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White Swans and the Moron Risk Premium

Interest rates and gilt yields are critical drivers of pension-scheme reserving and bulk-annuity pricing.  However, many UK pension schemes self-insure when it comes to economic risks, with Liability Driven Investment (LDI) a common approach.  This makes the turmoil in the UK Gilts market in Autumn 2022 of particular interest.  Daily movements of 10-20 standard deviations arose as the

Written by: Patrick KelliherTags: Filter information matrix by tag: gilt yields

Normal behaviour

One interesting aspect of maximum-likelihood estimation is the common behaviour of estimators, regardless of the nature of the data and model.  Recall that the maximum-likelihood estimate, \(\hat\theta\), is the value of a parameter \(\theta\) that maximises the likelihood function, \(L(\theta)\), or the log-likelihood function, \(\ell(\theta)=\log L(\theta)\).  By way of example, consider the following three single-parameter distributions:

Written by: Stephen RichardsTags: Filter information matrix by tag: mis-estimation risk, Filter information matrix by tag: log-likelihood

Turning Back The Clock

We previously discussed the concept of biological and epigenetic measures of aging. One use for such epigenetic clocks would be in determining the extent to which any regenerative medical intervention is actually working.
Written by: Gavin Ritchie

Walking the Line

In mortality forecasting work we often deal with downward trends.  It is often tempting to jump to the assumption of a linear trend, in part because this makes for easier mathematics.  However, real-world phenomena are rarely purely linear, and the late Iain Currie advocated linear adjustment as means of judging linear-seeming patterns.  This involves calculating a line between the first and last points, and deducting the line value at ea

Written by: Stephen Richards

Robust mortality forecasting for multivariate models

In my previous blog I showed how univariate stochastic mortality models, like the Lee-Carter and APC models, can be robustified to cope with data affected by the covid-19 pandemic.  Such robustification is necessary because outliers, such as the 2020 experience, bias parameter estimates and affect value-at-risk (VaR) capital requirements.  Kleinow & Richards (2016) showed how one-year VaR-style capital requirements are heavily de

Written by: Stephen RichardsTags: Filter information matrix by tag: outliers, Filter information matrix by tag: coronavirus, Filter information matrix by tag: random walk, Filter information matrix by tag: drift model

Robust mortality forecasting for univariate models

The covid-19 pandemic led to high levels of mortality in many countries in 2020. Figure 1 shows that the number of deaths in England & Wales in 2020 was an outlier compared to preceding years.

Figure 1. Total deaths by calendar year for females in England & Wales. Source: HMD data, ages 50–105.

Written by: Stephen RichardsTags: Filter information matrix by tag: ARIMA, Filter information matrix by tag: coronavirus, Filter information matrix by tag: outliers

Portfolio mortality tracking: USA v. UK

In Richards (2022) I proposed a simple real-time mortality tracker that can be implemented in a spreadsheet or R. The tracker is useful for exploratory analysis, spotting data-quality issues and communication with non-specialists. To recap, we require just three items of data:

Written by: Stephen RichardsTags: Filter information matrix by tag: season, Filter information matrix by tag: mortality shocks, Filter information matrix by tag: Nelson-Aalen, Filter information matrix by tag: OBNR, Filter information matrix by tag: reporting delays

Dr. Iain D. Currie

It is with great sadness that we note the passing of our long-term collaborator, Dr. Iain D. Currie, on 24th May 2022.

Written by: Stephen RichardsTags: Filter information matrix by tag: obituary

Reheating a Cold Case

In criminal investigation, it is well known that passing time obscures the facts, making what happened more difficult to discern. Eventually, the case turns cold - unlikely to be solved unless we discover new evidence. In some ways for over a century, epidemiologists have been dealing with just such a cold case, picking through the rubble of the 1918 Influenza pandemic and trying to make sense of what they find. But as we will see, debate continues in a number of areas.

Written by: Gavin RitchieTags: Filter information matrix by tag: coronavirus, Filter information matrix by tag: pandemic, Filter information matrix by tag: influenza, Filter information matrix by tag: cardiovascular

Virus evolution

Humanity has suffered from many pandemics in the past, but the SARS-Cov-2 virus is the first to have its genome studied so extensively while the pandemic is ongoing.  In a previous blog I looked at how the Delta variant displaced all other variants in the UK due to its increased infectiousness.  Unfortunately, the increased infectiousness of Delta was not accompan

Written by: Stephen RichardsTags: Filter information matrix by tag: coronavirus