Mortality rates are estimated anywhere between 30% and 100% without treatment. Many estimates are towards the top end of this range, 80% to 95%. Treatments are available (mostly antibiotics) and are generally effective. Mortality rate where adequate treatment is administered within 24 hours can be 11%. (Either “just 11%” or “11%!” depending on whether you’re counting up from 0% or down from 95%.)
There is a Mauritian insurer called Island Life. Best name ever for an insurance company.
I firmly believe in anthropogenic climate change. I am not an expert, but my reading has convinced me of the seriousness of the issues, the overwhelming evidence that it is humans at fault. Having young children makes me seriously concerned about our ability to remedy the mess we’re in for their sake.
Part of my very inwards focussed, selfish research was on the practical impact for where I live. Unfortunately for my cycling aspirations, this is current on the bottom slopes of Table Mountain. Fortunately for my flood risk, the same.
I reader asked why so many practitioners use high Equity Risk Premiums in their valuations and fairness opinions.
In particular, he mentioned a specific assumption set he had seen including:
ERP of 6.8%
company specific risk premium of 4%
He also commented on how haphazard the use of risk premiums can be and referenced a few sources I’ve used myself.
The ERP of 6.8% does seem high. However, it really isn’t possible to comment on the specifics of the company specific risk premium without knowing the company.
Although I haven’t updated my research on this in a few years, in my own work I still generally stick with a range of 3% to 5% for an ERP, before considering company specific factors, liquidity, and so on. Historically / empirically estimated ERPs shouldn’t change frequently since the time series used is long. Another few years on a 20 year estimation period shouldn’t have much impact.
Why some practitioners persist in using too-high ERP estimates
This is particularly relevant given the ambition of some InsurTech players to hyper select risks or price on many more factors than are traditionally used in order to gain a competitive advantage. Thomas doesn’t argue that it will be individual insurers’ interests to allow adverse selection, but if these companies are successful it may then have implications for policy makers.
Ah models, my old friends. You’re always wrong, but sometimes helpful. Often dangerous too.
A recent article in The Actuary magazine addressed whether “de-risking in members’ best interests?” I say “recent” even though it’s from August because I am a little behind on my The Actuary reading.
In the article, the authors demonstrate that by modelling the impact of covenant risk, optimal investment portfolios for Defined Benefit (DB) pensions actually have more risky assets than if this covenant risk is ignored.
The covenant they refer to is the obligation of the sponsor to make good deficits within the pension fund. Covenant risk then is the risk that the sponsor is unable (typically through its own insolvency) to make good on this promise.
On the surface it should seem counterintuitive that by modelling an additional risk to pensioners, the answer is to invest in riskier assets, thus increasing risk.
The explanation proffered by the authors is that the higher expected returns from riskier assets allow the fund to potentially build up surplus, thus reducing the risks of covenant failure.