How the Share Sleuth portfolio almost tripled

As the year draws to a close, it's tempting to look back and assess what went well, and what went badly. The easy thing to do would be to look at share prices, and the value of the model Share Sleuth portfolio I run, what went up and what went down, and backfill that account with explanations.

That would be unhelpful. It may seem a diabolical thing for an investor to say, but I didn't start 2016 with the intention of profiting from rising share prices in this particular year. Apart from the dividend, the only way to profit from a share is to sell it, and I didn't start the year intending to sell any shares at all.

Over many years the share prices of good companies do well, but over months or even a small number of years, they may not. For a long-term investor, focusing on short-term price movements is at best a waste of time because they are meaningless: the by-product of other people's buying and selling and their often fathomless motives.

At worst, we might be tempted to believe the aggregate of other people's trading is more informative than our own analysis, in which case we shouldn't have been taking our own decisions in the first place. There's an investment for people who don't have the confidence (or inclination) to pick stocks. It's called an index tracking fund.

We must judge our annual performance by the goals we set at the beginning of the year.

Feed the engine

2016 started with a New Year's resolution, to "feed the engine more efficiently". The engine that needs feeding is my Decision Engine, an algorithm that ranks shares according to the mostly subjective information I have collected about them.

If the information going in is good, and the algorithm that uses the information effective, it should help me make better decisions. Over the course of the year, I fed the engine and tinkered with the algorithm and the improvements mean I'm increasingly going along with the decisions it makes. In fact, I'm beginning to rely on it.

You might well ask why. Why make judgements about companies: how readily I can understand them, how stable they are, whether they have advantages that may be harbingers of prolonged prosperity. And why I then dump all that information into a spreadsheet and let it tell me what to do. Since I've worked out so much already, why not make up my own mind?

If I had a photographic memory, I might. But I need help visualising the portfolio, and the individual strengths and weaknesses of its constituents. It's not only my memory I don't trust, though. It's my ability to synthesize all that data objectively.

This year I added four companies to the Share Sleuth portfolio, Victrex in January, Next in June, Solid State in July, and XP Power in November. While it's tempting to dub Next a Brexit bargain and fabulate some kind of Trump-related justification for XPP, I added both shares in the immediate aftermath of the respective votes, they were business as usual for me. All four shares were (and are) ranked highly by the Decision Engine.

To fund the purchases in the model portfolio, I used cash from sales in 2015, dividends earned by the portfolio, and proceeds from the ejection of Camellia and Electronic Data Processing in July, and Rolls-Royce in November.

I gave up on Camellia, a conglomerate of agricultural, industrial and logistics firms, and Rolls-Royce, the famous engine maker, because of their complex businesses, or combinations of businesses. Accounting for them was too difficult. Electronic Data Processing couldn't figure out a way of breaking out of its software niche and put itself up for sale.

All three companies were failed investments in so far as they reduced the portfolio's value. Although I may have been aware of their weaknesses, I allowed myself to be seduced by strengths I admired. Psychologists call the tendency to be influenced by particularly attractive aspects of a person or thing, the 'halo effect'. Whatever attracted US voters to elect Donald Trump, they may have allowed their enthusiasm to shroud his deficiencies.

The halo effect may also have influenced me to buy the new tablet computer I am writing this article on. Ironically it has a 'halo' keyboard that allows it to be particularly slim and portable, but it's attached to a weedy central processor and a smallish screen. I may regret my decision to buy the computer in the long-term, but for now, I'm enamoured.

EDP seduced me with its bargain share price and long record of profitability, allowing me to overlook the absence of an obvious competitive advantage. At Rolls-Royce I was attracted by a prestige brand. Camellia's annual reports spoke to me directly. This was a company investing for the long-term in far-off countries.

Policemen interview witnesses separately to prevent them from influencing each other. Each of the criteria I use to determine what makes a share a good long-term investment is like a witness providing evidence about the strengths of a share, but I have tended to conflate their testimonies.

This year, l simplified the Decision Engine's algorithm. I shrank the number of criteria to five distinct traits, which I grade independently from 0 to 2 to give an overall score out of 10. My witnesses' testimonies reveal whether a firm is:

1. Straightforward

It should be apparent how the company makes money, and the accounting should be clear.

2. Generating excess returns

Over a long period, preferably at least a decade, the firm should have earned a return on capital not less than 8%, and more in most years. It should also generate enough cash to fund present and future activities.

3. Resilient

The business should be adaptable and profit from activities that are likely to remain relevant for at least the next 10 years.

4. Managed equitably for the long-term

Management should profit through the ownership of shares held for the long-term. They should be paid fairly according to the demands of the job, and relative to employees.

5. Valued attractively

I use a much adjusted cousin of the price earnings ratio, an average earnings yield, to compare company valuations. The algorithm progressively favours earnings yields above 5%, and penalises those below 5%.

Since I can't be trusted to weigh up these factors objectively, I get a second opinion from the computer.

Just for the record, it's just over seven years since I started the Share Sleuth portfolio and in that time a notional £30,000 has increased in value to £82,052, an increase of 174% including dividends, stamp duty and fees. The same amount invested in accumulation units of an index tracking fund over the same period would be worth £56,099, 87% more than it was worth in September 2009.

Happy Christmas!

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Contact Richard Beddard by email: richard@beddard.net or on Twitter: @RichardBeddard

This article is for information and discussion purposes only and does not form a recommendation to invest or otherwise. The value of an investment may fall. The investments referred to in this article may not be suitable for all investors, and if in doubt, an investor should seek advice from a qualified investment adviser.