Successful investing depends as much on analytical skills and the quality of available data as on how we think. An intelligent person with enough information can still make a wrong conclusion.
Have you ever wondered why obtaining significantly different diagnoses from the same physicians is common? Did you know that judges have been found more likely to grant parole at the beginning of the day or after a food break than immediately before such a break?
For a few years now, I have been studying best practices in decision making as part of the effort to improve my overall investment results. Most would agree that finding a great business at a good price is the simplest formula for success. But when your favourite company reports a profit warning, is it a signal that your assumptions are no longer valid and you need to sell or is it just a temporary issue and all you need is to remain patient?
I have been reading many books on the subject of thinking and have reviewed some of them on my website. One such book which I have recently finished reading is Daniel Kahneman’s Noise: A Flaw in Human Judgement.
I have summarised the action points on how you can improve your decision process based on the insights in that book.
Actionable points on how to improve your decision making
1. Check your mental state. Ask yourself if there is anything that makes you overly excited or too pessimistic, an event that you keep regretting or other factors making you feel frustrated or nervous, or experience any other feelings keeping you out of emotional balance. Lack of quality sleep also impacts your decision-making skills.
2. Defer the decision, do not make an immediate decision. Returning to the same question in a few days may not lead you to find a better answer, but a combination of your first thought and the second one would lead to a better final decision. Extending your decision-making process reduces the impact of random factors (including your emotions). When you slow down before making a decision, you switch on your System 2, which is more analytical and critical thinking. You will increase the chances of considering more relevant points and getting a more rounded view before deciding.
3. Work out guidelines/checklists/rules. In investing, for example, this can be the minimum number of profitable years a company should have for you to invest. Or as simple as never investing in an IPO, or a minimum level of historical growth rate, specific leverage criteria etc. Rules also help distinguish between objective facts and personal preferences and values. We should try to see the world as it is, not as we want it to be (e.g. a typical mistake is a reaction like - “It doesn’t make any sense, this cannot happen.”).
Rules, formulas and algorithms are better than human judgement not because of some superior insight they bring but because they are noiseless.
The primary reason model does better than people is that they are less noisy. They may not reflect reality perfectly, and their predictions will not be 100%, but they will still deliver better results than humans whose decisions are too noisy.
Guidelines are better than rules as they do not entirely eliminate the need for judgements. Yet guidelines reduce noise because they decompose a complex decision into several easier sub-questions.
A formula does not have to be complex to be helpful; a simple one is also good. Complex rules will often give you only the illusion of validity and, in fact, harm the quality of your judgments.
I think using more equal weights in investment portfolios will reduce the number of decisions you make and potentially improve your returns. It will force you to think about each investment and its characteristics and will not give you an escape route when you discover increased risk by saying, ‘This is just a 2% position for me. I cannot lose too much’.
As a compromise, you may have only two or three types of weights (e.g. 20% for core stocks where the risks are extremely low, like Berkshire Hathaway; 10% for all others and 5% for new positions to have the opportunity to increase their weight to 10% gradually and, thus, reducing timing risk).
4. Wisdom of the crowd. A group of people making independent judgements will produce a better outcome than an individual, even an expert. A group of independent experts will generate even better results. There are also decisions made at group meetings. It is then preferable to have private votes first and then the discussion. If you start the conversation first, the order in which each group member speaks can impact the thinking of other members who are yet to speak. The order in which experts talk at a meeting can influence the final decision made by the group.
5. Try to find your own ‘Charlie Munger’. Warren Buffett praised his long-life business partner and friend, Charlie Munger, for helping him make better decisions. Kahneman refers to studies suggesting that a second expert’s view will significantly improve your decisions. If you ask the same question yourself at a later time (Point 2), you will only receive a third of the benefit compared to asking your expert friend.
6. Watch out for great stories. It makes a case look more coherent, you become overconfident and may pay attention to irrelevant facts (but fit well the overall story). Going back to Point 3, if you have a checklist, you know what you are looking for and do not let random facts impact your views and start building an exciting story.
In investing, rather than reading an in-depth research note on a stock or checking a company’s PE multiple, it is better to first look at the key fundamentals like sales growth, profit margins, FCF and dividend payments, and ROIC. Afterwards, think about the fair price for such a business.
Then check the actual price and multiple. Think about the reasons why the market may have a different view than you. Ted Weschler also described this method in one of his rare interviews in 2022.
7. Keep a diary to avoid a hindsight bias. Write down the rationale for each decision, the factors behind it, and your concerns at that time.
8. Try to take more outside view, less inside view. Statistical thinking [outside view] considers individual cases as instances of broader categories [base rate]. A specific case is not seen as resulting from a chain of particular events but is viewed as a statistically likely (or unlikely) outcome, given prior observations of cases that share predictive characteristics with a case in point. The inside view is looking at all the specific details of a particular case and trying to work out the decision from the inside. The risk with the inside view is that you overweight specific facts and draw wrong conclusions ignoring the bigger picture and other points you may not be aware of.
9. Think about the opposite decision (instead of buying a stock, you short it), then write down why this could be a good decision. This forces you to consider new information and factors for the first time. If the opposite decision is correct, what reasons could be behind you making the wrong decision (the original one)? What assumptions could have been incorrect? What does it imply? Was your first decision too optimistic or too conservative? After going through the exercise, make a new estimate (judgement). This technique is partially an alternative to asking a second opinion as you effectively become that other person when you think on an opposite view.
It is also helpful to seek counterarguments and speak to people who may disagree with you or have different perspectives.
10. Decompose a complex question into sub-components. In investing, it means having a clear set of criteria for an ideal investment and then analysing each component of a company in question. It is a better way than trying to decide straight away if this is a great company to invest in.
11. To improve decisions at large firms, it is vital to have the right culture where disagreement is accepted and different views are encouraged. According to Kahneman, the most significant factor for noise at large firms is “simply the discomfort of disagreement. Most organisations prefer consensus and harmony over dissent and conflict. The procedures in place often seem expressly designed to minimise the frequency of exposure to actual disagreements and, when such disagreements happen, to explain them away.”
This point is similar to Dalio’s principle of ‘radical transparency’.
12. Ranking is better than ratings. In investing, it means that rather than estimating a company’s fair value precisely, it is better to pick the best investment out of several options. The more alternatives you have, the better. This also explains why generalists are generally better than narrow-sector specialists.
Explicit comparisons between objects of judgment support much finer discriminations than ratings of objects evaluated one at a time. When analysing a company, it helps if you can relate it to other companies rather than try to come up with the most precise valuation. Use comparative judgements (ranking) to reduce noise.
Studying many companies helps to evaluate new investment opportunities better. Not surprisingly, one of the best investors in the world, Warren Buffett, developed a habit of going through Value Lines stock snapshots in the early years of his career.
Generalists also have an advantage as they have more sectors and a wider range of companies to put a particular investment opportunity in the right context. Narrow sector-focused experts will miss potentially more lucrative opportunities or bigger trends (e.g. buying an oil stock that trades on a single PE at a time of record oil prices and emerging signs of recession).
13. Avoid big mistakes (e.g. buying an overleveraged company); they reduce noise much more than small mistakes. “To minimise MSE, you must concentrate on avoiding large errors. If you measure length, for example, the effect of reducing an error from 11cm to 10cm is 21 times as large as the effect of going from an error of 1cm to a perfect hit.” “Unfortunately, people’s intuitions in this regard are almost the mirror image of what they should be: people are very keen to get perfect hits and highly sensitive to small errors, but they hardly care at all about the difference between two large errors.”
14. Correcting predictions.
I. Make your intuitive guess. (A)
II. Look for the average (mean) for such cases. Forget about individual characteristics. (B)
III. Estimate the value of the information you have (quite challenging). It should be expressed as a correlation between the evidence and the outcome you try to predict. In the social sciences, correlations of more than .50 are very rare. Many correlations that we recognise as meaningful are in the 0.20 range. (C)
IV. The final step is a simple arithmetic combination of the three numbers you have now produced. Expressed as a formula, the Final outcome = Intuitive guess X Correlation + Mean (Base Rate) x (1 - Correlation).
Or, Final outcome = A x C + B x (1 - C). If rearranged, the Final outcome = B + (A - B) x C.
Suppose you are trying to estimate the growth rate of a company ten years from now. So far, it has averaged 25% CAGR over the past 15 years. Given your knowledge of the product, management and general understanding of the competition, you think the company can maintain the same rate in Year 10. Then you should look for the base rate. Let us assume that a typical company can grow its sales at about a 5% rate, which roughly matches normal GDP growth of 2% and some inflation (let’s say 3%).
Then you have to estimate the quality of the information you have for your specific company. What is the correlation between your data and the future outcome (sales growth of 25% in ten years)? Given that 0.5 is considered very high and unless you have unique insights and skills, a 0.25 correlation would be viewed as good.
The final step is to work out the corrected prediction using the formula above. The adjusted growth rate is only 10%, much closer to an average company than to the historical rate of the company you are analysing. This is, of course, a very theoretical exercise. Your experience, skills, and knowledge of the company, sector and other circumstances can dramatically impact the forecast.
One final and pretty sad thought about this formula is that you will most often reject investing in startups and the next Amazon or Google, given that statistics work against such companies (the base rate of success is extremely low). And identifying such companies using financial statements or general knowledge about the product cannot materially boost your predictive power (correlation).
You can read the full review of Kahneman’s book in the Library to learn more about sources of noise at the individual and firm level, strategies to reduce judgement errors, what types of errors increase noise more and also what leads to bigger errors: biases or errors.
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