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All about the base(line)

When we first developed a technique for putting longevity trend risk into a 1-in-200 framework consistent with Solvency II, we sought to accommodate model risk by supporting a wide range of stochastic projection models.
Written by: Gavin RitchieTags: VaR, smoothing, mortality projections

Signal or noise?

Each year since 2009 the CMI in the UK has released a spreadsheet tool for actuaries to use for mortality projections. I have written about this tool a number of times, including how one might go about setting the long-term rate. The CMI now wants to change how the spreadsheet is calibrated and has proposed the following model in CMI (2016a):

\[\log m_{x,y} = \alpha_x + \beta_x(y-\bar y) + \kappa_y + \gamma_{y-x}\qquad (1)\]

Written by: Stephen RichardsTags: CMI, APCI, APC, Lee-Carter, Age-Period, smoothing

Graduation

Graduation is the process whereby smooth mortality rates are created from crude mortality rates.  Smoothness is an important part of graduation, but another is the extrapolation of mortality rates to ages at which data may be unreliable or even non-existent.
Written by: Stephen RichardsTags: graduation, extrapolation by age, smoothing, splines

Canonical correlation

At our seminar earlier this year I looked at the validity of assumptions underpinning some stochastic projection models for mortality. I looked at the assumption of parameter independence in forecasting, and examined whether this assumption was borne out by the data. It transpires that the assumption of independence is a workable assumption for some models, but not for others. This has important consequences in a Solvency II context — an internal model must be shown to have assumptions grounded in fact.

Written by: Iain CurrieTags: VaR, smoothing, mortality projections