Experts are inferior? It’s true. Trust me I’m an expert. I want to explore how you can rise above the errors.
One of the great books on both economics and how we behave and think is “Thinking Fast And Slow”. It asks the question: “why are experts inferior to algorithms?”. Algorithm is maths-speak for a straightforward process – sometimes a process which is no more than a checklist.
Medicine, economics, and social sciences are expert-strewn environments with high levels of uncertainty and/or complexity. Of course, there are obvious exceptions in each field, but they are exceptions.
As Kahneman* pointed out, a simple process (or algorithm for those who want to get with the parlance) will match and frequently outperform human decision-making, in particular it will outperform experts in that field.
In one case researchers began by creating, as a starting point, a very simple algorithm, in which the likelihood that an ulcer was malignant depended on seven factors doctors had highlighted, each equally weighted. The researchers then asked the doctors to judge the probability of cancer in ninety-six different individual stomach ulcers, on a seven-point scale from “definitely malignant” to “definitely benign.” Without telling the doctors what they were up to, they showed them each ulcer twice, mixing up the duplicates randomly in the pile so the doctors wouldn't notice they were being asked to diagnose the exact same ulcer they had already diagnosed.
The researchers assumed that this simple first attempt (with the seven factors), was just a starting point. They thought the algorithm would need to become more complex, and require more advanced mathematics. For example, it might need to account for the subtleties that would guide more experienced doctors. For instance, if an ulcer was particularly big, perhaps they should reconsider the weighting of the other six cues.
But when the data was analysed the story became unsettling (the chief researcher described the results as “generally terrifying”.**) Firstly the simple model proved to be extremely good at predicting the doctors' diagnoses. The doctors might want to believe that their thought processes were subtle and complicated, but a simple model captured these perfectly well. That did not mean that their thinking was necessarily simple, only that it could be captured by a simple model.
More surprisingly, the doctors' diagnoses were very inconsistent. Not only did the expert doctors not agree with each other. When presented with duplicates of the same ulcer, every doctor had contradicted himself and rendered more than one diagnosis - the doctor could not even agree with themselves.
If you wanted to know whether you had cancer or not, you were better off using the simple algorithm that the researchers had created than you were asking the radiologist to study the X-ray. The simple algorithm had outperformed not merely the group of doctors; it had outperformed even the single best doctor.
Algorithms don’t contradict themselves. The same inputs generate the same outputs every single time. They don't get distracted, they don't get bored, they don't get mad, they don't get annoyed. They don't have off days. They don’t get over-confident in their expertise! The algorithm doesn't even have to be a complex one.
I certainly accept all of that eye-opening research. Yet the trap I/we mustn’t fall into is to over-simplify.
For example, I often say successful investing is just about process and discipline – ignore the continual wittering of experts.
But those two words cover a number of strands. Let me explore that via the recent reports for founder Gold Members.
The recent Winning Funds Reports were fascinating (I know I keep saying that, but it is true). They gave me and my colleagues great insights.
For example, there are a good number of Gold Members with VERY focussed portfolios, with no more than 6 or 8 funds, some with just 3 or 4. They aren’t just very focussed, but the fund choices are measurably excellent. This is what the portfolios of the world's most successful investors look like- high conviction, very concentrated, high quality (AKA high potential).
In contrast there are a greater number of Gold Members with a large number of funds, plus individual shares. These aren’t terrible by any means. Most have plenty of good funds, and the portfolio needs some tweaking around the edge to transform the potential.
What will be interesting is how each of these two groups responds to the biggest problem which lies not far ahead, but whose exact positioning remains fog-bound. The next bear market.
Ironically those in the second group are more likely to apply stop losses and thereby have the ammo to buy bargains as they emerge. This is because they are not high conviction investors - so the act of selling under stress, applying a stop loss, is less mentally painful.
In contrast the high conviction investors are more likely to be over-confident . They will behave more like experts, with a tendency to try and out-think the market. At least that is what the behavioural research tends to suggest. As the expert-resembling investors achieve greater success, they risk becoming dangerously over-confident. Despite a highly complex environment, the illusion of knowledge grows with success - importantly, success achieved in relatively calm markets.
We can’t predict with any precision the next bear market. But we can recognise the growing vulnerability to a bear market. If we can’t predict, we must prepare.
The most successful investors do just that, even the likes of the great Sir John Templeton. He gave his brokers a standing order to buy certain stocks when the price was down, say, 50%. Why? Because as his great niece tells us via James Montier, when the market was down that much he knew he wouldn’t have the discipline to buy.
Even such an extraordinarily successful investor knew his weakness when tasked with making decisions under great stress – we could say he was a great investor precisely because he knew his weaknesses. His solution was to plan in a calm moment, and make a pre commitment. That kind of humility marks out a great investor – but over-confidence can destroy an expert investor.
Part of your plan, your process, must be to decide how you will act when markets are sharply lower, which will require both selling and buying under conditions of stress. Don’t be seduced by the profitability and simplicity of your (our) process when markets are calm.
*Nobel Prize-winning behavioural theorist Daniel Kahneman
**For balance I should add that the results from similar research on the investment industry found them far more terrifying than doctors. For more on all this do read the superb “Little book of behavioural investing” by James Montier.