Navigating the Decumulation Dilemma: Watch Hugh Cutler's Presentation

28 November 2024

Author

Hugh Cutler
Chief Commercial Officer

Back in October, our Chief Commercial Officer, Hugh Cutler took part in a webinar hosted by The Virtual Panel.

This webinar was titled: 'The Decumulation Dilemma', in Hugh's section he explores the complexities of managing retirement income, the impact of increasing volatility, and the benefits of a flexible open architecture approach to building decumulation solutions.

You can view Hugh’s section below (Duration 8:19):

If you would like to discuss any of the topics raised in this video or would like to discover how Mobius can assist you further we would love to hear from you.

Speak to a member of our team

The full replay of the webinar is also available to watch on-demand. Featuring speakers from Berenberg, Standard Life and Hymans Robertson you can view the webinar replay below. (Registration required).

Click here to view the full webinar

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Video transcript:

With 30 years of investment experience and now working for Mobius Life, who's kind of the, well, we think we're the leading platform, but a leading platform, offering solutions for DC and I'm also the son, grandson, and brother of doctors. So if, anyone should know how to plan for retirement, it should be me. But, in fact, I don't. I was made better, made to feel a bit better about that because someone with twice my IQ and twice more than twice my experience also admitted to finding it tough. This is Bill Sharpe of the Nobel Prize for economics and the inventor of the sharp ratio. He said this is the hardest problem in finance. He also said it's the nastiest problem in finance because running out of money in retirement, isn't a whole lot of fun.

So why is it so hard? I think you're probably familiar with, with these things, there's just too many unknowns. The investment returns are, are unknown. You don't really know your income needs. You don’t know if you're going need care or, what else you're going to come up in, retirement. You obviously don't know your life expectancy if you don’t know how long you're actually going to live, and there's massive variation in that. Tax is complicated and it's also variable and might be changing as soon as the end of the month. So, there's always things to worry about there. Then you have this big issue of path dependency or sequencing risks, which sort of impacts your returns in retirement and makes the investing problem, pretty complicated.

So we've all heard of pound cost averaging and when you are paying into your pension you put the same amount in every month and you buy more shares when the markets are down and less when they're up, but in the end, you end up buying at a cheaper average price. Volatility actually kind of helps you, in terms of enhancing your returns a little bit. But when you're taking money out, you have the opposite effect, and it makes a huge difference. So you take the same amount out every month, but when markets are down, you are selling a lot of shares effectively, and this volatility really hurts you. We try to kind of get a bit of a handle on that.

How, how painful is that? How important is it? What can you do about it? So we ran a little, simulation and we took an example investor. We said they start with a million pounds. because it makes the numbers round. As we saw from Mark's numbers, that's obviously a very big pot, but the numbers scale of course. So you start with a million pounds, and you take out £40,000 a year increasing with inflation. If you don't have any volatility and you just get a very steady return, that money lasts for 34 years. But if you start to run with volatility at 10% volatility, which might be like a balanced fund kind of level, it lasts less than 30 years because of this sequencing or pound cost averaging issue. At 15% vol, which is kind of more like a global equity portfolio or something might be, it's actually under 25 years. These are just the averages, like the medians of what happens. Actually, when you run it and look at kind of what are the bad cases, often with these sort of 10% or 15% volatility, the money runs out in 10 years. So you just end up, end up withdrawing at the wrong time.

This was a kind of theoretical model of how much difference it makes. Then I was very lucky, this week, I saw on LinkedIn a firm called Albion had come up with this example, which I thought was a really good way of describing it. They started with a million pounds in the year 2000 and took out £50,000 pounds a year increasing with inflation and left the money invested in equities. Basically, you ran out of money by 2023. What happened was you had the tech crash in the early two thousands, so you lost a lot of money, but you're still taking this 50 grand a year out and plus inflation, et cetera. And then just when you thought things were okay, you had the global financial crisis. You can see that in the chart and then your money (although you were getting good returns for most of the last decade) just trickled away and by 2023 you had nothing left. Now what happens if we run history backwards? If you did 2023 first and then 22, then 21 backwards through time, turns out that after 23 years having taken 50 grand out a year, you've still got a million left at the end of it. So it just makes so much difference when you start and what the risk profile is.

So, you have to be thinking really hard about this problem of how do you build portfolios that are going to be resilient in drawdown. What you're trying to do is to minimize the variability of the income and also keep the capital value stable as possible. So you can take out whether it's 4% a year or 5% a year, whatever level you're trying to take out you can take that out without really suffering this sequencing risk. So things like index tracking global equities are pretty hard to beat when you're 20 and you're investing for a 40-year time horizon without touching your money and you're just putting contributions in. But for this sort of, investment problem, the assets that do well are portfolios of things like private credit, high-yielding bonds, asset-backed securities. Real assets, infrastructure, real estate, income generating, equity income strategies, and then protected strategies, things that are using, options or other structures to try and reduce volatility, but still give stability of return. That's exactly what, Berenberg do, and we're going to hear about that, in a minute. Then not only do you have to have all of these ingredients, but you then need to bring them together into a solution.

So how do you do that in practice? Well, the first thing, you need a lot of strategies. You've got to have a lot of flexibility so you can include all of these, like private markets, leverage loans, structured equity, sort of complicated strategies. You can't just do it using like daily dealing, usage-type funds. You need to think about things like tax efficiency. Things like withholding taxes that UCITS funds pay on equity income is a big problem in retirement because you're looking for these income strategies. Obviously you need to look at getting low fees and high scale.

We think openness is really important. If you want structured equity, Berenberg, might be the people you want to speak to, but if you want to buy a private credit strategy, it could be someone else and it might be someone else for, for high yield. Then you need to think about the kind of the features that, that you're going to need to build into it. So obviously income-paying strategies, because that's the point, right? You've got to pay income out of these solutions. If you're going to do longevity pooling, how do you think about structuring that into your investment solution? And then to deliver all of that, it's a massive technology challenge. Huge volumes of trading, a lot of members, a lot of rebalancing, and a lot of different sorts of packages of funds.

So hopefully that, that kind of brings together some of the problem and the theory and also maybe, you know, a few ideas about how you can think about solving the problem in practice.

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