13 Jul 2022 5 min read

When buy-in opportunities knock

By John Southall

How planning ahead and target-setting may help schemes access more favourable de-risking scenarios.

Sweets-jars.jpg

In recent blogs I’ve explored some interesting different aspects of defined benefit (DB) endgame strategy:

In this blog we outline an example of how a scheme may begin to tie these threads of our recent research together to help form a practical de-risking framework. This doesn’t represent a complete endgame solution but does outline how some of the insights could work together as part of an overall strategy.

Taking your foot off the throttle

A key ingredient required for an overall framework is a way of setting a target return as a function of funding position and scheme maturity. As I’ve explained in previous blogs, there is a mix of rational and behavioural drivers at play1.

Debates on the reasons for de-risking aside, a common strategy for setting target returns in practice involves assessing how much return is ‘needed’ to expect to reach full funding by a certain date. If experience is better than expected, this may allow the scheme to de-risk.

Automated triggers allow fast crystallisation of funding level improvements, which can be useful given governance constraints. Should the funding level deteriorate, re-risking is a logical flipside but is usually not automated, given that ‘doubling down’ can be a dangerous strategy. These de-risking triggers might look something like the below. Crossing one of the dashed green lines would trigger a de-risk to a lower ‘gilts plus’ return target:

derisking-chart-1.png

Detailed de-risking

In our buy-in trigger blog we calculated a heatmap that shows  what proportion of pensioners in might be appropriate to buy-in, depending on the circumstances. In reality, of course, there is much more to decide around investment strategy. For a given overall scheme return target, once a buy-in has been secured at a particular price this leaves a certain amount of return to generate from the remaining assets. The question is: how should this return be achieved?

To start with, collateral constraints will require that a minimum proportion of remaining assets be held in liability-driven investments (LDI), primarily to maintain hedging of rates and inflation risks. Apart from this, a key choice is how much of a bias towards credit there should be. Heavy credit allocations may be justifiable based on the benefits of hedging moves in buyout pricing. A barbell strategy, on the other hand, could make some sense as a deliberate ploy to mismatch buyout pricing – this was the subject of our second blog. In many cases a combination may make the most sense. Whilst various models can help, ultimately trustees need to get comfortable with a set of sensible strategy changes.

The chart below gives an idea of what this might look like for an example scheme that assumes pensioner buy-in liabilities are 50% of scheme assets. Key assumptions are provided at the end of the blog. For simplicity we have depicted only nine asset allocations, corresponding to three scheme return targets and three buy-in spread levels.

derisking-chart-2.png

Each row can be thought of as corresponding to the dashed green lines you can see on the first chart. An improvement in funding level that crosses one of the three lines leads to a change in strategy (moving up the grid in the second chart). You may also be moving left to right, depending on how buy-in spreads move.

As always there are complications. For example:

  • We have only considered pensioner buy-ins but it could make sense to buy-in some deferred members at low enough return targets
  • The proportion of pensioners is expected to increase over time so the framework would need regular recalibration
  • Buy-ins are irreversible so moving right to left as in the picture above is impossible!2 Schemes should consider what they will do if funding positions improve, they buy-in and then the funding position falls

The details are open to debate. The main point, however, is simply to be prepared! Scheme circumstances can change rapidly. Having a plan of action where all the various nuances have been considered in advance may put trustees in a good place to capture opportunities.

Key model assumptions

Diversified growth has a median expected return of gilts + 3.6%

LDI has an expected return of gilts

Diversified growth has a standalone Sharpe ratio of 0.4

Credit has a standalone Sharpe ratio of 0.2

Expected return on IG credit over gilts = 1.75 x buy-in spread + 0.8%

Modelling of buy-ins follows same approach as for this blog

Risk of the portfolio is measured relative to a 30% credit, 70% LDI strategy. This recognises that some degree of bias towards credit is likely to make sense in the endgame

The correlation between diversified growth and credit returns is 50%.

 

 

1. The main rational driver is that it is not possible to ‘catch’ buyout instantaneously in practice - this may promote a more buyout-aware strategy when close to full funding. (It certainly demands a buyout aware strategy if more than fully funded and waiting for a buyout to be executed). Behavioural and other drivers include regret risk, the influence of loss aversion and regulatory factors.

2. This irreversibility explains why you need to be careful before pulling the trigger – playing the waiting game can make some sense.

John Southall

Head of Solutions Research

John works on financial modelling, investment strategy development and thought leadership. He also gets involved in bespoke strategy work. John used to work as a pensions consultant before joining LGIM in 2011. He has a PhD in dynamical systems and is a qualified actuary.

John Southall