Behavioural Finance: Part 2




In part 1, Wim Steemers explained the difference between passive and active investing, and how to outperform a market which is, according to theory, efficient. In this second part, Wim is diving deeper into how to actively invest and beat the EMH.


A fund manager cannot hope to, and in fact is ill-advised to try, get every stock call right. Rather, the aim is to have a net positive batting average over time, i.e. get more calls right than wrong. “Over time” in this context means several years – often a rolling 3-year period is used – but the longer the better (I’d think 5 year is probably a good rule of thumb[1]). Active managers usually spell out an approach that they will use to try and achieve a target return. Examples include:

  • “We try to find companies that have gone through some hard times, but we believe will recover, and where the stock price has overreacted”

  • “We buy high-quality companies that have an above-average growth profile”

  • “We have developed a quantitative approach that combines momentum, value and earnings revisions to construct an optimal portfolio”




The Problem There are many possible approaches, but they all suffer from one and the same fundamental issue: they are all designed and implemented by Humans, not Econs, who all have behavioural biases. These biases lead to suboptimal decisions (by definition). Examples of these biases are:

These biases and heuristics[2] show up in all aspects of life. Here are some ways they show up in the investing world – this is by no means an exhaustive list:

  • I’ve just bought stock ABC a week ago. I now read a newspaper article that describes how on the one hand in the company’s main market a new competitor is growing fast, while on the other hand the company is expanding into emerging markets. Confirmation bias will lead to my brain remembering the international expansion and dismissing the competitive threat.

  • I’ve bought stock DEF for $10. The stock is now trading at $8. Loss aversion will result in a reluctance to sell – my brain is telling me that, even if I no longer believe in the long-term upside of the stock, I should wait until it hits $10 again and then sell it.

  • I’ve just had a great meal in a restaurant owned and operated by company GHI. I go out and buy their stock, because Representativeness leads me to confuse a good dining experience with a good investment.

  • I’ve been underweight the tech sector for a while, and with dismay watched tech stocks go up and up and up. I finally decide to invest in the sector because Herding leads me to believe this must be the right decision – everybody else seems to think so, after all.




The Solution Broadly speaking, people tend to suggest three ways to beat these biases:

  1. Avoid the biases by being aware of them.

  2. Make the behavioural biases work FOR you instead of against you by studying how these biases lead other investors astray and take advantage of the resulting excess return opportunity.

  3. Go completely quant[3], i.e. take out human decision making.

Sadly, none of these work!

  1. Every fund manager you speak with will tell you that she is aware of these biases and is overcoming them through their process. This is, however, impossible!! It is akin to claiming that you are not Human. We know from academic research that knowing about a behavioural bias does nothing to prevent the bias from influencing your behaviour. Think about this for a second. This is very different than, let’s say, running. If my running coach tells me I’m leaning too far forward while running, I will become aware of this and I will be able to correct this through conscious effort. Behavioural biases don’t work this way. You can learn about them, be aware of them, but you cannot stop yourself from exhibiting them.

  2. Similar to nr. 1, you can’t ask a Human to be an Econ, and therefore asking Humans to take advantage of human biases is an oxymoron.

  3. It is an illusion that quant models have no human input. They are designed by humans and very much reflect the designer’s beliefs and biases. Anyway, even the best designed quant models suffer from a host of problems, especially around turning points in the market.





Should we give up?

I can see two things that can be done:

  • · Teamwork: as mentioned, academic research shows that it is hard to deal with your own biases; however, it is possible to learn to recognize them in others. Therefore, if you can create a team with the right dynamics (in particular, everybody must be allowed and even encouraged to comment on everybody else’s opinions, regardless of seniority, without destroying interpersonal relationships), you stand a chance.

  • · Combine the elements of “other people’s biases” and “take the human out”: create a quantitative behavioural finance fund[4].



Closing Remarks From all the comments above, it seems clear that in case you decide to invest your hard-earned money in an actively-managed equity fund, look for this:

  • A long track record (at least 3, preferably 5 years).

  • Proof that the manager has not changed approach through good times and bad.

  • The portfolio is team-managed, rather than relying on a star individual.

  • Don’t worry about last year’s performance.

  • Fees are important, but performance is more important.


Other common-sense tips include:

  • Don’t try to time the market – you will fail! If you had missed the best 10 days out of the past 10 years (2608 trading days), your return would be 44% less than if you had been invested the whole time.

  • Do not, under any circumstances, watch CNBC all day long and take investing tips from there!! They are not interested in your investment returns! Anyway, it will make you depressed…

  • Invest regular amounts over time.

  • Don’t look at your statements more than once a year.

That is it for this behavioural finance mini-series by Wim Steemers!






References and Notes

[1] If a manager outperforms 6 and underperforms 4 out of every 10 years, the probability that he will by chance produce 3 bad results in a row is 6.4%, while the probability he will do so 5 years in a row is 1%.

[2] Heuristic is jargon (there it is again!) for a short-cut in decision-making. They make life easier and under most circumstances lead to decisions that are good enough. Example: when I look at a menu in a restaurant, I will choose the first item that looks interesting – I will not create a spreadsheet with all the pluses and minuses of each item. [3] More jargon, sorry! Quant model = Quantitative model: an investing approach where you write a computer program that evaluates and then picks stocks purely based on quantitative criteria. Thus the daily buy and sell decisions do not have any human input that is clouded by biases and emotions.

[4] Rosevalley Funds is a series of funds that are based on systematic application of Behavioural Finance principles. They are based in Australia. Learn more at www.rosevalleyfunds.com.

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