Behavioural Bias: Investors ignore at their peril

For the most successful species in the history of our planet, human beings are surprisingly poor at making sensible decisions based on our observations of the world around us.

Anton Pietersen

Anton Pietersen

Senior Specialist: Investment Analytics

Joseph Pearson

Joseph Pearson

Head: Analytics

We ‘moderns’ may like to flatter ourselves that we are rational thinkers but in fact we are vulnerable to a range of unconscious biases that can lead us to irrational conclusions. STANLIB’s Analytics team uses the principles of behavioural finance to make our portfolio managers aware of these biases and help them refine their investment processes accordingly.


Daniel Kahneman: Explaining the pathology of irrational thinking

In his book ‘Thinking, Fast and Slow’, Nobel laureate Daniel Khaneman conceived a model of the human mind as an alliance of two ‘systems’.


System 1: Fight or flight

System 1 is our ‘ancient’ brain which evolved to help Homo Sapiens survive and thrive in an environment full of danger. System 1 is fast and fully autonomous (you don’t need to ‘think’ about whether the lion emerging from the tall grass is a problem) and is constantly maintaining a model of our surroundings. System 1 is capable of rapid, effortless assessments but is also highly vulnerable to cognitive bias.


System 2: The clever bit

System 2 is the ‘modern’ brain which allows us to grasp abstract concepts and wrestle with complex problems. System 2 is slow and demands conscious effort but is responsible for splitting the atom and putting a man on the moon.


System 1 made us a successful species; System 2 made us masters of our planet. In addition to being time consuming, lazy and energy-intensive, System 2 has one structural weakness: before setting off on a problem-solving exercise, it will always ask System 1 for its ‘opinion’, thereby importing our ancient brain’s unconscious biases. In this way our most ‘rational’ thinking can be subtly distorted in surprising and important ways.


Here are some examples of the unconscious biases which can influence the judgement of even the most ‘rational’ investor.


Hindsight bias

Humans are tempted to believe that we perfectly understand the past and can therefore predict the future. Google’s success looks obvious in hindsight but it has inevitably been the product of luck as well as judgement: the influence of fortune is a ‘known unknown’ which barely registers in the scale of our cognitive process beside the monolithic reality of Google today. We naturally conclude that it was always destined for greatness. As Warren Buffet points out, “In the business world, the rear-view mirror is always clearer than the windshield.


Loss Aversion

Humans have an instinctive appreciation of risk and reward which may surprise you. Here are a couple of scenarios to consider:


Decision 1: choose between:

           A: a guaranteed profit of $250, or

           B: a spin of a wheel which gives you a 25% chance of winning $1,000 and a 75% chance of winning nothing


Decision 2: choose between:

          C: a guaranteed loss of $750, or

         D: a spin of a wheel which gives you a 75% chance of losing $1,000 but a 25% chance of losing nothing


In the language of probability, each pair of choices have the same expected value, but Kahneman’s experiments reveal an interesting pattern: people will give up a chance of a big win to lock in a smaller profit (choice A), but will gamble to avoid locking in a loss (choice D). This is Loss Aversion: the reality that people are so innately reluctant to lock in a loss that they will risk an even bigger loss just to have a chance of escaping intact. To quote Kahneman, ‘An investment said to have an 80% chance of success sounds far more attractive than one with a 20% chance of failure. The mind can’t easily recognise that they are the same’.


This bias is conspicuous in the behaviour of gamblers who are having a bad day at the races: they will often bet more than their usual stake on the last race to recoup their losses. This is obviously irrational, but ‘loss aversion’ is whispering in their ear that they have a chance to ‘make it all back’. It rarely ends well.


One can imagine how Loss Aversion can influence a portfolio manager’s decision-making: as human beings they are innately reluctant to sell positions at a loss. One way to consciously override this bias is for the portfolio manager to see each stock within the context of the portfolio as a whole; they know that not every position will be a winner but can take comfort in diversification and portfolio construction to deliver good returns (assuming that their asset selections are right at least half the time). If they can consciously adopt this framework, they will find it easier to make rational decisions to cut their losers. As Nobel laureate Harry Markowitz said, ‘diversification is the only free lunch in investing’.


The reality of running a portfolio cannot be entirely reduced to simple aphorisms like Peter Lynch’s observation that selling your winners and holding your losers is like ‘cutting the flowers and watering the weeds’: sometimes losing stocks are just cheaper than ever, and sometimes winners are overvalued. Nevertheless, Loss Aversion is a powerful bias which against which we must be on our guard.


The Narrative Fallacy

As mentioned above, System 2 is clever but lazy. Storing information consumes intellectual energy so System 2 will look for ways to package data to save space. Narratives are an effective way to do this.


In ‘Thinking, Fast and Slow’ Kahneman gives a typically accessible example of this phenomenon. If you were asked to memorise fifty random numbers, it would be a daunting task. If on the other hand you were told that the fifty numbers in question were the even numbers between zero and 100 it would take no effort at all since they are described by a system, or narrative.


The laziness of System 2 predisposes us to impose narratives on data, whether justified or not, and to be persuaded by them. In financial markets the Narrative Fallacy manifests itself in the temptation to extrapolate historic trends into the future and falsely impute a causal link between events. This is particularly dangerous for portfolio managers whose job it is to understand the range of future outcomes based on historic data.



Asset management is a ‘knowledge’ industry: portfolio managers are paid to produce accurate assessments of economies, industries and companies and then express them effectively through the capital markets. Given the complexity of the task, successful individuals can be hailed as brilliant operators even though fortune always plays an unquantifiable role (as the market adage has it, ‘Never confuse brains with a bull market’). Winning portfolio managers are tempted to believe their own hype as their belief in their own powers grows their healthy fear of the unknown must inevitably recede.


As Mark Twain put it, ‘It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.’ Overconfident managers build excessively concentrated portfolios as the benefits of diversification dim alongside their sense of their own talent. A strong risk management framework is the only remedy to overconfidence.


“The essence of risk management lies in maximising the areas where we have some control over the outcome while minimising the areas where we have absolutely no control over the outcome and the linkage between effect and cause is hidden from us.” ― Peter L. Bernstein, Against the Gods: The Remarkable Story of Risk


Confirmation bias

Overconfidence is compounded by humans’ desire to justify their own beliefs, if only to avoid the intellectual effort involved in integrating new information and the psychological cost of adjusting one’s view of the world. This is Confirmation Bias, the tendency to emphasise data points that confirms one’s existing beliefs and to ignore those that contradict them. This is a deep bias that can contaminate a manager’s entire investment process; it exacerbates Loss Aversion (see above) and undermines their ability to accept that events are not playing out in their favour. Confirmation Bias is anathema to John Maynard Keynes’s famous aphorism: ‘When the facts change, I change my mind. What do you do?


STANLIB Analytics: guarding against biases in portfolio management

Behavioural finance attempts to map the minefield of cognitive bias that investors must navigate to achieve consistent success. For STANLIB, helping portfolio managers to be aware of cognitive bias is a cornerstone of effective risk management. This is the mission of STANLIB’s Analytics team which supports STANLIB’s investment teams with advanced analytical and insights which can help them make better investment decisions.


STANLIB’s Analytics team follows a simple 3-stage process:


  1. Inform and Challenge

The Analytics team produces research to raise STANLIB’s portfolio managers’ awareness of behavioural bias. The team produces daily, monthly or quarterly analysis which digs deep into portfolio construction, individual investment decisions and trading patterns to extract insights. The Analytics team presents these insights to the portfolio managers and then plays ‘devil’s advocate’, providing alternative or contrarian views to help the managers re-examine their investment process.


For example, if a portfolio is significantly overweight a stock which is contributing disproportionate risk the analytics team will highlight it to the portfolio manager. Even a cursory overview of the biases above should make it clear that it is precisely a manager’s high conviction positions that pose the most behavioural risk to the portfolio. The analytics team may be able to help the portfolio manager to revisit their thesis, be aware of potential bias and confirm that the position is correctly sized.


  1. Revisit

Standardised reporting and consistent communication allow the Analytics team to maintain an ongoing conversation with STANLIB’s portfolio managers and to track the evolution of their investment process from a behavioural point of view. The team uses its Routine Quarterly Investment Risk Reporting as the basis for regular engagements with the portfolio managers, highlighting trends or possible biases emerging in their portfolios. A two-step process is used to provide insights into the portfolios within a specific investment team.


Firstly, portfolios are grouped according to their investment mandate or client outcome; this analysis provides a top-down view to check alignment in terms and risk and performance and also to ensure that clients are being treated fairly. The team then performs a detailed bottom-up analysis of proxy portfolios within each grouping.


  1. Incorporate

It is critical to implement behavioural insights to make sure that STANLIB’s investment process keeps evolving; the opportunity is to reduce the size and impact of adverse outcomes. The Analytics team helps our portfolio managers to visualise their portfolios’ resilience (or fragility) under various stressful scenarios such as the Global Financial Crisis of 2008.


In a world of ‘Black Swans’ like the COVID pandemic and Russia’s invasion of Ukraine, this is a valuable prompt for portfolio managers to keep tail risks in mind and consider how their portfolios might underperform the benchmark or fall short of their client mandates.


STANLIB Analytics: The Power of Self-Awareness

Even in an era of ubiquitous computing power STANLIB understands that building effective investment portfolios requires the creative and analytical genius of the human mind. Unfortunately, that genius cannot be separated from the unconscious biases that compound the difficulty of protecting and growing capital in an uncertain world.


STANLIB understands that behavioural bias represents a real risk to performance. STANLIB’s Analytics team is a specialist in-house resource which provides dedicated behavioural risk management tools to our investment professionals.


The team maintains a constant dialogue with our portfolio managers, raising their awareness of behavioural issues and helping them mitigate their innate biases. If our managers are brilliant F1 drivers, our Analytics team is the support crew that can alert them to hazards around the next bend, helping them stay on the track and out of the gravel.


The Analytics team plays a fundamental role in STANLIB’s mission to protect and grow our clients’ capital.

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