Beating the UK indices in 10 hours a year

How do you like that for a clickbait title? Southbank Investment Research, sign me up!

In this article I’ll explain my hands-off, no tinkering, annual portfolio system. I’ll show how it’s beaten the indices for the last four years, in a range of environments, and how you can do it yourself. You just need the steely temperament needed to close your eyes and step away from the trade buttons.

This all stems from an experiment I started in December 2018. My hypothesis was that you could do much better than the UK small cap indices with the bare minimum of work. By excluding perennial cash burners, blue sky ‘jam tomorrow stocks’, and ethically challenged businesses, I reckoned you could do much better than the FTSE. I also wondered how much of a benefit you would get if you went a bit further, and just focused on actual businesses. You know, those making real cash flows with decent people in charge.

In many ways, you can think of this as being like a more hands version of the StockRanks system the folks at Stockopedia use. Their system is purely quantitative, but it comes from the same philosophy: get rid of the dogs and your investing results will massively improve.

But, without any further ado, let me explain to you how it all works.

An annual exercise

Every December, with a mince pie in hand and festive spirit in my heart, I download a list of every UK listed company.

That’s about 2200 businesses worth of ‘raw material’.

As UK investor, this is my universe in the broadest possible sense of the word.

To start with, I run this universe through a purely mechanical filter, looking for the following characteristics:

  • Is it an operating company? I’m not considering funds or investment vehicles here
  • Does it operate in a sector I understand? I don’t do biotechs, mining, oil & gas, or other commodity plays
  • Is it between £20m and £1bn in market cap? This is my sweet spot: big enough to be investible, not so big as to be overanalysed

This year, 477 businesses passed that first stage filter. It’s a huge drop off – predominantly because there are an enormous amount of investment vehicles listed in London. Funds, ETFs, trusts and so on. There are 168 iShares vehicles alone.

After that, I run what’s left through a subjective filter. This answers five questions, some of which require shoot-from-the-hip judgements:

  • Is it UK managed?
  • Is it consistently profitable?
    • I give them a free pass if they have a single year with some sort of write down, or had a tough time during COVID
  • Are revenues meaningful relative to the size of the business?
    • I used to call this the ‘blue sky filter’
  • Do I think this business is ‘clean’?
    • This is the most subjective: I call it ‘ethics, regulator, country and accounting’
    • Countries operating in certain countries, sectors or with certain individuals are tainted from step one, in my view
  • Is the balance sheet acceptable?
    • I use simple metrics to determine this: eyeballing the current ratio and the net shareholder deficit versus free cash flow

I let a company fail on one of these tests, but I kick ’em out if they fail more than that. This eliminates another 15% of businesses.

What I’m left with is a funnel process which looks something like this:

The 404 remaining businesses are not all fantastic. But I have removed the obvious duds in which I would never invest.

Ranking the remainder

Next up comes the fun job: taking the remaining businesses and giving them a rank.

I use a 1-4 ranking system. 1-5 is too easy. You end up putting everything in ‘3’.

1-4 forces you to lean one way or the other.

By design, this ranking process is incredibly quick. If I spent 10 minutes on each business it would take 70 hours. That’d be a month of short bursts, realistically, since the intensity it requires frazzles you after a few hours.

If I had to generalise, though, it looks something like this:

  • If I don’t know the business, I flick through a presentation and try to get a conversant understanding of what they actually do
  • I pull up a spreadsheet with a 15-year financial history of the business
  • I look at the most recent trading update and gauge the direction of forecast changes and underlying trading momentum

I write a little note next to each name on the spreadsheet with my immediate judgement and why I’ve ranked it the way I have. Obviously, given the time investment, these are not exhaustive analyses of the business. They’re helpful for jogging my memory later.

After all of that slicing and dicing, this year I ended up with a distribution of ratings which looked like this:

Usually, I have fewer rank 1s and more rank 4s. Perhaps I’m getting more generous in my old age: or perhaps my gut is telling me the market is cheaper than it has been.

For context, among the rank 1s, I have things like:

  • Macfarlane: “9x forward for a business of this quality and consistency is way too cheap. Steady grower”
  • James Latham: “Elevated earnings, but 1.5x book value is still lower end of historic. Great track record”
  • Andrews Sykes: “Circa 11x ex-cash for a super high quality business with v. consistent profile”

Disclosure: I own shares in Macfarlane. You can read about it here

And among the rank 4s, I have things like (I’m not including the names to save blushes, but points if you can guess them in the comments):

  • “An incredibly ethically compromised business”
  • “It’s a fraud. There’s not even a debate”
  • “Recent float with awful recent trading; not even cheap. Terrible”

Looking back

I’ve now conducted this annual exercise since December 2018. That means I have four years of data as to how these picks have performed.

Have the Rank 1s outperformed? Does my 3-minute shoot-from-the-hip judgement actually have any value? What about companies which fail my filter at the first hurdle and I consider uninvestible – how have they done?

I can answer that:

It’s a nice, clean sweep from top to bottom.

Granted, there’s not a huge difference once you step down from the Rank 1s. I’m not massively surprised by this. I don’t think I’m very good at differentiating between flavours of poorer businesses. I do like to think I have a good nose for stuff which is decent, honest and reasonably priced.

It’s humbling that this performance is a little better than my actual portfolio.

You can’t read too much into it – you should never put too much faith in hypothetical numbers. They ignore the very real constraints of trading, spreads, liquidity and other issues. Still, I think it’s a fascinating starting point.

I will interject here to say that this breaks my cardinal rule of not posting anything performance related on the internet. I’ll proviso it with this comment: you should take any performance claim made with a huge pinch of salt. I could have made this whole thing up in five minutes. I’m not posting the raw data, and even if I did post the raw data, I could’ve backtested and invented this whole post as an elaborate hoax.

My aim is not for you to think I’m a good investor. If you judge my recent posts on this blog, you might come to the conclusion I’m a rather mediocre one. My aim is that you think it’s interesting enough that it sparks a desire to conduct your own experiments on screening and stock-picking.

Fire up your spreadsheets

So, please try this sort of exercise yourself.

Too many investors keep a poor log of their historic decisions.

When I played poker, I had a database keeping track of every decision I made over hundreds of thousands of hands, and I could see my profitability in every conceivable scenario. This sort of thing is an invaluable tool, because looking back enables you to be better.

Investing is nowhere near as easy. The timescales are too long, the factors involved are too nebulous, and the game is less strictly defined.

But that’s not an excuse for giving up on data collection entirely.

Maybe you don’t want to conduct the sort of experiment I’ve done. Fair enough. But next time you do a bunch of research but don’t buy the stock, jot it down with a date next to it. In a few years’ time, you’ll have a spreadsheet with 50 names and dates. You might see that your ‘should would couldas’ are outperforming your actual stocks. Maybe that’s just random chance… but maybe it’s instead a pervasive, fixable behavioural bias you have.

The only way to find out is to test it!

3 Comments

  1. Really interesting post, thanks for sharing!
    Why do you limit yourself to the UK market? This is something I find odd with lots of UK based investors, limiting themselves to a small fraction of the global stock market. Even if aiming to use tax advantaged ISA / SIPP vehicles, it is still easy to access international stocks.

    • Hi Alan,

      Thanks – glad you enjoyed it.

      Practically speaking, it’s because I have a professional mandate to do this, and I invest alongside that. So I’m focused for that reason.

      But that’s a bit of a cop-out answer. Even prior to that professional situation, I only invested in the UK. My assessment has always been that the benefits of a high degree of specialisation, knowledge of management, culture and so on all outweigh the benefits of diversification. I don’t know if that’s true or not, but I do know I could never complete this exercise for a global universe given how much the ‘soft knowledge’ of the UK and these businesses helps me out.

      Obviously this all means I bear a conspicuous and enormous ‘UK Plc’ risk, which isn’t something I’m delighted bearing given my views on the UK as an economy..!

      In the future I expect I will branch out.

      Best,
      Lewis

      • Alan

        Thanks for thoughtful answer. Personally I run quite a concentrated portfolio, but with stocks from various international markets. It’s an interesting topic, as for individual stocks it seems a lot of UK investors perhaps almost default to UK listed, which narrows the opportunity set enormously.

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