27 Feb 2023 4 min read

Credit where it’s due: explicit and implicit hedging for buyout

By John Southall

In our latest DB pensions blog, we explore how well-funded schemes might look to reduce risk relative to buyout or buy-in liabilities.


Buyout liabilities are sensitive to credit spreads due to the corporate bonds that insurers use to back annuities. In our first blog in the series, we estimated that buyout liabilities have a sensitivity to credit spreads of about 60% of PV01 for schemes with durations around 10 years, dropping to around 40% of PV01 for schemes with durations of around 20 years.  

The risk of under-hedging credit sensitivity is that if credit spreads fall, buyout liabilities rise (all else equal) and assets fail to keep up. But how much asset exposure do you have to spreads already? To understand, let’s delve into the ideas of ‘explicit’ and ‘implicit’ hedging.

Credit sensitivity

As previously explained, we use something called ‘CS01’ to measure credit sensitivity. We define this as the expected change in market value from a one basis point (0.01%) change in the value of investment grade (IG) credit all-stocks spreads[1].

Our definition is slightly different from ‘regular’ CS01 (which concerns a one basis point move in the spread of the underlying asset), as CS01 alone can be a poor measure of credit risk. This is because if the spread on a high-quality bond moves by one basis point, it’s likely that the spread on a lower-quality bond will move by more than one basis point.

Explicit hedging

Academic studies and our own research show that spread volatility is roughly proportional to spread levels, so a suitable approximation for CS01 is[2]:

CS01 = (Credit spread of strategy)/(Spread of IG credit all stocks) x PV01

This idea uses the same concept as duration times spread from the world of credit investing. However, for assets whose returns are less strongly correlated to IG credit spreads, this approximation is poor, even if a spread is available. For equities there is no spread.

Implicit hedging

Assets such as equities and property provide ‘implicit’ hedging; estimating these hedges requires regression analysis (see the section at the end for details). We’ve given a few examples in the table below; rather than give the raw sensitivities (PV01 etc.), we’ve expressed exposures relative to what you can obtain from all-stocks nominal gilts, linkers or IG credit.


As you can see, risky assets can contribute substantial credit exposure. This reflects the fact that although they only have a moderate correlation to credit, they’re much more volatile. I’d stress that they also come with a lot of other risk, uncorrelated to buyout price moves – if your aim is purely to minimise risk relative to buyout pricing they’re not the right answer.

Credit hedge ratios

The next table illustrates how explicit and implicit hedging might look for an example scheme interested in funding level hedging,[3] with 25% of its assets in IG credit, 15% in growth assets (high yield, equity and property) and 60% in LDI and cash. We’ve assumed the aim is to hedge the funding level, rather than the deficit.[4]


Increasing the credit hedge

As in the above example, many schemes will find that they are significantly under-hedged in terms of their credit exposure. One way to increase asset sensitivity would be to buy more physical credit. Another might be to use credit default swaps (CDS), where the scheme acts as a protection seller. Potential benefits of CDS include leverage and high liquidity, albeit not in the UK. However, there are some drawbacks:

  • CDS spreads are about half as volatile as physical spreads. This is good for an asset-only investor, but bad for a scheme trying to gain credit spread sensitivity
  • The duration of CDS indices is relatively short[5]
  • CDS spread moves are not as highly correlated to buyout spread moves as physical credit

Endgame preparation

The above discussion may make matching solvency sensitivities appear complicated and an exact science. It’s not. At the same time, given buyout is on the horizon for many schemes, we believe getting a feel for how sensitive liabilities and assets (including non-credit assets) are to credit spreads is increasingly important for managing risk in the endgame.


Calculating implicit rates, inflation and credit exposures:

  • We regress the returns of an asset class on three other asset classes: nominal gilts, linkers and duration-neutral IG credit all stocks. Next, the asset class can be considered a weighted sum of these asset classes plus an uncorrelated residual amount
  • We work out PV01, IE01 and CS01 for gilts, linkers and duration-neutral credit directly
  • We combine the values from (2) using the weights from (1) to get the implicit PV01, IE01 and adjusted CS01 for the asset class in question


[1] 50% GBP, 50% US; Bloomberg Barclays corporate index spread used for illustration.

[2] For floating credit, replace PV01 in this formula with regular CS01.

[3] Buyout liabilities: 19-year duration and 60% real; 40% of IG spread moves pass through into moves in the buyout spread. IG credit has eight-year duration. Calculations as at 31 March 2022.

[4] Funding level hedging benefits from not requiring an accurate buyout liability estimate.

[5] Ten-year iTraxx and CDX indices, which can be used to gain EU and US exposure respectively, involve only coupons stretching out for 10 years, so have a duration of about five years. Constructing bespoke CDS exposures can reduce these issues.

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