We may not like to admit it, but our human brains can be as defective as they are brilliant. When those defects impact our investing decisions – we pay the cost.
Human brains have evolved to deal with simple issues that we can see and touch. While we have developed complex systems of financial education, our ‘caveman’ brain can still trip and fall in a variety of ways as we navigate the financial markets.
When investing in shares or buying property, we can let biases affect our decision-making, and we consistently fail to notice logical pitfalls that we’ve already fallen into.
While we cannot change the make-up of our brains or remove all biases, we can reduce their impact by simply being conscious and aware of them. Other issues like logical fallacies can be avoided entirely by educating yourself about their characteristics and taking note to never again succumb to their charms.
A few quick definitions:
Bias: a tendency to agree with, or lean toward a sub-optimal solution
Logical fallacy: a defective thought process that generates an objectively incorrect conclusion
In this ambitious and ever-expanding article, we attempt to describe every single cognitive bias, logical fallacy or irrationality that affects investors. We’ll also offer our suggestions on how you can avoid the issue affecting your investment returns.
We’ll group together similar biases to give this article a sense of order and to allow you to make connections between similar issues.
Group 1: Anchoring biases
Anchoring biases are a group of biases involving our brains clinging to a particular piece of information undeservedly. Anchoring can result in us placing disproportionate weight on some information, at the expense of other (possibly more useful) information when making an investment decision.
- Anchoring bias
- Common source bias
- Conservatism bias
- Functional fixedness
- Law of the instrument
Anchoring bias
Anchoring bias is the tendency for us to latch onto the first thing we learn about a subject. We tend to remember this first piece of information, and don’t give equal prominence to potentially conflicting information discovered at a later date.
Example: At the pub, a friend shares a stock tip in the shape of a company which they believe is severely undervalued. You go away and perform further research about the company, but regardless of what you subsequently learn, your gut feeling about the company is likely to be biased towards the positive, compared to if your friend had written off the company’s prospects.
How to avoid: Challenge your ‘gut feel’ about a company, particularly when looking to make a punt on individual shares. A stock tip is nothing more than a single opinion in a sea of thousands. Assess whether you have collected enough evidence to justify your rosy view, or whether your introduction to the company or investment was the factor that has tipped the scales in favour of investing. This can be done by asking yourself: “How would I feel about this company if I had not heard that first piece of information?”
Common source bias
Our ability to be swayed by the existence of multiple published viewpoints that all appear to support a conclusion, where in reality each published piece was prompted by the same underlying source of information. In this way, a single viewpoint has multiplied to give the impression of a more persuasive series of agreeing arguments. This is an incredible pervasive issue because of the way that all media outlets follow the same newswires and therefore they consistently prepare content derived from the same underlying prompts and sources.
Example: Multiple online media outlets publish negative information about a company, using data and viewpoints expressed by a single hedge fund / short seller paper published earlier that day.
How to avoid: Read beyond headlines to ensure that you always understand the ‘what’ of an article but also the ‘why’. Specifically, why is this information being published? This check will expose a common source bias across multiple articles you’ve seen.
Conservatism bias
Conservatism bias holds that older information and opinions become entrenched and we find it hard to change our minds when the facts on the ground change over time. Said another way, conservatism is our inability to move our point of view when new information presents itself. This isn’t to be confused with how the word ‘conservative’ is used in British politics, although parallels could arguably be drawn between the two.
Example: Long-held investing rules of thumb that have become outdated fit this bias. For example, the 4% pension drawdown rule. This % was conceived during a period of high investment returns, and its sustainability has been brought into doubt after a decade of low growth in the UK economy. However, many investors who have looked ahead to their retirement with this percentage in mind will not let go of it lightly.
How to adapt: Keep your finger close to the pulse of new thinking in finance by following blogs and commentators that seek out the latest academic research and trends. Don’t be afraid to challenge ‘conventional’ nuggets of wisdom that you have lived by for years and years.
Functional fixedness
Functional fixedness is our tendency to use services or objects only for the narrow uses they were intentionally created for. This constrained thinking can be observed by handing packaging to a child and allowing yourself to be staggered at the sheer number of uses they can find for a box.
Example: In finance, we investors tend to use brokerage services for the products that are marketed. Perhaps we’ll use a fund supermarket to invest in funds, a stockbroker to buy shares and a traditional pension provider for our pension. All three of these financial institutions probably have a compelling version of each of these offerings, yet we tend towards using a service for what we feel it is ‘meant for’. This is subtly different to what it is objectively ‘best for’.
How to address: Take a closer look at the ancillary services offered by your UK stockbroker and you may be surprised by how competitively priced they are.
Law of the instrument
The law of the instrument is that when we are very familiar with a particular tool or solution, our thinking can be constrained in that we tend to think of every problem as being best-fixed with said solution, despite the opposite being true.
Example: If you’re a day trader, with a slick trading platform at your fingertips, you may be conditioned to react to most news by increasing or decreasing your holdings, even if trading isn’t actually the best course of action in each scenario. You have the urge to take action, trading is your comfort zone, therefore you buy or sell in a crisis, and may not give due consideration to the possibility of holding your positions.
How to avoid: Have a quick think about the tools you have at your disposal and decide whether you over-rely upon one because it’s your favourite. Reflect upon whether you have used it recently for a purpose it was ill-suited.
Group 2: Apophenia
Apophenia is the human ability to make connections between unconnected things. It’s easy to apply these biases or logical fallacies to the technical analysis (chart-reading) discipline and other stock research.
Clustering illusion
Attaching inappropriate meaning to relatively short runs of recurring data points or outcomes within a vast dataset.
Example: Witnessing three days of successive market gains and drawing a conclusion that a bear market has reversed. In reality, the bear market could continue for months.
How to avoid: The antidote to the clustering illusion is to consider how likely it is for a short string of interesting results to appear in a large dataset. To help you, you can bear in mind that in just 1,000 flips of a coin, you should expect to observe a run of at least ten heads in a row at some point.
Illusory correlation
Incorrectly making a connection between two events that in reality are totally independent.
Example: Seeing that UK equity prices are falling at the same time that Pound Sterling is weakening and assuming that the weak pound is driving the stock market lower.
How to avoid: Similar to the clustering illusion, we must be careful to not make sweeping conclusions about how two data sets are correlated until we have observed over a large data set. A few days of prices moving ‘in step’ is not enough evidence that the two are actually correlated.
Pareidolia
The human ability to notice and attach meaning to patterns in completely random data.
Example: Technical analysis follows can fall victim to Pareidolia when scouring charts to find a fit with pre-defined curves and shapes on their technical analysis books.
Repeated studies have shown that the asset prices of financial markets follow a ‘random walk’ which means that price data is essentially unpredictable. That’s because the future events that will trigger the next price movement are also unpredictable (relative to the market’s best estimate), thanks to the wisdom of crowds.
Yet, almost every conceivable curve shape sitting in the pages of chart-reading guides, together with supposed predictions of what this curve means for the future price action of the security. This will lead investors to draw many tangible conclusions from completely random price data and attach enough meaning to these conclusions to generate trading ideas.
Looking back at historical charts with the benefit of hindsight hands technical analysis authors with a massive advantage when attempting to bolster their methodology. They can cherry-pick examples that are subtly (or not so subtly) informed by the knowledge of what happened next.
For example, to show an example of the Head & Shoulders pattern indicating the end of a bullish price rise, authors may scan charts for the end of a bull run, and hone in on the lead-up. This is self-selection and ignores examples of where Head & Shoulders patterns appeared during a continuous price rise or even at the bottom of the market.
How to avoid: While this will be disputed, investors could accept that price movement is effectively random and therefore no meaning can be drawn from short-term patterns than appear in pricing data.
Group 3: Association Fallacy
Authority bias
The urge to trust that the statements of those in a senior position will be more accurate & true, regardless of the actual content or argument being made.
Example: Believing Turkish President Erdogan’s statement that lower interest rates reduce inflation (his justification for pursuing a questionable monetary policy).
Publicly siding with the opinion of those in charge is often expedient and avoids conflict. However remember that this bias refers to us tending to genuinely believe and agree with the statement, rather than simply deferring to a superior during a disagreement.
This bias may reflect a reasonable assumption that those in power speak carefully and usually represent authorities that put due consideration into public statements. However, recent events in British politics have shown that the veracity of public statements is not always guaranteed.
How to avoid: Try to hold the points of view of your heroes to the same standard as if they came from your friend in a pub. Do not allow your critical thinking function to take a break. As many financial news websites state: should you not rely upon their words as financial advice and still need to perform your own research.
The Halo effect
Allowing the observable positive traits of someone to bias our prediction of other (unobservable) traits.
Example: Subconsciously assuming that a handsome, smartly dressed financial speaker with an R.P English accent is highly intelligent or relatively qualified without any proof to support. This might be why most successive salespeople for overpriced ‘investment courses’ tend to be visually attractive. These visible positive characteristics will be helping them subconsciously convince others of their investing genius.
How to avoid: Try to reserve judgement on the trustworthiness or credibility of someone until you’ve considered how sensible their statements are.
As this is a subconscious bias, you won’t be able to actively prevent this bias but if interviewing a financial adviser or speaking to a fund manager, if you notice positive visual traits you may remind yourself that these could be influencing your estimation of how much money these individuals will actually make you.
Group 4: Attribution bias
Actor-observer bias / fundamental attribution error
When we observe someone else’s behaviour, we tend to focus on how their personality drove their decision-making, but when we reflect on our own behaviour we look more at the situational context to explain why we did what we did.
Example: “They sold at the bottom of the market because they didn’t have conviction, however, I only sold at a similar point because I needed to buy a house in the near future.”
This bias acts as a defensive mechanism because it deflects blame away from our own traits and seeks to explain any poor decisions as a consequence of unfortunate external factors that forced our hand.
This is to our detriment because it prevents us from genuinely accepting the mistakes we made and changing our investing approach as a result.
How to avoid: Become aware of your own shortcomings and be willing to accept that no one has the perfect mental pre-deposition to become a top investor. We all make decisions that in hindsight were sub-optimal. Have a think about which trades you would have made differently if you could turn back the clock to discover just how many times you have personally tripped up.
Extrinsic incentives bias
When witnessing positive behaviour, our cynical assumption is that others are doing so merely to gain external rewards (such as reputation and credit) while genuinely believing that we act the same way due to our intrinsic desire to do good.
Example: That investment fund is only investing in green stocks because it’s a fashionable trend that will attract more capital, and not because the fund managers are ethical.
How to avoid: We must remember that companies and institutions are no more or less than a group of people just like us.
Group attribution error
Drawing the incorrect conclusion that traits of group members are universal and reflect the entire group.
Example: Believing that all emerging market companies are corrupt on the basis that several high-profile corporations in emerging markets have been exposed as engaging with bribery and state capture.
How to avoid: This error can be addressed by performing research on an asset class before investing. We are most vulnerable to making a poor call based on group attribution error where we’ve only dipped our toes in a topic. The nature of financial news means that we’re only likely to hear about the largest success and failure stories if we haven’t immersed ourselves in an area. Because negative news is a bigger seller than positive news, we should recognise that we are likely to have negatively tainted our impression of asset classes that we don’t know much about, such as emerging markets and frontier market equities.
Hostile attribution bias
A subconscious instinct to interpret ambiguous behaviour in others as malicious, even if the intent was actually innocent.
This probably stems from a desire to not be ‘fooled’ or ‘swindled’ by evil enterprises, but produces a bias towards the negative when ambiguity exists.
Example: Interpreting a stock sale by the CEO as a negative news item, as may imply the CEO sees a storm approaching. In reality, the stock sale may have e to enable the CEO to buy a new island.
How to avoid: Keep an open mind as to the motivation behind events until evidence makes this clear.
Intentionality bias
Our tendency is to judge consequences or behaviours as purely intentional rather than by chance or random.
Example: Using the excellent recent track record of a fund manager as strong evidence that they are exceptional and will continue to outperform the market in the future. Read our article about a goldfish operating an investment fund to understand the full implication of this when trying to pick star fund managers.
How to avoid: Recognise that in a market with few massive winners, the odds of those winners being the outcome of sheer luck is very large. We must be cautious before attributing the success of fund managers to their skill or strategy.