financial Supervisory Authority)

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    Abstract

    This work studies and develops tools to quantify and manage the risks and uncertainty relating to the pricing of annuities in the long run. To this end, an idealized Monte-Carlo simulation model is formulated, estimated and implemented, which enables one to investigate some typical pension and life insurance products. The main risks in pension insurance relate to investment performance and mortality/longevity development. We first develop stochastic models for equity and bond returns. The S&P 500 yearly total return is modeled by an uncorrelated and Normally distributed process to which exogenous Gamma distributed negative shocks arrive with Geometrically distributed interarrival times. This regime switching jump model takes into account the empirical observations of infrequent exceptionally large losses. The 5-year US government bond yearly total return is modeled as an ARMA(1,1) process after suitably log-transforming the returns. This model is able to generate long term interest rate cycles and allows rapid year-to-year corrections in the returns. We also address the parameter uncertainty in these models. We then develop a stochastic model for mortality. The chosen mortality forecasting model is the well-known model of Lee and Carter (1992), in which we use the Bayesian MCMC methods in the inference concerning the time index. Our analysis with a local version of the model showed that the assumptions of the Lee-Carter model are not fully compatible with Finnish mortality data. In particular we found that mortality has been lower than average for the cohort born in wartime. However, because the forecasts of these two models were not significantly different, we chose the more parsimonious Lee-Carter model. Although our main focus is on the total population data, we also analysed the data for males and females separately. Finally we build a flexible model for the dependence structure that allows us to generate stochastic scenarios in which mortality and economic processes are either uncorrelated, correlated or shock-correlated. By using the simulation model to generate stochastic pension cash-flows, we are then able to analyse the financing of longevity risk in pension insurance and the resulting risk management issues. This is accomplished via three case studies. Two of these concentrate on the pricing and solvency questions of a pension portfolio. The first study covers a single cohort of different sizes, and the second allows for multiple cohorts of annuitants. The final case study discusses individual pension insurance from the customer and long-term points of view. Realistic statistical long-term risk measurement is the key theme of this work, and so we compare our simulation results with the Value-at-Risk or VaR approach. The results show that the limitations of basic VaR approach must be carefully accounted for in applications. The VaR approach is the most commonly used risk measurement methodology in insurance and finance applications. For instance, it underlies the solvency capital requirement in Solvency II, which we also discuss in this work.

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    File URL: http://www.suomenpankki.fi/en/julkaisut/tutkimukset/erillisjulkaisut/Documents/E44.pdf
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    Bibliographic Info

    Paper provided by Bank of Finland in its series Scientific Monographs with number E:44/2012.

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    Length: 124 pages
    Date of creation: 25 May 2012
    Date of revision:
    Handle: RePEc:hhs:bofism:2012_044

    Contact details of provider:
    Postal: Bank of Finland, P.O. Box 160, FI-00101 Helsinki, Finland
    Web page: http://www.suomenpankki.fi/en/
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    Related research

    Keywords: equities; stocks; jump model; bond; longevity; Lee-Carter model; stochastic mortality; cohort mortality; dependence model; asymmetric dependence; parameter uncertainty; stochastic annuity; pension; cohort size; solvency; internal model;

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    1. Costantini, Mauro & Lupi, Claudio, 2007. "An analysis of inflation and interest rates. New panel unit root results in the presence of structural breaks," Economics Letters, Elsevier, vol. 95(3), pages 408-414, June.
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    6. Ronald Lee & Timothy Miller, 2001. "Evaluating the performance of the lee-carter method for forecasting mortality," Demography, Springer, vol. 38(4), pages 537-549, November.
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    11. Wu, Yangru & Zhang, Hua, 1996. "Mean Reversion in Interest Rates: New Evidence from a Panel of OECD Countries," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(4), pages 604-21, November.
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