New working paper on parameter risk in mortality forecasting

Torsten Kleinow of Heriot-Watt University and Stephen Richards of Longevitas have published a working paper on parameter risk in time-series mortality forecasts.

The projection of mortality rates is an essential part of valuing liabilities in life-insurance portfolios and pension schemes.  An important tool for risk-management and solvency purposes is a stochastic projection model for mortality. The paper shows that ARIMA models can be better representations of mortality time-series than simple random-walk models.  The paper also considers the issue of parameter risk in time-series models.  The authors find that, while certain kinds of parameter risk are negligible, others are too material to ignore.

The conclusions have relevance to projection models used by insurers in the European Union under Solvency II.