There has been a dramatic increase in the popularity of drawdown products since April 2015. It is likely that many, when they opted for these choices, did not realise all the risks they faced.
A well-informed pensioner might well know about the risk of living too long or not getting a good return on his or her pension pot, but will probably not have realised that the timing of investment returns is also crucially important. Getting off to a bad start can ruin even a cautious drawdown strategy.
Current equity market volatility and the prospect of further falls should give us pause for thought and concern for the many pensioners who took advantage of the Pension Freedoms last year and opted for drawdown. As an industry, we should be asking ourselves how we can help them avoid running out of retirement savings midway through their retirement – a fate that has befallen many pensioners in the US and Australia, where pension freedom has been available for decades.
To get a true picture of the risks that pensioners face, and to enable successful ongoing management during retirement, advisers and pensioners need to use a stochastic asset model to show the range of potential outcomes. Deterministic projections are worse than useless. For the most part, the assumptions used (often a best estimate, low and high returns) are based on little evidence and, where there is some analysis, it is historical and not forward-looking. As we all know because it has been drilled into us by the FCA, “past performance is no guide to the future”.
If this were not enough to condemn deterministic projections, the final nail in their coffi – as a means of managing drawdown – is that there is no allowance whatsoever for the ups and downs of investment markets. The timing of investment returns with income drawdown is a critical risk factor. Poor returns in the early years of drawdown, when retirement savings are at their highest, can do irreparable damage.
So is the answer to use a stochastic model to manage income drawdown? Well, sadly, this is not quite so simple. The term ‘stochastic’ is a generic term, and stochastic models can differ widely in terms of how they are built and what they are suitable for. There are two basic types of model:
• Mean, variance co-variance (MVC) models, and
• Economic scenario generators (ESGs).
MVC models are very simple, and are primarily used for making short-term tactical asset allocation decisions. They use a single set of assumptions about the expected return for each asset class, its volatility (or variance) and how asset classes move relative to one another (co-variance). The set of assumptions can either be based on current market conditions or on views about long-term “normal” conditions. What an MVC model cannot do is tell you anything about how markets might progress from current conditions into the future. MVC models provide a ‘snapshot’ at a single point in time.
