A few readers that have emailed me recently seem to follow some kind of system for picking, buying and selling stocks.

This surprised me a little as I would have assumed that quant or systematic strategies were quite far removed from our usual emphasis on business quality, valuation and, in many cases, focusing purely on asset allocation and buying index funds instead.

This got me thinking about some of the investing systems I’ve come across in my time and the costs and benefits that might come with following one.

Potential benefits of investing systems

1. Can help you find potential investments faster

The first ‘system’ I remember discovering was Joel Greenblatt’s Magic Formula. Greenblatt made his name as a stock picker (and a very successful one at that). His firm Gotham ran highly concentrated portfolios and scored outstanding returns in the nineties and early 2000s.

In his books for everyday investors, though, Greenblatt warned against selecting individual stocks without a strong knowledge of business analysis and its valuation.

One of his answers for this was the “Magic Formula”, which was basically an attempt to identify a pool of potential investments in above average quality companies (measured by return on capital) trading at below average valuations (measured by a higher than average cash flow yield).

It’s hard to argue with his criteria. So if you are time poor, running a screen based on his formula can be a quick way to find ideas that, on paper at least, seem to be more attractive than average. I still do it every now and then out of curiosity.

2. Can add structure to your approach

David Dreman’s book Contrarian Investment Strategies outlines the author’s method for buying the market’s cheapest and most hated stocks based on data alone. I wrote about it in this article.

By buying these stocks, Dreman was trying to tune out the noise and benefit from the tendency of investors to become overly depressed about stocks with poor near-team outlooks. He would then sell shares once they reached the market’s average valuation.

Having a defined strategy for entering and exiting a position makes each trade more deliberate. This, in theory, is a lot better than trading purely on emotion or out of boredom.

Our approach at Morningstar isn’t really aligned with frequently churning positions or buying and selling companies based on statistics alone. But we are very much on board with adding more structure your investment process.

To see how you can follow 4 steps to define your investing strategy, read this article by Mark LaMonica.

Potential trade-offs of investing systems

1. Back-testing and real life are very different

A lot of systems are touted on the basis of back-tested returns. Apart from the fact that the past and the future are not the same thing, there are several reasons that you shouldn’t put a lot of weight on back-tested results being replicated in your future returns.

First of all, will you realistically be able to execute the strategy in the same way as the back test, with perfect accuracy? For example, is it feasible to own anything like the same number of shares that the backtest was carried out on? Many tests looking for so-called “factor outperformance” are carried out on samples of a size far bigger than one person would realistically hold in a portfolio.

Also consider that back-tests deliver you returns in hindsight. They are not the same as experiencing the ups and downs along the way.
As Joel Greenblatt has said in the past, some ways of investing work over long periods of time precisely because they don’t work all of the time. If they did work all the time, everybody would do them and there would be no edge.

Are you sure you can stick with your system through a bad stretch? When people are making money in other things? Or – god forbid – with another appealing stock system? Also consider that back-tested investing systems are as good an example of survivorship bias as you are likely to see.

What about all of the other potential systems that were also back-tested but failed to make the cut?

2. Do systems and overtrading go hand in hand?

The idea of a system is that it tells you what to buy and what to sell. If it tells you to buy and sell a lot of things, this will lead to lots of trading.

A lot of trading leads to lots of fees and – if your system works – lots of short-term capital gains taxes that get in the way of compounding. Were those included in the back-tested returns that attracted you to the system? For an example of how overtrading can destroy your investment returns, see my reflection on a shameful 2021 of investing here.

Having to sell every position at a set point also precludes truly spectacular winners at the stock or investment level. This could be important because the long-term return of most investors (and most indices) are dominated by a small number of humungous winners.

If you constantly clip winners after a set increase in price or once they pass a P/E ratio of X times, this won’t happen to you.

One prescient decision to buy and hold a long-term winner like this can pay off for years, even decades after you have made it. It can also make up for several other not so great purchases. Churning more often requires you to be right far more often – and the smaller gains are less likely to make up for as many losers as a 10 or 20 bagger can.

3. Do you really have an edge?

Outperforming the market average – and if you aren’t, what is the point of following a system? – requires you to have some kind of edge.

There are three main sources potential sources of investment edge: informational, analytical and behavioural.

  • An informational edge is having access to more or better quality information. Most investment systems are based on public data, which means you don’t have an informational edge.

  • An analytical edge is making better use of the same information. When you consider the billions upon billions of dollars invested by firms into databases and quantitative algorithm writers with rocket science PHDs, I think it is hard to claim a durable edge here. Even if you find a better formula, chances are they’ll find it soon too. A lot of popular systems were discovered before big data really took off and may have benefited from this edge before technological progress extinguished it.

  • A behavioural edge is where you avoid mistakes that other investors – both individual and professional – are prone to making. A system designed to benefit from mispricings caused by these mistakes – like David Dreman’s attempt to benefit from over-pessimism – might be interesting. But if it can be captured by numbers, you will probably run into the previous problem again.

Another potential issue with systems

The biggest issue I have with trading systems is that they are essentially an attempt to simplify things – business dynamics, valuations and stock market movements – that are extremely complex and, in the case of stock market movements, are often completely random.

It’s almost like our brains can’t deal with how random and disorderly reality is, so we try to make things fit into neater pattern when they really don’t.

As I alluded to at the start of this article, systems also reduce stocks to tickers and trading instruments rather than real ownership interests in real businesses. The quantitative is completely prioritised over the qualitative. And, just as importantly, no attention is paid to the investor’s circumstances or what they actually want to achieve through investing.

To see why forming a clear investing goal is so important, read this article by Mark Lamonica.

Do you currently follow a systematic approach to your investments? Or have you done so in the past? I'd love to hear from you at [email protected].

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