Image from xkcd
In a great scene from the classic film, The Wizard of Oz, Dorothy and her friends have — after some difficulty and fanfare — obtained an audience with “the great and powerful Oz.” When, during that audience, Dorothy’s dog Toto pulls back a curtain to reveal that Oz is nothing like what he purports to be, Oz bellows, “Pay no attention to that man behind the curtain,” in an unsuccessful effort to get his guests to focus their attention elsewhere.
Like the Wizard, the great and powerful on Wall Street would have us pay no attention what is really there — “behind the curtain.” Yet once in a great while the Street rats itself out so that we get to find out, beyond a shadow of doubt (if you still had any), what the big investment houses really think about what they do and who they do it to.
The now-defunct Bear Stearns won a noteworthy 2002 legal decision involving former Fed Governor and then-Bear Chief Economist Wayne Angell over advice he and the firm gave to a Bear Stearns client named Count Henryk de Kwiatkowski (really) after the Count lost hundreds of millions of dollars in a just a few weeks (really) following that advice by trading currency futures on margin (really). The Count had been born in Poland, escaped invading Nazis, been banished to Siberia by the Soviets, escaped and travelled across Asia on foot to Tehran, talked his way into the British Embassy, became a renowned RAF pilot, moved to Canada, became an engineer, and made a fortune trading used airliners, most famously selling nine 747s to the Shah of Iran over a game of backgammon in the royal palace (really). He also became the owner of the famous thoroughbred racing institution, Calumet Farm (really).
Bear offered the Count “a level of service and investment timing comparable to that which [Bear] offer[ed its] largest institutional clients” (which is not to say that they were any good at it). The key trade was a huge and ultimately disastrous bet that the U.S. dollar would rise in late 1994 and early 1995. At one point, the Count’s positions totaled $6.5 billion nominally and accounted for 30 percent of the total open interest in certain currencies on the Chicago Mercantile Exchange. The jury awarded a huge verdict to the Count but the appellate court reversed. The appellate judges determined, quite conventionally, that brokers may not be held liable for honest opinions that turn out to be wrong when providing advice on non-discretionary accounts.
But I’m not primarily interested in the main story. Instead, I’m struck by a line of testimony offered at trial by then-Bear CEO Jimmy Cayne that does not even show up in subsequent court opinions, despite extensive recitals of the facts of the case. The generally “cocksure” Cayne apparently thought that his firm could be in trouble so he took a creative and disarmingly honest position given how aggressive Bear was in promoting Angell’s alleged expertise to its customers. Cayne brazenly asserted that Angell was merely an “entertainer” whose advice should never give rise to liability.
Economists are right only 35 to 40 percent of the time, Cayne testified. “They don’t really have a good record as far as predicting the future,” he said. “I think that it is entertainment, but he probably doesn’t think it is” (and I doubt that the Count was much amused). Cayne even noted that Angell did not have a real job description at Bear (a claim that Angell’s bio seems to support). “I don’t know how he spends most of his time,” testified Cayne. “He travels a lot and visits people and has lunches and dinners and he is an entertainer.”
Notice that Cayne did not even pay lip service to the idea that Bear’s clients were entitled to the firm’s best efforts based upon the best research (or even their best research). Moreover, he did not seem to think that the Count deserved honesty together with competent advice. For Cayne, the goal was simply to be entertaining and to make sales. That the Count lost hundreds of millions of dollars was merely collateral damage (and not even necessarily unfortunate at that).
To look at the Count’s case a bit differently, in an odd sense, Cayne was precisely if hypocritically correct. As I have noted many times before, we’re in the Wall Street “silly season” of predictions and forecasts for the New Year. There is nothing inherently wrong with them, and they can be very entertaining indeed. But you should be very careful about taking them any more seriously than Jimmy Cayne did.
And you should always be aware of who has (and especially who doesn’t have) your best interest in mind — practically, realistically and legally. None of us should ever ignore who is behind the curtains Wall Street tries to put between itself and the public to try to hide what’s really going on.
So what were these “entertainers” up to in 2015? Sadly, it was same ol’, same ol’. As ever (see here, here, here, here, here and here for just a few past examples), their predictions and forecasts were simply dreadful. It’s almost getting boring to point out the obvious – we humans simply don’t generally make forecasts very well.
In general, Wall Street’s top strategists expected the S&P 500 to rally 10 percent in 2015.* Instead, it ended 2015 at essentially the same level it started. It opened the year at 2,058.9 and closed the year at 2,043.9, a loss of less than one percent (nominally; with dividends factored in, the S&P 500 gained a bit over one percent). Note the following strategist forecasts for the S&P 500 and by how far – yet again – they missed the mark in the aggregate.
- Goldman Sachs’ David Kostin: 2,100
- Barclays’ Jonathan Gilonna: 2,100
- Credit Suisse’s Andrew Garthwaite: 2,100
- Deutsche Bank’s David Bianco: 2,150
- BTIG’s Dan Greenhaus: 2,200
- Citi’s Tobias Levkovich: 2,200
- Bank of America Merrill Lynch’s Savita Subramanian: 2,200
- Nuveen’s Bob Doll: 2,200
- UBS’ Julian Emmanuel: 2,225
- BMO’s Brian Belski: 2,250
- Morgan Stanley’s Adam Parker: 2,275
- Oppenheimer’s John Stoltzfus: 2,311
- RBC’s Jonathan Golub: 2,325
- FundStrat’s Tom Lee: 2,325
- Blackstone’s Byron Wien: 2,368
Moreover, the overall list of bad Wall Street predictions is both long and broadly based. For example, the median economic forecast tabulated by Bloomberg for the 10-year U.S. Treasury note yield for year-end 2015 as of a year ago was 3.24 percent. On the other hand, DoubleLine’s Jeff Gundlach claimed that the 10-year that finished 2014 yielding 2.12 percent should take out its modern-era low of 1.38 percent yield during 2015. Instead, they were all wrong – by a lot! – as the 10-year note closed the year yielding 2.27 percent. Similarly, a Reuters survey of 33 economists and analysts forecast North Sea Brent crude would average $74.00 a barrel in 2015 after ending 2014 above $60; it closed the year at $37.28. And, despite untold amounts of effort, discussion and ink (real and digital), Wall Street expected the Fed funds rate to end the year at 1.00 percent but it actually closed with a target of 0.25-0.50 percent.
Wall Street hasn’t cornered the market on these sorts of failures, of course. For 2015, alleged experts claimed that things were looking up for Greece, that Meerkat would be a game-changer, that things would be fantastic at Volkswagen, that Jeb Bush would be the Republican presidential frontrunner, that Scott Walker would be the nominee, and that Donald Trump wouldn’t run and surely wouldn’t be very popular. And it was easy to think that a Trump candidacy would turn out to be a joke who “sounds like a know-it-all down at the OTB.” That last prediction is technically true, of course, but not in the intended manner as the Donald is the Republican frontrunner by a bigly margin.
Going back over previous forecasts offers a veritable parade of horribles in terms of accuracy. Irving Fisher was a noted 20th century economist. No less an authority than Milton Friedman called him “the greatest economist the United States has ever produced.” However, he made a statement in 1929 that all but destroyed his credibility for good. Three days before the famous Wall Street crash he claimed that “stocks have reached what looks like a permanently high plateau.”
James Glassman and Kevin Hassett authored a book in 1999 entitled Dow 36,000. That book’s introduction states: “If you are worried about missing the market’s big move upward, you will discover that it is not too late. Stocks are now in the midst of a one-time-only rise to much higher ground — to the neighborhood of 36,000 on the Dow Jones Industrial Average.” Sadly, it didn’t exactly work out that way and a used paperback copy of the book may now be purchased online for as little as a penny. It isn’t even worth that much except perhaps as a reminder of the perils of forecasting.
Of course, there are many similar (and even worse) examples. Peter Schiff is still saying, as he has for years now, that gold (which closed the year at $1,062.80) is going to $5,000 per ounce. And as he does pretty much every year, Marc Faber is again calling for a market crash in 2016. Some year one of them might eventually (if only coincidentally) be right.
History has provided a long list of such whoppers. Analyst Clifford Stoll argued that “no online database will replace your daily newspaper.” Bob Metcalfe, an electrical engineer widely credited with the invention of Ethernet technology, stated: “I predict the Internet will soon go spectacularly supernova and in 1996 catastrophically collapse.” Federal Communications Commission commissioner T.A.M. Craven stated in 1961 that “There is practically no chance communications space satellites will be used to provide better telephone, telegraph, television or radio service inside the United States.”
Marconi predicted that the “wireless era” would make war ridiculous and impossible. In 1962, Decca records rejected the Beatles because they didn’t like the group’s sound and thought guitar music was on the way out. Thomas Bell, the president of the Linnean Society of London, summing up the year 1858 (which included the announcement of Charles Darwin’s theory of evolution by natural selection), stated, “The year which has passed has not, indeed, been marked by any of those striking discoveries which at once revolutionize, so to speak, the department of science on which they bear.”
In April 1900, the great physicist Lord Kelvin proclaimed that our understanding of the cosmos was complete except for two “clouds” — minor details still to be worked out. Those clouds had to do with radiation emissions and with the speed of light, and they pointed the way to two major revolutions in physics still to come: quantum mechanics and the theory of relativity. And, at the World Economic Forum in 2004, Bill Gates predicted that, “Two years from now, spam will be solved.”
Oh that he had been right. But my spam filter and my email inbox prove otherwise.
At least with respect to market predictions, most of the alleged experts (entertainers) making them are highly educated, vastly experienced, and examine the vagaries of the markets pretty much all day, every day, Yet they are wrong a lot — pretty much all the time in fact. Why are we so bad at this?
One obvious starting point is the ancient admonition of Publilius Syrus: “The eyes are blind when the mind works on other things” (caeci sunt oculi, cum animus alias res agit), or Orwell’s more recent iteration: “to see what is in front of one’s nose needs a constant struggle.” I think that Publilius had it right those many centuries ago, even though science has only much more recently demonstrated it. Still, this problem is deeper and more complicated than just that.
The great Russian novelist Leo Tolstoy gets to the heart of the matter when he asks, in the opening paragraphs of Book Nine of War and Peace (coming as a television series in a couple of weeks): “When an apple has ripened and falls, why does it fall? Because of its attraction to the earth, because its stalk withers, because it is dried by the sun, because it grows heavier, because the wind shakes it, or because the boy standing below wants to eat it?” With almost no additional effort, today’s scientists could expand this list extensively. But (as Kahneman and Tversky so powerfully pointed out) we evolved to make quick and intuitive decisions for the here-and-now ahead of careful and considered decisions for the longer-term. Thus we intuitively emphasize (per anthropologist John Tooby) “the element in the nexus that we [can] manipulate to bring about a favored outcome.” Thus, “the reality of causal nexus is cognitively ignored in favor of the cartoon of single causes.”
Even when we recognize the fallacy of thinking in terms of single, linear causes (Fed policy, valuations, etc.), the markets are too complex and too adaptive to be readily predicted. Just as the King thought (albeit wrongly) about Mozart’s music containing “too many notes” in Amadeus, there are simply too many variables to predict market behavior with any degree of detail, consistency or competence (the explanation for the recent shuttering of Nevsky Capital, a previously well-regarded hedge fund, provides merely the latest evidence for this idea). Unless you’re Seth Klarman or somebody like him (none of whom is accepting capital from the likes of us), your crystal ball almost certainly does not work any better than anyone else’s.
All that said, the idea that we can live our investing lives forecast-free is as erroneous as the market predictions that are so easy to mock. As my friend Cullen Roche repeatedly emphasizes, “any decision about the future involves an implicit forecast about future outcomes.” As Philip Tetlock wrote in his wonderful new book, Superforecasting: The Art and Science of Prediction: “We are all forecasters. When we think about changing jobs, getting married, buying a home, making an investment, launching a product, or retiring, we decide based on how we expect the future to unfold.” The key then, as Cullen argues, is that we should shun low probability forecasts. By contrast, Superforecasting points to (and laughs at) the general inaccuracy of financial pundits at CNBC, whose performance prompted Jon Stewart to remark, “If I’d only followed CNBC’s advice, I’d have a million dollars today — provided I’d started with a hundred million dollars.”
The central lessons of Superforecasting can be distilled into a handful of directives. Base predictions on data and logic, and try to eliminate personal bias. Working in teams helps. Keep track of records so that you know how accurate you (and others) are. Think in terms of probabilities and recognize that everything is uncertain. Unpack a question into its component parts, distinguishing between what is known and unknown, and scrutinizing your assumptions. Recognize that the further out the prediction is designed to go, the less specifically accurate it can be.
In other words, we need rigorous empiricism, probabilistic thinking, a recognition that absolute answers are extremely rare, regular reassessment, accountability, and an avoidance of too much precision. Or, more fundamentally, we need more humility and more diversity among those contributing to decisions. We need to be concerned more with process and improving our processes than in outcomes, important though they are. “What you think is much less important than how you think,” says Tetlock; superforecasters regard their views “as hypotheses to be tested, not treasures to be guarded.” As he told my friend Jason Zweig of The Wall Street Journal, most people “are too quick to make up their minds and too slow to change them.”
Most importantly, perhaps, Tetlock encourages us to hunt and to keep hunting for evidence and reasons that might contradict our views and to change our minds as often and as readily as the evidence suggests. One “superforecaster” went so far as to write a software program that sorted his sources of news and opinion by ideology, topic and geographic origin, then told him what to read next in order to get the most-diverse points of view.
The best forecasters are all curious, humble, self-critical, give weight to multiple perspectives and feel free to change their minds often. In other words, they are not (using Isaiah Berlin’s iconic description, harkening back to Archilochus), “hedgehogs,” who explain the world in terms of one big unified theory, but rather “foxes” which, Tetlock explains, “are skeptical of grand schemes” and “diffident about their own forecasting prowess.”
But as Tim Richards explains, we are both by design and by culture inclined to be anything but humble in our approach to investing. We invest with a certainty that we’ve picked winners and sell in the certainty that we can re-invest our capital to make more money elsewhere. But we are usually wrong, often spectacularly wrong. These tendencies come from hard-wired biases and also from emotional responses to our circumstances. But they also arise out of cultural requirements to show ourselves to be confident and decisive. Even though we should, we rarely reward those who show caution and humility in the face of uncertainty (see Trump, Donald).
One forecast we should invoke, at least until the evidence demonstrates otherwise, is that the markets will generally trend upward. According to University of Oregon economist Tim Duy, “As long as people have babies, capital depreciates, technology evolves, and tastes and preferences change, there is a powerful underlying impetus for growth that is almost certain to reveal itself in any reasonably well-managed economy.”
Because of the many problems we have with forecasting generally, our portfolios should also be diversified. A diverse portfolio – one that reaches across market sectors – greatly increases the odds that at least some of a portfolio’s investments will be in the market’s stronger sectors at any given time – regardless of what’s hot and what’s not and irrespective of the economic climate. At the same time, a diverse portfolio will never be fully invested in the year’s losers. For example, according to Morningstar Direct, about 25% of U.S. listed stocks lost at least 75 percent of their value in 2008 but only four of over 6,600 open-ended mutual funds lost more than 75 percent of their value that year. Thus a diversified approach provides much smoother returns over time (even if not as smooth as desired!). On the other hand, a well-diversified portfolio will always include some poor performers, and that’s hard for us to abide.
Next, make sure your time horizon is long enough. If you don’t have at least a five-year time frame before using the money, stocks are almost surely a bad idea for you. That’s because the chances of negative returns over shorter time periods are too high. But over the longer-term, our investment prospects are reasonably bright.
Image courtesy of Pragmatic Capitalism
Finally, recognize that there are limits to how precise even good forecasting techniques can be. John Bogle offers a reasonable one (outlined by Jason Zweig here) as does Jeremy Grantham’s GMO (see here). But even these shouldn’t be seen as more than the roughest of outlines. Your mileage can and will vary. On the other hand, if (as Barry Ritholtz recently pointed out) Wall Street’s entertainment establishment suggests you buy the FANGs or short oil or fade small caps or go to cash to avoid the crash, ignore all that as so much noise. Keep your attention focused squarely on specific needs, goals and what you can actually expect to control about your portfolio and its results. That might be a New Year’s resolution worth keeping.
* To be sure, a 10 percent return prediction isn’t stupid. After all, predicting a negative return is a fool’s errand given that (a) Wall Street strategists are paid to get customers to buy, and (b) on an annual basis, the S&P 500 is positive more than two-thirds of the time. Since the S&P 500 has averaged well over 12 percent per annum in the post-war era, a 10 percent expected return is a reasonable guess. But note that it’s a probabilistic guess based upon likely outcomes rather than a true forecast based upon market conditions.