Information Matrix

Filter Information matrix

Posts feed
Publication date

Double trouble

Scientists strongly prefer ideas and processes which have undergone anonymous peer review in published, refereed journals.
Written by: Stephen RichardsTags: deduplication, duplicates, annuities

Interesting times

The Bank of England has reduced its current bank rate to 1.5%, the lowest since it was founded in 1694.  Whilst this is good news for borrowers, it is bad news for those in retirement who are living off the interest on their savings.
Written by: Stephen RichardsTags: interest, annuities

Table talk

When valuing a portfolio, an actuary must often make a decision as to what tables to use for the risk.  The ideal is to use tables which have been created from the portfolio's own experience, preferably using a statistical model to account for the various risk factors. 
Written by: Stephen RichardsTags: standard table

Size isn't everything

In an earlier post we discussed the correct way of using postcodes for analysing mortality, and also how this works in countries outside the UK.  It is worth re-iterating why insurers use so-called geodemographic profiling.
Written by: Stephen RichardsTags: postcodes, geodemographics

Great Expectations

When fitting statistical models, a number of features are commonly assumed by users. Chief amongst these assumptions is that the expected number of events according to the model will equal the actual number in the data. This strikes most people as a thoroughly reasonable expectation. Reasonable, but often wrong.

Written by: Stephen RichardsTags: GLM

Confounding compounding

Earlier posts discussed the importance of deduplication in annuity portfolios and pension schemes and some of the issues around the deduplication of names, specifically the use of double metaphone to look through common variant spellings of the surname or family name.
Written by: Gavin RitchieTags: deduplication, duplicates

A likely story

The foundation for most modern statistical inference is the log-likelihood function.  By maximising the value of this function, we find the maximum-likelihood estimate (MLE) for a given parameter, i.e. the most likely value given the model and data.  For models with more than one parameter, we find the set of values which jointly maximise the log-likelihood.

Written by: Stephen RichardsTags: Makeham, log-likelihood

Do we need standard tables any more?

Actuaries are long used to using standard tables. In the UK these are created by the Continuous Mortality Investigation Bureau (CMIB), and the use of certain tables is often prescribed in legislation. As actuaries increasingly move to using statistical models for mortality, it is perhaps natural that they should first consider incorporating standard tables into these models. But are standard tables necessary, or even useful, in such a context?

Written by: Stephen RichardsTags: standard table, GLM, survival models

New SAPS tables

On 31st October 2008 the CMIB published the new SAPS S1 mortality tables based on the mortality of defined-benefit pension schemes. These tables follow the previous release of the '00 Series' mortality tables based on the mortality of life-office pensioners. 
Written by: Stephen RichardsTags: standard table

Why we don't fit models in Excel

Actuaries are very heavy users of spreadsheets, especially Microsoft® Excel.  One question we are occasionally asked is why we wrote our software in C++, instead of letting people have direct access to our code as a spreadsheet. 
Written by: Stephen RichardsTags: spreadsheet, Excel, C++