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If any doubt about Linux and Open Source technologies existed in Enterprise IT departments it must surely have been erased by last week's news: The London Stock Exchange, one of the engines that propelled the UK to the top of the World Economic Forum rankings, has invested in a Linux trading platform.
Part of the story
The Institute of Actuaries' sessional meeting on 28th September 2009 discussed an interesting paper. It covered similar material to that in Richards (2008), but used different methods and different data.
Back(test) to the future
Stochastic projections of future mortality are increasingly used not just to set future best-estimates, but also to inform on stress tests such as for ICAs in the UK.
Forecasting with limited portfolio data
In a recent post on basis risk in mortality projections, I floated the idea of forecasting with limited data and even suggested that it would be possible to use the method to produce a family of consistent forecasts for different classes of business. The present post describes an example of how this idea works in practice.
A Scottish question
The Scots are an innovative bunch, including the inventor of the telephone and the discoverer of penicillin.
Out for the count
In an earlier post we described a problem when fitting GLMs for qx over multiple years. The key mistake is to divide up the period over which the individual was observed in a model for individual mortality.
Stabilising projections
With many stochastic models of mortality, projections of future mortality rates are done using a time series. In a landmark paper, Currie, Durban and Eilers (2004) introduced the idea of using P-splines as an alternative means of generating a forecast.
Partial buy-outs
It is quite common for a pension scheme to want to reduce its risk, but to be unable to afford a full buy-out. The question is how best to reduce risk with the funds available, i.e. which liabilities to buy out first.
The Lee-Carter Family
In a recent paper presented to the Faculty of Actuaries, Stephen Richards and I discussed model risk and showed how it can have a material impact on mortality forecasts. Different models have different features, some more desirable than others. This post illustrates a particular problem with the original Lee-Carter model, and shows how it can be combatted via smoothing. The choice of which parameters to smooth in the Lee-Carter model leads to a general family
Expectations v. extrapolations
The CMI has published two working papers along with its new mortality projection model. The proposed new model blends current improvement rates into an expected long-term average rate of improvement. The hope is that such models can incorporate expert opinions on mortality trends to improve the accuracy of projections.