MAY 2015
LEGAL & GENERAL INVESTMENT MANAGEMENT
De-Risking Dynamics.
Glidepaths in Defined Benefit Pension Schemes
For investment professionals only. Not for distribution to individual investors.
In this edition of De-risking Dynamics, we explore the arguments for de-risking over
time and the putting in place of trigger schedules to help a scheme capture funding
improvements. We also look into how this de-risking journey can be constructed and
how the precise trigger levels may be chosen.
Introduction
John Southall –
Senior Investment
Strategist
The endgame of a pension scheme is the long-term investment objective – typically
either a self-sufficient run-off strategy, a buy-out with an insurance company, or a
combination of the two. The journey to the endgame for a scheme, particularly how
the investment strategy changes over time, is generally known as the glidepath.
Constructing a glidepath is a difficult task. The glidepath should reflect schemespecific liabilities and objectives, and have a clear plan for how the investment
strategy will evolve over time. In particular, the right asset class building blocks
need to be chosen, they need to be assembled in appropriate proportions and
these proportions may need to change over time in response to changes in market
conditions and scheme-specific circumstances.
In this edition of De-risking Dynamics, we explore:
Marcus Mollan –
Head of Investment
Strategy
•
the arguments for strategic de-risking over time (Part I)
•
the use of trigger schedules to help a scheme capture good experience (Part II)
•
implementation covering how the precise trigger levels may be chosen and some
comments on how the shape of the glidepath may be constructed (Part III).
A recap of the key de-risking components
A glidepath typically has two key components:
•
In many cases, a strategic de-risk over time. This prescribes a maximum level of
investment risk that may be taken at any point in time, where this maximum level
of risk reduces over time – irrespective of market conditions and irrespective of the
funding level of the scheme.
•
Exploitation of volatility in the funding level over time, to lock in improvements to
the funding level by shifting growth assets (such as a diversified growth fund) to
liability hedging assets (such as cash, bonds and swaps) when opportunities arise.
This reduces investment risk further than would be implied by a strategic de-risk,
if and when the funding level has improved significantly. Such an approach can be
achieved by implementing a set of de-risking triggers which automatically shift out
of growth assets at pre-defined funding levels.
We discuss each of these below.
Part 1: The rationale for strategic de-risking
Static investment strategy versus strategic de-risking
A scheme can target full funding based on two basic approaches: the first, a strategic
de-risk, is a strategy that will reduce in risk over time irrespective of market conditions
and the funding level; the second, a static neutral strategy, maintains a constant
percentage allocation to growth assets.
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LEGAL & GENERAL INVESTMENT MANAGEMENT
The theoretical motivation behind
a constant percentage allocation to
risk assets (other than simplicity) is
that, under certain assumptions, this
can give the most ‘time-diversified’
strategy. The basic idea is that
this avoids over-reliance on the
performance of growth assets in a
relatively short period, since the risk is
spread more evenly over time.
However, there are some practical
issues with this approach. In particular,
the time-diversification argument
assumes that the scheme is only
concerned about the distribution of
outcomes at a certain date in the future
and will completely ignore the situation
in the meantime.
One consideration is the increasing
maturity of a scheme that is closed
to future accrual. The more mature
a scheme, the less time there is to
ultimately make good on benefit
promises to members, so it is unlikely
that the deficit contributions can be
spread over as long a recovery period.
This could put the sponsor under
increased cashflow pressure in terms
of the volatility of deficit contributions.
In addition, whilst payment of pensions
reduces both assets and liabilities, it
does not (at least not immediately)
impact the deficit. A shrinking scheme
does not necessarily imply a shrinking
deficit. The decreasing timeframe may
result in increasing pressure to make
substantial deficit contributions.
If it is accepted on day 1 that there
is likely to be a preference to de-risk
due to the increasing maturity (and
shortening duration) of the scheme,
because of the regular reviews
of strategy, then it is important to
incorporate this into the overall
de-risking plan. This should be done
from the start rather than making an
unrealistic assumption that reviews
will not take place and that the interim
position will be ignored.
The Pensions Regulator (TPR)
A strategic de-risking approach is
consistent, in our view, with recent
comments from TPR. In their ‘Defined
benefit funding regulatory and
enforcement policy’ (June 2014), the
TPR has said that when assessing
the risk of pension schemes they
will include investment strategy risk
within their suite of risk indicators.
It is interesting to note that they
assess the degree of investment risk
a scheme is taking ‘having regard
to the scheme’s maturity’ based on
the most recent asset allocation data
they have available. They state that,
in general, schemes which hold a
higher proportion of growth seeking
assets, have a greater proportion of
pensioner members or are supported
by weaker covenants are more likely
to show a higher level of risk under
this indicator. In addition, in the TPR’s
‘Funding Defined Benefits’ Code of
Practice (July 2014), they say: ‘As
a scheme matures, the increasing
net outgoings tend to increase the
potential for crystallisation of the
risks in the investment strategy.
Running investment risk during this
time may be appropriate but it is
vital that trustees and the employer
understand and manage the risk this
brings.’
This suggests that a strategic de-risk
in light of the increasing maturity of
the scheme is a practical assumption
to make under most circumstances.
The probability of success over
different time frames
Another argument in favour of
strategic de-risking is that generally
it is considered to make sense to
back longer dated liability cashflows
with a higher allocation to ‘growth’
assets. This is not universally
accepted, but is widely seen as
appropriate because of the greater
probability of an additional return
on these growth assets over longer
time horizons. Holding no growth
assets is a low volatility strategy but
guarantees a low return over the long
run. The longer the time period, the
more confident the scheme can be
that growth assets will outperform
and achieve an acceptable rate of
return. For a scheme with longerdated cashflows, there is also more
time for the sponsor to make up
for any shortfalls that may arise,
if performance is poor. To put this
another way, a reduced allocation
to growth assets can be less risky
in the short term, in terms of lower
volatility, but can be more risky in
the long term as it may be less likely
to meet the funding target over the
recovery period.
Other reasons for a strategic derisk include a concern that the
sponsor covenant might deteriorate
significantly – there is generally more
02
certainty over the strength of the
sponsor in the shorter term than the
longer term, and this should arguably
be reflected by expecting a lower-risk
strategy in the future. It is only if you
are very confident that the sponsor
will definitely survive the whole
glidepath timeframe that arguments
around optimal time-diversification
can really come into play.
The form of a strategic de-risk
If a scheme does choose to
implement a strategic de-risk they will
need to decide what this looks like.
How aggressive the planned de-risk
is will likely depend on affordability.
Simple straight-line de-risking (i.e.
decreasing the fraction in growth
assets by the same amount each
year) is pragmatic and can work well.
Many schemes operate with a dual
discount rate (i.e. a pre-retirement
discount rate and a post-retirement
discount rate) which implicitly
assumes that the allocation to growth
and matching assets will mirror the
split between non-pensioner and
pensioner liabilities as the scheme
matures. This can help inform the
choice of strategic de-risk.
Part II: De-risking triggers as a
complement to strategic de-risking
(or in isolation)
Whether a strategic de-risk is adopted
or not, the funding level at any point
in time should, in our view, be an
important input into the level of
investment risk that is taken at that
point in time. Schemes that are very
well funded will generally want to
hold less in growth assets because
there is little benefit to being more
than 100% funded on a suitably
‘strong’ (prudent) basis. If the scheme
gets better funded over time then,
from the trustees’ point of view, there
is less upside relative to downside
risk of holding growth assets so the
case for de-risking becomes more
compelling. As a simple example,
a very low-risk strategy at a very
high funding level (say 105%),
improves the likelihood of achieving
full funding whilst only sacrificing
unnecessary upside outcomes.
The idea behind de-risking triggers is
to allow gains – both sustained and
fleeting – to be captured, particularly
between formal investment reviews.
This involves monitoring the
funding position of the scheme and,
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03
Re-risking
Gilt Funding Level
Figure 1. Example growth allocation triggers
100%
95%
90%
85%
80%
75%
70%
65%
60%
55%
Fraction assets allocated to growth portfolio
1
2
3
4
5
6
7
8
Years
9
10
11
12
Re-risking, or increasing the
growth allocation following
poor performance, is usually not
automated via triggers. This is
because the decision of what to do
following deterioration in the funding
level is less clear-cut, and a more
fundamental review of objectives,
and the best approach to achieving
those objectives, is likely to be more
appropriate. Nevertheless automated
re-risking may be appropriate,
provided suitable risk limits are set.
0%
11%
21%
32%
43%
54%
64%
75%
13
14
15
Source: LGIM
Table 1. Initial position of our illustrative scheme
Assets
£55.8m
Liabilities (Gilts basis)
£100.0m
75%
Proportion in growth
Target
To understand the impact of triggers,
one approach is to use a stochastic
modelling engine to generate many
scenarios of future performance
for the scheme and examine the
distribution of outcomes. Such an
approach can be used to understand
the impact of different trigger
schedules on the risk profile of a
scheme.
56%
Funding level
Deficit contribution schedule
The impact of triggers on risk
£1.3m in year 1, £1.9m in year 2 increasing to
£2.3m in year 10
Full funding on a gilts basis within 15 years
None assumed
Strategic de-risk
Source: LGIM
depending on when the scheme meets
certain funding levels, taking steps to
de-risk. De-risking will typically involve
a decrease in the proportion of funds
in growth assets and/or an increase in
the liability hedge level of the scheme.
De-risking triggers give the potential
to reduce risk sooner than you would
have been able to do otherwise.
This can be shown with an illustrative
scheme. Some basic information
about the example scheme that we
consider is given in table 1. The
scheme aims to be fully funded on a
gilts basis in 15 years. The triggers in
figure 1 make an allowance for deficit
contributions agreed by the employer
which are assumed will be paid in any
event, so lower triggers are possible
earlier in the recovery plan as a
greater amount of future contributions
can be allowed for.
Figure 1 shows an example set of
funding level triggers for the growth
allocation for this illustrative scheme,
where, for simplicity of understanding,
we assume no strategic de-risk.
There would typically also be an
accompanying set of funding level
triggers for the liability hedge level.
Calculation of triggers
It is important to calculate triggers
using a basis that does not allow
for outperformance that may not
materialise. If, for example, the
Technical Provisions (TP) basis of
our example scheme currently uses
a discount rate of 3% pa over gilts
then it would be inappropriate to fully
de-risk on reaching 100% funding on
this basis. The problem is that the TP
basis depends on the asset allocation
held – so after de-risking it no longer
makes sense to allow for such a large
premium over gilts in the discount
rate. It is more direct, and less
circular, for a scheme to set triggers
based on getting to 100% funding on
a very strong basis (such as buy-out,
gilts, or a bond-based self-sufficiency
strategy) that is independent of the
asset allocation.
Figure 2 illustrates the expected (i.e.
the mean average over the scenarios)
impact on the growth allocation of
implementing the trigger overlay
shown in figure 1 to our illustrative
scheme. It can be seen that, on
average, the growth allocation
declines smoothly over time due to
the triggers. There is also a steady
increase in the average hedging
level of the liabilities (not shown). In
addition, as seen in figure 3 there is
a significant reduction in the likely
volatility of the scheme’s deficit
over time (i.e. the amount that the
deficit could vary by over a one-year
period) relative to a static investment
strategy. In fact, without de-risking,
because of the expected increase in
asset and liability value over time, the
volatility of the scheme increases in
Having said this, trustees may wish to
be careful that the de-risking schedule
is also consistent with achieving
100% TP funding in a shorter time
frame such as 10 years.
Figure 2. Projection of the expected allocation to growth assets with and without
triggers
Average allocation to growth assets
100%
80%
60%
40%
20%
0%
0
1
2
3
4
With triggers
5
6
7
8
9
10
11
12
13
14
15
Time (years)
Without triggers
Source: LGIM
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LEGAL & GENERAL INVESTMENT MANAGEMENT
04
guide these decisions. Triggers can
be set using either a deterministic
framework, which looks only at how
assets and liabilities may be expected
to behave in a single case, or a
stochastic framework which looks at
many possible simulated possibilities
to help understand the impact of derisking decisions on the distribution
of possible outcomes.
Figure 3. Expected reduction in volatility as a result of introducing de-risking
triggers
Expected volatility of deficit
40
£m pa
30
20
10
0
0
1
2
3
4
With triggers
5
6
7
8
9
10
11
12
13
14
15
Time (years)
Without triggers
Source: LGIM
One criticism of de-risking triggers is
that planning to implement them does
not always have an obvious substantial
impact on the distribution of longterm outcomes, when all possible
scenarios are analysed. Figure 4 shows
the chances of achieving different
funding levels at the end of 15 years.
For example, there is an approximately
88% probability of achieving a funding
level of at least 60% by the end of
the recovery period, with or without
triggers. As can be seen, there is little
to no reduction in the probability of the
worst outcomes.
The reason for this is that the worst
outcomes generally do not come
from good performance followed by
bad performance; they usually come
from sustained underperformance.
The scenarios that benefit from derisking following outperformance are
swamped by scenarios with sustained
underperformance.
However, this criticism misses the
point of dynamic de-risking; it is still a
good idea to de-risk if outperformance
materialises as this can control the
range of possible outcomes from that
point onwards. This is shown in figure
5, which illustrates how the funnel of
outcomes may be impacted by derisking. In this example, the scheme
is de-risked after four years due to
an improvement in the funding level,
and this serves to narrow the range of
outcomes from the fifth year onwards
while still expecting in the central case
to achieve full funding at year 15. The
trade-off, as shown in figure 4, is that
some of the potential for very high
funding levels is sacrificed: however,
from a trustee point of view, provided
the basis on which the funding level
is measured is sufficiently strong
(e.g. does not make allowance for
outperformance of the assets that
may not materialise), any such
surplus is arguably unnecessary and
so the risk reduction from de-risking
is often seen as worthwhile.
Later in this piece we describe more
sophisticated approaches for this
important asset allocation decision
and how best to capture the riskreward trade-off.
In summary, de-risking triggers are
not a silver bullet in terms of risk
management and offer no protection
if the scheme suffers only poor
experience. However, they can
nonetheless be effective as part of a
suite of risk-management tools.
Part III: Implementation and how to
construct a glidepath
It is easy to talk in generalities about
a need to de-risk over time, and
the importance of capturing good
performance. Deciding exactly what
the shape of the glidepath should
look like, or exactly what the triggers
should be, can be more challenging.
No single model can be expected
to capture all the relevant factors.
However, schemes may find it helpful
to use a modelling framework to help
This typically involves de-risking,
following good performance, so that
the scheme still expects to reach
full funding by a given date under
the assumptions used. This is the
mechanism illustrated in figure 5 and
is why the solid lines converge to the
same point at 15 years. It is relatively
easy to calculate (no stochastic
calculations are needed) and can
substantially reduce the expected
volatility of the deficit whilst broadly
keeping on track to meet the scheme’s
objectives over the long term.
Some care is needed in applying
such an approach. For example, if
the assumptions adopted are bestestimate, then expecting to reach
full funding corresponds to a 50%
probability of meeting this objective.
In this case, de-risking following good
performance reduces the probability
of meeting the target (back to
broadly 50% so the scheme remains
as likely as not to reach the target).
This can lead to the overall chance of
meeting the target being reduced. The
implementation of de-risking triggers,
without any re-risking, can therefore
be detrimental to the central outcome
unless suitable care is taken.
Trustees are likely to be interested
in strategies that have more than
a 50% likelihood of allowing the
scheme to meet its objectives. Prudent
Figure 4. Long-term distribution of outcomes with and without triggers.
Only ‘unnecessary’ surplus is sacrificed.
Probability exceed
Funding Level
monetary terms over time.
Deterministic de-risking
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
‘unnecessary’
surplus is sacrificed
0%
20%
40%
60%
80%
100%
120%
140%
160%
Funding Level (FL) at end of recovery plan
Prob exceed that FL - With triggers
Prob exceed that FL - Without triggers
Source: LGIM
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LEGAL & GENERAL INVESTMENT MANAGEMENT
05
it is not allowed to go below zero). In
other words the measure helps reflect
that better funded schemes have less
upside relative to downside than
poorer funded schemes.
130%
120%
110%
100%
90%
80%
70%
60%
50%
40%
This sort of approach can help
determine an appropriate level of
risk that allows for a more nuanced
consideration of the risk-return tradeoff than a deterministic approach.
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
In addition to long term targets,
short-term risks should also be taken
into account as a possible constraint.
The tolerance for short-term risk is
likely to be largely dependent on the
strength of the employer covenant.
Year
5th percentile FL from time 0
expected FL from time 0
95th percentile FL from time 0
actual experience
5th percentile FL from time 4 following de-risking
expected outcome from time 4 following de-risking
95th percentile FL from time 4 following de-risking
assumptions, for example a lower than
best-estimate assumed expected rate
of return on growth assets, can help
increase this likelihood. However, in
the absence of a stochastic model, the
degree of prudence taken is unclear
and the risk-return trade-off involved
with different sets of triggers is unlikely
to be fully understood.
Stochastic approaches
In terms of constructing a Strategic
Asset Allocation (SAA), a de-risking
event is effectively a change in SAA to
allow for a change in circumstances,
for example an improved funding
level. If we can pre-determine and
agree a collection of SAAs for different
funding levels and times in advance,
this allows an automated change in
SAA should the funding level change.
In terms of constructing these SAAs,
our view is that a stochastic approach
should ideally be a key part of that
process, even if there is always a
qualitative overlay. Whilst it can be
hard to demonstrate that a stochastic
approach is necessarily better (and
you could always argue, at least in
hindsight, that you could have got to
broadly the same place via a simpler
process), without a stochastic process
you don’t really know what you are
optimising, what the probability of
underperformance is, what degree
of prudence is sensible and so on. A
stochastic approach to triggers offers a
more sophisticated approach for those
clients who are interested.
As an example, the triggers could be
set to minimise the expected shortfall
Source: LGIM
Hybrid approaches
It is possible to combine both
stochastic and deterministic features
in a framework. For example we
can use stochastic analysis to find
an efficient set of portfolios that
minimise short-term risk for a given
expected rate of return. The question
then is what rate of return should be
targeted. This could be set so that
the scheme is projected to reach full
funding over a certain period, based
on prudent assumptions. The level of
prudence may come from the scheme
valuation assumptions, recovery
plan assumptions or be informed by
stochastic considerations. In any case,
it is possible to show the stochastic
impact of any set of triggers, no
matter how they have been derived.
of the fund by a given date where the
shortfall is defined as the greater of
liabilities minus assets (the deficit)
and zero. Our definition of expected
shortfall is illustrated in figure 6 and
in table 2 assuming five equally likely
scenarios. In practice we would model
thousands of different scenarios.
The expected shortfall represents the
mean average amount the sponsor
would need to inject into the scheme
to make good the deficit.
Minimising expected shortfall
naturally leads to de-risking when
the funding level improves, because
when the scheme is better funded
there is more scope for the shortfall
to increase rather than decrease (as
Figure 6: The relationship between surplus and shortfall
600
500
400
Shortfall
Gilt Funding Level
Figure 5. Impact of de-risking on funnels of doubt
300
200
100
-600
-400
0
0
Surplus/(deficit)
-200
200
400
600
Source: LGIM
Table 2. Expected shortfall
Scenario
1
Surplus/(Deficit)
Shortfall
(100)
100
2
250
0
3
(300)
300
4
2
0
5
(45)
Expected shortfall
45
(100 + 0 + 300 + 0 + 45)/5 = 89
Source: LGIM
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LEGAL & GENERAL INVESTMENT MANAGEMENT
Dynamic tilts
The output from both the deterministic
and the stochastic models can be
tilted, based on any active views the
scheme or its manager may have or
any other considerations not factored
into the model. Appropriate liability
hedge level decisions may also be built
into the triggers to take into account
the interaction of the assets with the
liabilities. We aim to explore these
questions in a coming edition of
De-risking Dynamics.
We have seen that the glidepath
should include some key components.
In particular, it should:
•
set out the shape of the de-risking,
recognising the advantages and
disadvantages of spreading
investment risk over time as
opposed to a ‘take more risk now
and less risk later’ approach
•
recognise the likely endgame,
managing asset risk relative
to this, whilst not disregarding
the importance of other liability
measures such as Technical
Provisions
•
avoid the potential regret of not
having de-risked by using trigger
schedules to help a scheme
capture good experience. A
trigger is an important asset
allocation decision. As for
any asset allocation decision,
stochastic analysis may help the
trustees choose the triggers and/
or appreciate the benefits and
trade-offs of having some triggers
in place.
Conclusion
Most trustees and investment advisors
would agree that a pension scheme’s
assets should be well diversified and
hedge any risks that are considered
unrewarded. This can normally be
achieved by choosing appropriate
building blocks, such as diversified
growth funds and liability driven
‘matching’ assets such as gilts
and swaps.
However, in addition to having the
right building blocks, the scheme
needs these to be assembled in
appropriate proportions, with these
changing in response to changes
in market conditions and schemespecific circumstances. A glidepath
is a guide for doing so and can offer
considerable advantages in terms of
risk management.
06
As scheme liabilities mature and
funding levels increase, more pension
schemes will approach their endgame
funding objective, whether that is
self-sufficiency or buy-out. As they
do so, it is important that they have
a clear plan and robust framework
in place to deliver a liability-aware,
multi-asset solution that evolves with
the changing needs of the scheme.
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