Throughout the history of financial markets, investors have formed theories to explain why some assets go up and others go down in value, and some writers have promoted simple strategies derived from these models, observe Christopher Chabris and Daniel Simons in ‘The Invisible Gorilla’ (www.harpercollins.co.in).
An example that the authors mention is of the Dow theory, based on the late-nineteenth-century writings of Wall Street Journal founder Charles Dow, and premised on the idea that investors could tell whether an upswing in industrial stocks was likely to continue by looking for a similar upswing in transportation company shares.
Another example they give is of the ‘Nifty Fifty’ theory of the 1960s and early 1970s, which claimed that the best growth would be achieved by fifty of the largest multinational corporations traded on the New York Stock Exchange, and that those were therefore the best and safest investments. “The 1990s saw the ‘Dogs of the Dow’ and the ‘Foolish Four’ – models that advocated holding particular proportions of the stocks from the Dow Jones Industrial Average that paid the highest dividends as a percentage of their share prices.”
Simple, but not simpler
Just as a lightweight model airplane keeps a few key features of a real airplane but leaves out all the rest, each of these theories represents a particular model of how the financial markets work, one that strips down a complex system into a simple one that investors can use for making decisions, the authors explain.
They cite Albert Einstein’s recommendation that ‘everything should be made as simple as possible, but not simpler,’ and rue that the ‘Foolish Four,’ the ‘Nifty Fifty,’ and similar models unfortunately fall into the ‘simpler’ category.
Why so? Because these models cannot adapt to changes in market conditions, do not account for an inevitable decrease in their profitability when more people adopt the same strategies, and often assume that trends in historical financial data will recur in the future, reason Chabris and Simons. “By basing their projections so closely on past data patterns (a statistical foible known as ‘overfitting’), they are almost guaranteed to go wrong once conditions change.”
Retrofitted arguments
What the authors find even worse are investment strategies that appear to start with a target value, usually a nice round marketable number, and then calculate the rate of growth in stock prices needed to reach the target. “Arguments are then retrofitted to the numbers to explain why such a high rate of growth is plausible, or even likely. The stock market bubble of the dot-com era generated a bumper crop of this nonsense.”
At the time of writing Dow is at 11,020. Looking back to where it stood in October 1999, at 11,497, after a long run-up, Chabris and Simons remember James K. Glassman and Kevin Hassett, who published ‘Dow 36,000,’ forecasting that stock prices would more than triple within six years.
“Their optimism surpassed that of ‘Dow 30,000’ but was no match for ‘Dow 40,000,’ let alone ‘Dow 100,000.’ (All of these are real books, by different authors, and every one of them was selling for just one cent – plus shipping and handling, of course – on Amazon.com’s used-book marketplace as of April 2009.) … By the time the stock market began to recover from the dot-com bust, more titles appeared, including ‘Dow 30,000 by 2008: Why It’s Different This Time.’”
False sense of understanding
The sheer number of these titles, as the authors fret, testifies to the large market for simple models that investors can easily assimilate and act on because they give a false sense of understanding.
The world financial system is perhaps the ultimate complex system, say Chabris and Simons. They remind that this system reflects decisions made by literally billions of people every day, and those decisions are all based on beliefs about how much, or how little, various investors know. “Any time you buy an individual stock, you are acting on an implicit belief that the market has undervalued the stock. Your purchase represents a claim that you have better knowledge than most other investors about the future value of that stock.”
Conceding that it can be difficult to determine how well our simple models correspond to the realities of complex systems, the authors add that it is easy to determine three things, viz. how well we understand the simple models; how familiar we are with the surface elements, concepts, and vocabulary of the complex system; and how much information we are aware of, and can easily access, about the complex system. They caution that to consider our knowledge of these particular things as signals that we understand the system as a whole can be an utterly unwarranted inference that can quickly land us in hot water.
Illusion of knowledge
Take the case of the recent financial crisis. “Analysts understood their models, they were familiar with the vocabulary of subprime mortgages, CDOs, and the like, and they were swimming in a river of financial data and news, giving them the illusion that they understood the housing market itself – an illusion that persisted until the market collapsed.”
The authors warn that with more and more financial information available at higher speed and lower cost (e.g. CNBC, Yahoo! Finance, and online discount stockbrokers), the conditions for this illusion have spread from professional market participants to ordinary individual investors.
If you find it tough to escape the illusion entirely and still think of yourself as a knowledgeable stock picker, the authors’ counsel is to try limiting how much the illusion can affect you, by allocating just a small proportion of your assets to active investment decisions, and thinking of those investments at least partly as a hobby. A corollary to their advice is that the rest of your money could be dedicated to strategies that are less subject to the illusion of knowledge, such as passively investing in index funds that just track the movements of the overall market.
“That’s also a reasonable plan for a gambler who wants to keep his or her hobby under control: Set aside a small bankroll and focus on the entertainment that comes from the practice rather than counting on it to generate significant income.”
Two messages
An instructive piece of research discussed in the book is of Brad Barber and Terrance Odean, who studied six years of trading records for 60,000 accounts from a brokerage firm and compared investment returns between people who bought and sold stocks frequently, and those who traded rarely. “Presumably investors who make lots of trades believe that they have lots of knowledge and good ideas about stocks – that each of their trades will make money because it is anticipating a market move. But once their returns were adjusted for the costs and tax payments generated by all the trades they made, the most active traders earned one-third less per year than the least active ones.”
The book wraps up with two messages. The first is a negative one, asking you to be wary of your intuitions, especially intuitions about how your own mind works when having to decide on important matters. The second one, however, is an affirmative message that you can make better decisions if you do your best to look for the ‘invisible gorillas’ in the world around you – the important things right in front of you that you are not noticing due to the illusion of attention, rather than due to stupidity, arrogance, ignorance, or lack of focus.
Imperative read over the weekend.
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