Doomsayers and market prophets

Prophets of doom

2018 has been another hard year for prophets of doom. Even though some markets have suffered minor corrections (and there are still four months to go!), in most cases broad-market indices in first-world nations are either up or not far from their levels in January. Here are some recent doomsday predictions (note that the author of the blog or article is not always the one making the prediction):

2015

2016

2017

2018

A few other such predictions are given here, from which some of the above items were taken.

In general, the record of market forecasters is rather dismal, to say the least. As mentioned in an earlier blog, a recent study of 68 forecasters found that the average accuracy, according to some very specific criteria and weights, was only 48%, i.e., slightly less than random chance. That is hardly a ringing rate of success!

“I told you so…”

As has been noted before, both mild and severe corrections are the inevitable fate of all financial markets. Indeed, a correction might well be underway when you read this. And when either a mild or a severe correction arrives, numerous market prophets invariably claim credit, pointing to some recent or not-so-recent prediction as evidence of their supreme prescience.

But statistically speaking, what is the substance of such predictions, particularly when similar hyperbole is repeated over and over again, month after month, year after year? After all, highlighting correct predictions, and ignoring countless incorrect predictions, is a classic “selection bias” (also known as “survivorship bias”) statistical error, one that, sadly, is endemic in the field of finance. Nor is finance alone — similar problems have arisen numerous fields of modern science and technology. For example, pervasive selection bias problems in the pharmaceutical industry have led to a call for all trials, successful or not, to be made public.

Some doomsaying predictions are based on chart analysis (i.e., “scary charts”) — see articles A, B and C for example. Yet as we have emphasized before, such predictions are tantamount to pseudoscience.

It should be acknowledged that a significant fraction of the doomsday prophets do not give a specific deadline for their prophecies to be fulfilled, and so some argue that the prediction was correct but just not yet. But such predictions fail from another scientific standard, namely falsifiability. As Karl Popper explained nearly 100 years ago, a scientific assertion that cannot be readily falsified is essentially worthless.

Why the gloom and doom?

Why is the financial world so replete with gloom and doom? As Deidre McCloskey of the University of Chicago laments,

For reasons I have never understood, people like to hear that the world is going to hell, and become huffy and scornful when some idiotic optimist intrudes on their pleasure. Yet pessimism has consistently been a poor guide to the modern economic world.

Similarly, the 19th century philosopher John Stuart Mills once wrote

I have observed that not the man who hopes when others despair, but the man who despairs when others hope, is admired by a large class of persons as a sage.

See also this article by Shawn Langlois.

Perhaps the most cogent explanation, however, is simply to follow the money. Financial news columnists, including numerous well-known pundits, long ago observed that the most sensational articles, certainly including doomsday predictions, yield the most clicks and therefore the most money. It’s sad to say, but every time we click on such articles, we are placing money in the pockets of those who make such predictions and those who publish them.

The public’s penchant for gloom and doom is not limited to finance. It may come as surprise to many, but by numerous measures, society continues to advance across a wide front. Worldwide life expectancy has soared from 29 in the late 19th century to 71 today. The fraction of the world population living in extreme poverty has fallen by a factor of 4.5 within the past 35 years. Crime has fallen dramatically, not only in the U.S. but in numerous first-world nations. Deaths in war have dramatically declined. Yet relatively few in the public are aware of these developments, because good news of this sort tends not to yield clicks on websites or views on TV/cable. For additional details, see this Math Scholar blog, as well as Steven Pinker’s books The Better Angels of Our Nature: Why Violence Has Declined and Enlightenment Now: The Case for Reason, Science, Humanism, and Progress.

Can markets be predicted?

For that matter, why is the investing world, public and professional, so keen on “knowing” the future, whether the prediction is for fair weather or foul? We know that this is not possible — there are far too many variables and uncertainties in extremely complex systems such as the financial markets. And if one could consistently predict any market, even for a short period of time, even only slightly better than chance, one would not be operating a blog or writing financial news columns but would instead be using this knowledge to reap millions in profits.

After all, as we have emphasized before, markets by definition encapsulate the collective wisdom of tens of thousands of highly trained market analysts (many with advanced mathematical training), assisted by some of the most sophisticated mathematical algorithms and some of the most powerful supercomputers on the planet, all fed by enormous real-time datasets. The net result of these competing analyses is to squeeze out any potential intelligence, leaving nothing but noise and perhaps a few obscure signals that relatively unsophisticated analyses have little chance of even seeing, much less profiting from.

So we should not be surprised when market prophets do poorly — after all, they are betting against a (nearly) random walk. One would do just as well throwing darts at a dartboard. Instead, individual investors in particular would do well to follow Jack Bogle’s advice, which is to have confidence in the mathematics of patient, long-term, low-cost investing.