Two months ago I wrote a long article about Discounted Dividend Models and how I’ve started to use them to value companies.
I then added a template to my investment spreadsheet so I could quickly build a standardised dividend model for any company which I could then refine and expand upon later.
After that I spent several weeks hammering out one dividend model after another so that I now have reasonably detailed models for all of my portfolio‘s 30 or so holdings.
As I now have a lot more experience of what it takes to build discounted dividend models in the real world, I thought it would be useful to outline some of the major pros and cons I’ve run into while using this approach.
Let’s start with the positives:
Pro #1: Building dividend models helps you focus on the long-term
Most of the information investors look at is backward looking. Earnings, dividends, revenues, book value, debt; whatever it is, it’s a measurement of something in the past.
But the future is where the action is. It’s where businesses will grow or shrink, it’s where they’ll pay or suspend dividends and it’s where shareholders will get richer or poorer.
Before I started building dividend models I think I spent too much time looking at the hard numbers of the past rather than thinking about the uncertain fog of the future.
It’s not that thinking about the past is wrong, because it isn’t. It’s absolutely necessary. But looking at the past is only useful when it’s used to build your understanding of the future. And by “the future” I don’t mean the next year or two. I mean the next ten years at the very least.
Why bother thinking about where a company might be in ten years?
The answer is simple. When I invest in a company I want to buy it at a discount to its intrinsic value.
The intrinsic value of a business is the present value of all its future cash flows from and to shareholders (e.g. dividends and buybacks), discounted by an appropriate interest rate (I discount future dividends by 10% per year as that’s my target rate of return).
And since the intrinsic value of a business is the sum of all its future cash returns, looking out one or two years is not enough. What happens over the next ten years and beyond is far more important, and building a long-term dividend model is a fantastic way to keep you focused on that sort of time horizon.
Pro #2: Building a dividend model helps you think about markets as well as companies
Once you start thinking about the intrinsic value of a company and how it depends on dividends, buybacks and other cash flows over the next 10 years or more, then long-term industrial and geographic trends become important.
They’re important because the long-term fate of most companies is determined by the growth or decline of their core markets combined with the company’s ability to move into closely related adjacent markets.
For example, one of my holdings is Domino’s Pizza Group (DPG), which runs the Domino’s Pizza franchise in the UK.
DPG is focused on a single subsector (manufacturing and delivering pizzas) and a single geography (the UK), and has no stated intention to expand beyond either, at least for now.
On that basis it would be both realistic and conservative to assume that DPG’s growth over the next decade will be limited mostly by its ability to expand within the UK pizza delivery market. And to answer that, we need to have an opinion on how much the market and DPG’s market share will grow or shrink.
For a long time DPG’s management have said they expect the UK to be able to support around 1,600 Domino’s stores. Currently there are 1,200, so that leaves around 400 more stores before the UK reaches saturation point. That’s a potential 33% increase in the number of stores, and given the company’s historic roll-out rate that could happen within the next decade.
Management also expect “system sales” (total sales across all of DPG’s franchisee and corporate stores) to reach £1.6-1.9 billion per year over the medium-term, up from around £1,350 in 2020. That’s an increase of 20-40%, also within the next decade.
Based on those goals, plus a few other things (such as historic profit margins, returns on capital and so on), it’s fairly easy to argue that a realistic and conservative growth rate for DPG over the next decade would be somewhere around 2-4% per year.
That relatively slow growth rate would likely leave the company with more cash than it could reinvest, and that’s probably why management recently announced a regular buyback program as a way of returning excess cash to shareholders.
The buyback for 2020 has been set at £45m, larger than the 2020 dividend which was a mere £43m, so these buybacks are not trivial. In my dividend model I assume DPG buybacks over the next decade average around 70% of the dividend.
The resulting reduction in outstanding shares would be enough to add another percent or so to the company’s per share growth, leaving DPG with an annual dividend growth rate of around 5% to 2030:
Note: The above model has been extended to take account of buybacks, so it’s slightly more complicated than the template in my investment spreadsheet.
This approach to valuing companies is very different to just extrapolating Domino’s historic 10% growth rate out into the dark eternity of the future and then assuming that somehow it will find enough pizza lovers to keep growing that quickly. Perhaps it can, but that seems optimistic and I’d rather be realistic and conservative, at least when it comes to investing.
If I didn’t have to build a dividend model it might have been easier to gloss over the company’s long-term growth prospects, and the resulting valuation would have been less robust.
In summary then, companies operate in markets that are in long-term decline or growth, they use distribution channels which are about to be boosted or decimated by the internet and some of them have acres of room for growth within their core markets while others have long since reached the limits to growth.
All of this can be factored, realistically and conservatively, into a discounted dividend model.
Note: If you’re wondering about the impact of Just Eat and Deliveroo on Domino’s in the UK, my assumptions are that (a) food delivery aggregators will help grow the overall food delivery market, (b) Domino’s has a far more efficient vertically integrated supply chain which is a material advantage and (c) aggregators will undermine Domino’s market share. I assume the net effect of all this is highly uncertain but unlikely to be terrible for Domino’s, so I’m currently estimating the net effect as zero until reality proves otherwise. And if it does, I’ll adjust my model.
Pro #3: Building dividend models helps you think about business units and not just whole companies
As I’ve built dividend models for my 30 or so holdings over the last few weeks, I found that many of them can’t be modelled sensibly without deconstructing the business into its major business units.
There are limits to this of course, and I’m not going to deconstruct Unilever (which I hold) into all of its hundreds of brands. The data isn’t available anyway and it would probably be a massive waste of time anyway.
But breaking Unilever down into Beauty & Personal Care, Home Care and Food & Refreshment and then tracking how revenues for each business unit evolved over the last decade; that’s probably quite sensible. And you could do the same thing by its major geographic regions as well, e.g. Asia, The Americas and Europe.
If you laid all that out in a spreadsheet it would become clear that Beauty & Personal Care has grown by a third over the last decade, while Food & Refreshment has shrunk by about 15%.
You could then look at how much exposure the company has to each, how these areas are expected to grow (or shrink) in the future, how that all ties in with the company’s stated growth strategy, and then you could put together a realistic and conservative estimate of what the future might look like.
Okay, so to some extent I did deconstruct companies like this even before I started building dividend models, but having a dividend model as a concrete outcome makes it clear how this sort of information feeds into your final valuation.
Admiral is another example of a business where an analysis of its component parts may be useful.
Historically Admiral was primarily a UK car insurer, and it still is. But only just, because it has several smaller but faster growing businesses operating in different insurance and geographic markets.
Its international insurance businesses (including L’Olivier in France, ConTe in Italy and Balumba in Spain) have mostly been operating for more than a decade and have started to become consistently profitable in recent years (insurance is a price-driven business so it’s all about economies of scale, which means building scale is more important than making profits in the start-up and scale-up phases).
These international insurance business have grown aggregate turnover at a compound rate of 20% per year for the last decade, although of course that has started to slow as they’ve become significantly larger.
Their average combined ratio (the ratio of losses and expenses to premiums) has fallen almost every single year, from 164% in 2011 to 108% in 2020. Once it falls below 100% (meaning costs are less than premiums) these companies will produce material underwriting profits which will hopefully fuel additional dividend growth. For some context, Admiral’s UK combined ratio is usually around 90%.
Outside of car insurance, Admiral has successfully expanded into UK home insurance, with consistent profits now flowing from that business and with many cross-selling opportunities ahead.
Admiral has also recently moved into travel insurance (which obviously wasn’t great in 2020) as well as pet and home insurance in Europe.
It’s also started looking outside insurance with Admiral Loans, where it has has a toe in the water of the UK unsecured lending market, leveraging its expertise in pricing risk.
If I’m going to estimate Admiral’s dividends over the next decade and beyond then I need to have at least a reasonable understanding of the company’s various activities, which bits are growing and how fast, and how that might pan out over the years ahead.
This doesn’t necessarily mean you have to do a ten-year revenue and profit forecast for every part of a business, but it might.
In Admiral’s case I haven’t. I’ve just pulled out and analysed the historic data and used that to give me some “feeling” for what a realistic and conservative growth estimate might be for the next decade and beyond.
With Admiral this means I’m more comfortable estimating a higher perpetual growth rate (beyond ten years) because it has successfully expanded outside the UK and outside of its core car insurance market.
So rather than estimating perpetual growth of 3% (which is my default for high quality but UK-only companies) I’m currently estimating 4% for Admiral’s long-term growth rate. And if Admiral continues to successfully expand into new markets then I might up that to 5% which would then increase my estimate of Admiral’s intrinsic value.
PRO #4: DIVIDEND MODELS GIVE YOUR INVESTMENT RESEARCH FOCUS
So far I’ve said that building discounted dividend models can help you think about the long-term; specifically the long-term evolution of markets and the underlying components of a business.
This is much better than looking at a company’s short-term headline results, such as whether revenues, earnings and dividends are up down this year.
However, it isn’t like I wasn’t doing all of that before I started building dividend models. I was. I was thinking about the long-term, I was thinking about industrial and geographic markets and I was thinking about business units as well as whole companies.
What’s changed is that the work I do to understand a company, its markets, its business units and its long-term potential now has a much more concrete outcome. And that outcome is the dividend model.
I now analyse the evolution of a company’s major components because I want to build a good dividend model. I now look at how relevant geographic and industrial markets have evolved in the past and might evolve in the future because I want to build a good dividend model. And I now think about the long-term prospects of a business because I want my dividend models to be more than pure fantasy.
And this doesn’t end once I invest in a company. Instead, the dividend model retains its central position. Every time a company puts out new quarterly, interim or annual results, I review and, if necessary, update the model. If a company announces a major acquisition or disposal, I update the model. If anything happens which is likely to materially change the company’s future, I update the model.
This turns all of the research from qualitative statements like “this company has strong competitive advantages” and “management have a good strategy for expanding into Asia” into a concrete and tangible model which hopefully encapsulates everything I think about a company’s prospects.
So those are the initial benefits I’ve seen from my first few months as a dividend modeller. What about the downsides?
Con #1: Building dividend models can take a lot of time
The only notable downside I’ve seen from building dividend models is that it can take a lot of time. Obviously it doesn’t take long to punch a few numbers into a spreadsheet. What takes time is the research which underpins those numbers.
Whether this is really a downside depends on how much you like analysing companies and how much time you have to do it.
If you hate analysing companies and you have no spare time, then building dividend models is probably a bad idea. But if you enjoy analysing companies and if you have a few hours here and there to spare, then I’d say building dividend models is definitely worth the additional effort.
Having said that, building dividend models for 30 companies over the last month or two was not always a fun experience and I wouldn’t generally recommend it. Far better to spread the analyses out so you don’t build more than, say, one model per week from scratch.
I’ve also found that holding 30 companies is too many, because at certain times of the year (such as during results season) there’s just too much work to do analysing all the results and updating all the models.
The obvious fix is to hold a more concentrated portfolio of higher quality companies. That’s the direction I’ve been headed since late last year anyway, having ended up with 35 holdings after an excessive buying spree during the 2020 market crash.
I now have a target of getting down to 20-25 holdings by the end of 2021, with perhaps 20 being the goal beyond that.
That may sound very concentrated to some people, but as John Maynard Keynes once said:
“It is a mistake to think that one limits one’s risk by spreading too much between enterprises about which one knows little and has no reason for special confidence”
“[A portfolio should hold a] careful selection of a few investments (or a few types of investment) having regard to their cheapness in relation to their probable actual and potential intrinsic value over a period of years”John Maynard Keynes