Today, when I read the news or browse through social media, I notice a deluge of confident expert opinions and ‘scientistic’ forecasts (too readily) available in our information age.
This is why I am fascinated by the reliability — or lack thereof! — of expert opinions and forecasts. This interest was further developed through my IB Theory of Knowledge presentation, which explored the extent to which it’s possible to make reliable
economic predictions. I learned that we frequently derive false security from precise numerical forecasts, which
are often based on data that can be conveniently measured rather than the most important parameters (which
might be difficult or even impossible to measure).
Hayek’s speech titled ‘The Pretence of Knowledge’ further led me to conclude that economists can make
directional predictions, not precise forecasts. Hans Rosling’s Factfulness even describes a quiz in which
chimpanzees outperformed so-called experts. I learned that forecasts reported in the media are often made by
overconfident pseudo-scholars — and even when made by a genuine scholar, forecasts are still bound by any
model's limitations.
Yet thoughtfully developed predictive forecasts remain important for effective decision-making, which (particularly in the investing world) requires an
implicit consideration of a necessarily uncertain future. Experts’ analytical, frequently imaginative statements about
the future are powerful tools that allow us to build models and glimpse through a translucent lens into a potential
future.
During my exploratory journey in the world of value investing, I have learned that investing requires us to distinguish meaningful signals from the cacophony, generated by experts and media pundits and amplified by social media, surrounding the global economy. I am certain that our ability to separate the wheat from the chaff — or, more appropriately, the signals from
the noise — is what will determine whether or not we are able to generate alpha over a long period of time. As I once said Leave it to the Experts (Don't)!!!
I have read pretty much all of Marks' memos, and this one is one of the best yet. The key implication for (equity) investors, if I understand correctly, is that a great businesses can be a poor investment at the wrong price, whilst a terrible business can be a great investment at the right price. Instead of trying to identify winners, we must seek to identify - and capitalise on - 'mispricings'.
I first read this book, a perfectly-worded reflection on the most iconic (if I may use such a word!) speculative episodes in human history, after studying the Great Depression and the New Deal at school. I am fascinated by the mass insanity and “the associated financial deprivation and larger devastation” of every speculative episode; the infectious boom, is alwaysaccompanied by“desperate and largely unsuccessful efforts to get out”. There is almost no doubt in my mind that “speculative episodes end not with a whimper but with a bang”. In this post I will try to highlight a few insights I picked up from this brief and impactful must-read.
There is no such thing as financial innovation - only credit.“The world of finance hails the invention of the wheel over and over again, often in a slightly more unstable version. All financial innovation involves in one form or another, the creation of debt secured in greater or lesser adequacy by real assets.” This is why Galbraith advises, “when there is a claim of unique opportunity based on special foresight, all sensible people should circle the wagons; it is the time for caution.”
Any association of money with intelligence is nothing short of “specious”. People are entranced “by the great financial mind” because there is a “feeling that with so much money involved, the mental resources behind them cannot be less.” This belief leads to the bidding up of asset “values [and] confirms the commitment to personal and group wisdom. And so on to the moment of mass disillusion and the crash”.
Crowd behaviour and FOMO spread the infection. “Anyone taken as an individual is tolerably sensible and reasonable - as a member of a crowd, he at once becomes a blockhead. - Friedrich Von Schiller, as quoted by Bernard Baruch.” When irrational herd behaviour sets in and a mood of excitement (or god forbid, euphoria!) ripples through the market, speculation (quite literally!) “buys up...the intelligence of those involved.”
The financial memory is extremely brief. “Dementia comes forward to capture the financial mind” every ten years (rule of thumb?). This “is also the time generally required for a new generation to enter the scene, impressed, as had been its predecessors, with its own innovative genius”.
As Buffett says, “What the wise do in the beginning, the fool does in the end.” Booms often begin because there is a kernel of truth in the so-called innovation, but they quickly escalate into episodes of mass insanity.
I am fascinated by the way in which we seek to apportion blame after the inevitable bang that marks the end of a speculative episode. Instead of looking at the way in which market participants were foolish, we instead seek to fault governments, banks, and institutions (to blame the public's mass insanity would be cruel, cold-hearted, and politically incorrect).
This post is based on Friedrich August von Hayek's lecture titled 'The Pretence of Knowledge' to the memory of Alfred Nobel, on December 11, 1974. Adapted quotations may be used without quotation marks.
Key Learnings
Investing, like economics, is essentially complex. This is because outcomes do not depend only on the relative frequency of individual actions or occurrences, but also on the manner in which the individual actions are connected with each other. For this reason we cannot replace information about every individual actor (human being) with statistical information, and require full information about each actor if we wish to derive specific predictions about individual events.
All of the particular information possessed by every one of the participants in the market drives the value of assets (or goods). This means the price is determined by a sum of facts which in their totality cannot be known to the scientific observer, or to any other single brain. This is the source of the superiority of the market order, and the reason why free markets are the most efficient allocators of resources using information which only exists in dispersed form.
Our inability to assimilate all of this data means that investing and economics must not be treated as Physical Sciences. In fact, Hayek says that a scientistic attitude is decidedly unscientific in the true sense of the word, since it involves a mechanical and uncritical application of habits of thought to fields different from those in which they have been formed. As mentioned above, we do not have the ability to access (or even measure) all of the necessary data. This is why economists and investors with scientistic attitudes frequently treat the data which happens to be accessible to measurement as important that – not necessarily the best data. We know, for example, that good quality management is essential for a good business to grow sustainably. However, there are shades of grey in measuring the quality of management. This is why a purely numbers-based/scientific approach to investing would only take measurable quantities into account, proceeding on the fiction that the factors which can be measured are the only ones that are relevant.
Without access to all the necessary information, we are confined to making directional predictions – predictions of general attributes, but not containing specific statements. It is possible to say, for example, that a company will be worth substantially more over a long time horizon; however, we must not – or more precisely, cannot – predict the exact value and the time at which this value will be attained.
Implications for Investing
Hayek's paper does not criticise the use of numerical evidence to help put the magnitude and implications of forecasts into a context. However, he cautions against the dangers posed by the false sense of comfort that numbers can give us, and critically aware of the arrogance that (successful) precise predictions can engender. This is why he refers to the "danger [posed] by the exuberant feeling of ever growing power which the advance of the physical sciences has engendered and which tempts man to try, 'dizzy with success', to use a characteristic phrase of early communism, to subject not only our natural but also our human environment to the control of a human will." His speech culminates with a reflection on the importance of humility when dealing with essentially complex phenomena: "The recognition of the insuperable limitsto his knowledge ought indeed to teach the student of society a lesson ofhumility which should guard him against becoming an accomplice in men’s fatal striving to control society – a striving which makes him not only a tyrant over his fellows, but which may well make him the destroyer of a civilisation which no brain has designed but which has grown from the free efforts of millions of individuals." All of this means there are a few key things we must remember as investors.
The market is typically efficient because it is the sum of all of our viewpoints. This is why it is important for investors to ask themselves: Who doesn't know that?
Trying to be overly scientific, particularly with insufficient data and knowledge, is dangerous.
Rely on first principles thinking as opposed to blindly using correlations. These correlations are directional – not deterministic – and only work when the ceteris paribus condition holds, till an unexpected event leads people to stop believing in their determinism. In the real world, there are many variables at play, and simple relationships are only useful oversimplifications.
A great many (important) facts cannot be measured and so, are disregarded. The idea that only facts which can be measured are relevant, is fantastical.
You must have an understanding of the Narrative and Numbers of the business.
We must use numbers directionally (as a reality check), and try to avoid being seduced by the false sense of comfort that numbers may offer.
Is this changing?
To an extent. We are becoming more able to collect data. Not only do firms such as Facebook and Google target advertisements based on our online interactions and search history, but Amazon has a record of our purchases, Netflix a record of what we watch, and Spotify a record of what we listen to. Investors can (or might eventually be able to) analyse traffic in parking lots outside malls, the weight of bags being carried by consumers, lexical choices in transcript, and even the expressions and tones of voice of CEOs to determine their confidence and honesty levels. This is both, good and bad; we will have more data to test hypotheses, but we will also risk becoming more comfortable and more arrogant as we make misleadingly precise predictions.
Research suggests that happy employees are good for firms and investors.
THERE IS an old joke about a new arrival in Hell, who is given the choice by Satan of two different working environments. In the first, frazzled workers shovel huge piles of coal into a fiery furnace. In the second, a group of workers stand, waist-deep in sewage, sipping cups of tea. The condemned man opts, on balance, for the second room. As soon as the door closes, the foreman shouts “Right lads, tea break over. Time to stand on your heads again.”
Terrible working conditions have a long tradition. Early industry was marked by its dirty, dangerous factories (dark, satanic mills) and in the early 20th century, workers were forced into dull, repetitive tasks by the needs of the production line. However, in a service-based economy, it makes sense that focusing on worker morale might be a much more fruitful approach.
Proving the thesis is more difficult. But that is the aim of a new study which examines the relationship between happiness and productivity for workers at British Telecom. Three academics—Clement Bellet of Erasmus University, Rotterdam, Jan-Emmanuel de Neve of the Saïd Business School, Oxford, and George Ward of MIT—surveyed 1,800 sales workers at 11 British call centres. All each employee had to do was to click on a simple emoji each week to indicate their state of happiness. Those workers were charged with selling customers broadband, telephone and television deals. In total, the authors had adequate responses from 1,161 people over a six-month period.
The results were striking. Workers made 13% more sales in weeks when they were happy than when they were unhappy. This was not because they were working longer hours; in happy weeks, they made more calls per hour and were more efficient at converting those calls into sales. The tricky part, however, is determining the direction of causation. Workers may be happier when they are selling more because they anticipate a bigger bonus, or because successful sales pitches are less stressful to make than unsuccessful ones.
The academics tried an ingenious way to get round this causation problem by examining a very British issue—the weather. Workers turned out to be less happy on days when the weather in their local area was bad and this unhappiness converted into lower sales. Since they were making national calls, not local ones, it is unlikely that customer unhappiness with the weather was driving the sales numbers. So it was worker mood driving sales, not the other way round.
Even if this reasoning proves to be correct, businesses may struggle to find it of comfort. Short of locating all their call centres in California or Hawaii, companies cannot control the weather conditions their workers face. The academics point out that “what we are not able to do, given our data and setting, is adjudicate as to whether investing in schemes to enhance employee happiness makes good business sense”. It is possible that the costs of such schemes might outweigh any gains in productivity.
More research is clearly needed. But there is evidence that happier workers are good news for shareholders, as well as productivity. Analysts at BofA Merrill Lynch Global Research studied the stocks of firms rated on Glassdoor, a website which allows employees to rate the companies they work for. Those with the highest ratings outperformed those with the lowest by nearly five percentage points a year between 2013 and 2019. The analysts also used software that picked over the text of employee reviews and found that incorporating this approach improved the risk-reward trade-off (as measured by the Sharpe ratio) of the strategy.
The analysts have now applied the same approach to picking stocks based on particular sectors. Again, the sectors where workers gave the best reviews on Glassdoor over the 2013-2019 period easily outperformed those where employees gave a thumbs down. None of this is unequivocal proof. The history of equity investing is littered with strategies that worked well when back-tested but then disintegrated when applied in the real world. But at the very least, it suggests that companies should consider the merits of a contented workforce. And that might mean giving them harps and ambrosia, rather than devilish treatment.
