Numbers matter, not the narrativeMay 7, 2021 2023-05-11 8:30
Numbers matter, not the narrative
Numbers matter, not the narrative
Letter # 40, 7 May 2021
Let’s start with a fun exercise. Based on the past 20-years’ stock returns, match the following companies to the following returns (without looking them up):
Companies: (a) Hindustan Unilever, (b) Nestle, (c) Colgate, (d) Infosys, (e) JSW Steel and (f) Vedanta.
Stock returns (CAGR): (a) 35%, (b) 25%, (c) 21%, (d) 19%, (e) 18% and (f) 15%.
Let me share a couple of interesting stories, before we come to the results.
Philip Tetlock, a professor of psychology, in his book Expert Political Judgment writes that he spent 15 years (1988 – 2003) studying the decision-making process of 284 experts. He defined experts as people who appeared on television, were quoted in newspaper & magazine articles, advised governments & businesses, or participated in punditry roundtables. All of them were asked about the state of the world; all gave their prediction of what would happen next. Collectively, they made over 27,450 forecasts. Tetlock kept a track of each one and calculated the results. How accurate were the forecasts? No better than dart-throwing chimpanzees!
You might think that people may not be great at making predictions, but when it comes to facts, they know their stuff, right?
Hans Rosling, a renowned medical doctor and public educator, in his book Factfulness asks 12 (multiple choice) fact questions about the world (how many girls finish primary education, how much population lives in low-income countries, etc.) to a variety of people (12,000 people in 14 countries in 2017). On average, they scored just two correct answers of 12. No one got a perfect score and a stunning 15% scored zero.
Respondents included medical students, teachers, scientists, investment bankers, journalists, senior political decision makers. The most appalling results came from Nobel laureates and medical researchers. These were not just wrong results, but they were systematically wrong. The test results were not random, they were worse than random. Chimpanzees (who have no knowledge at all) would have done a better job. He writes, “every group of people I ask thinks the world is more frightening, more violent and more hopeless–in short, more dramatic–than it really is.”
How is it that well-educated people with access to all the data would score worse than chimpanzees in their knowledge of facts or their forecasts? Rosling writes that only ‘actively wrong knowledge’ can make us score so badly. We build a narrative of the world view based on what we hear in the news, what we see on television and who we interact with; this makes us form a world view that is different from reality.
However, Daniel Kahneman, in his book Thinking fast and slow, has a more nuanced answer. He writes that our cognitive processes are divided in two modes of thinking: (a) thinking – traditionally referred to as intuition (system 1); and (b) reason – described as slow and rule governed (system 2). Whereas system 1 operates automatically, quickly, and effortlessly with no sense of voluntary control, operations of system 2 require concentration. And, although we like to think of ourselves as having sturdy system 2 ability, in fact much of our thinking occurs in system 1.
Now, answers to the quiz. Ranking from highest to lowest stock returns: (a) Vedanta – 35% CAGR, (b) JSW Steel – 25% CAGR, (c) Nestle – 21%, (d) Colgate 19%, (e) Infosys – 18% and (f) Hindustan Unilever – 15%.
You might think that 2002-08 was a super-cycle–a once in a century event, which skews returns. Here are the returns for the past five years–JSW Steel 42%, Vedanta 32%, Nestle 25%, Hindustan Unilever 24%, Infosys 20% and Colgate 14%.
These numbers may appear counter intuitive; after all, how can a capital-intensive commodity business outperform a consumer staples or an information technology business over a 20-years’ time frame? The people who Tetlock tracked and Rosling spoke to might appear distant, but haven’t we, over the past few years, been fed a certain narrative (companies with higher revenue growth with strong return ratios outperform in ALL market conditions or don’t buy commodity companies or don’t buy PSU stocks) that needs to be seriously questioned after these results?
Well narrative aside, numbers have always told a different story, i.e., if we were willing to listen. In the future, at some point of time the returns of commodity businesses will likely look sub-par, but therein lies the important lesson. I am reproducing the table (updated for latest data) that I had written about in the December 2020 letter (1). Over different market cycles, different sectors tend to drive (or lag) indices and the narrative that there could be ‘one investment strategy that can beat the markets at all times’ is largely a hoax.
However, if numbers spoke that loudly, why would a lot more investment managers not include cyclicals as part of their investment framework? Because we have the recency bias and until recently (a year back or so), commodities did not look like an investible asset class. The narrative of a framework that included cyclicals was very difficult to sell to people who would invest in funds.
Morgan Housel summarises it well when he writes, “few people make financial decisions purely with a spreadsheet. Most make them at the dinner table or in a company meeting. Places where personal history, your own unique view of the world, ego, pride, marketing and odd incentives are scrambled together into a narrative that works for you”. Marketing experts that sell financial products are aware that building a simple narrative has a stronger chance of generating a sale. Paraphrasing Kahneman – we might think we are deploying reason (system 2) while making a decision, but in fact, much of our thinking happens through intuition (system 1), which is gullible to narrative. For system 1, narrative matters more than numbers, which guarantees a sale; but for generating superior long-term investment returns, the numbers will always matter more!
(1) Jailing short sellers, capital returns and long-run cycles – Buoyant Capital
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