ERP update – delayed response to a blog reader

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 delves into the area of philosophy, but here are my top reasons (a post from 2011 also covers this): Continue reading “ERP update – delayed response to a blog reader”

ENID not Blyton

ENID is a term widely used, just generally not in South Africa. For some reason we didn’t import the term along with most of Solvency II.

This has nothing to do with the Famous Five. While it is most common in the general insurance space, it is relevant across the spectrum of risk management and assumption setting.

Events Not In Data or “ENID” is the forgotten cousin of “what to do with outliers in your data”.

Outliers and where to find them

Outliers are observed values substantially different from others in a sample. Some more formal definitions include:

“An outlier is an observation that lies an abnormal distance from other values in a random sample from a population”

“an outlier is an observation point that is distant from other observations”

Not these sort of outliers. Entertaining book though.


How to deal with outliers?

Simple question, complex answer. It depends a great deal on the context.

Ultimately you need to make the judgement call “are these outliers under- or over-represented in the data”. Continue reading “ENID not Blyton”

Why the last 7 years have felt rough

We’ve been in and out of recession. We’ve had more political drama than I’d like for a lifetime. We’ve had several lifetimes of obvious, unresolved corruption and fraud. We’ve had a volatile and depreciating currency by and large.

This graph brought it home a little to me:

You can see the sharp decline in South Africa’s GDP measured in USD terms over the period.

Egypt, despite an Arab Spring has not experienced the same precipitous decline. Nigeria’s recent troubles are now also clear.

Our USD GDP is below the point it was in 2010, offsetting a brief period after 2010 when it was still increasing. So maybe it’s more about the last 5 years than the last 7.

Of course, that is the wrong chart. GDP is affected by population growth and what we experience as individual citizens within a country is closer to GDP per capita. Continue reading “Why the last 7 years have felt rough”

Credit Life regulations and reactions (1)

Credit Life regulations have been live for long enough now that insurers are starting to feel the impact and the shake-up of amongst industry players is starting to emerge.

There have been plenty of debate around the regulations, in part because of the dramatic financial and operational impact they will have, and partly because of how imperfectly worded they are and the scope for interpretation.

I’ll be posting about this more in the coming days.

Basing the premium on initial or outstanding balance

First, a real anomaly is the ability for insurers  to charge the capped premium rate either on initial loan balance or on the declining outstanding balance.

There are good practical reasons to want to charge a single, known amount to policyholders. It is easier to administer and policyholders have greater clarity on what they are paying. Continue reading “Credit Life regulations and reactions (1)”

Who owns Defined Benefit holes?

In 2014, John Oliphant was fired from the Government Employees’ Pension Fund (GEPF) where he was principal executive officer.  There were allegations, some details not disputed, that had Mr Oliphant accused of exceeding his powers and not following due process which amounted to, at the maximum, some hundreds of thousands of Rands.

That outcome, with those modest numbers, especially with the murk that surrounded the allegations, contrasts markedly with the hundreds of millions of Rands known to be deeply mired in scandal at the moment without consequence.

The GEPF and the Public Investment Corporation (the PIC, which investments money on behalf of many state entities) are proximate with huge amounts of money. It could be expected to be an attractive target for those with sticky fingers and connections. So when stories emerge of PIC directing GEPF investments towards SOEs or other private investments for merits other than the investment returns for the fund, nobody is surprised but plenty are concerned.

Most of the stories in the press on this matter are misinformed.  The claims that pensioners’ money is at risk are misleading at best. One exception is the Daily Maverick article by Dirk De Vos. In this article, De Vos explains why tax payers rather than (only) government pensioners will bear the burden of failed investments for the GEPF. Continue reading “Who owns Defined Benefit holes?”

South Africa ranks 2nd in financial inclusion study

The Brookings Financial and Digital Inclusion Project measures South Africa one place behind Kenya in terms of financial inclusion.

I’m still working my way through the full report, but Kenya’s score is a significant jump above South Africa and the closely contested positions below it. Is Kenya genuinely making such inroads or is this a function of the measures used?