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In my role as guest editor of the British Actuarial Journal, I wrote an editorial piece about how actuaries can assess the suitability (or otherwise) of models for projecting mortality rates.
Benchmarking VaR for longevity trend risk
I recently wrote about an objective approach to setting the value-at-risk capital for longevity trend risk. This approach is documented in Richards, Currie & Ritchie (2012), which was recently presented to a meeting of actuaries in Edinburgh.
Hitting the target, but missing the point
Targeting methods are popular in some areas for mortality forecasting. One well known current example is the CMI's model for forecasting mortality.
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.
Seminar on stochastic projection models
We previously ran a seminar on stochastic projection models for longevity risk. Our follow-up seminar focuses on specific aspects of ICAs and Solvency II.
All bases covered
It is fairly obvious by now that we are strong advocates for stochastic projection models. Such models crucially provide a basis with two components - a best-estimate force of mortality by age and year, and matching standard error values for the same 2D range.
Ahead of his time
I'm giving away rather too much information about my age when I say I started work in 1990 right after graduating from university. Not long into my first job at a UK insurer, I was called to a meeting of the actuarial department.
Steady as she goes
If you'll forgive the nautical metaphor, forecasting longevity over the past few decades has proven to be anything but plain sailing. Those plotting a course with unshakable certainty have usually ended up storm-tossed and floating in a barrel.
Shifting sands
In civil engineering, no building can be sounder than the foundation on which it rests. A similar comment applies to statistical analysis, which is obviously limited by the quality of the underlying data.
The limits of limits
Is there a limit to life expectancy?